Chemical Engineering Education

http://cee.che.ufl.edu/ ( Journal Site )
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Title:
Chemical Engineering Education
Alternate Title:
CEE
Abbreviated Title:
Chem. eng. educ.
Physical Description:
v. : ill. ; 22-28 cm.
Language:
English
Creator:
American Society for Engineering Education -- Chemical Engineering Division
Publisher:
Chemical Engineering Division, American Society for Engineering Education
Place of Publication:
Storrs, Conn
Publication Date:
Frequency:
quarterly[1962-]
annual[ former 1960-1961]
quarterly
regular

Subjects

Subjects / Keywords:
Chemical engineering -- Study and teaching -- Periodicals   ( lcsh )
Genre:
serial   ( sobekcm )
periodical   ( marcgt )

Notes

Citation/Reference:
Chemical abstracts
Additional Physical Form:
Also issued online.
Dates or Sequential Designation:
1960-June 1964 ; v. 1, no. 1 (Oct. 1965)-
Numbering Peculiarities:
Publication suspended briefly: issue designated v. 1, no. 4 (June 1966) published Nov. 1967.
General Note:
Title from cover.
General Note:
Place of publication varies: Rochester, N.Y., 1965-1967; Gainesville, Fla., 1968-

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
oclc - 01151209
lccn - 70013732
issn - 0009-2479
Classification:
lcc - TP165 .C18
ddc - 660/.2/071
System ID:
AA00000383:00199

Full Text




































Feature Articlesj




















































and ChE at ...^^^^^B^^^^^^BBBI^^^^^^^BBBiBBBII^^^^^^^~















SThis one-page column will present practical teaching tips in sufficient detail that ChE educators can
adopt the tip. The focus should be on the teaching method, not content. With no tables or figures
the column should be approximately 450 words. If graphics are included, the length needs to be
reduced. Tips that are too long will be edited to fit on one page. Please submit a Word file to Phil
Wankat , subject: CEE Teaching Tip.


CHALLENGE PROBLEMS
PHILLIP C. WANKAT
Purdue University West Lafayette, IN 47907


ou just wrote a really interesting and relevant quiz
or test problem and you start to solve it. A few hours
later it dawns on you that although interesting and
relevant, the problem is too long and/or too difficult to use
as a test problem. What do you do with this lovely, but long,
problem? You could use it as a homework problem, but unless
some method is developed to motivate the students, many will
give up when the going gets tough. As an alternative, make it
a challenge problem with a suitable reward for students who
successfully solve the problem.
In Spring 20121 was teaching the junior-level separations
course at the University of Canterbury in Christchurch, New
Zealand. As part of the section on crystallization from solution
the class was studying precipitation by adding anti-solvent.
I developed the following practical and surprisingly difficult
problem using published datam" on precipitation of salts from
water by adding methanol.
In a salting out experiment we dissolve NaCI into 1000 g
water until it is saturated at 30 C.
A. How many moles of NaCl are in solution?
B. How many moles of methanol need to be added to precipi-
tate exactly 14 of the moles of NaCI dissolved in Part A?
When I solved this problem, I found part B was clearly
too difficult and too time-consuming for the quiz. Four fac-
tors make the problem difficult: 1. Data is reported using a
combination of mass and molar units. 2. Data is presented
in graphical form that has to be converted to digital form.
3. Addition of methanol decreases the moles salt/mole solvent,
but increases the moles of solvent. As a result the amount of
salt that will dissolve first decreases but may then increase.
4. The result is quite sensitive and small errors in reading
the graph are multiplied. One student, who got the correct
answer, commented, "By time I realized it was hard, I had
spent several hours on it so I was determined to finish."
Since this problem covered the same objectives as the quiz
but required deeper learning, it was offered as a challenge
problem. Students who turned in a successful solution by 5:00
p.m. on Thursday received 100% on the quiz scheduled for


noon on Friday and were excused from that quiz. Students
turning in an incorrect solution were not penalized, but were
expected to take the quiz. The problem was to be done in test
mode-no consulting other students or academic staff. Since
there is some error in reading the graph, the students needed
a correct procedure and their answer had to be within 9%
of the correct number of moles of methanol added.
Students in New Zealand are just as grade conscious as
students in the United States. The chance to earn a 100 without
taking the quiz was very motivating for many students. Out
of a class of 61 students, 27 students (44%) turned in a solu-
tion and 11 (41%) passed. Successful solutions ranged from
hand and spreadsheet calculations based on reading a series
of equilibrium concentrations off the graph to rather elegant
spreadsheet solutions that included a polynomial fit to the
data. Since the solution had to be handed to me in my office,
I talked to more students on Thursday than the entire rest of
the semester combined. The general consensus of students
who were successful was they spent more time solving the
challenge problem than they would have studying for a quiz.
Good challenge and quiz problems both focus on course
objectives. Challenge problems, however, should include
course objectives that cannot be included in a test problem
such as use of computer tools, solving complex multiple-step
problems, and the value of persistence. Since the ability to
evaluate one's own work is valuable although seldom taught,
a good challenge problem will follow the old adage, "Every
difficult problem has a simple answer, and it's wrong."

ACKNOWLEDGMENT
The hospitality of the Department of Chemical and Pro-
cess Engineering at the University of Canterbury is greatly
appreciated.

REFERENCES
1. Lozano, J.A.F., "Recovery of Potassium Magnesium Sulfate Double
Salt from Seawater Bittern," Ind. Eng. Chem. Process Des. Develop.,
15(3) 445 (1976) 0
Copyright ChE Division ofASEE 2013


[e. teaching tips )












BUSINESS ADDRESS:
Chemical Engineering Education
5200 NW 43rd St., Suite 102-239
Gainesville, FL 32606
PHONE: 352-682-2622
FAX: 866-CEE-OJRN
e-mail: cee@che.ufl.edu

EDITOR
Tim Anderson

ASSOCIATE EDITOR
Phillip C. Wankat

MANAGING EDITOR
Lynn Heasley

PROBLEM EDITOR
Daina Briedis, Michigan State

LEARNING IN INDUSTRY EDITOR
William J. Koros, Georgia Institute of Technology

PUBLICATIONS BOARD-

CHAIR
C. Stewart Slater
Rowan University
VICE CHAIR*
Jennifer Sinclair Curtis
University of Florida
MEMBERS
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Worcester Polytechnic Institute
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Rowan University
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North Carolina State
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Tuskegee University
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University of Tennessee, Chattanooga
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University of Alberta
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Aachen Technical University
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University of Kentucky
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Bucknell University
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University of Akron


Chemical Engineering Education
Volume 47 Number 1 Winter 2013

DEPARTMENT
2 Chemical Engineering at the University of South Alabama
Srinivas Palanki

o CLASS AND HOME PROBLEMS
59 Transport Phenomena Projects: Natural Convection Between
Porous, Concentric Cylinders-A Method To Learn and To Innovate
Esteban Saatdjian, Francois Lesage, and Josd Paulo B. Mota

t CURRICULUM
27 Use of Research-Based Instructional Strategies in Core ChE Courses
Michael Prince, Maura Borrego, Charles Henderson,
Stephanie Cutler, and Jeff Froyd
38 Teaching Chemical Engineers About Teaching
Daniel E. Heath, Mary Hoy, James F. Rathman,
and Stephanie Rohdieck
48 Online Data Resources in Chemical Engineering Education: Impact
of the Uncertainty Concept for Thermophysical Properties
Sun Hyung Kim, Jeong Won Kang, Kenneth Kroenlein,
Joseph W. Magee, Vladimir Diky, Chris D. Muzny,
Andrei F. Kazakov, Robert D. Chirico, and Michael Frenkel

RANDOM THOUGHTS
25 You Got Questions, We Got Answers: 1. Miscellaneous Issues
Richard M. Felder and Rebecca Brent

CLASSROOM
9 A Joint Learning Activity in Process Control and Distance
Collaboration Between Future Engineers and Technicians
J-S. Deschenes, N. Barka, M. Michaud, D. Paradis,
and J. Brousseau

LABORATORY
15 High-Performance Liquid Chromatography in the Undergraduate
Chemical Engineering Laboratory
Douglas D. Frey, Hui Guo, and Nikhila Karnik
65 Technology in the Classroom: Transitioning Lab and Design To an
All-Digital Workflow
Daniel Anastasio, Aravind Suresh, and Daniel D. Burkey

OTHER CONTENTS
inside front cover Teaching Tip: Challenge Problems
Phillip C. Wankat
inside back cover Guest Editorial
Lisa G. Bullard
58 Book Review

CHEMICAL ENGINEERING EDUCATIONI7SSN 0009-2479 (print); ISSN 2165-6428 (online)] is published quarterly
by the Chemical Engineering Division, American Society for Engineering Education, and is edited at the University of
Florida. Correspondence regarding editorial matter, circulation, and changes of address should be seat to CEE, 5200 NW
43rd St., Suite 102-239, Gainesville, FL 32606. Copyright 2013 by the Chemical Engineering Division,American Society
for Engineering Education. The statements and opinions expressed in this periodical are those of the writers and not
necessarily those of the ChE Division, ASEE, which body assumes no responsibility for them. Defective copies replaced if
notified within 90 days of publication. Write for information on subscription costs andfor back copy costs and availability.
POSTMASTER: Send address changes to ChemicalEngineering Education, 5200 NW43rd St., Suite 102-239, Gainesville,
FL32606.Periodicals Postage PaidatGainesville,Florida, and additional post offices (USPS 101900). www.che.ufl.edulCEE


Vol. 47, No. 1, Winter 2013









LI4= department


Chemical Engineering at...


the University of South Alabama


Shelby Hall: Current home of the Department of Chemical and Biomolecular Engineering.


SRINIVAS PALANKI
University of South Alabama Mobile, AL 36695
he University of South Alabama is a public, doctoral-
level university located in Mobile, Alabama, that was
created by the Alabama legislature in 1963. It is the
only major public university in the upper Gulf Coast and is
strategically located to serve a population of over one mil-
lion people living in the greater Mobile area. The university
includes 10 colleges: Allied Health, Arts & Sciences, Busi-
ness, Education, Engineering, Medicine, Pharmacy, Nursing,
Computing, and Continuing Education.
The university started offering bachelor's degrees in en-
gineering soon after its inception, primarily to support the
large number of manufacturing industries in the vicinity of
Copyright ChE Division of ASEE 2013


Mobile (mainly ship-building, chemical, pulp and paper,
and aerospace). The first two bachelor's degrees in chemical
engineering were awarded to Donald Dodge (Winter 1969)
and Gene Powers (Spring 1969). At that time engineering
was a division within the College of Arts & Sciences. By
1976, there were 577 students pursuing engineering degrees
at the University of South Alabama and in response to this
increased enrollment, the College of Engineering was created.
Chemical engineering faculty member Harold Rodriguez
was appointed as the first dean of Engineering. The chemical
engineering program had only two other faculty members:
Crews Askew and John Stark, with Stark serving as the first
department chair. There were 77 students registered in the
chemical engineering program at that time. The university de-
cided to add more faculty lines to the department in response
to increased enrollment. At this time, the department moved


Chemical Engineering Education










to the Engineering Laboratory Building, which provided for
increased space for its growing student enrollment. Professors
Ted Huddleston, Steven Morisani, and Jagdish Dhawan
joined the department in 1981,1982, and 1983, respectively.
Huddleston took over from Stark as department chair in 1981
and soon after, in 1985, the department's bachelor's program
received ABET accreditation. The undergraduate program
has been continuously accredited since then, receiving its
most recent six-year accreditation in 2012. In 1986, John
Stark decided to retire and Keith Harrison was hired as his
replacement. In 1989, Harold Rodriguez retired as dean of
Engineering and was replaced by David Hayhurst, a chemi-
cal engineering faculty member hired from Cleveland State
University.
In 1987, the Alabama Commission on Higher Education ap-
proved a Master of Science Program in Chemical Engineering
and the department now had a new mission of not only teach-
ing undergraduate classes but also of conducting research at
the graduate level. By that time, there were several chemical
engineers working in the local industry who wanted to pursue
a graduate degree to improve their qualifications. By 1990,
there were 15 master's students enrolled in the department.
While most of these students were pursuing a coursework-
only master's degree, Harrison and Dhawan initiated indepen-
dent research programs. These research programs were started
on a shoestring budget as there was no entrenched research
culture or a mechanism for securing external funding in the
college at that time. Harrison had worked in Monsanto for
10 years before coming to the University of South Alabama
in the area of process simulation and he quickly initiated a
research effort to develop a computer program for predicting
the energy release hazards of pure chemicals and mixtures.
This resulted in the computer program CHETAH, which is
a unique tool for predicting both thermochemical properties
and certain reactive chemical hazards associated with a pure
chemical, a mixture of chemicals, or a chemical reaction.
This program is available from ASTM International and
version 9.0 was released in 2009. Dhawan had worked in the
chemical process industry for eight years before he joined
the department. With a background in thermodynamics,
coal liquefaction, and supercritical extraction, he initiated a
research program to convert scrap tires into useful fuels in
collaboration with Richard Legendre from the Chemistry
Department. He was awarded a U.S. patent for a "Method
of Reclaiming Scrap Vulcanized Rubber Using Supercritical
Fluids" in 1995; this was the first patent issued to a College
of Engineering faculty member in the University of South
Alabama and this technology was soon licensed to Advanced
Recycling Sciences, a company based in Tustin, California.
In 1996, Nicholas Sylvester, a chemical engineering fac-
ulty member, joined the university as senior academic vice
president for Academic Affairs. Sylvester had formerly been
vice president of Research at the University of Akron where


The Engineering Laboratory Building, home to the
Chemical Engineering Program from 1978 to Summer 2012.
he guided Akron's $125 million capital campaign, increased
the university's externally funded research support, improved
the profitability of non-credit continuing education, and
negotiated various long-term royalty agreements for the uni-
versity's technology. Prior to that, he was a faculty member
at the University of Tulsa where he rose through the ranks
to become chair of the Department of Chemical Engineering
and then dean of Engineering. Sylvester started his academic
career at the University of Notre Dame and had extensive
research experience, directing 19 doctoral students and pub-
lishing more than 75 refereed journal publications before he
joined the University of South Alabama. In 1997, he decided
to relinquish administrative duties and became a full-time
professor of in the Chemical Engineering Department.
In 1998, Huddleston stepped down as department chair and
was replaced by Harrison. Manish Misra was hired in 2003
when Huddleston subsequently retired in 2002. The closure
of several paper mills in the Mobile area in the late 1990s
and early 2000s (notably International Paper) and the general
downturn in the chemical industry saw a significant decline
in student enrollment in the chemical engineering program.
Furthermore, Hayhurst stepped down as dean of Engineering
(and subsequently left to become dean of Engineering at San
Diego State University in 2001) and Harrison served as in-
terim dean in addition to being chair of Chemical Engineering
until 2003, when John Steadman was hired from the Uni-
versity of Wyoming. Harrison continued to serve as associate
dean of Engineering and chair of Chemical Engineering until
2005 when he was promoted to the position of associate vice
president of Academic Affairs and dean of Graduate Studies.
An external search was initiated to hire a new chair for the
Chemical Engineering Department, with Dhawan serving as
interim chair until December 2006. In January 2007, Srinivas
Palanki was hired from Florida State University as the new
department chair. By this time, the department undergraduate
enrollment had dropped to 74 students from a peak of more
than 150 undergraduate students in the 1990s.


Vol. 47, No. 1, Winter 2013









The past five years have been a
period of significant change for all ::
facets of the department's academic -'::
mission in teaching, research, and
service. The mission of the university
and the college now includes a signifi-
cant research component. In 2007, the
university hired its first vice president
of Research, Russ Lea, from the Uni-
versity of North Carolina. While the
faculty members hired in the 1980s
were essentially expected to spend most
of their time in teaching activities, fac-
ulty members hired in the department
since 2007 were required to develop
a research program of national repute
in addition to their teaching duties.
With the departure of Misra in 2007,
the retirement of Askew in 2008 and
Morisani in 2009, and Dhawan's un-
timely death in 2011, the department
had several faculty openings to fill. Furthermore, in 2007-09
the university received $40 million in federal funding through
the efforts of Alabama Senator Richard Shelby for the con-
struction of a new engineering and computing building, and
the promise of a new doctoral program in engineering. All
these factors coupled together gave the department a unique
opportunity to essentially reinvent itself from the ground
up. The department has hired five new faculty members in
the past five years (four tenure-track lines and one adjunct
line). Kevin West and Silas Leavesley joined the faculty
in 2008, Christy Wheeler and Daniel Balzaretti followed
in 2011 and the latest hire to the department was T. Grant
Glover in 2012. The infusion of these several new faculty
members into the department was followed by a thorough
revision of both the undergraduate and graduate programs as
described in the succeeding sections. In Spring 2010, a new
biomedical engineering track within the doctoral program
in Basic Medical Sciences was approved by the College of
Medicine in response to the growing collaboration between
the colleges of Medicine and Engineering at the University
of South Alabama. In Spring 2012, the Alabama Commission
on Higher Education approved a new doctoral program in
Systems Engineering at the College of Engineering. Several
faculty members in chemical engineering are already actively
involved in research activities consistent with these doctoral
programs. In Summer 2012, the department moved to its new
home in Shelby Hall, the new 155,000-sq.-ft., state-of-the-art
engineering and computing building. The current activities
of the department are described below.

CHEMICAL ENGINEERING AT SHELBY HALL
The department is located in the 4th floor of Shelby Hall. In
addition to a newly designed faculty office suite, the depart-


N~


Research laboratory in Shelby Hall.

ment has access to eight state-of-the-art research laboratories
for conducting cutting-edge research: Green Chemistry Lab,
Specialty Chemicals Lab, Reaction Engineering Lab, Process
Separations Lab, Alternative Energy Lab, Analytical Chem-
istry Lab, Biodevices Lab, and Tissue Culture Lab. Each
laboratory has the necessary bench space, chemical/biological
hoods, glassware, and access to specialty gases for research.
Major pieces of equipment in these laboratories include a gas
chromatograph-mass spectrometer, an intelligent gravimetric
sorption analyzer, a porosimeter, a BET surface area and pore
size analyzer, a differential scanning calorimeter, an atomic
force microscope, high pressure reactors, optical microscopes,
and hyperspectral imaging systems. Furthermore, there are
17 regular classrooms, three large multimedia auditorium
classrooms, five computer labs, five student study areas, and
seven student design rooms that students and faculty use for
instructional activities.

BACHELORS PROGRAM
In 2007-08, the department embarked on a major revision of
the undergraduate curriculum. While the department had re-
ceived its full six-year accreditation in 2006, there was general
consensus among the department faculty that the curriculum
did not reflect new developments in chemical engineering. The
course material being taught at that time had not been revised
since the late 1970s. The assessment process inherent in the
ABET 2000 guidelines was used to make significant changes
to the curriculum after getting input from the department's
stakeholders. Some of the major changes are listed below.
Biology in the chemical engineering curriculum: In re-
sponse to the growing demand for chemical engineers in the
life sciences area (biochemical, biomedical, pharmaceuti-
cal), chemical engineering students are now required to take
Chemical Engineering Education










at least one course in biology. Furthermore, several core
chemical engineering courses (e.g., reaction engineering,
separations) now have modules that focus on engineering
problems with a biomolecular flavor. The basic science core
and electives are now structured in a way that the bachelor's
program in chemical engineering is now a pre-med degree
and all the courses required to take the MCAT are required
courses in the department. To indicate the new emphasis on
biology, the department changed its name to Chemical and
Biomolecular Engineering in 2008. This change has led to
a significant increase in the number of pre-med students in
the Chemical Engineering Program and now about 10% of
our students have a declared interest in eventually pursuing
a degree in medicine.
Introductory courses in engineering: The first course in
engineering is EG101 (Freshmen Engineering Seminar).
West and Leavesley completely restructured this course
in Fall 2008 to include more engineering calculations
and design projects. This course is now a required course
for all freshmen and provides an avenue for freshmen to
interact with engineering faculty during their first year in
the university. The first course in chemical engineering is
CHE 203 (Elementary Principles of Chemical Engineering).
This 4-credit-hour course now includes both material and
energy balances. In the past, this material was covered in two
separate 3-credit-hour courses and this put the department
out of line with most other chemical engineering programs
and made it difficult for transfer students to transition to
the University of South Alabama. This course, restructured
by Wheeler, also introduces students to computer-based
calculations. Furthermore, the software "Sapling Learning,"
which provides interactive home assignments, is used in
this course.
Thermodynamics Sequence: Students in the chemical
engineering program take a sequence of three courses in
thermodynamics: EG 270 (Engineering Thermodynamics),
CHE 331 (Chemical Engineering Thermodynamics I) and
CHE 332 (Chemical Engineering Thermodynamics II).
This sequence has been restructured and modernized by
West in the past four years and covers the fundamentals of
thermophysical property estimation and modeling of non-
ideal pure and multicomponent fluid systems, including an
introduction to multicomponent vapor/liquid equilibria, a
molecular level viewpoint to applications of thermodynam-
ics principles to complex chemical engineering problems
including multicomponent, non-ideal fluid phase equilibria
(VLE, VLLE, SLE), and chemical reaction equilibria. The
concepts of chemical potential, fugacity, and partial molar
and excess properties, as well as complex activity coefficient
models, are introduced to solve these problems. Simulation
and computational tools (EXCEL, MATLAB, ASPEN Plus)
are extensively used. Furthermore, an experimental com-
ponent on measurement and estimation of thermophysical
properties of mixtures has been added.
Vol. 47, No. 1, Winter 2013


Transport Sequence: Students in the chemical engineering
program take a sequence of four transport phenomena courses
that cover fluid mechanics, heat transfer, mass transfer, and
separations. This sequence, restructured by Sylvester and
Leavesley, covers this material from a more fundamental
viewpoint rather than a "unit operations" viewpoint. Fur-
thermore, experimental components on fluid mechanics, heat
transfer, and mass transfer have been added.
Design Sequence: Students in the chemical engineering
curriculum take a series of four design-oriented courses: CHE
372 (Reactor Design), CHE 452 (Process Control), CHE 461
(Process Design I), and CHE 462 (Process Design II). This se-
quence, which was restructured by Palanki, now has laboratory
components in reactor design and process control. Computa-
tional tools such as MATLAB andASPEN Plus are extensively
used in these four courses. Furthermore, the capstone design
experience that is embedded in Process Design II now include
several guest speakers from industry and a set of eight safety
modules developed by SAChE. Separate design projects are
assigned to each student team and are graded by Daniel Bal-
zaretti, an adjunct faculty member with significant industry
experience, as well as by a three-member committee composed
of chemical engineers from local engineering companies.
Laboratory Sequence: Students in their junior year first
take a course in engineering communication (CHE 342) that
is taught in the department and covers the essentials of tech-
nical report writing and oral presentations. Then, they take
a sequence of two 1-credit-hour laboratory courses (CHE
351, CHE 352) and two 2-credit-hour laboratory courses in
the senior year (CHE 441 and CHE 442). The experiments
included in this sequence of courses were developed by West,
Leavesley, Balzaretti, and Palanki and include a mix of tra-
ditional and non-traditional experiments in thermodynamics,
separations, transport phenomena, and unit operations. Cur-
rently, efforts are under way to automate a large number of
these experiments via the use of LABView software.
The Use of Podcasts: With the availability of inexpensive
desktop computing tools for producing podcasts, the depart-
ment has been experimenting with providing some of the
course content via podcasts. In the process control course
(CHE 452) all the lectures are available via podcasts. Students
view these podcasts, developed by Palanki, before they come
to class and during the lecture time, active-learning techniques
are utilized to review this material and solve problems. This
approach has resulted in a significant increase in student
learning outcomes. In the simulation of chemical processes
elective course (CHE 463), students learn to use ASPEN Plus
via podcasts developed by West. This course is offered at an
accelerated pace in the summer term and students have to
come to campus only to take weekly tests. This format has
proven to be very successful as students are able to review the
lecture material online when they are in front of the computer
running ASPEN Plus Programs.










Undergraduate Research: The department recently approved
a new course in research methods where students are given
formal instruction on how to properly read and analyze a sci-
entific journal article, how to perform a literature search, the
proper methods of experiment design, how to properly record
and document data, how to prepare a research proposal, and the
basic principles of the responsible conduct of research. These
tools are used to develop a research project that is typically
conducted over one year. This research counts as two chemical
engineering elective courses in our program. Over one-third of
the juniors and seniors in the chemical engineering program
are involved in undergraduate research with department faculty
members. Several of these students do a senior thesis as part of
the university or departmental Honors program.
These changes have had a significant positive impact on
the undergraduate program. Department enrollment has
increased significantly as shown in Table 1. The department
now attracts some of the best students that join the University
of South Alabama and ranks in the top two in terms of ACT
scores of incoming freshmen among all departments in the
university. The department ranks in the top three departments
in the university in terms of the number of Honors students
graduated. Our alumni and senior exit surveys indicate an
increased appreciation for the education that we provide.
One external measure of the level of preparedness of our
program is our students' performance in the Fundamentals
of Engineering Examination. Students in the department
are required to take (but not pass) this examination before
they graduate, and as shown in Table 2, our student perfor-
mance has increased significantly in the past five years and
compares well with the success rate of students nationally.
Most undergraduate students join the process industry upon
graduation. Recent graduates have been placed in Chevron,
Evonik, BASF, Rockwell, Georgia Pacific,Ascend Specialty
Materials, FMC, and DuPont.

MASTER'S PROGRAM
The department currently has 13 students in
its master's program. In the past, most master's
students had been following the coursework Semester


TABLE 1
Chemical Engineering Undergraduate
Enrollment
Semester Enrollment
Fall 2006 74
Fall 2007 83
Fall 2008 80
Fall 2009 111
Fall 2010 140
Fall 2011 166
Fall 2012 179


option; however, since 2007, the department has completely
restructured its master's program and now almost all mas-
ter's students (over 90%) follow the thesis-option master's
program. Students take a 1-credit-hour research ethics course
and four 4-credit-hour core courses in advanced transport
phenomena, thermodynamics, reaction engineering, and
mathematical modeling in the first two semesters. This is fol-
lowed by a 4-credit-hour directed independent-study course in
the summer, where students work with their research advisor
in conducting a literature survey on a current research topic.
By the end of the first year, the bulk of the coursework is
finished and students are left with only one additional elec-
tive course to take. The second year is focused mainly on
research. Students typically defend their thesis prospectus in
their third semester and finish their thesis at the end of two
years. Student theses in the past five years have focused on
a variety of topics such as characterization of ionic liquids,
development of hyperspectral imaging systems, and modeling
of alternative energy systems. Much of this work has resulted
in refereed journal publications co-authored by graduate
students and faculty.

DOCTORAL PROGRAM
There are three doctoral students supervised by faculty
members in the department; two pursuing doctoral degrees
in the Biomedical Engineering track in Basic Medical Sci-
ences and one in the recently approved Systems Engineering
doctoral program. These are also the first three doctoral stu-
dents in the College of Engineering. Thesis topics range from
biomedical imaging to systems analysis and optimization of
polysilicon manufacture.

RESEARCH INTERESTS
In the past five years, the department has transformed itself
from a teaching-only department to one with considerable
research activity. There are a variety of ongoing fundamen-

TABLE 2
Fundamentals of Engineering Examination Performance
USA Pass National Pass Carnegie Comparator


percentage rercentage rass percentage
Spring 2005 44 86 78
Spring 2006 53 86 71
Spring 2007 25 87 81
Spring 2008 58 87 79
Fall 2008 81 68 64
Spring 2009 89 84 NA
Fall 2009 64 88 67
Spring 2010 100 87 72
Fall 2010 89 84 78
Spring 2011 75 1 87 173
Fall 2011 89 83 165

Chemical Engineering Education






































Faculty and Staff from the Department of Chemical & Biomolecular Engineering. From left to right: Ms. Toni Brown,
Dr. Nicholas Sylvester, Dr. Silas Leavesley, Dr. Grant Glover, Dr. Srinivas Palanki, Dr. Keith Harrison, Dr. Kevin West, and
Dr. Christy Wheeler.


tal and applied research projects in the department that are
funded from a combination of federal and industrial sources.
The department currently has four active NSF grants and a
substantial NIH grant in collaboration with the College of
Medicine. In addition, faculty members in the department
have received funding from Chevron, AkzoNobel, Orion,
Evonik, and Pfizer for applied research projects. Research
expenditures in the past two years have exceeded a million
dollars. Current full-time faculty members and a brief descrip-
tion of research interests are discussed below.
T. Grant Glover (Vanderbilt): The research goal in Dr.
Glover's Laboratory Research Group is to design and build
nanoscale structures for energy storage (hydrogen and meth-
ane storage), as well as carbon dioxide sequestration and air
purification. Varied novel materials are investigated for these
purposes, including Metal Organic Frameworks (MOFs),
Carbon Silica Composites (CSCs), Engineered Silicas, zeo-
lites, metal oxides, and molecular sieves. Particular emphasis
is placed on understanding the physical adsorption of gases
in these materials, as well as reactions that may take place
on the adsorbent surface. In addition to porous adsorbents,
the Glover Research Group is also interested in nanoparticle
impregnates in adsorbent materials and the surface chemistry
of nanoparticles, with particular interest in superparamagnetic
nanoparticles. Building adsorbent materials from a molecular
level provides the opportunity to tailor the material to target
Vol. 47, No. 1, Winter 2013


specific adsorbate functionalities. Molecular-level control of
porosity, topology, and surface chemistry of porous materials
is a significant advance in adsorbent technology over tradi-
tional adsorbents, such as zeolites and carbons, that do not
provide this level of design control. Molecular-level control,
however, also increases the complexity of the design and fab-
rication of these novel materials. Therefore, work is required
to not only rationally and judicially synthesize these novel
materials, but also to understand the novel materials' adsorp-
tion capacity, mass transfer rates, and molecular stability.
B. Keith Harrison (Missouri): This group is developing
a computer program, CHETAH, for predicting the energy
release hazards of pure chemicals and mixtures. This pro-
gram is a unique tool for predicting both thermochemical
properties and certain reactive chemical hazards associated
with a pure chemical, a mixture of chemicals, or a chemical
reaction. The calculations are made using only information
concerning the molecular structure of the components, using
the well-accepted Benson's second order group contribution
technique to predict important thermodynamic properties.
The database of molecular fragments (Benson's groups) used
to describe the molecules is believed to be the largest such
database in existence (with 880 groups currently), allowing
a very large number of possible molecules to be calculated.
Also, CHETAH has an extensive database of molecules for
which the complete necessary thermochemical data are avail-









able from the literature for immediate calculations. CHETAH
also is a useful tool for predicting a number of parameters
associated with the flammability in air of a pure material or
in some cases for mixtures.
Silas Leavesley (Purdue): The over-arching theme of
Leavesley's research has been to apply optical technolo-
gies to problems in the biological, pre-clinical, and clinical
imaging communities. The use of ultra-violet (UV), visible
(VIS), and near-infrared (NIR) light to non-invasively probe,
diagnose, and treat pathologies is an area of high interest.
These wavelengths of light are minimally or non-damaging,
even at relatively large doses of radiation, when compared to
more traditional methods such as x-ray or CT. Light at these
wavelengths, however, experiences a high degree of scattering
and absorption when passing through living tissue. This has
been the greatest limitation of applying optical imaging in the
clinical environment. Research that addresses the limitations
of visible light, therefore, holds great promise, regardless of
whether the solutions are through novel device development,
analytical and computational methods, or a pairing of the
two. Current projects in Leavesley's research group focus on
the application of spectroscopic and hyperspectral imaging
approaches for characterizing tissues at the microscopic and
macroscopic level.
Srinivas Palanki (Michigan): Palanki's research focuses
on the application of systems engineering tools to problems
in engineering and biology. The overall research goal is to
develop a comprehensive methodology for optimal operation
of dynamic systems using automation principles. Using tools
from differential geometry and nonlinear analysis, a novel
framework for real-time optimization of dynamic processes
has been developed. Current applications include design
and operation of packed-bed reactors for portable power and
optimal dose design for cancer therapy. Another research
area is in the systems engineering aspects of utilizing forest
products as an alternative to fossil fuels for the production
of platform chemicals that are used in the bulk and specialty
chemicals industry. Design tools are being used in conjunc-
tion with ASPEN Plus simulations to develop economically
viable routes for renewable energy. Palanki's group is also
working in the development of innovative strategies for
engineering education via the use of podcasts. Of particular
interest is the development of podcasts that can be used across
multiple disciplines.
Nicholas Sylvester (Carnegie Mellon): Sylvester's research
focuses on microcontinuum fluid mechanics and multiphase
chemical reactor analysis. He is currently conducting research
in pipeline systems analysis and catalytic chemical reactor
design with application to hydrogen fuel cell systems.
Kevin West (Georgia Tech): The research in West's labo-
ratory focuses on using a molecular level understanding of


physical organic chemistry, thermodynamics, and kinetics to
develop novel and environmentally benign chemical reaction
and separations processes, as well as to investigate interest-
ing chemical and thermophysical phenomena. Recently, his
group, along with colleagues in chemistry, demonstrated that
incorporating unsaturations into the alkyl chains of n-alkyl
methyl imidazolium-based ionic liquids can significantly
lower the melting points of these salts, while preserving
structural features (the long alkyl chains) which should imbue
the species with non-polar-like solvent properties. Currently,
the thermophysical properties of these systems, including
binary SLE, VLE, and LLE with molecular solvents, are
being characterized to determine where these ionic liquids
can be effectively used as solvents for reactions and separa-
tions. Another research project is directed at characterizing
the thermophysical properties of several promising candidate
ionic liquids for CO2 capture, which has applications in the
CO2 removal from confined spaces such as submarines and
spacecraft as well as carbon capture processes.
Christy Wheeler (Georgia Tech): The research in Wheeler's
lab focuses on novel catalysts, both homogeneous and het-
erogeneous, with applications in a variety of fields including
pharmaceutical synthesis and fuel processing. Her group is
studying the catalytic activity of a new type of "quat" salt
containing sulfur in the hydrocarbon chains. The presence
of the sulfur is an artifact of the way the quat salt was syn-
thesized, via a novel method that allows for tailoring of the
tails of the salt and designing new, task-specific quats. Thus
far, research indicates that these new molecules are active as
phase transfer catalysts, and her group is exploring new pos-
sibilities for their application in two-phase reactive systems.
Current research directions in aerogel synthesis and applica-
tions include incorporation of ceria and zirconia into silica
aerogels, as they have been shown to promote the water-gas
shift reaction. Her group is also investigating deposition of
metals, particularly platinum, from solution during the drying
process and from supercritical fluids. The goal is to synthesize
a material with high catalytic activity employing a minimum
amount of costly precious metals.

SUMMARY
The university is completing 50 years and is excited about
the path to the next 50 years, leading the way in high-caliber
undergraduate and graduate education and cutting-edge
research. The department supports the university's mission
to offer high-quality programs of teaching, research, public
service, and health care that create, communicate, preserve,
and apply knowledge in service to the people of Alabama as
citizens in a global community. We look forward to providing
an innovative education solution that seamlessly integrates
high-quality teaching with cutting-edge research for students
in the Southeastern United States. C


Chemical Engineering Education










LM[ classroom


A Joint Learning Activity in

PROCESS CONTROL AND

DISTANCE COLLABORATION

Between Future Engineers and Technicians







J-S. DESCHPNES1, N. BARKA,1 M. MICHAUD,2 D. PARADISE 2 AND J. BROUSSEAU'
' Ddpartement de mathimatiques, d'informatique et de genie, Universite du Quebec a Rimouski, Rimouski
(Quebec), Canada G5L 3A1
2 Departement de technologies de l'electronique industrielle, Cdgep de Riviere-du-Loup, Riviere-du-Loup
(Qudbec), Canada G5R 1R1


recently available industrial automation technologies
offer many interesting possibilities, including the
operation of production systems from a distance,
access to real-time process and plant data, live video feeds
from the plant, etc. Such technologies are often involved in
distance troubleshooting by service and equipment providers,
to reduce the need (and thus the costs) for personnel travel-
ing. Some companies also integrate similar tools into their
higher management structure as an almost real-time feed of
plant performance and production.Ell For future graduates to
successfully integrate this reality, their education has to be
adequate and kept up-to-date with these technologies.
This project was realized with the participation of Premier
Tech, a world leader in the field of bagging equipment for
different types of products. Their experience with distance
collaboration between teams for the installation and trouble-
shooting of various types of equipment was an important
added value to this project. A joint collaboration between a
university (engineering students) and a college (technical-
level students) was elaborated to also add a dimension of in-
tegrating people from different disciplines and backgrounds to
work toward a common goal: The ability to communicate and
interact effectively with other professionals is an important
skill for graduates,2"1 and it is not often acquired during the
education stage. This project is a response to those needs, at
least in the field of industrial automation and process control.
Vol.47, No. 1, Winter 2013


Most of the work involving remote (or in some cases,
virtual) systems is in the context of distance education.
Methodologies for preparing and building such laboratory
Jean-Sebastien Deschines is a professor of control engineering at the
University du Qu6bec a Rimouski. He obtained his Ph.D. in engineering
from Universite Laval in 2007 in the subject of process control and biopro-
cesses. His research program at UQAR involves the development, modeling,
control, and real-time optimization of marine biomass-based bioprocesses,
mainly microalgae.
Noureddine Barka is a professor of mechanical engineering at UQAR.
He holds a Ph.D. (2011) in mechanical engineering from ETS (Ecole de
Technologie Superieure) in Montreal and a master's degree (2005), also in
mechanical engineering, from Universite du Quebec a Chicoutimi.
Mario Michaud is a teacher at the Cegep de Riviere-du-Loup (College), and
holds a master's degree in engineering obtained in 2006 from Universit6 du
Qudbec a Rimouski. He also has a bachelor's degree in electrical engineer-
ing from the Ecole de Technologie Superieure and a certificate in computer
science from Universite Laval. He has 24 years of teaching and engineering
experience in automation, process control, and industrial computing.
Denis Paradis is currently both teacher and head coordinator of the industrial
electronics technology program at the Cegep de Riviere-du-Loup (Col-
lege). He obtained his B.Sc. in electrical engineering from ETS (Ecole de
Technologie Superieure) in Montreal (Canada) in 1984, and has more than
25 years of teaching and engineering experience in the field of industrial
automation. He is often involved in research projects with UQAR professors
and industrial partners.
Jean Brousseau (P Eng.) is currently dean of undergraduate studies at Uni-
versite du Que6bec a Rimouski (UQAR). He obtained his Ph.D. in mechanical
engineering in 1994 from Universite Laval (Quebec). He is the founder of
engineering at UQAR. He highly contributed to the success of engineering
programs at UQAR, in great part by introducing design workshop courses
throughout the curriculums.
Copyright ChE Division ofASEE 2013










activities can be found in References 5 and 6. Interesting
examples from various engineering disciplines can be found
in References 7-9. Collaboration between students or with a
professor in this context is sometimes possible (e.g., Refer-
ences 8, 10, and 11), although it is rarely a requisite of the
activity. A form of built-in student interaction activity close
to our own was found in Reference 12, where students from
two distant universities joined forces in a long-term product-
development project. Another interesting paper is Reference
13, where very similar planning to our own was done for a
distance controls experiment and interaction between college
and engineering students (with technology from more than 10
years ago), but the experiment was never fully conducted with
the students, thus no results nor feedback from students were
provided. The uniqueness of our work lies in the following:
a more complete focus is placed on the software involved in
an industrial setup (both the controller programming and the
user interface software), with a more concrete collaboration
between the distant teams (one engineering student team and
one engineering-technology student team) on the software
programming and the control design and tuning tasks through-
out the activity. Both teams work toward a common goal in
process control and system automation using the most recent
cutting-edge industrial automation technologies and real-time
remote plant access, sharing their different knowledge on the
subject throughout the four-week duration of the activity.
The paper is organized as follows: first, the general network
and software environment for supporting the activities is pre-
sented. The physical setup used is then presented, along with
the activities it supported. Feedback and appreciation from
the students and faculty are then finally presented, before the
concluding remarks.

NETWORKING ENVIRONMENT
As part of the activities, two types of interaction were
planned: "people-to-people" and "people-to-equipment."
Such events are to be allowed both locally and remotely, at
each site. People-to-people interactions, depending on the
stage of the activities, need to be allowed either in real-time
(synchronous) mode or off-line (asynchronous) mode. People-
to-equipment interactions necessarily occur in real-time,
through industrial hardware and software. For all such events
to occur efficiently, a suitable networking environment had
to be deployed and properly configured.
At the university, students have access to a computer, a large
videoconference screen, a web cam, a microphone, speakers,
and an Internet connection. Whereas the college students, on
their part, work in close proximity to the physical industrial
setup, and have access to a laptop computer with all the same
commodities, and their Internet connection is wireless. Real-
time people-to-people interactions were realized through use
of Skype software. For the asynchronous people-to-people
communications, an e-mail alias was created for each student


team (both at the university and the college), which also in-
cluded the teaching staff e-mails to help them keep track of
the communications.
Remote access to the automation equipment was realized
through a VPN (Virtual Private Network) bridge over the
Internet, linking the LANs (Local Area Networks) of the
two institutions. Access is granted through use of a valid
username and password. This secure connection allows
communications to remain hidden from third-party inter-
ventions. The programming of the industrial controllers
(Allen-Bradley CompactLogix L32E model) is realized with
the RSLogix5000 proprietary software, from either location.
Monitoring of the systems was also possible from both lo-
cations, using either FactoryTalk (from Allen-Bradley) or
InTouch (from WonderWare) HMI (Human-Machine Inter-
face) software. IP cameras were also installed in dedicated
locations to allow real-time visualization of each individual
workstation of the physical system, and another providing
a global view of the installations. These video streams are
accessible via any common web browser, protected again
by a secure login procedure.
Fast response times and high data throughput are required
in automation applications. For this reason, STRATIX 8000
switches have been installed at the core of both Ethernet-
IP networks. These switches are specifically designed for
handling the data traffic between different sections of an
automated plant and network access points. Sustained avail-
ability of the Ethemrnet-IP network is crucial for the adequate
operation of the automated system. Special care was taken at
the moment of installation to minimize the risk of interference
with electromagnetic noise or perturbations throughout the
local networks. A simplified general view of the networking
environment between and at both sites is shown in Figure 1.

ACTIVITY DESCRIPTION
This section will go into further detail about the physical
setup and the activities it allows. In the end, the objective is
to deliver a fully functional automated system for use by a
hypothetical client, in the context of a distant collaboration
between two teams from a same service provider (e.g., an
installation team and a system development team).
The Physical Setup
The physical equipment available at the college is an
educational setup manufactured by the Lab-Volt com-
pany (Instrumentation and Process Control Training System,
# 3531). Two such complete training systems are available,
each comprising two independent workstations, thus accom-
modating a maximum of four student teams. Each system
features a large common stocking tank, usually filled with
water, which serves both workstations. Each of the latter
comprises a variable-speed motor-driven pump, a control
valve (pneumatic, with choice of "air-to-close" or "air-to-


Chemical Engineering Education










Distant site
(University)









Student
teams








ci


*6


open" configuration), two tanks of different dimensions (both
cylindrical, of either small or larger diameter), level sensors
(ultrasonic or capacitance measurement technologies) and
flow meters (either ultrasonic or magnetic technologies).
Such a setup allows coverage of many aspects of process
control engineering, including familiarization with a good
variety of sensor and actuator technologies, their calibration
and location, and the study of various loop configurations. All
controllers are of the Allen-Bradley family, CompactLogix
L32E processors with various I/O cards.
Learning Situations
The focus of both courses (at the university and the college)
is limited to single input-single output (SISO) situations. A
different setup is considered for each student team to limit
the risk of plagiarism, and to allow a wider exploration of
the system possibilities. In general, all four workstations are
used, and the loop configurations include: the control of the
level in either (large or smaller) tank or the control of a flow
stream, while varying the sensor technology and the actuator
configuration. Student teams from each institution are paired
to work together on their given situation over a period of four
weeks. Technician students play the role of the installation
team (being on-site), and the engineering students play the
role of the product development team (e.g., system designers).
The task of the teams is to deliver a fully functional automated
system for a hypothetical client.
The necessary steps include the development of the control


Installations site
(College)




IP Camera
-- ----- ----- ----- -------------....-------... .. .. ..,^ -
Instrumentation and Process I
Control Training System td
Student
E teams






Server -.




- i^^J IRockwell I
EAutomation
.. . . . . I. . . . . . .. . . . . . . I. . . . . .


programs (for the controller and the user interface), so a gen-
eral end-user will be able to use it. Compatibility between the
two programs has to be ensured throughout the development
phase (which involves asynchronous collaboration between
the distant student teams), and its effective behavior on the
real system has to be validated in practical experiments
(synchronous collaboration events). At this stage, the system
dynamics have to be understood and quantified, and the tun-
ing of the controller (PID type) has to be realized. Students
are invited to implement their different tuning methods and
compare their results, as the university and the technology
students have different approaches. Finally, the control per-
formances have to be assessed and validated over the entire
range of operation of the system. After satisfactory results
are obtained, the system is considered to be end-delivered.
At the beginning of the project, university students are
taken to the college to visit the installations and meet their
co-workers for the activity. They are introduced to the basic
procedures for operating the system (start-stop sequences,
safety issues, and protections, etc.) and have the actual op-
portunity to view it running. Specifications are handed out
to the teams, and they can start discussing automation issues
(number of variables, names to be used, conventions, neces-
sary tags, etc.) to ensure the compatibility of their programs.
They then separate to realize the work (university students
have the responsibility of the controller program, while col-
lege students are responsible for the user interface) over the


Vol. 47, No. 1, Winter 2013


Figure 1.
Overview
of the
networking
environ-
ment.









first two weeks. They may communicate asynchronously
during this period by using their assigned e-mail group alias,
as needed, to further discuss different issues.
In week #3, a first (synchronous) interaction session takes
place between the two distant teams. A first implementation
of the two programs, a potential debugging phase plus the
gathering of system response data at different operating
points (for system identification), should be realized by the
end of this session. During the following week, and before the
next interaction session, engineering teams have to analyze
the data and determine proper controller (PID) tuning. The
last interaction session (week #4) consists of implementing
this solution (with potential modifications) and validating
the control performances over the system's entire range of
operation. A final troubleshooting phase of the programs may
also take place in this session, after which the system has to
be end-delivered, fully functional.
The activity took place during the third month of a four-
month semester course, after the adequate preparation of the
students with the automation tools used (L32E Allen-Bradley
controllers, RSLogix5000 programming software, and "In-
Touch" user interface software from WonderWare). Without
such proper introduction, it is the belief of the authors that the
activity could not have been conducted over such a "short"
period, and that students might have been discouraged with
an otherwise longer project.

ACTIVITY EVALUATION
The activity has been conducted twice at the time of this
writing, and was evaluated on both occasions at the two
institutions independently, by the students' point of view
and the teaching teams' point of view. At the university, the
evaluation with the students took two forms: a questionnaire
and a general group discussion. At the college, only the group
discussion took place. Each teaching team at each institution
discussed its impressions before a meeting between the two
teaching teams where they formed a common conclusion on
the matter. These evaluations were realized each year the
activity was held, and were used to improve specific aspects
of the activity for the following year.
Feedback From Students
The questionnaire handed out to university students is sum-
marized in Table 1. Table 2 (page 14) shows the survey results.
The same questionnaire was used on each occasion, covering
the communication and the automation tools, the quality of the
relationship and communications with the other student team,
and general appreciation of the activity. A four-level Likert
scale was used for most questions while some more-specific
questions offered only three choices. On both occasions (2009
and 2010), student attendance was 15 for the course, although
only 14 out of 15 were able to attend the evaluation session
the first year (all were present the second year).


Communication tools were considered either highly appro-
priate (~70%) or somewhat appropriate (~30%) for the activ-
ity, and very user-friendly (~40%) or somewhat user-friendly
(~60%) in both occasions. Most student had never used Skype
before, and active student participation in communications
increased from 64% to 80% between the two years. Quality of
communications was best perceived the second year, as 53%
vs. 29% considered there was no problem at all (or only very
minor ones) at the technical level. None of the students were
experts in network technologies. All students (but one, the
second year) considered controller programming as highly or
somewhat important to learn in an engineering curriculum.
Programming a user interface was, however, considered less
essential, as 20% in each year even felt it was not important.
Quality of the interactions with college student teams has
increased over the years as 73% felt it was excellent the sec-
ond year (vs. 57% the first year). This could be explained by
the fact that a physical encounter between all students at the
beginning of the project only took place the second year, and
helped improve camaraderie. After the activity, the students
felt they had achieved a high (~10%) or sufficient (~80%)
level of competence on controller programming (similar each
year). Students felt less competent, however, on user interface
programming the second year (53% vs. 85%), as this task was
left to the technical-level students on that occasion (to even
the workload between student teams). Student satisfaction
about the overall experience was very high or high (~90%)
on both occasions. All of them affirmed it definitely has its
place in an engineering formation.
A group discussion was held with the university students,
where the strong and weak points of the activity were under-
lined, and what in their opinion should be kept or changed for
the next time. The strong points on which everybody agreed
were: the possibility to interact with a distant student team, the
interaction experience with future technicians, the high quality
of the automation equipment and technologies involved, and
the quick dynamics (rapid time constant) of the system that
allowed a quick feedback during test phases. Students also
greatly appreciated the ability to visit the installations and
meet the other student team in person at the beginning of the
project. The absence of a written report was also something
students felt should be kept. On the other hand, students felt
they should have received more specific directives on what
was to be done, and provided with a systematic methodol-
ogy to proceed for the programming. They also wished more
formal instructions were provided on the role of each team for
each step of the process, and some did not like to have to rely
solely on the other team for something to be done.

Feedback From the Teaching Staff
It is the opinion of both teaching teams that the activity was
a success. Most teams have performed very well, and learned
much from interacting with their counterparts. They all had to


Chemical Engineering Education













TABLE 1
Survey Questions for University Students
Theme 1 Communication Tools
Survey Questions Choice ofAnswers
a) Very good.

Ql. Regarding the communication tools used, how would you rate their user-friendliness? b) Somewhat good.
Q2. Regarding the communication tools used, how would you rate their appropriateness for the activity? c) Somewhat bad.

~~~~~~____~~~~~____________________________________d) Very bad.
a) Main user / Leader.
Q3. About your role in the communications, what was your degree of involvement in the team? b) One of the users.
c) Mainly an observer.
Theme 2 Quality and success of the communication
a) No problems at all.
b) A few minor problems.
Q4. Did you experience any communication problems? c) Quite a few problems, some
of them major ones.
d) A lot of major problems.
a) Expert.
b) Knowledgeable.
Q5. How do you rate your level of knowledge on network technologies? bKnwegal
c) Very limited knowledge.
d) No knowledge at all.
Theme 3 Automation tools
a) Very pertinent.

Q6. How do you perceive the pertinence of learning about industrial controller software in engineering? b) Somewhat pertinent.
Q7. How do you perceive the pertinence of learning about user interface software in engineering? c) Somewhat not pertinent.

d) Not quite pertinent.
a) Very competent.
Q8. How would you now rate your competence on the use of the industrial controller software? b) Somewhat competent.
Q9. How would you now rate your competence on the use of the user interface software? c) No or somewhat low
r c) No or somewhat low
competence.
Theme 4 Team interaction and cooperation
a) Very good.

Q10. About the interaction with college students, how would you rate their degree of cooperation? b) Somewhat good.
Q 11. How would you rate their level of competence? c) Somewhat bad.

d) Very bad.
a) Main person interacting.

Q12. About your role in these interactions, what was your level of participation? b) One of the persons
interacting.

c) Mainly an observer.
Theme 5 General appreciation
a) Very good.
Q 13. Overall, how do you perceive the pertinence of distance interaction with another team? a)-----------
Q14. Overall, how do you perceive the pertinence of interacting with future technicians? b) Somewhat good.
Q 15. Overall, how do you perceive the pertinence of this activity in your curriculum? c) Somewhat limited.
Q16. Overall, how do you perceive the global added-value of this activity? d) Quite bad.

Theme 6 General comments
Please state your personal comments on the activities, suggestions for the future, etc.


Vol. 47, No. 1, Winter 2013











learn from each other about terms that describe similar
phenomenon, for example. Some were even impressed
(favorably) by the level of knowledge of their counter-
parts. Communication between teams was very good in
general (one exception over the last two years), and so
was the level of collaboration. The exchange of informa-
tion was efficient between teams, and the students were
respectful towards each other. The last comments from
the students about receiving more detailed instructions for
the activity shows that they have to further develop their
confidence and better tools for project management, as
relying on others is unavoidable in the job market. This is
an aspect that both teaching teams will insist on in the fol-
lowing years to best prepare the students for this reality.

CONCLUSION
This paper presented an innovative activity conducted
between college students (future technicians) and univer-
sity students (future engineers), in the field of process
control and industrial automation. Learning activities
were presented, followed with feedback from the students
and the teaching teams. Results showed that students
worked and understood each other very well despite their
different skills, terminologies, and background. Training
objectives were attained, while students also greatly ap-
preciated the experience.

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Educ., 18(1), 53, (2010)
7. Tanyildizi, E., and A. Orhan, "A Virtual Electric Machine Laboratory
for Effect of Saturation of the Asynchronous Machine Application,"
Comput. Appl. Eng. Educ., 17(4), 422 (2009)
8. Liang, J.S., "Design and Implement a Virtual Learning Architechture
for Troubleshooting Practice of Automotive Chassis," Comput. Appl.
Eng. Educ., 18(3), 512 (2010)
9. Dominguez, M., JJ. Fuertes, M.A. Prada, S. Alonso, and A. Moran,
"Remote Laboratory of a Quadruple Tank Process for Learning in
Control Engineering Using Different Industrial Controllers," Comput.
Appl. Eng. Educ., not yet published
10. Jara, C.A., F.A. Candelas, F. Torres, S. Dormido, F. Esquembre, and


TABLE 2
Survey Results for University Students in 2009 and 2010
Question Year a) b) c) d)
2009 36% 64% 0% 0%
Q1.
2010 40% 60% 0% 0%
2009 71% 29% 0% 0%
Q2.
Q 2010 67% 33% 0% 0%

2009 7% 57% 36% N/A
Q3.
Q 2010 7% 73% 20% N/A

2009 29% 57% 7% 0%
Q4.
Q 2010 53% 40% 7% 0%

2009 0% 43% 43% 14%
Q5.
2010 0% 33% 60% 7%
2009 71% 29% 0% 0%
Q6.
Q 2010 60% 33% 7% 0%

2009 29% 50% 14% 7%
Q7.
2010 27% 53% 20% 0%
2009 14% 79% 7% N/A
Q8.
2010 7% 80% 13% N/A
2009 14% 71% 14% N/A
Q9.
Q 2010 0% 53% 47% N/A

2009 57% 36% 7% 0%
Q10.
0 2010 73% 0% 7% 20%

2009 79% 21% 0% 0%
Qll.
2010 67% 13% 20% 0%

2009 14% 71% 14% N/A
Q12.
2 2010 0% 93% 7% N/A

2009 93% 7% 0% 0%
Q13.
Q3 2010 60% 33% 0% 7%

2009 86% 14% 0% 0%
Q14.
2010 47% 40% 13% 0%
2009 100% 0% 0% 0%
Q15.
5 2010 53% 47% 0% 0%

2009 64% 36% 0% 0%
Q16.
6 2010 27% 67% 7% 0%


0. Reinoso, "Real-time collaboration of virtual laboratories through
the Internet," Comput. Educ., 52, 126 (2009)
11. Gravier, C., J. Fayolle, and B. Bayard, "Coping with collaborative
and competitive episodes within collaborative remote laboratories,"
Proc. Int. Conf. Remote Eng. Virtual Instrum, (REV'08), Duesseldorf,
Germany, September (2008)
12. Zavbi, R., and J. Tavcar, "Preparing undergraduate students for work
in virtual product development teams," Comput. Educ., 44,357 (2005)
13. Baker, JR., D.L. Silverstein, and J.M. Benson, "A Multi-Institutional
Interdisciplinary Distance Controls Experiment: Bringing Engineering
and Engineering Technology Students Together," Proc. ASEE Annual
Conf., Montreal, Quebec, Canada, June (2002) 0


Chemical Engineering Education










i laboratoryy


HIGH-PERFORMANCE

LIQUID CHROMATOGRAPHY

In the Undergraduate Chemical Engineering Laboratory








DOUGLAS D. FREY, Hui Guo, AND NIKHILA KARNIK
University of Maryland Baltimore County Baltimore, MD 21250


he origin of modem high-performance liquid chroma-
tography (HPLC) can be traced back to the pioneer-
ing work on this technique performed in the 1960s
by Csaba Horvdth at Yale University and by Josef Huber at
Amsterdam University.1121 HPLC is based on the fundamental
transport phenomena principle that if the mass-transfer effi-
ciency in a packed bed of porous adsorbent particles is greatly
increased by reducing the particle diameter (most often to the
range of 3 to 6 pm) then a large number of "theoretical equi-
librium plates" can be achieved in a relatively short column,
albeit with a high inlet column pressure. More recently, the
basic HPLC method has been extended to produce "ultra"
high-performance liquid chromatography (UHPLC) by the
use of packing particles with diameters of 2 pm or less.t11

DESCRIPTION AND JUSTIFICATION
OF GENERAL APPROACH
The basic instructional objective of this laboratory exer-
cise is to introduce chemical engineering students to both
HPLC and size-exclusion chromatography (SEC) as well to
industrial applications of chromatography in general by using
experiments that can be performed conveniently in a typical
undergraduate laboratory setting. A major reason for selecting
HPLC and SEC in this context is that these methods, especial-
ly when combined, yield experiments that can be performed
rapidly. Rapid experiments in turn permit students to verify
reproducibility, to establish trends and investigate them in an
interactive manner, and to perform related tasks that would be
impossible to accomplish in the time available if slower modes
Vol. 47, No. 1, Winter 2013


of chromatography were used. Furthermore, HPLC in its own
right is a suitable topic for chemical engineering students to
study since it is widely used as an analytical technique in
the biochemical and environmental engineering subfields
of the broader chemical engineering discipline. Large-scale
HPLC is also employed industrially in several applications,
especially in cases where the rapid separation achieved can
be exploited to minimize undesired degradation reactions
during processing. Perhaps the most prominent example of
this last consideration is the commercial process used by Eli
Lilly to produce the Humulin brand of recombinant human


Douglas D. Frey is a professor in the Department of Chemical, Bio-
chemical, and Environmental Engineering at the University of Maryland
Baltimore County (UMBC). He received his Ph.D. in chemical engineer-
ing from the University of California, Berkeley, in 1984. His research and
teaching interests are in the areas of separation processes, transport
phenomena, and the chromatography of biological macromolecules.
Hui Guo is a graduate student in the Department of Chemical, Bio-
chemical, and Environmental Engineering at UMBC. She obtained her
M.S. degree in chemical and biochemical engineering from UMBC in
2008. Her research interests are in the areas of protein chromatography,
downstream bioprocessing, and the analysis of traditional Chinese
medicines by liquid chromatography.
Nikhila Kamik is a graduate student in the Department of Chemical,
Biochemical, and Environmental Engineering at UMBC. She obtained
her B.E. degree in chemical engineering from the University of Mumbai
in 2007 and her M.S. degree in chemical and biochemical engineering
from UMBC in 2011. Her research interests are in the areas of biotech-
nology bioseparations, and protein purification.

Copyright ChE Division of ASEE 2013










insulin where it has
been reported that an
HPLC column that
is 80 liters in vol-
ume is employed.t3'
Furthermore, experi-
ence with HPLC is
particularly valuable
to students special-
izing in biochemical
engineering since
large-scale chroma-
tography conducted
at low pressure is
often used in the
commercial produc-
tion of proteins, and
the principles un-
derlying both HPLC
and large-scale, low-
pressure chromatog-
raphy are similar.
It is also useful to
introduce students
specializing in bio-
chemical engineer-
ing specifically to
the technique of SEC
since large-scale ver-
sions of this tech-
nique are employed in


a variety of industrial applications.


One particular advantage of SEC for industrial applications
is that it generally preserves the biological activity of proteins
since ideally it does not involve physical adsorption at a
surface, but instead relies solely on a steric exclusion effect
for the separation mechanism. Examples of the application
of large-scale SEC in industry include its use as the final
"polishing" purification step in the commercial processes for
several therapeutic protein drugs, for buffer exchange and
desalting, for DNA removal from protein solutions, in protein
refolding methods, and for large-scale plasmid purification
in gene therapy and DNA vaccination applications.t3-71 SEC
also generally exhibits highly predictable behavior based on
principles that are commonly taught in the undergraduate
chemical engineering curriculum, such as the plate theory
of linear chromatography and the entropy contribution to
the phase equilibrium constant, which further enhances its
educational value.
Finally, due to the relative simplicity of the experiments
described here, and because the background needed for them
is contained in standard chemical engineering or biochemical
engineering textbooks,t8'9 these experiments can be conve-
niently taught as a self-contained exercise that introduces


students to chromatography. If desired, however, these experi-
ments can also be combined with other educational activities
involving chromatography that have been proposed by oth-
erst10t131 in order to extend those activities.

EXTENSION OF HPLC EXPERIMENTS INTO
BROADER AREAS
In addition to its extension to other chromatographic meth-
ods, including those where true adsorption takes place, this
laboratory exercise can also be extended so that it illustrates
a variety of additional chemical engineering principles such
as heat transfer, Darcy's Law and the Blake-Kozeny equation,
the Hagen-Poiseuille Law, Taylor dispersion in a tube, the
operation of a positive displacement pump, chemical reac-
tion equilibrium, and numerical simulations using differential
material-balance relations. Table 1 summarizes a variety of
experiments of this type that are suitable for inclusion in a
chemical engineering laboratory course. Some of the experi-
ments described in Table 1 are based on original concepts
developed by the authors while others are adaptations of
experiments described by others .[14,151 In the remainder of this
article, Topics 1-4 from Table 1 (i.e., separation of mixtures in
the analytical and overloaded regimes, measurement of chro-


Chemical Engineering Education


TABLE 1
Experiments incorporating chemical engineering principles that can be performed using an HPLC
instrument. Topics denoted by the asterisk are currently used in the undergraduate biochemical
engineering laboratory at UMBC.
Topic Experimental Topic Chemical Engineering
Number r Principle
1 Separation of mixtures in the analytical and overloaded Separation processes
regimes using various chromatographic methods
2* Measurement of liquid-solid equilibrium distribution coef- Phase equilibrium
ficients from chromatographic elution times
3* Investigation of band broadening mechanisms inside a chro- Mass transfer
matographic column

4* Investigation of the effect of molecular size and shape on the Phase equilibrium and statistical
elution time in size exclusion chromatography mechanics
Investigation of Darcy's Law, the Blake-Kozeny equation, Fluid mechanics
5 the Hagen-Poiseuille Law, and the operation of a positive
displacement pump
6 Measurement of liquid-phase diffusion coefficients by inves- Mass transfer
tigating Taylor dispersion in an open tube
SUse of inverse size-exclusion chromatography to determine Materials science
the pore structure of a porous solid
SUse of equilibrium size-exclusion chromatography to deter- Biochemical reaction equilib-
mine biochemical reaction stoichiometry. rium and stoichiometry
9 Heat effects caused by viscous dissipation during flow in Heat transfer
porous media
Measurement and interpretation of non-Gaussian chromato- Numerical simulations using
10 graphic band shapes differential material-balance
relations performed using Aspen
Chromatography


































Figure 1. Hewlett Packard/Agilent 1050 HPLC system assembled from donated
equipment and interfaced to FreeChrom software running on a notebook


computer as described in text.

matographic distribution coefficients, investigation of band
broadening, and investigation of the effect of molecular size
on elution times in SEC) will be discussed in detail since they
form the basis for the chromatography experiments employed
in the undergraduate laboratory at UMBC.

LABORATORY DESCRIPTION
Experimental Equipment
HPLC instruments have the reputation of being well
beyond the financial means of the typical undergraduate
chemical engineering laboratory. Instead of purchasing
new equipment, however, it is frequently possible to take
advantage of the fact that university and industrial research
laboratories that use HPLC periodically upgrade to the
newest HPLC models, and when they do they are left with
the problem of how to dispose of their older equipment in
an environmentally conscious manner. Consequently, it is
often possible to obtain donated, older HPLC equipment
from these types of laboratories that is still highly suitable
for an undergraduate chemical engineering laboratory, in
which case undergraduate chemical engineering laboratories
can participate in the efficient "recycling" of these older
instruments.
One potential problem with obtaining older donated
HPLC equipment is that the software needed to operate this
older equipment is likely installed on obsolete computers
of comparable age, and the cost of a software upgrade can
also be prohibitive in many cases. Furthermore, most com-


mercial software for HPLC data acquisi-
tion and instrument control is relatively
complex and therefore impractical to
use in the undergraduate laboratory
where students have a limited amount
of time for software training. To solve
this problem, the authors of this article
have developed simple and completely
portable chromatographic data acquisi-
tion software named FreeChrom that is
based on a compiled LabVIEW program.
This software, along with a brief user
manual, is available on request from
the authors. Consequently, if any HPLC
pump and detector can be obtained that
are controllable manually (e.g., by an
integrated keyboard) and that have ana-
log outputs, such as a "chart recorder"
output option, then a highly functional
and simple-to-use HPLC system can be
assembled virtually for free. One particu-
larly convenient option is for students to
install the FreeChrom software directly


onto their own notebook computers for
data collection. For those instructors who
are familiar with LabVIEW software, a more sophisticated
system for data acquisition and HPLC instrument control
can be developed with a modest amount of effort.[N61 Ad-
ditional functionality can also be achieved by using a more
complete chromatography software system, several of which
are available at a modest cost.1171

Figure 1 shows a Hewlett Packard (now Agilent) Model
1050 HPLC system assembled as described above consisting
of one HPLC pump and two UV-Vis absorbance detectors
that were donated to UMBC by BioAnalytical Systems
Incorporated (BASi) located in Baltimore, MD. For the
system illustrated in Figure 1, the analog outputs from the
UV-Vis absorbance detectors along with the analog pressure
output from the pump are first directed to a LabJack Model
U12 analog-to-digital converter board, and the digital sig-
nals from the board are then directed to a computer using
a standard USB port where they are visualized and stored
by the FreeChrom software. The system shown in Figure 1
also incorporates a Rheodyne Model 2799 sample injection
valve and a 30 cm X 4.6 mm ID Toso Bioscience TSKgel
Super SW3000 SEC column containing 4-urn-diameter
silica particles. The cost for setting up the system shown
was approximately $2,000 in current dollars since only the
injection valve, the LabJack board, and the HPLC column
had to be purchased. Alternatively, if donated equipment is
not available, then a comparable HPLC instrument can be
assembled from components obtained from various used
equipment websites for approximately $5,000.


Vol. 47, No. 1, Winter 2013










Experimental Procedures
Topics 1 4 shown in Table 1 can be investigated using
the following procedures: 1) prepare 600 mL of elution
buffer by mixing 117 mL of 0.2 M NaH2PO4 solution
containing 0.6 M NaCl with 183 mL of 0.2 M Na2HP04
solution containing 0.6 M NaCl, then add 300 mL of deion-
ized water, and then titrate with 1 M HC1 or 1 M NaOH as
needed to pH 7; 2) vacuum filter the elution buffer using
a 0.2 Rm pore size nylon membrane filter (What-
man, Sanford, ME, USA); 3) prepare a feed sample
by dissolving 3 mg/mL of each protein into 10 mL
of filtered elution buffer solution, and then filter the
sample again with a PVDF syringe-driven filter with
0.2 Um pore size (Whatman, Sanford, ME, USA); 4)
use a 30 cm X 4.6 mm ID Toso Bioscience TSKgel
SuperSW3000 column, a flow rate of 0.25 mL/min,
and a 10 VL sample loop to obtain results similar to
those shown in Figures 3-5; and 5) use a 30 cm X 7.8
mm ID Toso Bioscience TSKgel G3000SWXL col-
umn, a flow rate of 0.7 mL/min, and sample loops of
various sizes to obtain results similar to those shown
in Figure 6. Suggested experimental procedures for
the remaining topics listed in Table 1 appropriate
for either a single three-hour laboratory session or
for two such sessions can be obtained directly from
the authors.

Instructional Objectives and
Learning Outcomes
As mentioned earlier, variations of Topics 1 4
from Table 1 have been combined at UMBC into
a single exercise that was conducted as part of the
undergraduate biochemical engineering laboratory
course, although these experiments could equally well
be incorporated into a standard chemical engineering Fi
laboratory course especially if one of the goals of the
latter course is to introduce students to the field of
biochemical engineering. Typical instructional objectives for
Topics 1 4 are as follows: 1) to illustrate both HPLC and
SEC in various operating regimes using experiments that can
be conveniently performed in an undergraduate laboratory
setting; 2) to illustrate the basic principles and terminology
of chromatography; and 3) to measure and interpret theo-
retically the column plate height and the relation between
molecular weight and the elution time for proteins. The
major student learning outcome for Topics 1 4 is that, after
performing these experiments, students will have the ability
to predict and understand chromatographic behavior (such
as the retention times, the band widths, and the separation
resolution achieved) from knowledge of relevant physical
properties (such as the protein molecular weight, the fluid
flow rate, the feed volume amount, the particle size of the
column packing, and the shape and size of the pores in the
column packing particles).


DATA ANALYSIS
The Equilibrium Constant in Size-Exclusion
Chromatography
Consider a group of molecules (generally termed the
eluite or the analyte) that consists of a single, dilute species
distributed within a carrier fluid. It will be assumed here that
the eluite forms a continuous band inside a chromatography
column and that, as this band travels convectively through the


Protein


Column packing particle


- Accessible pore volume

SPore


gore 2. Cylindrical pore model (top) and fibrous solid cylinder
model (bottom).
column, the mass-transfer efficiency between the fluid and the
porous particles in the column is large enough so that mass-
transfer equilibrium is closely approached between these two
regions. In this case, if the average amount of eluite contained
within the column packing particles per unit volume of these
particles is denoted as q.1uite and the average concentration
of the eluite in the fluid phase contacting these particles at
equilibrium is denoted as Celuite, then an equilibrium constant,
denoted here as K can be defined as the ratio qeuite/Cuit.
Furthermore, by using the solute movement theory discussed
by Wankat,E81 the velocity of an eluite band, denoted as L/t
where L is the column length and t is the elution time, can be
expressed in terms of the mass-average velocity of the eluite
molecules constituting the band as follows:

L/t SbCIt Ufld(
bC-luite + (1- b) q,,,i, (1)


Chemical Engineering Education









In Eq. (1), Ufluid is the average interparticle fluid velocity
(sometimes also termed the average interstitial fluid velocity
or the average linear fluid velocity) and Eb is the interparticle
bed porosity, sometimes also termed the external porosity.
If the product Keq Ci"te is substituted for qeluit in Eq. (1),
and if U uid is written as L/t0, where to is the elution time for
a molecule that is sufficiently large that it does not enter the
particle pores, then Eq. (1) yields the following basic relation
describing linear chromatography"]:

K -(t-t) e (
t,, (l- ,) (2)
eq to (l -Eb)

In Eq. (2), eb = 0.35 in a properly packed column containing
spherical particles, and to is given by L/(usupr /b) where u ur is
the superficial fluid velocity given by F/A and where F is the
volumetric flow rate through the column and A is the column
cross-sectional area. Note that the average interparticle fluid
velocity, u0fu, is given by uuper /EIb and that the equilibrium
constant Keq is often denoted as K in the chromatographic
literature. In certain studies of SEC the ratio K e/p (generally
denoted as K S0) has been used as an equilibrium constant,
where ep is the intraparticle porosity defined as the volume
fraction of the particle accessible to a small molecule whose
radius is much smaller than the particle pore radius.
For the case where the eluite is a protein, the relation be-
tween Keq and the protein size depends in a complex way on
the structure of both the protein and the particles constituting
the column packing. One useful theoretical result for this
case can be obtained by representing SEC as the hard-sphere
interaction of a solid spherical protein of radius proteinn and
a cylindrical pore of radius r po, in which case there is no
enthalpy difference between molecules that are inside and
outside of the particles. Under these conditions K q is given
by the expression exp (AS/R), which can in turn be expressed
as the product of the particle porosity and the ratio between
the accessible pore volume and the total pore volume as fol-
lows (see Figure 2):
Keq = e (1-rpr /rpor )2 (3)

Additional details of the derivation of Eq. (3) and other
expressions for K q based on other pore geometries are dis-
cussed in various references.[P"8"91
An alternative representation of SEC results if the column
packing particle is represented as a randomly oriented, tangled
mass of long fibrous cylinders of radius rber. For this case,
Laurant and Killander developed the following result based
on earlier work by Ogston1201:

Keq = exp(-tILf, (r..e, +rfbo )2) (4)

In Eq. (4) Lfber is the total length of fiber per unit volume
in the particle. An alternative form for Eq. (4) results by not-
ing that nLiber r0b, is the volume of fibers per unit volume of
Vol. 47, No. 1, Winter 2013


particles, so that this quantity can also be written as 1 ep.
Eq. (4) can then be rewritten as
K, =exp(-(1- p)(l+ro, /rfibr )2) (5)

Many globular proteins are nonspherical in shape, in which
case the proper value of rprotei to use in the relations given
above is uncertain. Among other possibilities, the Stokes ra-
dius determined from the Stokes-Einstein equation, the radius
determined from intrinsic viscosity measurements, the radius
of gyration determined from light scatting experiments, and
the average radius determined from the three-dimensional
protein structure have all been investigated as a means for
interpreting elution time in SEC.1"211
A simple option that students can investigate as an approach
to fit data is an equivalent-volume-sphere method based on
the recent review of protein densities given by Fischer et al.1231
In particular, by evaluating protein density data published in
the literature, Fischer et al. concluded that the density of the
anhydrous form of a protein varies from 1.39 to 1.52 gm/cm3
and, to a good approximation, this density is a monotonic
function of the protein molecular weight. If the densities
tabulated by Fischer et al. for a representative set of proteins
are examined, it follows that a reasonable value for the aver-
age protein density is 1.43 gm/cm3. In addition, if a protein
with the molecular weight M. is represented as a sphere with
a uniform density of Ppoin. and a mass per molecule of Mw /
Na, where Na is Avogadro's number, then this protein would
have a radius given by

r proiin =(3 M /(4ltNaPp r i,,_ ))1/3 (6)

To account for the hydration that occurs when proteins
are in aqueous solution, it will be assumed here that a layer
of water molecules that is 0.3 nm thick is strongly bound to
the outer surface of the protein.1231 By substituting numerical
values into the relations given above, the final relation used
here between rprod (in nm) and Mw (in Daltons) for a hydrated
protein can then be written as
rproii. =(0.057xMw3)+0.3 (7)

Students may also find it useful to develop a more precise
version of Eq. (7) by replacing Pproinave in Eq. (6) with the full
empirical correlation developed by Fisher et al.1231 for ptein as
a function of Mw. Eq. (7) can be combined with either Eq. (3)
or Eq. (5) to obtain a direct relation between K q and M for
either the cylindrical pore model or the fibrous solid cylinder
model which students can compare with experimental results.

Plate Theory of Linear Chromatography
For the purpose of interpreting measurements of chromato-
graphic band widths, this section presents what might loosely
be described as the "plate theory of linear chromatography,"
although in reality the development given here combines ele-
































0 10 20
Time (min)


Figure 3. Size-exclusion chromatography of a protein
mixture using a 30 cm X 4.6 mm ID Toso Bioscience TSK-
gel Super SW3000 column. The flow rate was 0.25 mL/
min and the mobile phase was a 0.1 M phosphate buffer
with 0.3 M NaCI at pH 7. RNSA: bovine ribonuclease
A; BLAC: bovine 3 lactoglobulin A; BSA: bovine serum
albumin.
ments of several closely related theories. Detailed discussions
of the various theories of linear chromatography are given in
several references.[11,85241
To simplify the following development, it will be assumed
that the eluite band has a Gaussian shape with a maximum
concentration occurring at the time t, a standard deviation in
terms of time given by oa, and a variance given by o,2.
Since the individual contributions to band broadening occur
by statistically independent processes, it follows that
CF2 o. +L ,g 2 + +(V / F)2 /12 (8)
tota didffusion + dispersion +( panicle + exta +(V I / (
where the first four terms on the right side account for the
effects of axial diffusion in the interparticle fluid, axial dis-
persion in the interparticle fluid, intraparticle diffusion, and
extra-column broadening. The final term on the right side of
Eq. (8) accounts for the volume of the feed material used,
denoted as Vfe. By utilizing the analogy between a series of
equilibrium plates and a continuous chromatographic column,
it follows that the number of equilibrium plates provided by a
chromatographic column, N, is given by N = t2/o102 and the
reduced plate height, h, is given by h = L/(N d p) where dP is
the particle diameter and L is the column length. For the case
where the band shape is not Gaussian, o2. and tin the above


relations should be replaced by the second central moment
of the eluite band concentration profile and the first absolute
moment of this profile, respectively.
When the final two terms on the right side of Eq. (8) are
negligible, the reduced plate height when plotted as a func-
tion of the reduced fluid velocity uflud d p/Dm (denoted here as
v), where D. is the diffusion coefficient of the eluite in free
solution, generally follows the relation:
h=A(v)+B/v+Cv (9)

In Eq. (9), the three terms on the right side correspond to the
first three terms on the right side of Eq. (8) and are commonly
referred to as the "Aterm," the "B term," and the "C term" of
the plate height equation. For a properly packed chromatogra-
phy column, the parameter B in Eq. (9) is generally between
the values of 2 and 4 and the parameter C, which typically has
the value of 0.05, is given by the following relation:

C- = (K (1-,)) (10)
30(eb +(l-e-)Kd)2

where is the diffusion coefficient of the protein in free
solution divided by the diffusion coefficient of the protein
inside the particle.
Under ideal conditions the function A(v) in Eq. (10) is typi-
cally represented by the expression v113, but often A(v) needs
to account for various nonidealities.t11 For example, since they
contain highly porous silica particles, the columns employed
in this article are prone to particle fracturing and subsequent
bed consolidation. Under these conditions it is common for
a well-mixed void to form at the column inlet in which case
A(v) includes a contribution given by L / (dp (Viutio/ Nvoid)2) ,
where Vo is the elution volume for the eluite and Vvd is
the volume of the well-mixed column void.5111 Other factors
that contribute to the value of A(v), particularly for columns
whose performance has been degraded through extensive use,
are discussed by Guo and Frey.1251

ILLUSTRATIVE RESULTS
A typical chromatogram for a feed sample containing
bovine serum albumin (Sigma product A4503, denoted here
as BSA), bovine P3 lactoglubulin A (Sigma product L0130,
denoted here as BLAC), and bovine ribonuclease A (Sigma
product R4875, denoted here as RNSA) as the eluites and
obtained using the TSKgel SuperSW3000 SEC column is il-
lustrated in Figure 3. Note that a small feed volume of 10 pL
was used to obtain the results shown in the figure to facilitate
the measurement of basic parameters such as the value of Keq .
As shown in the figure, the time needed for the experiment
is less than 20 minutes, so that a large number of different
conditions can be conveniently investigated. For example, in
a typical three-hour laboratory session, students at UMBC
have been able to conduct different experiments in which the


Chemical Engineering Education










liquid flow rate and other factors are varied. Note that a
fourth band is present in the chromatogram shown in the
figure. This same band is also present when only BSA
is used in the feed sample, in which case this band most
likely corresponds to the dimer form of BSA, which is
reported to be present in the commercial preparation
of this protein used here."26
By using data obtained from several proteins of
different sizes, students are generally able to fit ex-
perimental Keq values using Eqs. (3), (5), and (7) with
reasonable values for the fitting parameters. This is
illustrated in Figure 4 where the values rpe = 5.7 nm,
rfi, = 1.25 nm, eb = 0.35, and ep = 0.95 for the cylindri-
cal pore model and ep = 0.87 the fibrous solid cylinder
model are employed to fit data for four proteins. These
fitting parameters can be compared to previous results
reported by Tarvers and Church1221 for a Toso Biosci-
ence TSK G3000SW column, which is similar to the
TSK SuperSW3000 column used in Figures 3 and 4.
According to Tarvers and Church, thyroglobulin (Mw
= 680,000) is the smallest protein used in their study
that is fully excluded from the particle pores in their
column. This indicates that the radius of thyroglobulin,
which according to Eq. (7) is 5.3 nm, should correspond
to the pore radius in the particles of their column. This
is in reasonable agreement to the value of 5.7 nm used
for rPO as a fitting parameter in Figure 4. Tarvers and
Church also found when using the TSK G3000SW
column that the dipeptide Gly-Tyr (Mw = 238) has a
K eqvalue of 0.85, which should also be a reasonable
eq
estimate of e for this column due to the small size of
this molecule. This value is somewhat smaller than the
value of eP = 0.95 used in Figure 4 for the cylindrical
pore model. In contrast, the fibrous solid cylinder model
used in Figure 4 employs a more reasonable value for
e while also achieving a better overall fit of the data,
in which case this latter model would appear to be the
preferred one for this column.
Reduced plate heights for the TSKgel SuperSW3000
column measured as a function of the reduced veloc-
ity are illustrated in Figure 5, which shows that the
reduced plate height is comparatively large and nearly
constant in value. In order to investigate the source of
the behavior shown in Figure 5, the column used was
disassembled, and it was observed that a void of ap-
proximately 0.3 cm in length was present at the column
inlet. According to the discussion given earlier, this void
should have contributed an increment of 13.5 to the total
reduced plate height. If this value is subtracted from the
reduced plate heights shown in the figure, the remain-
ing plate height amounts are typical of those observed
from the A(v) term alone in a column that has become
aged with repetitive use, but with no entrance void.1251


0.8
Cylindrical pore (ep = 0.95; rpore = 5.7 nm)
Fiber (ep = 0.87; rfier = 1.25 nm)----------

0.6


RNSA "
"0.4 -
BLAC "


0.2 BSA monomer \

BSA dimer N

0
0 . .. I . .. I*i,--, ""i ' '

103 104 105 106
M, (Daltons)

Figure 4. Fitting of experimental data for Kq using Eqs. (3), (5),
and (7). The conditions used were the same as described in the
caption to Figure 3.


50-


30 1


Reduced velocity, v

Figure 5. Reduced plate height for the Toso Bioscience TSK-
gel Super SW3000 SEC column as a function of the reduced
velocity with P lactoglobulin A as the eluite and using the same
fluid phase described in the caption to Figure 3. Results illus-
trate the plate heights obtained from an HPLC column whose
performance has become degraded through extensive use. The
dashed line illustrates the slope expected solely from the
"C term" in Eq. (9).


Vol. 47, No. 1, Winter 2013


C= 0.05


00
-o/
















"_ ouu
<
E
E
C
0


00
2 400

(0
CO

S200


Time (min)

Figure 6. Volume-overloaded size-exclusion chromatogra-
phy of a protein mixture using a 30 cm X 7.8 mm ID Toso
Bioscience TSK G3000SW column. The flow rate was 0.7
mL/min. Other conditions are the same as in Figure 3.

Figure 5 therefore illustrates results that would be typically
expected for heavily used columns of the type encountered in
an undergraduate instructional laboratory. In support of this
interpretation, it can be noted that Anspach et al.1271 measured
plate heights for a moderately used Toso Bioscience TSK
G3000SWXL column, which is the same column used to
obtained the results in Figure 6 presented in the next section,
and determined that the reduced plate heights measured using
bovine serum albumin varied from 10 to 12 when the reduced
velocity was varied from 4 to 80. Nevertheless, despite the
apparent tendency of the silica-based SEC columns used here
to exhibit reduced performance after moderate usage due to
particle fracturing and bed consolidation, these columns are
still able to exhibit a large number of theoretical plates even
in their degraded state (e.g., more than 2,500 theoretical plates
in the case of Figure 5). Plots of the reduced plate height as a
function of the flow rate for proteins in SEC columns under
more ideal conditions are given in various references.[1,24281

RESULTS IN THE VOLUME-OVERLOADED
REGIME
When chromatography is used for the purpose of obtain-
ing purified material, as opposed to its use as an analytical
method, feed overloading is used so that a significant quantity
of material can be purified per loading cycle. This aspect can


Chemical Engineering Education


be incorporated into Topic 1 in Table 1 by employing either
volume overloading where the last term on the right side of
Eq. (8) is significant compared with the other terms or, in
chromatographic systems where adsorption onto the column
packing occurs, concentration overloading so that the non-
linear portion of the adsorption isotherm applies.
Figure 6 illustrates the use of volume overloading to il-
lustrate conceptually the operation of large-scale SEC. In
particular, feed volumes of 10,50,400, and 1000 pL are used
together with a Toso Bioscience TSK G3000SWXL column.
As shown, the separation resolution between the two protein
bands is reduced as the feed volume is increased. More spe-
cifically, the term (VFeed / F)2/12 on the right side of Eq. (8)
can be calculated to be 1.53 and 97.1 s2 for the cases of using
feed volumes of 50 and 400 pL, respectively, while the tot2
values estimated for these same two cases obtained from the
band shapes in Figure 6 are 75.4 and 225 s2, respectively.
This indicates that the increase in o,2 that occurs when the
feed volume size is increased from 50 to 400 pL results to
a significant extent from the increase in the value of (VFee /
F)2/12. This is in agreement with previous studies on the scal-
ing up of SEC that have similarly concluded that the effect
of volume overloading on the band width is predicted with
reasonable accuracy by Eq. (8).[28]
Students can also extend these results by using the concepts
of product yield, product purity, and separation resolution (the
last quantity being defined as the difference in the retention
times between the two components being separated divided
by twice the sum of their atota values[8'91) and by comparing
measurements of these quantities with predictions using Eq.
(8) as the feed volume is varied. By conducting experiments
such as those shown in Figure 6, student should be able to
conclude that large-scale applications of SEC tend to be
restricted to cases where the molecules being separated dif-
fer significantly in size, which is generally the case for the
example applications described earlier.

PERSPECTIVES ON THE USE OF THE PLATE
THEORY OF LINEAR CHROMATOGRAPHY
The approach employed here for describing band broadening
where a chromatography column is envisioned as a series of
equilibrium plates applies to the case of linear equilibrium and
exploits the analogy between the concept of a height equivalent
to a theoretical plate (HETP) as used for a packed distillation
column and the equivalent concept in chromatography.["8]
Chemical engineering students are likely to appreciate this
analogy since it ties together the seemingly disparate fields of
traditional separation processes and chromatography. In addi-
tion, students benefit from learning about the plate theory of
linear chromatography since it is frequently used in industrial
practice as a simple scale-up method, for the measurement of
physical properties related to chromatography, and for inves-
tigating irregularities in packed column performance.[2931 It










is also frequently the case that the newest concepts from the
field of analytical chromatography employ ideas from the
plate theory of linear chromatography, such as the concepts of
kinetic plots and separation impedance, in which case chemical
engineering students need to be familiar with this theory so that
they can understand these developments.1311
Although previous work12832a31 indicates that the plate theory
of linear chromatography (or simple extensions of it) will be
useful for most applications of SEC, students should also
recognize the limitations of this approach. For example, when
the eluite band is non-Gaussian in shape, it may be difficult
to extract meaningful statistical moments from experimental
data. In addition, in many industrial applications of chroma-
tography where eluite adsorption occurs, the nonlinear por-
tion of adsorption isotherm may apply. Finally, even in the
linear adsorption regime, numerous complicating factors may
occur such as surface diffusion of adsorbed species and the
situation where molecules of different size access completely
different pore regions. In many of these cases full numerical
solutions of chromatography may be required to account for
phenomena involved, with one option for accomplishing
this being the use of commercial software such as ASPEN
Chromatography. Although outside the scope of this article,
these types of numerical simulations have been used in other
situations where students have sufficient opportunity to fully
assimilate them.11 121

STUDENT ASSESSMENT AND FEEDBACK
The assessment of the student learning outcome for this
experiment was achieved in the laboratory course by having
students take a quiz on the material before they conducted
the experiment and then also submit a written report after the
experiment was performed. Grades for the quiz and report
have been determined by the extent to which students use the
proper terminology and theory, whether students are able to
explain systematic deviations between theoretical predictions
and experimental results, and whether students properly ac-
count for experimental errors. Assessment results over the
last several years have indicated that the student learning
outcome has been achieved since students have demonstrated
an acceptable level of understanding of the relation between
chromatographic performance and system properties.
For the preparation of this article specific feedback from
students, in the form of comments about this experiment,
was also obtained. Typical comments included the following:
We learn a lot of theory in classes but it definitely helps
to actually conduct the experiment and see everything
happen.
I had a much better understanding of chromatography
after this experiment.
Overall, the experiment was good for me because it
helped to connect the derivation of equations that were


abstract to real, physical data.
This experiment helped show me how it was possible to
predict column behavior based on readily available data.
Some students also mentioned in their comments that these
experiments could be improved if they were made more visu-
ally interesting. To address this, an improved version of these
experiments could employ a mixture of colored proteins as the
feed material. The separated proteins can then be collected in
separate vials after they pass through the detector so that the
separation achieved can be directly seen.

CONCLUSIONS
This article illustrates the use of HPLC in the undergradu-
ate chemical engineering laboratory. In particular, a set of
experiments is described whose major learning outcome is
to provide students with the ability to predict and understand
the chromatographic behavior of proteins using appropriate
physical properties. In addition, since the principles under-
lying HPLC and large-scale, low-pressure chromatography
are similar, this experiment presents many opportunities for
students to learn about the industrial use of chromatography.
Finally, by learning about the history of HPLC, students gain
an appreciation of the versatility of the chemical engineering
profession since Csaba Horvdth, who is widely regarded as
the "father of HPLC," conducted a large body of engineering
research on the method while he was a member of the Chemi-
cal Engineering Department at Yale University.

ACKNOWLEDGMENTS
We thank Changyi Li (Thorlabs Quantum Electronics Incor-
porated) for his assistance in producing the FreeChrom soft-
ware and Govind Rao (Department of Chemical, Biochemical,
and Environmental Engineering and Center for Advanced
Sensor Technology, UMBC) for his helpful comments on this
work and for his assistance in including this experiment in
the biochemical engineering laboratory course at UMBC. We
also thank BioAnalytical Systems Incorporated for donating
the HPLC equipment. Support from grant 0854151 from the
National Science Foundation is greatly appreciated. This ar-
ticle is dedicated to the late Professor Csaba Horvath of Yale
University whose lifelong advocacy of HPLC and chemical
engineering education provided its inspiration.

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2. Greibrokk, T., "The contributions of Csaba Horvdth to liquid chroma-
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3. Wheelwright, S.M., Protein purification: Design and scale up of
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Vol. 47, No. 1, Winter 2013











and R. van Reis, "Buffer exchange using size exclusion chromatog-
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6. Prazeres, D.M.F., G.N.M. Ferriera, G.A. Monteiro, C.L. Cooney, and
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7. Jungbauer, A., W. Kaar, and R. Schlegl, "Folding and refolding of
proteins in chromatographic beds," Curr. Opin. Biotechnol., 15,487
(2004)
8. Wankat, P.C.,Separation Process Engineering, 3rded., Prentice Hall,
New York (2012)
9. Blanch, H.W., and D.S. Clark, Biochemical Engineering, Marcel
Dekker, New York (1996)
10. Lefebrve, B.G., S. Farrell, and R.S. Dominiak, "Illustrating chroma-
tography with colorful proteins," Chem. Eng. Educ., 41,241 (2007)
11. Wankat, P.C., "Using a commercial simulator to teach sorption separa-
tions," Chem. Eng. Educ., 40,165 (2006)
12. Evans, S.T., X. Huang, and S.M. Cramer, "Using Aspen to teach
chromatographic bioprocessing: A case study in weak partition chro-
matography," Chem. Eng. Ed., 44, 198 (2007)
13. Joye, D.D., A. Hoffman, J. Christie, M. Brown, and J. Neimczyk,
"Project-based learning in education through an undergraduate lab
exercise," Chem. Eng. Ed., 45,53 (2011)
14. Craig, D.B., "Equilibrium gel filtration chromatography for the mea-
surement of protein- ligand binding in the undergraduate biochemistry
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15. Lucy, C.A., L.LM. Glavina, and F.F. Cantwell, "A laboratory experi-
ment on extracolumn band broadening in liquid chromatography," J.
Chem. Ed., 72,367 (1995)
16. Smith, E.T., and M. Hill, "Constructing a LabView controlled HPLC
system: An undergraduate instrument methods exercise," J. Chem. Ed.,
88,317(2011)
17. SRI Instruments, Inc., "PeakSimple Chromatography Data Systems,"
product brochure, Torrance, CA (2012)
18. Knox, J.H., and H.P. Scott, "Theoretical models for size-exclusion
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19. Hussain. S., M.S. Mehta, J.I. Kaplan, and P.L. Dubin, "Experimental
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20. Laurent, T.C., "History of a theory of gel filtration and its experimental
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the Stokes radius of macromolecules determined by gel filtration
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22. Tarvers, R.C., and F.C. Church, "Use of high-performance size ex-
clusion chromatography to measure protein molecular weight and
hydrodynamic radius," Inter. J. Peptide Protein Res., 26,539 (1984)
23. Fischer, H., I. Polikarpov, and A.F. Craievich, "Average protein density
is a molecular-weight-dependent function," Protein Sci., 13, 2825
(2004)
24. Guiochon, G., S G. Shirazi, andA. Katti, Fundamentals of Preparative
and Nonlinear Chromatography, Academic Press, New York (1994)
25. Guo, H., and D.D. Frey, "Interpreting the difference between conven-
tional and bi-directional plate height measurements in liquid chroma-
tography," J. Chromatogr.A, 1217,6214 (2010)
26. Squire,P.G.,P. Moser, and C.T. O'Konski, "The hydrodynamic proper-
ties of bovine serum albumin monomer and dimer," Biochemistry, 7,
4261 (1968)
27. Anspach, B., H.U. Gierlich, and K.K. Unger, "Comparative study
of Zorbax Bio Series GF 250 and GF 450 and TSKgel 3000 SW and
SWXL columns in size-exclusion chromatography of proteins," J.
Chromatogr., 443,45 (1988)
28. Yamamoto, S., M. Nomura, and Y. Sano, "Scaling up of medium-
performance gel filtration chromatography of proteins,"J. Chem. Eng.
Jap., 19,227 (1986)
29. Arnold, F.H., H.W. Blanch, and C.R. Wilke, "Analysis of affinity
separations II. The characterization of affinity columns by pulse tech-
niques," Chem. Eng. J., 30, B25 (1985)
30. Rathore, A.S., and A. Velayudhan, "An overview of scale-up in pre-
parative chromatography," in Scale-up and optimization in preparative
chromatography: Principles and biopharmaceutical applications,
Chpt. 1, A.S. Rathore and A. Velayudhan, Eds., Marcel Dekker, New
York (2003)
31. Frey, D.D., and X. Kang, "New concepts in the chromatography of
peptides and proteins," Curr. Opinion Biotechnol., 16,552 (2005)
32. Athalye, A., S.J. Gibbs, and E.N. Lightfoot, "Predictability of
chromatographic protein separations. Study of size-exclusion
media with narrow pore size distributions," J. Chromatogr., 589,
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33. Li, Z., Y. Gu, and T. Gu, "Mathematical modeling and scale-up of
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Chemical Engineering Education










Random Thoughts...








YOU GOT QUESTIONS, WE GOT ANSWERS

1. Miscellaneous Issues








RICHARD M. FIELDER AND REBECCA BRENT


arly in 2012 we had the pleasure of giving a teaching
workshop at New Mexico State University, where
Tara Gray has created the most extensive and widely
attended faculty development program we have seen. After
the workshop, Tara organized a group of attendees who over
a five-week period read some of our papers and formulated
questions about them, starting with "The Top Ten Worst
Teaching Mistakes"11' and "Death by PowerPoint."'21 The
questions that follow were stimulated by those readings.
1. My teaching preparation takes a lot of time. How
do I keep it from getting in the way of my research
without sacrificing teaching quality?
Make sure you're not overpreparing. Your target should be
two hours of preparation for each hour of class. If it's taking
you much more than that, you're probably trying to jam too
much information into your notes, which you then have to
pump out like a fire hose in lectures to get through your syl-
labus. You consequently have no time for questions, interest-
ing digressions, and activities; the course is ineffective; your
evaluations are low; and you spend so much time preparing
your lectures that little is left over for doing research (not to
mention having a life). A much better approach is to write
a comprehensive set of learning objectives, make sure your
lecture notes contain only the material the students will need
to know to meet the objectives, and provide supplementary
references so the ones who want more information know
where to go for it.
The first time you teach a course you'll almost certainly
have trouble consistently meeting the 2/1 rule of thumb, and
you may sometimes push up to 3/1 or 4/1, which is accept-
able. If it's much more than that, however, you'll need to
back off to keep your research on track. For suggestions on
Vol. 47, No. 1, Winter 2013


minimizing the time burden of new course preparations, see
"How to prepare new courses without losing your sanity."'31
2. What advice do you have for integrating course
handouts and class activities with PowerPoint slides?
Rich's course handouts-which the students buy as a
coursepack after he has taught the course several times con-
tain his lecture notes with gaps at strategically chosen points,
supplemented by figures, tables, and reference lists. The gaps
may be skipped steps in derivations and problem solutions,
axes without curves, and questions with blank spaces for an-
swers. He has the class read straightforward parts of the notes
themselves, which they can do much faster than it would take

Richard M. Felder is Hoechst Celanese 1
Professor Emeritus of Chemical Engineer-
ing at North Carolina State University. He is
co-author of Elementary Principles of Chemi-
cal Processes (Wiley, 2005) and numerous .ii_
articles on chemical process engineering
and engineering and science education,
and regularly presents workshops on ef-
fective college teaching at campuses and
conferences around the world. Many of his
publications can be seen at effectiveteaching>.
Rebecca Brent is an education consultant
specializing in faculty development for ef-
fective university teaching, classroom and
f computer-based simulations in teacher
education, and K-12 staff development in
language arts and classroom management.
She codirects the ASEE National Effective
Teaching Institute and has published articles
on a variety of topics including writing in
undergraduate courses, cooperative learning,
public school reform, and effective university
teaching.
Copyright ChE Division of ASEE 2013










him to go through those parts on the board or in slides, and
when he gets to the gaps he either lectures on them or (better)
has the students work individually or in small groups to fill
them in.t4 All he ever does with slides are things he can't do
any other way, such as showing pictures, complex diagrams,
animations, and links to videos and simulations, but slides
may also be used effectively to highlight main points.
3. How do you maintain both structure and variety?
They're not incompatible. Your course outline should be
highly structured, so that you know what learning objectives
you'll be addressing and what content you want to cover at
each stage of the course. You can then provide variety in how
you cover it, using a blend of lecturing, individual activities,
and group activities in class, and a mixture of closed-ended
and open-ended problems, brainstorming, troubleshooting,
and critical and creative thinking exercises in class activities
and assignments and on tests.
4. What suggestions do you have for faculty who want to
establish relevance in their classes?
Stay with that goal! Relevance is critical to the success of
a course. If students can't relate course material to things that
interest them or the careers they're preparing themselves for,
only the ones motivated primarily by grades will do their best
to learn it, and the course will be ineffective for others with
just as much ability.
To help your students see the relevance of course material,
you first need to figure it out for yourself. Before you launch
into a long theoretical or analytical or memory-intensive pre-
sentation, ask yourself how you would answer a student who
asks "Why should I care about this stuff?" What important
engineering or scientific or social problems will the material
help them solve? What familiar phenomena does it explain?
What disasters might have been averted if it had been used?
And so on. If you can't think of anything, ask colleagues.
When you have answers, present them in class before you
start on the material, and keep referring back to them as you
proceed. If neither you nor your colleagues can think of a
thing that makes material relevant to students' interests or
goals, why are you teaching it?
5. What do you do when you try something new and it
doesn't work?
First, congratulate yourself for having the guts to try some-
thing new many faculty members never do and then try
to figure out what went wrong and what you could do dif-
ferently to make it work better. Next, go to a colleague who
is an excellent teacher or to someone in your Teaching and
Learning Center, discuss the situation, and get his or her ideas
and incorporate them if they make sense to you. Finally, take


whatever you end up with and put it in your lecture notes so
you don't repeat your mistakes next time you teach.
6. When students need to learn a lot of terminology and
other basic facts, what instructional or teaching method
would you recommend?
Give the students a study guide for the test on that material
and list the terms and facts they'll need to learn from their texts
or course handouts, and ask for definitions and explanations of
some of those terms and facts on a closed-book portion of the
test. Once you've handed out the study guide, you don't have
to waste a lot of class time droning through the definitions,
and you can use the time you save to go through higher-level
material in lectures and provide practice and feedback in ac-
tivities. Before the test, you might also form teams and run a
Jeopardy or Quiz Bowl contest with the material in question
as the subject matter.
7. What suggestions do you have for new faculty with mul-
tiple new courses and insufficient time to prepare them?
Remind your department head of all the proposals and papers
you're trying to write and ask to get your schedule changed
so you can teach courses you've previously taught or multiple
sections of one new course instead of all those new preps. He or
she may say no, but it doesn't hurt to ask. Then, read Reference
3. One of the suggestions in it is to go to a colleague who is a
good teacher and has taught one of your new preps and ask if he
or she would be willing to share the course materials (syllabus,
lecture notes, assignments, tests, ...) with you. The answer
will almost invariably be yes. You can use those materials
as a starting point for constructing your own, which will cut
down significantly on your preparation time. If you're really
desperate, you can use the materials with only minor changes
the first time you teach the course and start making serious
revisions later when you have a little more breathing space.
Questions about other papers in the NMSU reading list will
appear in future columns.
References
1. Felder, R.M., and R. Brent, "The top ten worst teaching mistakes. (a)
Mistakes 5-10," Chem. Eng. Ed., 42(4), 201 (2008), felder-publiclColumns/Badldeasl.pdf>; (b) "Mistakes 1-4," Chem.
Eng. Ed., 43(1), 15 (2009), Badldeasll.pdf>
2. Felder, R.M., and R. Brent, "Death by PowerPoint," Chem. Eng. Ed.,
39(1), 28 (2005), pdf>
3. Felder, R.M., and R. Brent, "How to prepare new courses while keep-
ing your sanity," Chem. Eng. Ed., 41(2), 121 (2007), felder-publiclColumns/Newprep.pdf>
4. Felder, R.M., and R. Brent, "Active learning: An introduction," ASQ
Higher Education Brief, 2(4), August 2009, public/Papers/ALpaper(ASQ).pdf> 0


All of the Random Thoughts columns are now available on the World Wide Web at
http://www.ncsu.edu/effectiveteaching and at www.che.ufl.edu/CEE.
Chemical Engineering Education











LugI curriculum
--________________


USE OF RESEARCH-BASED

INSTRUCTIONAL STRATEGIES

in Core Chemical Engineering Courses


MICHAEL PRINCE', MAURA BORREGO2, CHARLES HENDERSON3, STEPHANIE CUTLER2, AND JEFF FROYD4
I Bucknell University
2 Virginia Tech
3 Western Michigan University
4 Texas A&M University


increasingly, high-profile organizations including the
American Society for Engineering Education,1l National
Academy of Engineering,124' Association of American
Universities,[5] National Research Council,16-81 and the Na-
tional Science Board&910] are calling for widespread improve-
ments in undergraduate STEM education. Tremendous effort
over the past few decades has built up a substantial knowledge
base about STEM learning and research-based instructional
strategies"'1 such as active learning,121 cooperative learning,[121
problem-based learning,1"31 and service learning.114' Yet these
prestigious groups are increasingly expressing dissatisfaction
with the rate of implementation of research-based instruc-
tional strategies.
Given this situation, it appears that the greatest impedi-
ment to improving engineering education lies not in finding
more effective instructional strategies but in increasing the
use of those strategies already known to be more effective
than the traditional methods still found in most undergraduate
classrooms.115] Understanding how to promote broader use of
research-based instructional strategies in undergraduate engi-
neering classrooms is therefore a critical challenge requiring
more attention.[111" 16
To be effective, future efforts must be informed by 1) knowl-
edge of effective mechanisms for making faculty aware of the
relevant research, 2) information on the current adoption rates
of specific strategies by engineering faculty members, and 3)
understanding of factors that hinder broader adoption of each
strategy in undergraduate engineering classrooms. This paper
draws on a survey of 99 instructors of core undergraduate
chemical engineering courses to examine these issues. The
core engineering courses selected for study were fluid me-
chanics, thermodynamics, and heat/mass transfer since these
courses are common to most chemical engineering programs.


Specifically, the paper asks:
1. What are the levels of awareness and use of specific
research-based instructional strategies for chemical


Michael Prince is the Rooke Professor of Engineering at Bucknell
University. His research interests include assessment and repair of per-
sistent student misconceptions, examining factors that promote students'
self-regulated learning competencies, and exploring how to increase the
diffusion of educational research into educational practice. He received
his B.S. in chemical engineering from Worcester Polytechnic Institute
and his Ph.D. in chemical engineering from U.C. Berkeley.
Maura Borrego is an associate professor in the Department of Engineer-
ing Education at Virginia Tech, currently serving as a program director
at the National Science Foundation. Her research interests include
engineering faculty development, specifically how faculty members
decide to apply the results of educational research, and interdisciplin-
ary graduate education in STEM. She holds M.S. and Ph.D. degrees in
materials science and engineering from Stanford University.
Charles Henderson is an associate professor at Western Michigan Uni-
versity (WMU), with a joint appointment between the Physics Department
and the WMU Mallinson Institute for Science Education. He is the senior
editorforthejoumrnal Physical Review Special Topics Physics Education
Research. Much of his research activity is focused on understanding
and improving the slow incorporation of research-based instructional
reforms into college-level STEM courses. He holds a Ph.D. in science
education from the University of Minnesota.
Stephanie Cutler is a Ph.D.candidate in the Department of Engineering
Education at Virginia Tech. Her dissertation will focus on how engineering
education research is adopted into practice, specifically how Research
Based Instructional Strategies are implemented in the statics classroom.
She received her B.S. in mechanical engineering from Virginia Com-
monwealth University and her M.S.in industrial and systems engineering
with an emphasis on human factors from Virginia Tech.
Jeffrey E. Froyd is a TEES research professor in the Office of Engineer-
ing Student Services and Academic Programs at Texas A&M University.
His research interests include curricular and organizational change,
engineering faculty development, integrated curricula and learning
communities, and metacognitive development of engineering students.
He received his B.S. in mathematics from Rose-Hulman Institute of
Technology and his M.S. and Ph.D. degrees in electrical engineering
from the University of Minnesota.

Copyright ChE Division of ASEE 2013


Vol. 47, No. 1, Winter 2013









engineering faculty members teaching fluid mechanics,
thermodynamics, and heat/mass transfer?
2. What factors (such as gender, rank, and job responsibil-
ities) are correlated with a chemical engineering faculty
member's level of awareness and use of each strategy?
3. How do chemical engineering faculty members first
hear about research-based instructional strategies and
how do they pursue additional information about these
strategies after their initial exposure?
4. What barriers to broader adoption of research-based
instructional strategies do chemical engineering faculty
members report?
Preliminary results were presented in a previous confer-
ence paper,1171 the feedback on which we used to inform this
paper. The conference paper combined results from chemical,
computer, and electrical engineering faculty members, and we
found few meaningful differences by discipline. This paper
provides an expanded and substantially different introduction,
literature review, and discussion of the chemical engineering
results specifically targeted to the chemical engineering edu-
cation community. This paper also includes additional data
from a second wave of data collection.

PREVIOUS RESEARCH
Studies examining adoption rates of research-based instruc-
tional strategies in chemical engineering fit within a larger
body of literature on the diffusion of innovations .[1820] Several
relevant findings emerge from this broader literature. First,
individuals do not make decisions about adopting an innova-
tion (e.g., an instructional strategy) all at once. Instead, they
follow a fairly common progression of stages:
1. Awareness individual learns about the innovation
2. Information individual seeks for more information
3. Reflection individual sifts through pros and cons
4. Adoption (or Rejection) individual tries the innovation
(or not) and analyzes results
5. Follow-up individual makes decisions about continu-
ing (or not) to apply the innovation
While the number and description of the stages differ across
various adoption models, the finding that adoption occurs in
stages is common. This influenced our decision to differentiate
between awareness and adoption of strategies in our survey
and our subsequent report of the findings.
Second, characteristics of the instructional strategy impact
adoption rates. Not surprisingly, if the strategy is more con-
sistent with what the individual (and the department) values
and has experienced, then it is more likely to be adopted by
that individual. Also, if the instructional strategy is easier
to apply, its likelihood of adoption is higher. Prior work has
shown that faculty members have a common set of concerns
about adopting new strategies:
(a) Will I still be able to cover the content?t'2123J


(b) How much work do I need to do to apply the strategy?
(c) How will my students respond?"221
(d) How will my colleagues respond?24' and
(e) How well does the innovation fit with constraints of
my course, e.g., enrollment, classroom size, classroom
configuration, and length of class periods?123', 241
Third, individuals learn about the innovation through differ-
ent channels, which are more (or less) appropriate at different
stages of adoption. Communication channels can be charac-
terized as mass media or interpersonal. Mass media includes
journal articles, conference publications, and professional so-
ciety publications such asASEE's Prism. Interpersonal chan-
nels include having an informal conversation with someone
describing his or her positive experience with an instructional
strategy. Faculty workshops such as the National Effective
Teaching Institute25' are more efficient than one-on-one con-
versations, but provide similar personalized experiences and
advice. Rogers explains that mass media channels are more
important at the awareness stage, while interpersonal channels
are critical at the evaluation stage.1201 More specifically,"...the
heart of the diffusion process is the modeling and imitation
by potential adopters of their near peers' experiences with the
new idea. In deciding whether or not to adopt an innovation,
individuals depend mainly on the communicated experience
of others much like themselves who have already adopted a
new idea. These subjective evaluations of an innovation flow
mainly through interpersonal networks."[181
Building on this previous research, a survey was conducted
in 2009 of 197 U.S. engineering department chairs regarding
their personal awareness and their department's adoption
of seven engineering education interventions E[2 The chairs
estimated that, on average, 36% of their engineering faculty
members were using research-based instructional strategies
(labeled "student-active pedagogies" in the chairs survey).
Analysis of open-ended survey responses from department
chairs helped to identify some of the primary barriers to propa-
gation of educational research into the classroom. Department
chairs cited financial resources, class sizes, space constraints,
technology limitations, faculty time, student learning, and fears
of student resistance as considerations. These concerns were
frequently framed as weighing benefits against costs. Some
survey comments also indicated that the innovations were
perceived to be more complex than is necessarily the case, sug-
gesting the need for further education and faculty development
efforts. For example, many chairs suggested that active learning
requires costly technology when in fact many forms of active
learning require no additional resources. Although that study
offered insights into how department chairs perceive research-
based instructional strategies as well as factors that promote
and hinder adoption, studies that solicited data directly from
engineering faculty members are warranted to provide a more
comprehensive picture of instruction in engineering classrooms.


Chemical Engineering Education










RESEARCH METHODS
To begin to explore how these issues apply to U.S. chemi-
cal engineering faculty members, we conducted a national
survey focusing on 12 research-based instructional strategies.

Research Based Instructional Strategies (RBIS)
Table 1 lists the research-based instructional strategies ex-
amined in this study. These were selected because they have
documented use in engineering settings at more than one insti-
tution and demonstrated positive influence on student learning
in engineering or STEM. Definitions for each strategy, as well
as attempts to clarify distinctions between similar strategies
such as collaborative vs. cooperative learning or problem-
based vs. project-based learning, were drawn from the fol-
lowing references: active learning, '12,26,271 think-pair-share,126'
281 concept tests,1261 TAPPS ,1261 cooperative learning,112,291 col-
laborative learning,112, 301 problem-based learning,12, 13, 31, 321
project-based learning,[131 case-based teaching,[131 just-in-
time teaching,1331 peer instruction,1341 inquiry learning,13', 351
and service learning. J36, 371 Summaries of research supporting
the effectiveness of these specific instructional strategies are
provided in Prince,i12] Prince and Felder,1131 and Oakes.1141

Instrument
The survey instrument was divided into three sections. The


first section asked faculty about the amount of class time spent
on different activities generally associated with each instruc-
tional strategy. The second asked faculty specifically about
their knowledge or use of each of the targeted 12 strategies.
Respondents were provided with the definitions of the RBIS in
Table 1. The third section collected demographic information
such as gender, rank, and frequency of attendance at teaching
workshops. Due to space constraints, we report here the results
from the second and third sections, reserving comparison
between the first and second sections for a future publication.
The survey instrument was adapted by the authors from a
previous survey of introductory physics instructors. 11"3, The
physics instrument and a description of its development can be
found elsewhere .[11 The overall instrument reliability for the
chemical engineering survey is indicated by a Cronbach alpha
of 0.755, which is within the commonly acceptable range.1391
Sample
The population for this survey is all faculty members in
ABET-accredited chemical engineering programs who had
taught sophomore-level introductory thermodynamics, fluid
mechanics, and/or heat transfer in the last two years. A few
potential respondents were identified through an e-mail to all
chemical engineering department chairs. Then, the Virginia
Tech Center for Survey Research contacted all 158 programs


TABLE 1
Research-Based Instructional Strategies (RBIS) and Descriptions To Be Used in the Survey
RBIS Brief Description
Collaborative Asking students to work together in small groups toward a common goal.
Learning
Active Learning A very general term describing anything course-related that all students in a class session are called upon to do other than
simply watching, listening, and taking notes.
Problem-Based Acting primarily as a facilitator and placing students in self-directed teams to solve open-ended problems that require
Learning significant learning of new course material.
Inquiry Learning Introducing a lesson by presenting students with questions, problems, or a set of observations and using this to drive the
desired learning.
Concept Tests Asking multiple-choice conceptual questions with distracters (incorrect responses) that reflect common student misconcep-
tions.
Think-Pair-Share Posing a problem or question, having students work on it individually for a short time, and then forming pairs and reconcil-
ing their solutions. After that, calling on students to share their responses.
Cooperative A structured form of group work where students pursue common goals while being assessed individually.
Learning
Case-Based Asking students to analyze case studies of historical or hypothetical situations that involve solving problems and/or making
Teaching decisions.
Peer Instruction A specific way of using concept tests in which the instructor poses the conceptual question in class and then shares the
distribution of responses with the class (possibly using a classroom response system or clickerss"). Students form pairs,
discuss their answers, and then vote again.
Just-In-Time Asking students to individually complete homework assignments a few hours before class, reading through their answers
Teaching before class, and adjusting the lessons accordingly.
Thinking-Aloud- Forming pairs in which one student works through a problem while the other questions the problem solver in an attempt to
Paired Problem get them to clarify their thinking.
Solving
Service Learning Intentionally integrating community service experiences into academic courses to enhance the learning of the core content
and to give students broader learning opportunities about themselves and society at large.

Vol. 47, No. I, Winter 2013 2









via telephone with e-mail follow-up to identify the names and
e-mail addresses of faculty who met the selection criteria.
Ultimately, 505 faculty members were identified as potential
participants.

Survey Administration
In spring 2011, the Center for Survey Research sent e-mail
invitations to each of the instructors. Each person received a
unique survey link so that up to three weekly reminders could
be sent to those who had not yet responded. To increase the
response rate, the e-mail was endorsed and signed by a mem-
ber of the survey committee of AIChE and gift cards were
offered as raffle incentives to those who completed the survey.
The survey was sent to a total of 505 ChE faculty members.
There were 108 responses. After removing 15 who did not
teach the courses of interest and others who did not answer a
majority of the items, we were left with 92 usable responses
for a response rate of 19%. To understand potential response
bias, a second round of data collection was conducted in Fall
2011. Twenty-five faculty members who had not previously
completed the survey were contacted via telephone and e-mail
and offered a gift card for completing the survey. Four respon-
dents did not teach the course of interest, but an additional
seven usable responses were obtained. The two data sets were
combined because statistical comparison using Fisher's exact
test revealed no significant differences; bringing the overall
response rate to 20%.

Data Analysis
Most of the data presented here consist of simple descriptive
totals and percentages of various responses. In some cases,
response categories were combined. To address research ques-
tion 2 (demographic and job factors that correlate with aware-
ness and use of instructional strategies), we used a Fisher's
exact test because the sample size was too small to allow for
Chi-square analysis. All comparisons were based on 2X2
matrices created by combining responses. For example, for
each instructional strategy, only current users were considered
to be "Users," while all other respondents were considered
"Non-Users." Significance was determined using an alpha
of 0.01 due to the high number of comparisons. Phi was also
calculated to determine the strength of the relationship for
the significant results. All calculations were completed using
SPSS statistical software.
Limitations
This survey very likely overestimates the actual percentages
of chemical engineering faculty members using research-
based instructional strategies in their core engineering science
courses. We used a second wave of data collection to under-
stand potential survey bias. While the responses we received
were statistically similar, the response rate of 20% was still
low-although typical for web surveys.[40]1 In the earlier survey
of department chairs (whom we selected to reduce survey
bias),[201 76% of chemical engineering department chairs


Full
Professor.
33%


Other Lecturer
.2% r- 5%


Assistant
Professor

f37%


Associated
Professor
23%


Figure 1. Respondent rank.

reported that at least one of their faculty members was using
active-learning pedagogies and they estimated that 38% of
chemical engineering faculty members (in all undergraduate
courses) were using active learning on a regular basis. The
use of active learning reported in this survey is significantly
higher, suggesting the possibility of a response bias in this
study. In addition, one might reasonably suspect that faculty
members who are not interested in teaching, or who limit the
time they spend on teaching, are unlikely to fill out a survey
about their teaching. Looking at the number of attended teach-
ing workshops reported by respondents also suggests that this
sample of faculty is particularly committed to improving their
teaching quality. Finally, the high levels of awareness and use
of many of the research-based instructional strategies reported
in this study seem inconsistent with the experience of many
of us who routinely conduct faculty development workshops
with engineering instructors. For all of these reasons, we cau-
tion that the results and analyses reported here are more useful
for what they say about a particular subsection of chemical
engineering faculty and for the insights they provide about
the relative rankings of RBIS awareness and use, information
sources, and perceived barriers to adoption.

RESULTS

Characteristics of Respondents
Figures 1-4 illustrate some key characteristics of the survey
respondents. Compared to faculty in all engineering disci-
plines, female faculty are slightly overrepresented among
respondents; 20% of respondents were female, as compared
to 15% nationally.1411 Compared to faculty members in all
engineering disciplines, full professors are underrepresented
and assistant professors are overrepresented among our re-
spondents (ASEE reports 45% full professors, 25% associate,
20% assistant, and 10% lecturers among full-time faculty, as
compared to Figure 1).
Chemical Engineering Education















At least 4
articles
49% _


None
19%









I 1-3

Articles
32%


Figure 2. Respondent technical research publications for
past three years.

Among respondents, 58 recently taught thermodynamics,
49 recently taught fluid mechanics, and 41 recently taught
heat transfer. Their average class size was 48 students, and
they had an average of 12.2 years of experience teaching
undergraduates.
The majority, 57%, attended one to three workshops on
teaching in the past two years. Another 19% attended more
than that, but 24% attended none. Eight percent had attended
the National Effective Teaching Institute. Approximately half
of the respondents (49%) reported discussing teaching with
colleagues several times per semester or term. Figures 2-4
provide additional information about respondents' research
activity, job responsibilities with respect to teaching, and
frequency of teaching discussions with colleagues.

Awareness and Use of RBIS Among
ChE Faculty Ch
Table 2 presents faculty members' aware-
ness and use of the 12 research-based
instructional strategies, ordered by current
use. Results show that chemical engineering Collaborativ
faculty members who responded to the sur- Active Learn
vey are generally aware of most of the strate- Problem-Bas
gies; all but two are above 80% awareness. La
Based on these responses, efforts to make --r- ea
faculty aware of these practices have been Concept Test
generally successful. Results also show that Think-Pair-S
adoption trails awareness for every RBIS, Cooperative
and in many cases gaps between awareness Case-Based
and adoption are large. The smallest gaps Peer Instruct
are 32 percentage points for collaborative Just -In- Time
learning and 39 percentage points for ac- Thinking-A
tive learning. These two RBIS take the least Problem Sob
amount of preparation time outside of class.
_, , Service Lean
The largest gaps are for service learning (75 Service Lean
Vol. 47, No. 1, Winter 2013


Principally
Teaching


Half '- -than Half
Teachin.g Teaching
31% .- 12%







About
Half
------. _Teaching
48%

Figure 3. Respondent job responsibilities with respect to
teaching.

percentage points), peer instruction (72 percentage points),
cooperative learning (69 percentage points), and case-based
teaching (67 percentage points). In general, these require more
preparation time than active or collaborative learning, so the
large gap between awareness and adoption for these strate-
gies is likely influenced by realistic perceptions of required
preparation time.
In addition to examining initial adoption rates, we also
examined whether faculty who try an innovation continue
to use the strategy. The final column in Table 2 is a ratio of
current to past users. We see that discontinuation after some
initial use is a significant problem. Four RBIS have ratios less
than one, which means more faculty have tried and abandoned

TABLE 2
E Faculty Awareness, Current Use, and Past Use of RBIS
,, ,Ratio
Aware Currently Used Ratio
Aware use in past current: past
use in past usr
users
e Learning 97% 65% 14% 4.6
ing 99% 60% 21% 2.9
ed Learning 98% 35% 12% 2.9
,ing 96% 31% 21% 1.5
s 91% 27% 15% 1.8
hare 90% 25% 14% 1.8
Learning 86% 17% 18% 1.0
reaching 93% 16% 21% 0.8
ion 87% 15% 4.0% 3.8
Teaching 63% 10% 3.1% 3.3
oud-Paired
)ud-Paired 64% 6.1% 9.1% 0.7
ving _____________ ________
ning 80% 5.1% 12% 0.4











TABLE 3
How ChE faculty first found out about specific instructional strategies. Participants selected one option.
This question only allowed one response per strategy.
Total Do Col- Read Presenta- Pres. or In-depth Pres. or
Respon- not league article tion or workshop workshop workshop
dents recall (word of or book workshop at an of one at my pro-
mouth) about it on my engineering or more fessional
campus education days (e.g., society
conference NETI, confer-
(e.g., FIE, NSF-spon- ence (e.g.,
__________ ____ ________ ASEE) scored) AIChE)
Collaborative ^^^^^^ ^^
Collaborative 94 27% 28% 12% 13% 5.3% 7.4% 4.3%
Learning
Active
Active 98 20% 19% 12% 18% 8.2% 6.1% 6.1%
Learning
Problem-
Based 93 31% 19% 15% 11% 4.3% 6.5% 5.4%
Learning
Inquiry ^^ ^^ ^^
Inquiry 90 50% 11% 11% 6.7% 5.6% 6.7% 2.2%
Learning
Concept 90 31% 22% 16% 14% 2.2% 4.4% 4.4%
Tests
Think-Pair- g ^ ^ ^^ ^^
Think-Pair- 88 31% 17% 10% 16% 9.1% 4.5% 8.0%
Share
Cooperative 82 38% 23% 11% 13% 4.9% 4.9% 2.4%
Learning
Case^-Based g ^ ^ ^^ ^^
Case-Based 88 53% 14% 11% 3.4% 5.7% 4.5% 4.5%
Teaching
Peer
Instruction 83 41% 14% 12% 14% 6.0% 3.6% 2.4%
Instruction

Just-In-Time
Teaching 63 21% 24% 16% 11% 11% 1.6% 11%
Teaching
Thinking-
Aloud-Paired ^^ ^^ ^^ ^^
Aloud-Paired 63 38% 10% 14% 7.9% 6.3% 11% 9.5%
Problem
Solving
Service
Service 75 37% 23% 6.7% 17% 2.7% 6.7% 2.7%
Learning
Average
across all N/A 35% 19% 12% 12% 5.9% 5.7% 5.3%
RBIS I


than are currently using service learning, thinking-aloud-
paired problem solving, case-based teaching, and cooperative
learning. This suggests that significant effort is needed to
support faculty in their implementation of these strategies.
Most likely faculty will need to be supported in customizing
an instructional strategy for their situation. The reasons for
discontinuing use of an instructional strategy may also be
linked to the reported barriers for adopting innovative strate-
gies, which are discussed in more detail later in this paper.

Demographic Factors That Affect Awareness and
Use of RBIS
We examined how gender, rank, research activity, work-
shop attendance, teaching responsibility, and discussing


teaching with colleagues influenced awareness and use of
instructional strategies. Given the small sample size and
conservative nature of our statistical testing, no differ-
ences emerged for awareness and only three significant
differences emerged for use. First, faculty who talk with
their colleagues about teaching on a regular basis are more
likely to use collaborative learning (p = 0.003). Second,
ChE faculty who attended the National Effective Teach-
ing Institute were more likely to use thinking-aloud-paired
problem solving (p = 0.006). Third, faculty members
who attended any type of multi-day teaching workshop
were more likely to use peer instruction (p = 0.01).
These significant results provide some insight into how
faculty members are likely to learn about various instruc-


Chemical Engineering Education











TABLE 4
How ChE faculty found more information about specific instructional strategies.
This question allowed multiple responses. Percentages are based on number of respondents who selected each strategy.
Total Do not Col- Read Pres. or Pres. or In-depth Pres. or
Respon- recall league article workshop workshop workshop workshop
dents (word or book on my at an en- of one at my pro-
of about it campus gineering or more fessional
mouth) education days (e.g., society
conference NETI, confer-
(e.g., FIE, NSF-spon- ence (e.g.,
_____ ______ _______ _____ ASEE) scored) AIChE)
Collaborative ^ ^ ^
Collaborative 86 24% 42% 42% 28% 16% 17% 24%
Learning
Active
Active 95 12% 49% 52% 39% 19% 19% 26%
Learning
Problem-
Based 89 26% 37% 44% 17% 16% 18% 22%
Learning
Inquiry 89 42% 24% 30% 16% 10% 10% 16%
Learning
Concept Tests 86 28% 34% 31% 16% 16% 12% 13%
Think-Pair- g ^^
Think-Pair 88 25% 34% 27% 25% 15% 14% 16%
Share
Cooperative 80 31% 30% 38% 25% 15% 14% 19%
Learning
Case^-Based ^^ ^^ ^^ ^^
Case-Based 81 48% 25% 31% 12% 16% 7.4% 11%
Teaching
Peer
sr 77 36% 26% 56% 19% 7.8% 9.1% 13%
Instruction
Just-In-Time ^ ^ ^
Just-In-Time 59 25% 39% 36% 22% 15% 6.8% 14%
Teaching
Thinking-
Aloud-Paired ^ g y ^
Aloud-Paired 59 24% 29% 39% 20% 15% 15% 17%
Problem
Solving
Service
Service 67 48% 28% 22% 19% 12% 9.0% 10%
Learning
Average
across all N/A 31% 33% 37% 22% 14% 13% 17%
RBIS


tional strategies. The results presented here are consistent
in many ways with those found in physics education.[38]
In physics, differences between new faculty who tried and
did not try RBIS were significantly correlated with attending
a multi-day workshop and attending other talks or work-
shops related to teaching. Thus, there is strong support for
the continued use of workshops as important dissemination
mechanisms. On the other hand, the physics survey did not
find a correlation between knowledge or use of RBIS and
frequency of teaching discussions with colleagues. This is
likely because conversations about teaching can have a vari-
ety of forms, both logistical and pedagogical. More work is
needed to more fully understand the types of conversations
that can result in improved teaching.


Dissemination Mechanisms For Initial and
Follow-up Information About RBIS
Table 3 presents the various ways that faculty initially
found out about each of the 12 instructional strategies. For
the very first exposure to specific instructional strategies, "do
not recall" was the most frequent response (average 35%).
Colleagues were the most frequent initial source for all but
one of the instructional strategies (thinking-aloud-paired prob-
lem solving). The importance of colleagues is emphasized in
these results; trusted colleagues can be key in encouraging a
faculty member to seek more information about instructional
strategies.
Table 4 lists the various ways that faculty members found
additional information about research-based instructional


Vol. 47, No. 1, Winter 2013










strategies. Books and articles were the most popular supple-
mentary sources for most of the 12 instructional strategies;
in three cases (concept tests, think-pair-share, and service
learning), colleagues were a more frequent ongoing source
of information than publications.
In sum, engineering education scholars tend to focus on
conference papers and journal articles to propagate their
findings, but the results reported here underscore the impor-
tance of local colleagues. In fact, the literature emphasizes
frequent collegial discussions to help faculty members think
through how they might implement instructional strategies,
experiment, and improve their approaches over time.142, 43]
That emphasis is consistent with our findings.

Reported Barriers to Broader Adoption of Specific
RBIS
Table 5 presents the barriers faculty perceived to adopting


each of the 12 instructional strategies. Overwhelmingly, they
listed class time and prep time as the major considerations in
whether to use instructional strategies. For half of the instruc-
tional strategies, class time was a larger concern than prep
time (collaborative learning, active learning, think-pair-share,
cooperative learning, peer instruction, and thinking-aloud-
paired problem solving). For the other half, faculty preparation
time before class was more critical (problem-based learning,
concept tests, case-based teaching, just-in-time teaching, and
service learning). Clearly, efforts to improve adoption rates
of new instructional strategies must address these common
faculty concerns, which in some cases are actually misconcep-
tions about the strategies. For example, cooperative learning
typically requires significant preparation time but need not
consume any significant amount of actual class time, suggest-
ing that some faculty concerns stem from a misunderstanding
of what is required to implement some of these strategies. A


TABLE 5
Barriers to Adopting Specific Instructional Strategies. This question allowed multiple responses. Percentages are based on
number of respondents who selected each strategy.
Total Takes up Too much Lack of Students My depart- My depart-
Respon- too much advanced evidence to would ment does ment and
dents class time to prepara- support the not react not have the administra-
let me cover tion time efficacy of this positively resource to tion would
the syllabus required instructional support imple- not value it
strategy mentation
Collaborative
Collaborative 66 58% 29% 33% 27% 4.5% 4.5%
Learning
Active74 58% 38% 26% 20% 6.8% 4.1%
Learning
Problem-
Based 68 44% 53% 29% 21% 4.4% 4.4%
Learning
Inquiry 74 46% 46% 34% 22% 4.1% 2.7%
Learning
Concept Tests 67 39% 52% 30% 16% 4.5% 4.5%
Think-Pair- ^^ p ^^ ^^
Think-Pair- 64 64% 30% 33% 25% 3.1% 3.1%
Share
Cooperative 58 59% 34% 36% 28% 5.2% 1.7%
Learning
Case^-Based ^ ^ ^
Case-Based 71 44% 63% 39% 17% 2.8% 4.2%
Teaching
Peer
Peer 73 52% 25% 41% 37% 5.5% 2.7%
Instruction
Just-In-Time ^^^^^^^
Just-In-Time 58 47% 69% 28% 10% 12% 3.4%
Teaching
Thinking-
Aloud-Paired ^ ^ ^
Aloud-Paired 50 56% 26% 36% 38% 4.0% 4.0%
Problem
Solving
Service
Service64 41% 64% 33% 13% 9.4% 11%
Learning
Average
across all N/A 51% 44% 33% 23% 5.5% 4.2%
RBIS

'4 Chemical Engineering Education










Nearly Never Once or
every day. 3% twice per

9 semester






semester
or term
1849%
Weekly
21%






Several
times per
semester
or term
49%

Figure 4. Frequency of respondent discussions about
teaching with colleague.

secondary concern was that the instructional strategy might
not actually improve student outcomes. ChE faculty members
were most skeptical about peer instruction, case-based teach-
ing, thinking-aloud-paired problem solving, and cooperative
learning. Again, these perceptions are contrary to significant
research that supports the use of these strategies, suggest-
ing the need for better awareness of the relevant research
by engineering instructors. Some faculty members were
also concerned about student reactions to new instructional
strategies, particularly for peer instruction and thinking-aloud-
paired problem solving, but this concern was not as strong as
others overall. Finally, concerns about department resources
and value of teaching efforts in promotion and tenure were
surprisingly low (average 4.2 and 5.5%), with one notable
exception of case-based teaching (11% and 9.4%).
We can conclude that many ChE faculty members do not
believe their administration to be one of the most significant
barriers hindering use of research-based instructional strate-
gies. They do, however, list time as the primary barrier, and
pressures about how to spend one's limited time can be an
important indirect influence. Much of the discussion around
engineering faculty change includes efficiency arguments,
based on the assumption that if an instructional change takes
more time than the current approach, then faculty members
will not be interested. While time is clearly an important
concern, any instructional change, such as adopting a new
textbook or digitizing course notes, requires additional time.
In some cases, these changes result in efficiency gains in
later semesters; in others, they are done because the faculty
member believes it is important for student learning. It may
be the case that more nuanced arguments around faculty time
and responsibilities would better address these concerns.
Vol. 47, No. 1, Winter 2013


SUMMARY AND DISCUSSION
Awareness of RBIS among the ChE faculty members who
responded to this survey is quite high, in most cases above
80%. Use varies more significantly, from 5-65%. Faculty
members identified a number of barriers to adopting these
instructional strategies. Time, both preparing and in class
with students, was their biggest concern (average 44% and
51% of faculty members). Secondary concerns were lack of
evidence for the strategies' effectiveness and student reac-
tions, while concerns about department resources and values
were much lower. Few statistically significant differences
were identified between faculty respondents who do and do
not use specific instructional strategies, but those identified
reinforce the importance of teaching workshops and regular
discussions with colleagues about teaching. Similarly, most
faculty members initially found out about RBIS through con-
versations with colleagues. In a few cases, colleagues were
also the most frequently cited source for more information.
Overall, faculty tended to turn to publications to learn more
about research-based instructional strategies.
These results lead to several implications for chemical
engineering faculty members interested in using research-
based instructional strategies. First, they are in good company;
87% of faculty who completed the survey indicated that they
currently use at least one of these strategies. While there is
reason to believe that this number overestimates actual use,
for reasons discussed previously, it is clear that many of these
research-based instructional strategies are finding their way
into the classroom. Faculty members who are using these or
other innovative instructional strategies should take advan-
tage of opportunities to tell their colleagues about what they
are doing. One of the findings from this survey is that many
faculty members who know about an RBIS first learned about
it from a colleague. Unfortunately, collegial conversations
about teaching do not take place as often as they should. It is
up to everyone involved in engineering education to foster
these sorts of discussions. These informal discussions are also
opportunities for current users to discuss how they overcame
the barriers to implementation, particularly since many users
have tried and abandoned RBIS.
Faculty developers and educational researchers should ex-
pand their propagation (i.e., dissemination) approaches. The
traditional approaches of conference presentations, papers,
and other publications are important archival sources for
detailed information. More interpersonal approaches were
also found to be very influential, however. Beyond isolated
workshops, chemical engineering education innovators should
be working to develop local and virtual communities of
practice to help others learn about, adapt, and improve their
instructional approaches. The content of these propagation
approaches should address time concerns, particularly incor-
rect perceptions, including frank discussion about how much
time one might expect to spend implementing an RBIS and










the trade-offs involved in using class time on more interactive
strategies. For example, to what extent is it possible to teach
core engineering science topics using these RBIS?
These findings also suggest several opportunities for future
work. Use of RBIS varies significantly in ways that are not
entirely understandable from the information we collected
in the survey. More work is needed to understand how char-
acteristics of the RBIS, the instructor, and the instructional
context interact to impact RBIS use. Many faculty members
tried some of the RBIS but no longer use them. Again, the
reasons are not clear from the data we collected, but the high
percentage of faculty members who have discontinued use
begs additional investigation. Perhaps most significantly,
perceptions of time (both class time and prep time) are an
important barrier to the use of RBIS. Identifying ways to deal
with this time barrier is clearly important. Finally, perceptions
about time demands and equipment needs ,and evidence of ef-
fectiveness, were not necessarily consistent with the literature
on these RBIS, suggesting the need for additional education
efforts to make faculty more aware of the relevant research
and the real implementation issues for these various strategies.

ACKNOWLEDGMENTS
This research was supported by the U.S. National Science
Foundation through grants 1037671 and 1037724, and while
M. Borrego was working for the foundation. Any opinions,
findings, conclusions, or recommendations expressed in this
material are those of the authors and do not necessarily reflect
the views of the National Science Foundation. The authors
wish to thank Dr. Margot Vigeant and the Virginia Tech Center
for Survey Research for their partnership and assistance on
this project.

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Vol. 47, No. 1, Winter 2013











M25=1 curriculum


TEACHING CHEMICAL ENGINEERS


ABOUT TEACHING







DANIEL E. HEATH, MARY HOY, JAMES F. RATHMAN, AND STEPHANIE ROHDIECK


The Ohio State University Columbus, OH 43210
knowledge and techniques that enhance student learn-
ing have been developed through rigorous research
by researchers in both the fields of general education
and engineering.E'61 Chemical engineers are rarely exposed
to this body of work. Furthermore, the task of independently
exploring this knowledge to become a better teacher is both
time consuming and daunting. The Chemical and Biomo-
lecular Engineering Department at The Ohio State Univer-
sity-along with a growing number of other engineering
departments -believes incorporating this information into
the graduate student curriculum is beneficial in preparing
future faculty.(7-91 Due to this belief, the Chemical Engineering
Mentored Teaching Experience was developed. The Chemical
Engineering Mentored Teaching Experience is a two-term,
graduate-level elective course that organizes and highlights
educational knowledge; presents the material in a way that is
relevant to the chemical engineering classroom; and allows
participants to enter the chemical engineering classroom to
gain hands-on experience as educators. A selection of topics
covered through the modules in the first term of the course
includes:
OSUpolicies and procedures
Teaching portfolios andphilosophy of teaching
statements
Student learning
Designing lessons
Assessing student learning


Assessing teaching effectiveness
During the first term of the Experience, participants are also


Daniel Heath completed his Ph.D. in chemical engineering at The Ohio
State University where he worked with Professor Stuart Cooper to develop
novel polymeric biomaterials that specifically adhere a population of adult
stem cells. During this time he also earned a Graduate Interdisciplinary
Specialization in College and University Teaching. Currently he is con-
tinuing his post-doctoral education with the Singapore-MIT Alliance for
Research and Technology where he works with Professors Griffith and
Hammond of MIT and Professor Mary Chan of Nanyang Technological
University to develop a platform to improve the study of rare cells in com-
plex cell mixtures. In the next phase of his career he hopes to become a
faculty member, continue his research in the areas of biomaterials, and
help educate the next generation of engineers.
Mary Hoy earned her B. S. degree from The Ohio State University in 2000.
She served as the undergraduate studies coordinator in the Chemical &
Biomolecular Engineering Department at Ohio State from 2003 2008
and was previously employed by the First Year Engineering Program at
the university.
James Rathman completed his Ph.D. in chemical engineering at the
University of Oklahoma in 198Z He worked in industry for a number of
years in the areas of surfactants and surface chemistry before returnuming
to academia. His current research interests are molecular self-assembly
and surfactants at biological interfaces. He teaches a wide variety of
courses including Fundamentals of Chemical Engineering, Thermo-
dynamics, Reaction Kinetics and Reactor Design, Bioinformatics, and
Experimental Design.
Stephanie Rohdieck is assistant director of University Center for the
Advancement of Teaching (UCAT) and the instructional consultant for
Graduate Teaching Associate (GTA) programs. She is also an adjunct
instructor in the School of Educational Policy and Leadership. She has
a master's in social work administration and earned her B.A. in psychol-
ogy and women's studies. Her current interests are graduate teaching
preparation, teaching portfolio development, and writing reflectively
about teaching.
Copyright ChE Division ofASEE 2013
Chemical Engineering Education
























paired with a faculty mentor with whom they develop mul-
tiple lessons, including associated homework, test questions,
active-learning activities, and assessment devices. During
the second term, participants take on the role of instructor by
entering the classroom to deliver these lessons, assess student
learning, and evaluate their own teaching effectiveness. The
Chemical Engineering Mentored Teaching Experience is a
three-credit-hour course that spans two quarters. Students
earn two credit hours by successfully completing the first term
of the Experience and the final credit hour after successfully
completing the second term.

MOTIVATION FOR COURSE DEVELOPMENT
At the beginning of each academic year, Ohio State holds
campus-wide Teaching Assistant (TA) Orientation. During
this week, new TAs from across campus learn how to im-
prove as educators. One of the first activities facilitators ask
the new TAs to perform is to think about an educator in their
past from whom they learned a lot. Each TA writes down one
characteristic of this instructor, and shares it with the rest of
the class. Some of these responses from the 2009 orientation
are listed in Table 1.
This exercise clearly illustrates that teaching requires two
very different skill sets: (1) knowing the material and (2) being
able to develop a course culture that aids student learning. The
majority of time that a chemical engineer spends in gradu-
ate school is focused on developing technical knowledge in
a given field by conducting research. Very little attention is
paid to developing teaching skills. The Chemical Engineering
Mentored Teaching Experience is designed to fill this gap in
the chemical engineering curriculum.
In 2000 Gaff, Pruitt-Logan, and Weibi published Build-
ing the Faculty We Need. The authors argue that "doctoral
education [...] has become disconnected from the realities
of faculty work" and that "doctoral students preparing for
faculty careers should begin to learn about the entire range
of faculty roles-teaching, research, and service-while in
graduate school." The authors then call to change the way
future college educators are prepared.'101 Subsequently, Ohio
State's Chemical and Biomolecular Engineering Department,
and many other engineering departments at a variety of in-


stitutions, have implemented graduate assistant development
programs and programs aimed to better prepare future faculty.

HOW THE COURSE WAS DEVELOPED
OSU's Chemical and Biomolecular Engineering Depart-
ment is home to a small but highly motivated group of Ph.D.
students interested in pursuing faculty careers. Unfortunately,
there were no courses available in the graduate curriculum to
provide training in the field of teaching in chemical engineer-
ing. To better prepare these students, the department deter-
mined that a course should be designed to help them develop
as educators. In preparation for the course development, the
interested students were asked about essential course charac-
teristics. Some of their responses are listed below:
A way to learn about teaching while still maintaining
productivity as a researcher.
Information on educational resources.
Real life experience as a teacher in the classroom.
A way to learn from experienced educators in the field.
The Chemical and Biomolecular Engineering Curriculum
Committee collaborated with the University Center for the
Advancement of Teaching (UCAT) to develop an effective
course experience. Daniel Heath (a graduate student) directed
the development of the course in conjunction with Stephanie
Rohdieck, James Rathman, and Mary Hoy. Rohdieck, an
Educational Consultant from UCAT, provided educational
knowledge and resources. Rathman and Hoy, both members
of the department's curriculum committee, provided advice
on how to make the educational knowledge relevant to the
modem engineering classroom and aided in achieving course
approval.

COURSE DESCRIPTION
The goals of this course are to develop doctoral graduates
who are (a) well prepared to be engineering educators and (b)
reflective about their own teaching. To achieve these goals
the Mentored Teaching Experience presents participants with
an iterative model of teaching. In this model a participant
develops his or her philosophy on teaching, designs a course,
takes this course into the classroom, and assesses student


Vol. 47, No. 1, Winter 2013


TABLE 1
Characteristics of Teachers That Have Aided Student Learning
Remembers my name Engages students Doesn't test material that wasn't taught
Tries different ways of explaining Stays on topic Makes me think
difficult concepts
Grades consistently, fairly, and promptly Uses humor in the classroom Clearly describes student expectations
Encourages questions, doesn't make me Uses appropriate examples in class Is approachable
feel stupid
Is willing to say "I don't know" Explains fundamentals before diving into Is well organized
more difficult material


















Assess student
learning and
teaching
effectiveness



SDeliver these AN
lessons in the
classroom

Figure 1. Schematic of the iterative teaching model de-
scribed in the Chemical Engineering Mentored Teaching
Experience.

learning and teaching effectiveness. The participant then
reflects on this feedback in order to update his or her teach-
ing philosophy and implement changes to the course. This
cyclical model of course development is illustrated in Figure
1. Since OSU uses a 10-week quarter system, we felt there
was too much information to fit into one term. Therefore, the
Mentored Teaching Experience spans two terms. Gray boxes
in Figure 1 denote activities that occur during the first term of


the experience, while white boxes denote activities that occur
during the second term.

The Modules
Participants complete six online modules (lessons) during
the first term of the Mentored Teaching Experience designed
to introduce students to various ideas and techniques on teach-
ing. Upon completion of each module students take a basic
recall quiz to ensure digestion of the material and complete
other assignments to aid in lesson development. The module
topics and the associated assignments are compiled in Table 2.
In the following text, each module is discussed in more detail.

Module 1. OSUpolicies and procedures: Before entering the
classroom, educators need a solid understanding of the rules
and regulations that govern the educational environment.
Therefore, the first lesson introduces participants to the Family
Education Rights and Privacy Act (FERPA), Americans with
Disabilities Act (ADA), OSU's Sexual Harassment Policy, and
OSU's Academic Misconduct Policy. A description of these
policies and examples of their use in the chemical engineering
classroom are provided. While participants cannot be prepared
for all the potential situations, this lesson provides a working
knowledge of the policies designed to handle a variety of situ-
ations along with resources if other problems arise.

Module 2. Teaching portfolios and philosophy of teaching
statements: Many educators document teaching activities in a


TABLE 2
Modules At a Glance: Lessons, Content, and Assignments
Module Content Assignments
Family Education Rights and Privacy Act (FERPA)
OSU Policies Americans with Disabilities Act (ADA) Basic Recall Quiz
and Procedures OSU's Sexual Harassment Policy
OSU's Academic Misconduct Policy
Teaching
Portfolios and What is a Teaching Portfolio Basic Recall Quiz
Philosophy of What is a Philosophy of Teaching Statement Reflection Papers
Teaching How to Write Your Own Philosophy of Teaching Statement Writing a Philosophy of Teaching Statement
Statements
Cognitive Theory of Learning
How Students Types of Knowledge Basic Recall Quiz
How Students _l-. ,, _,
Learn Transferring Knowledge Learning Styles Inventory
Transferring Knowledge vs. Problem Solving Reflection Paper
Learning Styles
i-> -- ^ -. i* Basic Recall Quiz
Deciding Course Goals Basic Recall Quiz
Dcdn Goals *. * Decide Lesson Goals with Mentor
Designing Writing Specific Learning Objectives ie Secif Lari O ective
Lessons Identifying Course Content Write Specific Learning Objectives
SLesson Structure Develop Lesson Plan
Lesson Structure ,., ....
Develop Active-Learning Activities

Assessing Formal Assessment Methods Basic Recall Quiz
Student Informal Assessment Methods Generate Homework and Exam Questions
Learning Using Assessment for Course Improvement Create Primary Trait Analyses
Create Classroom Assessment Techniques
Assessing The Importance of Collecting Feedback
Tseahing Methods of Collecting Feedback- .,_ .
Teaching Methods of Collecting Feedback Create an Assessment of Your Teaching
Effectiveness Using Feedback to Improve Teaching
Effectiveness ",. *"
Closing the Loop
(0 Chemical Engineering Education















New information
New information
is received. A
learner focuses
on key aspects
and transfers
information to
working
memory.


New information
is encoded and
transferred to
long-term
memory.

4
Existing
knowledge is
recalled from
long-term
memory.


Figure 2. Model of cognitive learning theory used in the Chemical Engineering Mentored Teaching Experience.


teaching portfolio.An individual's portfolio typically includes
a selection of teaching artifacts and reflection papers that
showcases his or her teaching style and values as an instruc-
tor.11,i In this lesson, participants are introduced to the basic
principles of how and why to create a teaching portfolio. As an
assignment, participants are asked to create a principal artifact
of a teaching portfolio: a philosophy of teaching statement.
The philosophy is a narrative that includes an educator's
notion of teaching and learning, a description of how he or
she teaches, and a justification for his or her teaching style.
Writing a teaching philosophy helps participants solidify
their views on education; these principles determine how
material is presented in the course, expectations of students,
and student/teacher interactions.111121 Given that many of the
participants in the Mentored Teaching Experience do not have
any formal educational training or experience, a significant
amount of instruction is required to facilitate the development
of a teaching philosophy. To aid participants in developing
their ideas on teaching, they are first asked to write a series
of reflection papers to make them think critically about the
education process. A brief description of each reflection paper
is given below.
The perspective of a learner. Participants have spent a
large part of their lives in the classroom and are expert
learners. We first tap into this prior knowledge by asking
participants to reflect on their experiences as students.
Through these exercises participants gain a deeper
understanding of what characteristics they feel make a
good educator and how they would like to behave in the
classroom, present material, and interact with students.
SThe perspective of research. Participants complete the
University of Iowa's Teaching Goals Inventory, a survey of
53 common yet very diverse educational goals. The list in-
cludes goals such as "developing problem solving skills,"
"improving speaking skills," "developing an openness
to new ideas," "improving self-esteem/self-confidence,"
and "developing a capacity to make wise decisions," etc.
Through this exercise participants become more acquaint-
ed with their individual values as educators and what
expectations they have of their students!13'


The perspective of a peer. One goal of the experience
is for participants to think of themselves as educators.
Therefore, we ask them to observe two courses within the
department (a large core course and a smaller technical
elective), analyze the classes from the point of view of a
teacher, and discuss their ideas.
Participants are asked to write an initial teaching philoso-
phy after completion of these experiences. Each participant
invests a significant amount of time in the development of
this document because it is a cornerstone piece for the rest of
the course. Following completion of the course, participants
reflect back on their work over the duration of the Experience
and integrate new ideas into an updated teaching philosophy.
Module 3. Student learning: The goal of this module is
to introduce participants to concepts on student learning
mechanisms, types of knowledge taught in a classroom,
and how learning styles affect the teaching environment.
By being cognizant of these different aspects of learning,
participants can hopefully apply this knowledge to become
better educators.
As teachers, it is important to ask how we can aid student
learning. A good way to begin answering this question is to
study how people learn. Cognitive psychology has developed
a broad body of literature that describes the processes of
memory and learning. The learning model used in the Men-
tored Teaching Experience is shown in Figure 2. In this model,
a person focuses his or her attention on new information,
which moves it into his or her working memory. Information
stored in long-term memory is then recalled and compared to
the new information, which is encoded through the process
of assimilation or accommodation. Ideas on employing this
method in the classroom are presented in the module.i1 Four
key aspects stem from this theory of learning that can be used
to help improve teaching:
1. To learn, students must change long-term memory by
developing connections between new and old information.
2. Students must focus on key aspects of new information in
order to learn it.


Vol. 47, No. 1, Winter 2013


Working memory
Temporarily holds
information and
compares new
information with existing
memory.


Long-term memory
Holds all memories from
past experiences in an
organized network of
organized associations
schemataa).











Course goal: Enable students to derive a
rate law from a proposed reaction
mechanism and develop the ability to use
the pseudo-steady state assumption to
construct a simplified rate law.


When presented
with a reaction
network, the
student will be
able to correctly
explain if the
reactions could be
an elementary
network and why.


When presented
with an
elementary
reaction network,
the student will
correctly use
mass action
kinetics to derive
the full rate law.


When presented
with an
elementary
reaction network,
the student will
correctly identify
which species the
pseudo-steady
state assumption
can be applied to
and explain why.


When presented
with a full rate law,
the student will be
able to correctly
derive the
simplified model
using the pseudo-
steady state
assumption.


Potential learning objectives

Figure 3. A generic course goal and potential learning objectives that could be used to
measure the success of this goal.


3. Students must encode material into the long-term
memory in order to learn it.
4. Students must be exposed to new information multiple
times in order for learning to last.1"
In addition to the mechanism of student learning, partici-
pants are exposed to the idea that there are different types of
knowledge: (1) foundational knowledge-the basic vocabulary,
principles, definitions, and facts that underpin a field; (2)
structural knowledge-where a student has organized knowl-
edge and understands how individual pieces of knowledge
fit together (most educators refer to this as understanding
the material); (3) skills development-where students develop
the intellectual process of applying knowledge to a problem;
and (4) knowledge transfer-where students are able to take
knowledge and use it to solve a completely new type of
problem.111 Developing each of these four types of learning
is necessary to be a successful engineering student, therefore,
the course modules present strategies for incorporating each
type of knowledge in teaching.
Understanding and acknowledging that each student has
his or her own unique learning style-meaning each student
learns material best in certain ways-adds an additional layer
of complexity to developing effective lessons. For instance,
Jane might be a visual learner while Alex might be more audi-
tory. Furthermore, educators tend to teach how they learn. If
the professor of a class has a more visual learning style, then
Alex may be at a disadvantage in the class. To create a fair


learning environment it
is necessary for faculty
members to know their
own learning styles so that
they can adjust their teach-
ing to embrace all learning
styles. To achieve this,
participants in the Men-
tored Teaching Experience
complete a learning styles
inventory to gain insight
into their own learning
styles and write a reflection
paper on the results and
how this could affect their
classroom environment.111
Although recent research
has called into question
the validity of considering
learning styles when plan-
ning courses, the authors
feel more research needs
to be performed before
such a well established
concept can be removed
from the Teaching Men-
torship Program.1141


Module 4. Designing lessons: In this module, participants
are provided with methods for (1) planning lessons and (2)
structuring their courses to aid student learning. Participants
are first encouraged to gauge the initial level of student
knowledge vs. the intended knowledge outcomes of the
course. By clearly identifying the differences, an educator
can build a course that bridges the gap between these two
points. Secondly, instruction is provided to participants on
creating a course structure that creates a favorable learning
environment for students.
The module breaks the act of designing lessons into two
pieces: (1) course planning and (2) presenting the material.
For course planning, we use the motto "plan with the end
in mind." By knowing where your students are at the begin-
ning of a class and where you want them to be at the end
of the class you can design lessons that will bridge the gap
between these two points. To achieve this goal, we ask the
participants to first plan generic course goals, and then write
specific learning objectives that support these goals. Often
the course goals are very broad statements that are difficult
to measure. Writing specific learning objectives gives an
instructor a way to determine if students are meeting his or
her expectations in the course.,"151 Figure 3 presents a pos-
sible course goal for a kinetics course and specific learning
objectives an instructor could use to determine if students
are meeting this goal. Once the course goals and learning
objectives are specified, participants are encouraged to select
Chemical Engineering Education































Figure 4. The bookend model for class design: Course content, recaps, and active-learning activities are sandwiched
between pre-class and post-class summary bookends.

Student Scores
Primary Trait Possible points Student I Student 2 Student 3 Student 4 Student 5
Write lull rate law 5 4 5 5 5 4 23/25
Select simplifying assumptions) 3 3 3 3 3 3 15/15
Explanation of why assumption was chosen 5 0 3 5 3 0 11/25
Application of assumption 5 5 5 3 5 5 23/25
Simplifying math 2 1 2 1 1 2 7/10
Correct answer 5 0 5 0 0 0 5/25


Figure 5. Example of a primary trait analysis for the grading of a kinetics homework.


appropriate course content to enable students to successfully
meet these goals.
The second part of the module provides ideas about how to
best present these materials to the students. Often engineer-
ing classrooms are teacher-centered; however, we encourage
the participants to pursue a more student-centered classroom
model by engaging students through the use of in-class
active-learning techniques. Lecture has a definite place in the
chemical engineering classroom. It is a powerful technique for
relaying a large amount of information in a short amount of
time. Augmenting lecture, however, with other, more active,
techniques such as discussion, cooperative learning, problem
solving, case studies, and problem-based learning, can help
students better learn the material. In the module we encourage
participants to use the Bookend Model to structure lessons
as illustrated in Figure 4. When using the bookend model, a
teacher begins class by providing an outline for the lesson,
uses lecture regularly augmented with recaps and active-
learning activities to instruct students, and then provides a
summary at the end of the class.11,151
Vol. 47, No. 1, Winter 2013


Module 5.Assessing student learning: To ensure students are
meeting the goals of the class, it is an instructor's duty to as-
sess student learning. This module describes both formal and
informal methods of assessment along with the idea that as-
sessment needs to be an ongoing activity throughout the term.
If employed correctly, formal assessment methods, such as
graded assignments, can provide insight into student learning.
In the module we discuss how to use the goals of the course
and the specific learning objectives to design assignments
that accurately measure student achievement of course goals.
Participants are also introduced to primary trait analyses
(PTAs). PTAs are rigorous grading rubrics designed to ensure
fair and consistent grading, speed up the grading process, and
gain the maximum amount of feedback on student learning
through grading.1161 A sample PTA for a homework assignment
in a kinetics course is presented in Figure 5. The first two
columns of the PTA identify the primary traits you wish to
see in the students' work and the points allocated to each trait.
In the subsequent columns we see the scores of five students.
The sum of the columns (dark gray) provides information









on how each student performed on the assignment. For in-
stance, Student 2 performed very well, while Students 1 and
5 may need additional help. The sum of the rows (light gray)

Instructions: In today's class we discussed the 3 main type
with the material flow in and out of the system and the mixin
geometry. Please provide a sketch of each reactor geometry
information in the outline skeleton given below.

Types of chemical reactors, mass flow characteristics, and n

A. Reactor type 1: Batch Reactor
1. Sketch: L Impeller
^-Impeller


Reactio


2. Material flow in and out of system: Batch reactors an
no mass flow in or out.
3. Mixing assumptions: Batch reactors are assumed to t
meaning the content is completely homogenized during

B. Reactor type 2: Continuous Stirred Tank Reactors (CSTRs)
1. Sketch:


Reaction v(


I Outle
2. Material flow in and out of system: CSTRs are open
inlet stream and one outlet stream.
3. Mixing assumptions: The reactor is assumed to be id
content of the inlet stream is instantaneously dispersed
also means the concentration in the reactor is the same
outlet stream.

C. Reactor type 3: Plug Flow Reactors (PFRs)
1. Sketch:







2. Material flow in and out of system: PFRs are open s;
occurs as the material flows through the length of the re
3. Mixing assumptions: The fluid is assumed to flow dov
individual plugs. Each plug is ideally mixed in the radial
occurs between plugs (no axial mixing).

Figure 6. Example of an empty outline CAT used ir


provides very different information. These values provide
an educator with information on how students collectively
understand each of the traits of the assignment. For instance,
students in this class are
of chemical reactors along good at writing the full rate
g assumptions for each law (23/25 points), excellent
and organize this at selecting the simplifying
assumptions (15/15 points),
and good at applying the
rnixing assumptions, assumptions (23/25 points).
Students are largely incapa-
ble, however, of explaining
why they chose the specific
assumptions (11/25 points).
To help the students, the in-
structor may take additional
n vessel class time to re-explain what
each assumption physically
means, and why a particu-
lar assumption would be
e dosed systems. There is selected for use. Also, it
is important to notice that
ie ideally mixed. only one student arrived at
the correct simplified rate
law. If the assignment were
being graded strictly on a
right/wrong basis, only Stu-
dent 2 would receive credit
ssel for the problem. From the
PTA, however, we see that
largely the problem arises
from mistakes in mathemat-
t stream ics, not in the utilization of
systems with at least one the simplifying assumptions.
Formal assessments are
really mixed. This means the a powerful tool for probing
throughout the reactor. This student learning, but they do
as the concentration of the have shortcomings. For in-
stance, students often work
together on homework so
homework sets are not an
accurate reflection of what
Reaction vessel individual students under-
stand, and graded assign-
ments do not always provide
feedback frequently enough
on student learning.E3",61 We
Vstems since the reaction suggest the use of informal
actor. assessment methods [also
m the length of the pipe in known as classroom assess-
direction but no mixing ment techniques (CATS)]
to help an educator better
monitor the learning of his
a kinetics class, or her students. CATs are
Chemical Engineering Education









completed in the classroom, provide the instructor with im-
mediate feedback on student performance, and generally use
very little classroom time. Instructors are then able to apply
immediate feedback and adapt the course mid-stream to help
their students learn. Angelo and Cross's book Classroom
Assessment Techniques discusses 27 different CATs and
provides examples of how each can be used in the classroom.
Furthermore, the CATs are classified into five categories
based on the type of skills and knowledge you want to test:
(1) assessing prior knowledge, recall, and understanding; (2)
assessing skill in analysis and critical thinking; (3) assessing
skill in synthesis and creative thinking; (4) assessing skill in
knowledge transfer; (5) and assessing skill in application and
performance [13]
One CAT that we will discuss in more depth here is the
Empty Outline, where the teacher passes out an empty out-
line (or partially filled outline) and has students fill in the
missing information. This technique helps students organize
the information (build structural knowledge) and allows the
teacher to see how well the students absorbed the important
concepts of the lesson.J131 In Figure 6, a kinetics instructor
uses an empty outline to probe how well students picked up
on material flow into and out of batch, continuous stir tank,
and plug flow reactors along with the mixing assumptions of
each. Bolded text is provided to the students while the non-
bolded text represents the desired student response.

Module 6. Assessing teaching effectiveness: The best way
to improve courses is to collect data about teaching effective-
ness. At The Ohio State University, teaching effectiveness
is probed through an end-of-term student survey called the
Student Evaluation of Instruction (SEI).J151 Although this sur-
vey does provide valuable information, it is a stock survey so
there may be additional information a specific instructor may
wish to collect.1151 Furthermore, this assessment occurs only at
the end of the term, meaning that the results arrive too late to
help an instructor improve his or her teaching for the current
class. Several other assessment techniques are presented to the
participants in addition to the SEI: peer evaluation, evaluation
from an outside consultant, and teacher-generated evalua-
tions. Participants of the Mentored Teaching Experience are
required to develop a survey to assess their own teaching
effectiveness, which they will administer to their students in
the subsequent quarter.0171

THE MENTORSHIP EXPERIENCE AND
LESSON PLANNING
Completing the modules gives participants an introduction
to a cyclical model of teaching and guides them in develop-
ing a new perspective on engineering education.11'11-61 The
mentorship experience is designed to allow participants to
then apply that knowledge directly. Participants are paired
with a faculty mentor of their choice. Concurrently, they
develop multiple lessons for a course the faculty mentor will
Vol. 47, No. 1, Winter 2013


be delivering during the following term. Participants choose
their own mentor because we felt it was important to allow
the students the freedom to learn from an educator who has
a similar teaching style to what they would like to develop.
Although planning the lessons is up to the participants and
their mentors, participants are required to utilize the skills pre-
sented in the modules. Specifically, participants are required
to: develop generic lesson goals and write specific learning
objectives; incorporate at least one active-learning activity
(more are preferred) and at least one informal classroom
assessment technique into each lesson; and use the learning
objectives to generate test and homework questions that ac-
curately measure the achievement of lesson goals .1,13-161

Role of the participant and the mentor. During the lesson
planning the participants are expected to perform the bulk of
the preparation. The mentors, however, are also expected to
take on a substantial role. For instance, many professors have
taught this particular class multiple times, and have a wealth
of knowledge about what textbooks and extra readings are
helpful, what concepts are often difficult for students to grasp,
and how much material can be presented in a given class
period, etc. This prior knowledge is invaluable to a person
entering the classroom as the instructor for the first time, and
the Mentored Teaching Experience allows the participant ac-
cess to this prior knowledge.
Although the primary reason for the strong mentor involve-
ment in the lesson planning is to aid the participant, it is also
important to ensure that the course is cohesive and coherent
for the students taking the course; therefore, by supervising the
lesson development the primary instructor can ensure that all
the necessary information is being presented to the students.
The primary goal of the mentorship program is that participants
gain knowledge from their mentor; however, a secondary goal
is that the mentor is exposed to new ideas on teaching and can
also grow as an educator through this experience.

Evaluation of the participant and the course. At the be-
ginning of the Teaching Mentorship Experience we asked
participants to reflect on the educational experience from
various viewpoints. We ask them to do so again at the end of
the Experience by analyzing the feedback they gain through-
out the Experience. Feedback is gathered from classroom
assessment techniques, grades on homework and exams
(where feedback is maximized through the use of PTAs dur-
ing grading), and through formal surveys.E161 Mentor feedback
is given through direct communication between the mentor
and participant as they discuss the success of the lessons after
each class is presented. Lastly, participants are asked to write
reflection papers after each lesson and at the end of the course
to document how they felt the class went, what worked well,
and what should be changed the next time.
With feedback from the students, mentors, and themselves,
the participants are asked to update their teaching philoso-









phies. This enables participants to see how their views on
teaching have changed and how they have grown as educators.
Furthermore, we feel that "closing the loop" with students is
an important practice in order to create a classroom environ-
ment where students feel respected and listened to. Therefore,
we ask participants to share results of the surveys with the
class and let students know what changes they would make
to the lessons if they were to teach the lessons again in the
future.[1,15,171
For grading and reporting purposes, the mentor performs the
evaluation of the participant. At the beginning of the Mentored
Teaching Experience the participant signs a contract that lists
the tasks he/she will complete in order to successfully com-
plete the course. The contract includes such various entries
such as "the participant will complete all the modules" to "the
participant will dedicate at least 2 hours a week on average to
independent learning on an educational topic that is of interest
to him/her." At the end of the Mentored Teaching Experience
the mentor will approve the contract indicating that the stu-
dent has successfully completed all the goals of the course.
Although this contract is a unique method for evaluating a
student, we feel this reporting approach is suitable since the
Mentored Teaching Experience is unique and tailored to each
individual participant.

Where are they now? To date, seven students have par-
ticipated in the Mentored Teaching Experience. Six of the
students have completed their degrees while one is still in
the process of writing/defending her dissertation. Of the six
students who have graduated, one decided that he was not
interested in pursuing a teaching career, and another (due to
personal reasons) accepted a job in the private sector. The
remaining four individuals decided that they were indeed
highly interested in pursuing academic careers and are now
in post-doctoral positions at highly respected institutions.
One of these individuals entered the job market immediately
after completing his graduate degree and was offered a job
at a solely undergraduate teaching institution. The job was
offered to him largely due to his participation in the Teach-
ing Mentorship Experience and his participation in other
teaching-oriented activities. Although this individual is still
highly interested in teaching, he learned that he also wishes
to have an equally strong presence in research. Therefore,
he declined this offer in order to pursue a post-doc to further
develop his technical skills and hopefully find a position at
an institution with more balanced teaching/research thrusts.

Future work. As each participant finishes the Experience we
ask for his or her comments on the course and suggestions
for improvement. Similarly, the mentors are also queried as
to how the course could be improved. Several of the main
comments that are currently being addressed are listed below:
SAdditional reading material other than the Modules
should be used.


Having multiple students go through the Experience at the
same time would be helpful so that they can learn from
one another.
Mentors need to better understand what is expected of
them.
Students need to be introduced as to why someone other
than the instructor is teaching them.
Some of these concerns are easily addressed, while others
are not. For instance, a set of references is being compiled
for the participants so they can easily locate resources
that will help them learn more about the topics they are
interested in. Furthermore, an information page is being
drafted for the mentors so that they better understand the
goals of the Mentored Teaching Experience and what is
expected of them. Also, it is expressly explained to students
in the class why a graduate student is instructing several
of their lessons.
The second point is the most difficult to address. There
is a very motivated subset of students who are interested in
this type of course; however, only one student per year on
average participates in the Experience. To date we have not
advertised the course heavily. Instead, we have let students
take the initiative. In the future, however, we may choose to
be more aggressive about recruiting students to participate
in the course.
Another aspect of the Experience we are currently improv-
ing is the evaluation of the participants. Currently they take
a quiz upon completing each module to probe their assimila-
tion of the knowledge. The remaining assessment is done by
the faculty mentor. We are currently discussing methods for
adding more formal assessment into the second term of the
Experience, however, such as a final exam, etc.

CONCLUSIONS
The Chemical and Biomolecular Engineering Depart-
ment at The Ohio State University has developed an online
elective for Ph.D. students who are interested in pursuing
faculty careers. This course is designed to aid these students
in developing as an instructor by introducing them to ideas
on teaching, pairing them with a faculty mentor, and allow-
ing them to develop and administer two to three lessons in
an engineering classroom along with the associated assign-
ments and assessments. This course was first offered in the
2007-2008 academic year. To date, seven graduate students
have participated in the program illustrating that a subset of
graduate students desire this type of course in the graduate
Chemical Engineering curriculum.

ACKNOWLEDGMENTS
We would like to thank Angela Bennett, the Graduate Pro-
gram Coordinator for the Chemical and Biomedical Engineer-
ing Department at Ohio State, for her efforts in organizing

Chemical Engineering Education











the course, the mentors, and the participants; gaining course
approval from the university; and her general guidance. This
course could not be successful without her.


REFERENCES
1. Svinicki, M., Learning and Motivation in the Postsecondary Classroom,
Bolton, MA, Anker Publishing, Inc. (2004)
2. Svinicki, M., and WJ. McKeachie,McKeachie's Teaching Tips: Strate-
gies, Research, and Theory for College and University Teachers, 13th
ed., Belmont, Calif., Wadsworth (2011)
3. Marincovich, M., J. Prostko, and F Stout, The Professional Develop-
ment of Graduate Teaching Assistants, Bolton, Mass.,Anker Publishing
(1998)
4. Wankat, P.C., and F.S. Oreovicz, Teaching Engineering, New York,
McGraw-Hill (1993)
5. Wankat, P.C., and F.S Oreovicz, ."Teaching Prospective Engineering
Faculty How to Teach," Int. J. Eng. Ed., 21(5), 925 (2005)
6. Ambrose, S.A., and M. Norman, "Preparing Engineering Faculty as
Educators," The Bridge, 36(2), 25 (2006)
7. Brent, R., R.M. Felder, and S.A. Rajala, "Preparing New Faculty
Members to Be Successful: A No-Brainer and Yet a Radical Concept,"
Proceedings of the 2006 Annual ASEE Conference and Exposition,
Session 637
8. Linse,A.,J.Tumrns, J.M.H, Yellin, and T. VanDeGrift, "Preparing Fu-


ture Engineering Faculty: Initial Outcomes of an Innovative Teaching
Portfolio Program," Proceedings of the 2004 Annual ASEE Conference
and Exposition, Session 3555
9. Lewandowski, G., and C.C. Purdy, "Training Future Professors:
The Preparing Future Faculty Program in Electrical and Computer
Engineering and Computer Science at the University of Cincinnati,"
Proceedings of the 2001 Annual ASEE Conference and Exposition,
Session 2655
10. Gaff, J.G., A.S. Pruitt-Logan, and R.A. Weibl, Building the Faculty
We Need, Washington, D.C., Association of American Colleges and
Universities (2000)
11. Seldin, P., The Teaching Portfolio, 2nd Ed., Bolton, MA, Anker Pub-
lishing, Inc. (1997)
12. Edgerton, R., P. Hutchings, and K. Quinlan, The Teaching Portfolio:
Capturing the Scholarship of Teaching, Washington, DC, American
Association for Higher Education (1991)
13. Angelo, T., and K. Cross, Classroom Assessment Techniques, Hoboken,
NJ, Jossey-Bass, Inc. (1993)
14. Pashler, H., M. McDaniel, D. Rohrer, and R. Bjork, "Learning styles:
concepts and evidence," Psych. Sci. Pub. Intr., 9(3), 105 (2008)
15. The Ohio State University's University Center for the Advancement of
Teaching, Teaching at The Ohio State University, a Handbook (2001)
16. Walvoord, B., and V. Anderson, Effective Grading, a Toolfor Learning
and Assessment, Hoboken, NJ, Jossey-Bass, Inc. (2010)
17. The Ohio State University's Center for the Advancement of Teaching,
FYI: Feedback on Your Instruction (2002) 0


Vol. 47, No. 1, Winter 2013











fi2 curriculum


Online Data Resources in Chemical Engineering Education:


IMPACT OF THE UNCERTAINTY CONCEPT


FOR THERMOPHYSICAL PROPERTIES1'2



SUN HYUNG KIM AND JEONG WON KANG
Korea University Seoul, Korea
KENNETH KROENLEIN, JOSEPH W MAGEE, VLADIMIR DIKY,
CHRIS D. MUZNY, ANDREI F. KAZAKOV, ROBERT D. CHIRICO, AND MICHAEL FRENKEL
Thermophysical Properties Division, National Institute of Standards and Technology Boulder, CO 80305-3337


while the analysis of uncertainty has long been rec-
ognized as one of the cornerstones of measurement
science, its practical implementation in a variety
of scientific and engineering fields has typically seen less
emphasis than it deserves. This is particularly true for the
field of thermodynamics, which deals with more than 120
thermophysical and thermochemical properties that are of
paramount importance for the support of both the scientific
discovery process and a great number of large-scale industrial
applications. This point was clearly demonstrated by recent
study'l conducted by the Thermodynamics Research Center
(TRC) of the U.S. National Institute of Standards and Technol-
ogy (NIST), which involved a review of reporting practices
for uncertainty in the literature. Establishment of a global
communication process in the field of thermodynamicsE] that

Sun Hyung Kim received a B.S. from Korea University in 2008 in chemical
engineering. He is currently a graduate student under the guidance of Professor
Jeong Won Kang in the Department of Chemical and Biological Engineering,
Korea University.
Jeong Won Kang received a B.S., M.S., and Ph.D. from Korea University in
1988,1990, and 2001, all in chemical engineering. He worked at Hyundai En-
gineering Co. Ltd. from 1990 to 1997Z He is currently an associate professor in
the Department of Chemical and Biological Engineering, Korea University. His
research has been mainly focused on measurements and model development
for thermophysical properties of fluids.
Kenneth Kroenlein received a B.S.E. and Ph.D. from Princeton University in
2001 and 2007 respectively, both in mechanical and aerospace engineering. He
is currently a mechanical engineer with the National Institute of Standards and
Technology. His research has been mainly focused on thermophysical property
evaluation, cheminformatics, and combustion phenomena.
Joseph W. Magee received a B.S. in 1978 from Georgia Institute of Technol-
ogy, and an M.S.(1981) and Ph.D.(1983) from Rice University, all in chemical
engineering. He is currently a chemical engineer with the National Institute of
Standards and Technology. He has held engineering faculty adjoint/guest ap-
pointments at CU-Boulder and NDA (Yokosuka, Japan). His research interests
are in the areas of thermodynamic property measurements and data analysis/
evaluation.
Vladimir Diky received M.S. and Ph.D. degrees from Belarusian State Univer-
sity (Belarus) in 1990 and 1993, respectively. He is currently a chemist at the


involves NIST/TRC and five journals in the field (Journal of
Chemical and Engineering Data, Journal of Chemical Ther-
modynamics, Fluid Phase Equilibria, Thermochimica Acta,
and the International Journal of Thermophysics) has led to
the finding that at least 10% of articles reporting measure-
ment of thermodynamic properties contain some erroneous
information in numerical data and/or metadata. These findings
demonstrated, again, the necessity for unambiguous reporting
of uncertainties for all experimental data in order to aid the
process of data validation. This has led to new requirements

1 This contribution of the National Institute ofStandards and Technol-
ogy is not subject to copyright in the United States.
2 Products or companies named here are cited only in the interest of
complete technical description, and neither constitute nor imply
endorsement by NIST or by the U.S. government.

National Institute of Standards and Technology. His principal research interests
include analysis and modeling of thermodynamic data, communication of chemi-
cal information, and chemical process simulation.
Chris D. Muzny received a B.S. in 1982 from Southeastern Oklahoma State
University in physics and mathematics, and an M.S.(1986) and Ph.D.(1994) in
physics from the University of Colorado at Boulder. He is currently a physicist at
the National Institute of Standards and Technology. He works for the Thermody-
namics Research Center on the development and maintenance of a database
of thermophysical properties of a large range of mostly hydrocarbon substances.
Andrei R Kazakov received an M.S. in 1989 from Moscow Institute of Physics
and Technology (Russia) and a Ph.D. in 1997 from Pennsylvania State Uni-
versity. He is currently a physicist with the National Institute of Standards and
Technology. His research is in the areas of combustion physics and modeling of
thermodynamic properties.
Robert D. Chirico received an A. B. in chemistry from Rutgers University in 1974,
and a Ph.D. in chemistry at the University of Michigan in 1979. He is currently a
chemist with the National Institute of Standards and Technology. His research is in
the areas of thermodynamic property measurements and data analysislevaluation.
Michael Frenkel received an M.S. in chemistry from Belarusian State University
(Belarus) in 1975 and a Ph.D. in Physical Chemistry in 1981 from the same uni-
versity. Currently, he is director of the Thermodynamics Research Center at the
National Institute of Standards and Technology (Boulder, Colorado). His research
interests include phenomenological and statistical thermodynamics, molecular
modeling, and software expert systems.


Copyright ChE Division of ASEE 2013
18 Chemical Engineering Education









for mandatory provision of combined uncertainties within
data tables.E381 As recently demonstrated,191 inadequate, in-
complete, or missing uncertainty information for experimental
data can, in turn, lead to poorly developed structure-property
correlations. A lack of reliable estimates of uncertainties for
thermophysical property data commonly results in overde-
sign of production modules in chemical manufacturing with
an associated enormous waste of energy and materials.110-111
In the long term, we believe that undergraduate and
graduate-level educational institutions are the key venues in
which to address the issues associated with poor understand-
ing of the concept of uncertainties for physical properties.
Until very recently, however, progress has been limited, to a
significant degree, due to the absence of resources providing
comprehensively assessed uncertainties of critically evaluated
data. Recent development and software implementation of
the concepts of a Global Information System in Science with
application to the field of thermodynamicsl21 and of dynamic
data evaluation for thermophysical and thermochemical prop-
erties113'181 in combination with modem Web technologies for
data communication1191 now provide a unique opportunity to
bring state-of-the-art metrology to the classroom for a new
generation of chemical engineers. This article presents an
overview of the technical background and basic concepts
of propagated uncertainties, plus a summary of online data
resources for thermophysical and thermochemical proper-
ties, and then illustrates how the concept of uncertainties for
properties can be brought to the curriculum of traditional
chemical engineering courses, such as thermodynamics and
chemical process design, with the use of the available online
data resources.

UNCERTAINTIES OF THERMOPHYSICAL AND
THERMOCHEMICAL PROPERTIES
Efforts to provide guidance in the assessment of uncertainty
as a foundation for measurement science date back to the
1970s. Those efforts resulted in the publication of the Guide
to the Expression of Uncertainty in Measurement[201 in 1993.
These ISO (International Organization for Standardization)
recommendations were adopted with minor changes as the U.S.
Guide to the Expression of Uncertainty in Measurement.J211
Reference 20 is commonly referred to by its abbreviation, the
GUM. The GUMrecommendations have been summarized in
Guidelines for the Evaluation and Expression of Uncertainty
in NISTMeasurement Results,1223 which is available via free
download from the Web.1231 The GUM provides definitions of
all quantities and terms relevant to uncertainty, but by design,
does not provide their interpretation for specific scientific
and engineering fields. The GUM concepts were further in-
terpreted for the field of thermodynamics in 20031241 by an
IUPAC (International Union for Pure and Applied Chemistry)
Task Group as a part of the IUPAC project 2002-055-3-024
"XML-based IUPAC Standard for Experimentally and Criti-


cally Evaluated Thermodynamic Property Data Storage and
Capture."'251 This interpretation has now become a part of
the IUPAC standard for thermophysical and thermochemical
property data communication, ThermoML.J261 ThermoML was
first adopted by IUPAC in 20061271 and was further extended
in 2011 .1281
In compliance with the recommendations of the GUM and in
accordance with the provisions of ThermoML, various forms
of precision such as repeatability, root-mean-square (rms)
deviation from a fitted curve (for a data set), and measuring
device specification can be used to partially characterize
data quality for components of the metadata infrastructure
of thermophysical and thermochemical properties data (i.e.,
properties, variables, and constraints).
The only comprehensive measure of overall data quality,
however, is the combined expanded uncertainty. Basic prin-
ciples, definitions of terms and interpretation of the combined
expanded uncertainty for thermodynamic quantities have
been described in detail.1251 The quantity combined expanded
uncertainty reflects all possible sources of error associated
with propagated uncertainties for variables and constraints,
as well as in the case of experimental data, those related to
sample purity and quality of the measuring device, and in case
of predicted data, those related to the nature of the prediction
model. Combined expanded uncertainties for thermophysi-
cal and thermochemical properties are usually provided with
the coverage factor (multiplier of standard uncertainty) of 2,
which is associated with a level of confidence of 95%.
Critically evaluated data are recommended property values
generated through assessment of available experimental and
predicted data and their uncertainties.1131 Based on the analysis
above, it is clear that critically evaluated data, supplemented
with their combined expanded uncertainties, are the most
reliable information to be used in applications requiring
thermophysical and thermochemical property data.

THERMOPHYSICAL AND THERMOCHEMICAL
PROPERTY DATA RESOURCES
The evolution of data resources for thermophysical and
thermochemical properties (from hard-copy to main-frame
to PC to relational data facilities to the Web) has been dis-
cussed recently by Frenkel.t291 Currently, there are several of
high-quality data resources available online on a subscrip-
tion basis (DECHEMA,1301 PPDS,1311 DIPPR1321) or through
response-upon-availability query (Dortmund Data Bank).[331
Generally, all of these resources provide some assessment of
the quality of the data.
The recently developed NIST Web Thermo Tables
(WTT),119,34' also available on a subscription basis, provide
critically evaluated thermophysical and thermochemical
property data for pure compounds. A unique feature of
WTT is the characterization of each property value with a


Vol. 47, No. 1, Winter 2013










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combined expanded uncertainty. WTT
is a Web application of the NIST Ther-
moData Engine (TDE)[1'3-18'35] with a
Professional Edition (covering 23,399
compounds as of November 2011) and
a Lite Edition (covering most common
150 compounds) .4] TDE represents the
first full-scale software implementation
of the dynamic data evaluation concept.
This concept requires large electronic da-
tabases capable of storing essentially all
relevant experimental data known to date,
with detailed descriptions of metadata and
uncertainties. The combination of these
electronic databases with expert-system
software, designed to automatically gen-
erate recommended property values based
on available experimental and predicted
data, leads to the ability to furnish criti-
cally evaluated data dynamically or "to
order."[12'
WTT includes a system for cach-
ing evaluation results to maintain high
availability and an advanced window-in-
window interface that leverages modem
Web-browser technologies1191 with full
traceability to the original sources of
information. WTT provides a variety
of critically evaluated thermodynamic
property data for pure components,
including phase-diagram, volumetric,
energy-related, and transport proper-
ties. While WTT is limited currently to
pure compounds, its extension to binary
mixtures, ternary mixtures, and chemical
reactions based on TDE software libraries
is expected in the near future. Since WTT
provides critically evaluated data with
assigned combined expanded uncertain-
ties, it provides a unique opportunity to
illustrate the uncertainty concept in tradi-
tional courses of the chemical engineering
curriculum. Examples of extraction from
WTT of invariant and variable-dependent
thermophysical properties, plus their
uncertainties, for propane are provided
in Figures 1 and 2.

Figure 2 (left). Examples of tempera-
ture-dependent properties (saturated
vapor pressure and liquid viscosity) for
propane extracted from WTT Vapor
pressures are plotted on a logarith-
mic scale, as a function of reciprocal
temperature.
Chemical Engineering Education









USE OF WTT FOR EDUCATIONAL PURPOSES
-THERMODYNAMICS COURSES
Thermodynamics is one of the fundamental courses in the
curriculum for students majoring in chemistry, mechanical en-
gineering, and chemical engineering. In-depth understanding
of thermophysical and thermochemical properties is critical
for adequate progress in learning essentially all principal top-
ics in the chemical engineering curriculum (First and Second
Laws, power cycles, steam engines and turbines, fluid flow,
refrigeration, generalized p-V-T relations, the standard Gibbs
energy concept, etc.). This understanding lays a firm founda-
tion for their extensive use in other courses of the chemical
engineering curriculum and supports a unified approach to
consideration of flow processes, power generation, compres-
sion of gases, chemical equilibria, fluid flow, heat balances,
etc.[36] None of these topics can be satisfactorily analyzed
without state-of-the-art knowledge based on the concept of the
combined expanded uncertainty as the fundamental measure
of reliability of thermophysical and thermochemical proper-
ties. No one part of this information is more or less important
than others. In fact, numerical value, combined expanded
uncertainty, and metadata infrastructure (phases, variables,
constraints, units) are equally important and essential for
appropriate use of property data for educational purposes in
a thermodynamics course. The use of WTT provides the op-
portunity for students to analyze a broad variety of materials
outside of commonly used examples, such as water, air, and
refrigerants.
Two examples, similar to those provided in the textbook of
Smith et al.,1371 and fully described in the appendix (Appendix
1), provide a comparison of two calculations of molar volume
for ethylene (with its combined expanded uncertainty) at a
given temperature and pressure. In the first example, a three-
term virial equation of state is used, and in the second, the
critically evaluated density of the gas is applied. The identi-
cal results obtained illustrate that WTT technology enforces
thermodynamic consistency between the related properties
within their uncertainties.

USE OF WTT FOR EDUCATIONAL PURPOSES
-PROCESS DESIGN AND OTHER CORE
COURSES
Core courses in chemical engineering- such as elementary
process calculations, fluid mechanics, heat and mass transfer,
reaction engineering, conceptual design, process simulation,
and process control -require knowledge of a variety of ther-
mophysical properties to illustrate key concepts involved. A
process-design course, in many ways, integrates knowledge
from a number of core chemical engineering courses. In tak-
ing full advantage of computing capability and multimedia
support for self-paced instruction, Lewin et al.1381 emphasized
that presently, early-career chemical engineers are expected
to improve product quality, while at the same time reducing
Vol. 47, No. 1, Winter 2013


operating costs and environmental impact, improving oper-
ability, minimizing waste production, and eliminating hazards.
It is, therefore, incumbent on chemical engineering educators
to provide a modem curriculum for process design instruction
that addresses these needs, while being mindful of time con-
straints.1381 It is critical, in our view, that this instruction would
include sufficient focus on uncertainties of thermophysical
properties and their impact on decision-making including
selection of process technology, flowsheet, and its operating
parameters, particularly with regard to emerging interests in
energy and sustainability.1391 Indeed, for example, Larsent1101
showed that a 20% error in density may result in a 16% change
in equipment size (or cost), and a 20% error in diffusivity may
result in a 4% error in equipment size.
Successful efforts in teaching chemical process design are
impossible without extensive use of process simulators. Re-
cently,4,41]1 the elements of the NIST ThermoData Engine135]
were integrated into process simulation software. That de-
velopment provides an opportunity to analyze the impact of
uncertainty in thermophysical properties on characteristics
and cost of principal operation units through commercial
process simulators, such as Aspen Plus.1421 This is not pos-
sible to do online, however, which must be considered when
taking into account time limitations. Similarly, various chemi-
cal product design applications of the ThermoData Engine
technology are currently available only in the stand-alone
format.1171 Consequently, WTT presents a unique opportunity
to illustrate the impact of uncertainty of thermophysical prop-
erties on engineering applications within the core chemical
engineering courses.
The example provided in the Appendix 2 is similar to that
in the textbook by Denn'431 and illustrates propagation of un-
certainties in a pipe-sizing calculation. The results obtained
show that the impact of uncertainty in density on the pipe
diameter is much higher than that of the uncertainty in viscos-
ity. Fortunately, densities are usually reported with smaller
uncertainties than viscosities, but this cannot be assumed.
The example discussed in the Appendix 3 is similar to that
in the textbook by Incropera et al.1441 and illustrates the impact
of the combined uncertainty of the thermophysical properties
on design of a pipe-inside-pipe heat exchanger. This example
shows that the properties of the hot-side stream are of utmost
importance when considering the appropriate length of the
heat exchanger. It also shows that, in principle, disregarding
uncertainties in thermophysical properties of the process
streams may lead to serious problems in designing process
unit operations.

USE OF ONLINE DATA RESOURCES FOR
UNDERGRAD AND GRAD RESEARCH
As a comprehensive online resource for thermophysical
property data with combined expanded uncertainties, WTT
can be used extensively in graduate and undergraduate re-










search in chemical engineering, targeting the development
of new and modification of existing chemical processes. It
can also be used in development and verification of property
models and correlations using large data sets with uncertain-
ties as a measure of their reliability. Finally, graduate and un-
dergraduate students can use ThermoPlan,t451 a public domain,
free-access, online software product, to develop their plans
for experimental measurements of thermophysical properties.
Specifically, ThermoPlan is a software tool for assistance
in the process of experiment planning for thermophysical
property measurements. As it was for WTT, ThermoPlan
was also developed with ThermoData Engine technology, in
part, to respond to the increasing need of the scientific and
engineering communities for experiment planning in the field
of thermophysical property measurement science, which is
envisioned to undergo the transformation "from accuracy to
fitness for purpose."46l ThermoPlan provides recommenda-
tions concerning the relative merit of a given measurement
via assessment of the existing body of knowledge, including
availability of experimental thermophysical property data,
associated uncertainties, variable ranges studied, state of
prediction methods, and availability of parameters for deploy-
ment of prediction methods.

CONCLUSIONS
Themophysical-property data continue to be key and funda-
mental to chemical engineering education and research. The
concept of uncertainty of thermophysical property data cannot
be overlooked and is of increasingly high importance. The
availability of online resources of thermophysical properties
has permanently changed the landscape in both education and
research. We believe that these new opportunities should not
be lost and that extensive use of the concept of the combined
expanded uncertainty for thermophysical and thermochemical
properties in thermodynamics courses, as well as in other core
courses of the chemical engineering curriculum, including
chemical process design, is paramount to ensure that the new
generation of chemical engineers will be able to respond to
modern challenges in designing new chemical products and
processes.

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Constants for Pure Compounds," Fluid Phase Equil., 298, 131 (2011)
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namic Updates over the Web," J. Chem. Inf. Model., 47,1713 (2007)
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Abdulagatov, K. Kroenlein, and M. Frenkel, "ThermoData Engine
(TDE): Software Implementation of the Dynamic Data Evaluation
Concept. 5. Experiment Planning and Product Design," J. Chem. Inf.
Model., 51,181 (2011)
18. Diky, V., R.D. Chirico, C.D. Muzny, A.F. Kazakov, K. Kroenlein, J.W.
Magee, I. Abdulagatov, J.W. Kang, and M. Frenkel, "ThermoData En-
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Concept. 7. Ternary Mixtures," J. Chem. Inf. Model., 52,260 (2012)
19. Kroenlein, K., C.D. Muzny, V. Diky, A. Kazakov, R.D. Chirico, J.W.
Magee, I. Abdulagatov, and M. Frenkel, "ThermoData Engine (TDE):
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Thermo Tables," J. Chem. Inf. Model., 51,1506 (2011)
20. Guide to the expression of uncertainty in measurement (International
organization for standardization, Geneva, Switzerland, 1993). This
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IEC, ISO, or OIML, the Guide is published by ISO in the name of all
seven organizations.
21. US. Guide to the expression of uncertainty in measurement, ANSI/
NCSLZ540-2-1997. Boulder,CO: NCSLIntemational,ISBN 1-58464-
005-7 (1997)


Chemical Engineering Education










22. Taylor, B .N., and C.E Kuyatt, "Guidelines for the Evaluation and Ex-
pression of Uncertainty in NIST Measurement Results," NISTTechnical
Note, Gaithersburg, MD, 1297 (1994)
23. Accessed March 8,2012
24. Chirico, R.D., M. Frenkel, V.V. Diky, K.N. Marsh, and R.C. Wilhoit,
"ThermoML- an XML-Based Approach for Storage and Exchange of
Experimental and Critically Evaluated Thermophysical and Thermo-
chemical Property Data. 2. Uncertainties," J. Chem. Eng. Data., 48,
1344(2003)
25. Frenkel, M., IUPAC project 2002-055-3-024, "XML-Based IUPAC
Standard for Experimental and Critically Evaluated Thermodynamic
Property Data Storage and Capture," ects/2002/2002-055-3-024.html> Accessed March 10,2012
26. ThermoML IUPAC Namespace ThermoML/index.html> Accessed March 10,2012
27. Frenkel, M., R.D. Chirico, V.V. Diky, K.N. Marsh, J.H. Dymond,
W.A. Wakeham, S.E. Stein, E. K6nigsberger, and A.R.H. Goodwin,
"XML-Based IUPAC Standard for Experimental, Predicted, and Criti-
cally Evaluated Thermodynamic Property Data Storage and Capture
(ThermoML): IUPAC Recommendations 2006," Pure Appl. Chem.,
78,541(2006)
28. Frenkel, M., R.D. Chirico, V. Diky, P.L. Brown, J.H. Dymond, R.N.
Goldberg, A.R.H. Goodwin, H. Heerklotz, E. Konigsberger, J.E.
Ladbury, K.N. Marsh, D.P. Remeta, S.E. Stein, W.A. Wakeham, and
P.A. Williams, "Extention of ThermoML: the IUPAC Standard for
Thermodynamic Data Communications (IUPAC Recommendations
2011)," Pure Appl. Chem., 83, 1935 (2011)
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Demand for Chemical Process and Product Design," Comp. Chem.
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30. Accessed March 14,2012
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March 14,2012
34. Kroenlein, K., C.D. Muzny, A.F. Kazakov, V. Diky, R.D. Chirico,
J.W. Magee, I.Abdulagatov, and M. Frenkel. NIST/TRC Web Thermo
Tables: Professional Edition, NIST Standard Reference Subscription
Database 3 Accessed
March 14,2012; Lite Edition, NIST Standard Reference Subscription
Database 2 Accessed
March 14,2012
35. Frenkel, M., R.D. Chirico, V. Diky, C.D. Muzny, A.F. Kazakov, J.W.
Magee, I.M. Abdulagatov, K. Kroenlein, and Jeong Won Kang. NIST
ThermoData Engine: NIST Standard Reference Database 103b (Pure
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tions) Accessed March 12,
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Accessed March 14,2012
36. York, R., "Thermodynamics for Undergraduates in Chemical Engineer-
ing," J. Chem. Ed., 19,1935 (1942)
37. Smith,J.M.,H.C.Van Ness, andM. M.Abbott,Introduction to Chemical
Engineering Thermodynamics, 7th Ed., McGraw-Hill College, New
York, p. 117 (2005)
38. Lewin, D.R.,W.D. Seider, and J.D. Seader, "Integrated Process Design
Instruction," Comp. Chem. Eng., 26,295 (2002)
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in the Teaching of Process and Product Design," AIChE J., 56, 1120
(2010)
40. Watanasiri, S., "Development of On-Demand Critically Evaluated
Thermophysical Properties Data in Process Simulation," Pure Appl.
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41. Tremblay, D., and S. Watanasiri, Benefits of the NIST ThermoData
Engine in AspenONE Engineering V7.2, White Paper, Aspen Tech-
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pdf> Accessed Feb. 27, 2012


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(1980)
44. Incropera, F.P., D.P. DeWitt, T.L. Bergman, and A.S. Lavine, Funda-
mentals of Heat and Mass Transfer, 6th Ed., John Wiley & Sons, New
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M. Frenkel, ThermoPlan Experiment Planning and Coverage Evalu-
ation Aid for Thermophysical Property Measurements, NIST Standard
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46. Wakeham, W.A., M.A.Assael, J.K. Atkinson, J. Bilek, J.M.N.A. Fare-
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cal Property Measurements: the Journey from Accuracy to Fitness for
Purpose," Int. J. Thermophys., 28,372 (2007)

APPENDIX 1: EXAMPLE FOR A THERMODY-
NAMICS COURSE
Problem:
Calculate molar volume (V) and its uncertainty for ethyl-
ene at 25 C and 12 bar, with two solutions, designated by
(a) and (b):
(a) by using the truncated (three terms) virial equation of
state given by,

Z=I+B+ (1)
V V2

where Z is the compressibility factor, and B and C are the
second and the third virial coefficients; and, (b) derived from
the critically evaluated density in the gas state.
Solution:
T= 25 *C = 298.15 K,P= 12bar = 1.2x106 Pa, R = 8.314462
J-mol-l-K-1
(a) Values of virial coefficients are calculated from WT' at
a given temperature (see Figure 3, next page),
B = (-1.401 0.042) x 101 m-mol-1 and C = (7.47 0.37)
x 10-9 m6-mol-2,
=PV B C(2)
RT V V2 (2)

Numerical solution of the above equations with given con-
stants yields
V = 1.91918 x 10-3 m3mol-'. Combined expanded uncertainty
is given by


(av U av
u--tB Iuo+M cu


where uB and uc are the uncertainties of B and C, respectively. The
derivatives are obtained by differentiation of the virial equation:

BV R(PV +B 2C -
B=RT+V V =1.16 (4)


Vol. 47, No. 1, Winter 2013










r)V =fPV2 +B+ 2
a v = +B+V =6.06x102mol'm-3 (5)
(C RT V)

Then, the evaluation of the combined expanded uncertainty
yields the answer;
V = (1.9192 0.0049) x 10-3 m3n-mol-1.
(b) The critically evaluated density in the gas state is retrieved


from WTT at the given temperature and pressure (see Figure
3), p = (14.617 0.073) kg-m3. The density is converted
to molar volume with the molecular weight of ethane, W =
28.054 g-mol-1 = 28.054 x 10-3 kg-mol-1 (see Figure 3),V =W
/p = 1.91923 x 10-3 nm3-mol-'. The uncertainty is given by

U= = W-up =9.6x 10-6 m3. mol-' (6)
P|p


111 '7 r. X
.i ,-'a,, ,|.T J? *.n-.r,-, ,4. 3 l -* d ,it .r aJ.. 1.... I. L, *. :2, ... 1' ": ; ... . _._ |
[I T i !o o -= i ,~ I, D ,T i,] 'T j_ 7 _

;W..n"w HBWi I Ci-mp 5,i -.h S NWge OeW_____



,. ,_ .. ..


I e 1, -r 1 Fm'L CT2 H4






?I,




.- :; I..-:A. 9.1 1,I


f2011 0pynB6ytw US Sb dlcre oa s Q an* bchta eUIBdSolA.. a.n ,eread_


Then, the calculated molar volume,
with uncertainty, is V = (1.9192
0.0096) x 10-3 m3.mol-1.
As seen, the values obtained in (a)
and (b) agree. Identical results reflect
the fact that the WTT technology
enforces consistency across reported
thermodynamic properties.

APPENDIX 2: EXAMPLE
FOR A FLUID MECHANICS
COURSE
Problem:
2,6-Dimethyl-4-heptanol at 20C is
pumped through a commercial steel
pipe at a velocity u = 1.5 m-s-1. The
pressure drop per length is recom-
mended, generally, to be 350 Pa-m-.
Determine the diameter of the pipe
under the given conditions. The surface
roughness e for commercial steel is
considered to be 0.05 mm. Accept the
following assumptions:
* 2,6-dimethyl-4-heptanol is an
incompressible Newtonian fluid.
The pipe is a long horizontal pipe
of constant cross section.
No shaft work is done.
Losses in fittings and valves are
negligible.
Uncertainties associated with the
given conditions are negligible.
Solution:
The thermophysical properties of
saturated 2,6-dimethyl-4-heptanol ex-
Figure 3 (left). Second and third
virial coefficients as a function of
temperature and density as a func-
tion of temperature and pressure for
the gas phase for ethene extracted
from WTT for solving the problem
described in Appendix 1.


Chemical Engineering Education


I^CG ^ ^ m n a,, ^ C ^d s.. NK L ,^
l_ .. .'. jis,%, )/,, .


I










traced from WTT at T = 293.15 K (Figure 4) are: density Q =
(809.75 0.54) kg-m-3; viscosity ij = (0.0133 0.0026) Pa-s.
With the assumptions given, the pressure drop is related
only to the friction factor. The Fanning friction factor f is
defined by:

f= Ap D7)
2pu2 L '()

where Ap is the pressure drop, D is the diameter of the pipe,
L is the length of the pipe, p is the density of the fluid, and u
is the flow velocity. The fluid is assumed to have a turbulent
flow, and the Colebrook equation is used to calculate the
Fanning friction factor for turbulent flow:
1 (, e/D 1.256 (
f 3=-4 .7g Re- j (8)

where Re is the Reynolds number,

Re Dup (9)
TI

Substitution of the expressions for Re and f into the Colebrook
equation results in a non-linear equation with respect to D.
Its numerical solution yields D = 8.744 x 10-2 m. The earlier
assumption of turbulent flow is verified by evaluation of the
Reynolds number by use of the value of D, which yields Re
= 7.985 x 104. The combined expanded uncertainty of the
diameter is expressed by,

2 (lD) u 2 (D 2)


The derivatives in the above quotation are evaluated numeri-
cally by use of the central difference approximation,
lD = D(x+Ax)-D(x-Ax)
3x 2Ax

where x is the independent variable (either p or TI), and Ax is
its increment. The convergence of the central difference ap-
proximation was tested with increments of 1 % and 0.1 % of
the initial value for each variable. The converged results are

D =6.30x10-5m4 *kg-', (12)
ap

-l= 1.31m2 .-s.kg (13)


The combined expanded uncertainty for D is equal to:
uD = 3.4x10-3m (14)


Finally,


D=(8.740.34)xlO-2m


(15)


The combined expanded uncertainty in this example is


dominated by the uncertainty of viscosity, as the density
value is much more accurate (0.1 % uncertainty vs. 20 %
uncertainty). Indeed, (a D/D p)up equals 0.000034 m and
(a D/ TI)UI equals 0.0034 m.

APPENDIX 3: EXAMPLE FOR A HEAT AND
MASS TRANSFER COURSE
Problem:
A counter-flow, concentric-tube heat exchanger is used to
cool 2-aminoethanol for capturing carbon dioxide. The flow
rate of cooling methyloxirane through the inner tube (D, = 25
mm) is ic = 0.2 kg.s-1, while the flow rate of 2-aminoethanol
through the outer annulus ( D. = 45 mm) is ri, = 0.1 kg-s-1.
The 2-aminoethanol and methyloxirane enter at a temperature
of 100 C and 30C, respectively. How long must the tube be
made if the outlet temperature of the 2-aminoethanol is to be
60C? Accept the following assumptions:
Negligible heat loss to the surroundings
Negligible kinetic and potential energy changes
Negligible tube wall thermal resistance and fouling factors
Temperature andflow rate have negligible uncertainties
Heat capacities of both components at constant pressure
are equal to those at the saturation line.
Temperature, viscosity, and thermal conductivity of both
streams are equal to those at the saturation line.
Also use information provided in Table 1 to interpolate the
necessary Nusselt number as a function of (D/Do). The Nus-
selt number is assumed also to have negligible uncertainty.
Solution:
To calculate properties, the average temperature of the
methyloxirane and 2-aminoethanol streams must be deter-
mined. For the 2-aminoethanol stream, this temperature is Th


Vol. 47, No. 1, Winter 2013


TABLE 1
Nusselt number for fully developed laminar flow in a
circular tube annulus with one surface insulated and the
other at constant temperature."
D/Do Nu Nu
0 3.66
0.05 17.46 4.06
0.10 11.56 4.11
0.25 7.37 4.23
0.50 5.74 4.43
=1.00 4.86 14.86
* Kays, W.M., and H.C. Perkins, in: Rohsenow, W.M., and
J.P. Hartnett, eds., Handbook of Heat Transfer, Chapter 7.
New York: McGraw-Hill (1972)
t D and D. are the diameters of inner tube and outer annulus,
respectively. Nu and Nu. are the Nusselt numbers of inner and
outer surfaces, respectively.










= 353.15 K. For the methyloxirane stream, this tem-
perature TC can be found only by simultaneous de-
termination of the final temperature of the methylox-
irane T and the heat capacity of the methyloxirane
stream at its average temperature CS.C. We assume T
to be 43.6 C = 316.75 K as an initial approxima-
tion. The saturated properties of methyloxirane at T.
= 316.75 K extracted from WTT (Figure 5) are: heat
capacity C = (126.4 1.8) J-mol-l-K-1; viscosity ]
= (2.50 0.19) x 10- Pa-s; thermal conductivity, k
= (0.115 0.013) Wm-lK-1. For 2-aminoethanol at
Th = 353.15 K, these properties are (Figure 5): C5
= (181.0 + 2.6) J-mol- K-4; viscosity r] = (2.996 +
0.073) x 10-3 Pa-s; thermal conductivity, k = (0.234
0.005) W-m-' K-1. The molecular masses of methy-
loxirane and 2-aminoethanol are W = 0.05808
kg.mol' and Wh = 0.06108 kg.mol-1, respectively.
The required heat transfer rate q may be obtained
from the overall balance for the hot fluid, 2-ami-
noethanol:

q = h C (Th-T )=11.85kW
Wh


where rih is the flow rate of the hot stream (2-aminoethanol).
Th, and T, are the inlet and outlet temperature of the hot
stream, respectively.
The methyloxirane outlet temperature is obtained from the
corresponding balance,

q = rii C-(T -T,), (17)
qW
T: -. q = -+T,, =330.38K (18)


Then T = (330.38 + 303.15) / 2 = 316.76 K, which is close
to the initial approximation. Generally, the simultaneous de-
termination of the final temperature of the methyloxirane To
and heat capacity of the methyloxirane stream at its average
temperature C0 can be obtained with an iterative process.
The required heat exchanger length L may now be obtained
from the equation:
q=UAAT.m, (19)

where U is the overall convection coefficient, A =n D. L and
ATIm the log mean temperature difference defined by:
AT AT^ 20
Aln[AT-/AT] (20)
1.In [4. / AT (20

(T, -T o)-('T, -T ^)
ATIm = ( '-T' )-(T-' ',) =36.01K (21)
InLT.,- TJ / (T T "


-aa_ ~ Carpoqmd Sa=c. i_ SfO O
*Ow* 00*19 000CM.. I, Na,
Fa
aflJ irnaowai~i L
E..dY-woNn| j,,r MCI


T,

W- I,'
Ebu-a. [K.mur> C- b.. j | Ali

oJ 5.0. 0 'rw,460
Emnn1 60C4 .www 1 f.Ehuu L T,


x I


00 2.6&4mthVW4-hoptano1
hnta- CH"MO
W1 a 144.58
8a-ve Names, dsobulol caWthnol
4400Vanmo. 2.6-OMMa-iw


Figure 4. Density and viscosity for the saturated liquid phase as a
function of temperature for 2,6-dimethyl-4- heptanol extracted from
WTTfor solving the problem described in Appendix 2.


(16) For methyloxirane flow through the tube, the Reynolds
number Re is


Re=puDi=PDix rh -= 4th =40744
1 i pitD / 4 itDc,


(22)


Accordingly, the flow is turbulent and the Nusselt number
can be computed from the scaling equation


Nu =0.023Re415 PrO4,


(23)


where the Prandtl number Pr = CQI/W k. Substitution of prop-
erties for methyloxirane yields Pr = 4.731 and Nu = 208.81.
The resulting convection coefficient is

hi =Nu-k = 960.5 W. -M2 -.K' (24)
D,

For the flow of 2-aminoethanol through the annulus, the
hydraulic diameter D h is
D, = D D, = 0.02m, (25)

and the Reynolds number is

RepuDh = pDh x mh 4ih =607.1(26)
TI 11 pir(Do-D)/4 i7t(D,+D,)n

The annular flow, therefore, is laminar.
Linear interpolation between the values provided in Table 1
for the given (D/Do) results in Nu. =5.64.
The convection coefficient for the outer flow is

h. =NUi k-=66.01 W" 2K- (27)
D,


Chemical Engineering Education


Ay J" .1 WUM


.I L.1










The overall convection coefficient is, then,

U= -- I- =61.77 Wm-2* K-' (28)
(1/h,)+( (1/hI h)

and the sought length is

L= q -=67.85m (29)


Rigorous uncertainty analysis for this example is not
feasible due to the number of approximations made in the
process (such as constant thermophysical properties taken at
a representative temperature value). The following analysis
is performed to illustrate the effect of typical experimental
uncertainties of the input thermophysical properties on the
resulting value in practical calculations. As previously, all
partial derivatives were evaluated by use of a central differ-
ence approximation with increments of 1 % and 0.1 %. The
results are summarized in Table 2. As seen, the uncertainty of
the thermal conductivity of 2-aminoethanol has the largest ef-
fect on the predicted length of heat exchanger, followed by the
uncertainty of heat capacity of 2-aminoethanol. Uncertainties
in input thermophysical properties alone produce roughly 2.8
% uncertainty in the length of the heat exchanger. C

TABLE 2
Analysis of the impact of the uncertainties in thermo-
physical properties of methyloxirane and 2-aminoetha-
nol on the length of the heat exchanger of a pipe-inside-
pipe type.*
x aL L
ax U Lx
3x ~3x

methyloxirane
C, -0.188 mnmol-K-J-" 0.188 m
1 6.98 x 103 m-Pa'-s-'I 0.133 m
k -22.8 m2-K-W-' 0.296 m
2-aminoethanol
C, 0.501 m-mol-K-J-' 1.30mi
1 0 rn-mPa'-s-' 0 m
k -271 mI2-K-W-1 1.36m n
x, a property (C,, 1, or k); C., heat capacity in the liquid phase
at the saturation line; T1, viscosity in the liquid phase; k,thermal
conductivity in the liquid phase; L the length of the heat
exchanger;
3L
*x uncertainty of the required length of the heat
exchanger associated with the uncertainty of the property x.
For 2-aminoethanol,3L/aTI is zero because the flow is laminar.


Figure 5. Heat capacity, viscosity, and thermal con-
ductivity for the liquid phase at saturation pressure for
methyloxirane and 2-aminoethanol as a function of
temperature extracted from WTTfor solving the problem
described in Appendix 3.


Vol. 47, No. 1, Winter 2013










M book review
-- d________________


An Engineer's Alphabet- Gleanings From the Softer Side of a Profession
by Henry Petroski
Cambridge University Press (2011) $14.95


Reviewed by Frank Oreovicz
Purdue University, West Lafayette, IN 47907

Handbooks are books that, quite simply, are at hand, for just-
in-time use: find the information and move on. So it's rare to
find oneself more or less reading through such a guide. Some
occasional hopping around usually occurs, what with the lack
of a continuous narrative. Well, not since discovering Schott's
Miscellany have I enjoyed sitting and thumbing through a
little book as much as I have through Henry Petroski's An
Engineer's Alphabet Gleanings From the Softer Side of a
Profession. To the man or woman in the street, engineering, by
definition, is usually "hard engineering": bridges, highways,
turbines, and so on. So it's refreshing to read of the softer,
human side of the profession.
Prof. Petroski refers to the book as "an anthology, a com-
monplace book, and a reference volume." All of which are
accurate, but I like an older term-vade mecum, what early
handbooks were called-from the Latin "go with me." And
following the good Professor's guidance is certainly a pleasant
and rewarding experience.
A quick thumb-through of the index shows outlines of
engineering-as-hard-engineering as well, but you soon find
Aristotle, Asclepius, the Boston Red Sox, Walt Disney, Ham-
let, Charles Ives, Dilbert (!), Henri Matisse, Thomas Pynchon,
Ayn Rand, Shakespeare, Thoreau, Voltaire, Vonnegut, and
Andy Warhol, to name just a few.


Interested in egg drop competitions? See page 83. This
engineering staple for design contests for students of all ages
is soon followed by "Elegy to an engineer's sweetheart"
(85), "Faith of the Engineer" (106), fight songs for engineers
(121), novels about engineering (222), and St. Patrick (see
page 270 on why he's considered the patron saint of engi-
neers). Shakespeare on engineers soon follows (286), as do
slang and euphemisms of engineers (289). And what would
the softer side be without the famous "Stress Analysis of a
Strapless Evening Gown" (299)! See for yourself the many
other gleanings.
Even though the book is a compilation of earlier writings,
there is a consistency to Prof. Petroski's voice and style that
unifies the selections. A most cogent assessment was made
by one reviewer of an earlier work, who noted that "Petroski
writes... with the observant eye of an engineer and the imagi-
native heart of a novelist." (Review of Paperboy Memoir in
Cambridge Book Club interview).
Finally, having Prof. Petroski at my elbow has me thinking
along classical lines and recalling the sentiment of Callima-
chus (b. ca 350 BC) who lamented that excessively long works
were being produced by the likes of fellows such as Homer.
He suggested that mega biblion, mega kakon! loosely trans-
lated as "A big book is a big nuisance." By that criterion, "An
Engineer's Alphabet" is indeed a delight-enjoyable in any
form, whether electronic or traditional, though I'd argue for
the latter, as it's a handbook that nicely fits in one's hand! 0


Copyright ChE Division of ASEE 2013


Chemical Engineering Education










! class and home problems )


The object of this column is to enhance our readers' collections of interesting and novel
problems in chemical engineering. We request problems that can be used to motivate student
learning by presenting a particular principle in a new light, can be assigned as novel home
problems, are suited for a collaborative learning environment, or demonstrate a cutting-edge
application or principle. Manuscripts should not exceed 14 double-spaced pages and should be
accompanied by the originals of any figures or photographs. Please submit them to Dr. Daina
Briedis (e-mail: briedis@egr.msu.edu), Department of Chemical Engineering and Materials
Science, Michigan State University, East Lansing, MI 48824-1226.




TRANSPORT PHENOMENA PROJECTS:

Natural Convection Between Porous, Concentric Cylinders

-A Method To Learn and To Innovate




ESTEBAN SAATDJIAN, FRANCOIS LESAGE, AND JOSE PAULO B. MOTA1
ENSIC Ecole Nationale Supirieure des Industries Chimiques 54001 Nancy Cidex, France
' Universidade Nova de Lisboa 2829-516 Caparica, Portugal


t is well recognized worldwide that transport phenomena
courses are of fundamental importance in the chemical
engineering curriculum of major universities at both
the undergraduate and the graduate level. As defined in the
pioneering text Transport Phenomena by Bird, Stewart, and
Lightfoot,1[' which was first published in 1960, this science is
concerned with the balance of momentum (fluid mechanics),
energy, and mass in a wide variety of elementary and industrial
processes. An undergraduate program in chemical engineering
would typically have two required courses related to transport
phenomena (fluid flow, heat and mass transfer) and perhaps
several optional courses on some more advanced topics such
as non-Newtonian fluid mechanics, radiation heat transfer,
two-phase flow, rheology, etc. Although the basic conservation
of mass, energy, and momentum equations have not changed
since they were formulated a long time ago and an instructor
can still confidently use Reference 1 as background material to
his or her course, a modem transport phenomena curriculum
at the senior or graduate level could profit greatly from some
of the major research results that have been published over
the last 50 years. Furthermore, as illustrated below, many
different aspects of transport phenomena can be studied via
the solution of a well-defined project.
Today (and it was not the case 50 years ago) every un-
dergraduate owns a laptop computer; a student can solve
numerically practically all 2-D coupled transport phenomena
Vol. 47, No. 1, Winter 2013


problems that, 50 years ago, required the use of the computing
facilities of the university. Although the solution of partial dif-
ferential equations is part of a course on numerical methods,
as in the many excellent textbooks on numerical methods such
as Reference 2, adding or revisiting this material in a course
on transport phenomena makes a lot of sense today. The use
of an upwind scheme for the advection terms in a transport
equation is a good example of the symbiosis between these
two subjects.
A domain where considerable progress has been made over
the last 50 years is natural convection. Half a century ago an
undergraduate course on natural convection would focus mainly
on the dimensionless numbers of importance (Rayleigh number,

Esteban Saatdjian is, since 1989, a professor of chemical engineering
at ENSIC in Nancy, France, and an adjunct professor at Georgia Tech. He
teaches transport phenomena and computational fluid dynamics (CFD) to
undergraduate and graduate students. His current research interests are in
mixing of viscous fluids, magnetohydrodynamic flows, and micro-fluidics.
Francois Lesage is an associate professor of chemical engineering at
ENSIC. He teaches process control, CFD, and numerical methods to un-
dergraduate students. His research interests are in process optimization
and two-phase flow.
Jos6 Paulo Mota is, since 1997, a professor of chemical engineering at
Universidade Nova de ULisboa, Lisbon, Portugal. He teaches transport phe-
nomena, process control, and optimization. His current research interests
are in adsorption, mixing, and molecular simulations. He graduated from
the University of Porto in 1991 and obtained his Ph.D. in Nancy, France.
Copyright ChE Division of ASEE 2013










Grashof number), on the Boussinesq approximation and on
experimental correlations available for different geometries.
Experimental and numerical results obtained over the last 30
years have radically increased our knowledge on this subject.
The same argument is also valid for mixed convection, i.e.,
combined forced and natural convection.
Here we present a numerical natural convection project
that we have given to our senior/graduate students, it is based
on researcht3' published about 20 years ago. We highlight
the different aspects of transport phenomena that need to be
mastered in order to obtain a solution and discuss what the
students can learn from this work. We feel that this project
is in total agreement with the opinion of W.M. Kays[41 on
what problems for graduate students should be. Almost 50
years ago he wrote, "At some point, and the earlier the bet-
ter, the student must face up to the analysis of problems that
may require considerable time, possibly extensive outside
study, and that are incompletely stated or specified so that
individual judgement must be exercised." Although the first
PC appeared more than 10 years later he also wrote "Many
of the problems require numerical or graphical integration or
iterative calculation procedures. If (the students) have access
to a computer they ought to develop the habit of using it in
their problem work."
In a planned follow-up paper we will discuss different
variations to this problem for use in future years or in a
graduate course. These variations are fluid layers, heat
flow reduction, and a change in geometry. Natural convec-
tion also permits the instructor to introduce the student to
hydrodynamic stability.

NATURAL CONVECTION BETWEEN
CONCENTRIC POROUS CYLINDERS
The subject that we gave to our senior/graduate students in
the fall semester of 2011 was:
Consider two very long, horizontal, concentric cylinders
maintained at constant but different temperatures with
T > T A saturated porous material,for example glass
wool insulation, occupies the annular region between the
two cylinders. Write the appropriate conservation equations
for this natural convection problem and determine numeri-
cally the temperature and velocity fields in the annular
layer. Calculate the heat loss to the surroundings. Suggest
improvements in order to reduce these heat transfer losses.
Assume that the temperature difference between the two
walls (actually the Rayleigh number) is not too high so that
the flow inside the annular region is not turbulent.
Below we discuss the major steps involved in the solution
of this project.

Conservation equations and boundary conditions
The governing conservation equations must first be written
and simplified. The student must start by writing the continuity


equation in a porous medium. In vector notation and without
any assumptions it is:

EP+VpV=O (1)
at
where E is the porosity of the porous medium, p is the fluid
density and V is the velocity vector. To simplify the above
equation to V -V = 0, the continuity equation for an incom-
pressible fluid, the students will have to understand the dif-
ference between a fluid whose density depends on pressure
and a fluid whose density depends on temperature. We explain
this in the classroom by discussing the flow of air over a verti-
cal radiator in the winter, when the radiators are turned on.
The air flow rises along the radiator and the entrained dust
particles stick to the wall just on top of the radiator usually
in a parabolic velocity distribution shape. A review of vector
analysis will be necessary to write this equation in cylindrical
coordinates and, as we shall see later on, in other orthogonal
coordinate systems.
The simplest equation of motion for a fluid in a porous
medium is Darcy's law:

V=-k[VP-pg.] (2)

We have deliberately chosen a porous medium instead of a
pure fluid to simplify the numerical work for senior students.
When the annular layer is saturated with a pure fluid, the 2-D
numerical solution can be obtained using either a vorticity-
stream function formulation or by solving the primitive equa-
tions using a SIMPLE algorithm. The number of coupled pdes
to be solved is higher (three instead of two) and the treatment
of variables for which boundary conditions are not known
(vorticity or pressure) is required. Nevertheless, a pure fluid
such as a gas could be used in projects for graduate students
with a more solid background in numerical methods for partial
differential equations and on the solution of the Navier-Stokes
equations in particular. (We plan to discuss this topic in detail
in a later paper.)
Darcy's law is a linear relationship between fluid velocity
and pressure drop, the permeability of the porous medium k is
determined experimentally. Again a review of vector analysis
is necessary to write the (r, 0) components of this equation,
special care must be made both to express the gravity vector in
cylindrical coordinates and to define the origin of the tangential
coordinate 0. In natural convection and for moderate Rayleigh
numbers the flow velocity is relatively small so that Darcy's
law is more than adequate. Deviations from Darcy's law oc-
cur mainly when the flow rate through the porous medium is
high. Other more complicated flow equations for use in these
conditions (Brinkman equation, Forchheimer equation) exist,E51
and the students and the instructor can spend some time in the
classroom discussing these and deciding whether the use of a
more elaborate (empirical) equation is warranted.


Chemical Engineering Education









A control volume, on which a heat balance will be per-
formed, needs to be defined before a heat balance is written.
The control volume that was used in this project is partially
occupied by the fluid and partially occupied by the immobile
solid phase. The temperatures of the solid and fluid phases are
assumed equal for simplicity. The student must recognize that
both the accumulation of heat and the heat conduction terms
involve both the solid and fluid phases; however, the advec-
tion terms involve only the fluid phase. In this problem the
conditions are such that viscous heat dissipation is negligible.
The instructor and the students should spend some time in
the classroom discussing these assumptions and eventually
trying to develop a model where the temperatures of the fluid
and solid phases are different.
The conservation of energy equation that was used in our
project is:
(pc)) T+(pcP) (V.VT)= X*V2T (3)

where X* is the thermal conductivity of the porous medium. In
this equation fluid properties are marked with subscript f and
properties of the porous medium as a whole (solid and fluid)
are labeled with superscript *. The properties of the porous
medium as a whole could be evaluated using:

(pcP)f = (1-E)(pc,) +(pc )f
X* = (l F) X + F~f

but other alternatives are also possible .M5
The linear equation of state for an incompressible fluid
whose density varies with temperature is:
p=po[l-0(T-To] (4)

where P is the thermal expansion coefficient. Natural con-
vection is driven by gravity forces, the fluid density is as-
sumed constant everywhere except in the body force term
in Darcy's law, this is the Boussinesq approximation. As
Joseph Boussinesq (1842-1929) wrote (originally in French):
"One must know that in most fluid movement provoked by
heating, volume and density are practically constant even
though the difference in weight of the fluid is the cause of
the movement under analysis. From there results the pos-
sibility of neglecting density variations when they are not
multiplied by the gravitational acceleration g, although one
must take into account in the calculations the product of
these two quantities."
The Boussinesq approximation was tested some 30 years
ago when experiments were realized in the Skylab where
there is practically zero gravity. When a liquid was heated
from below, no convective movement was observed. Because
of this, the time required to boil water under zero gravity is
much longer than on earth. This experiment confirms that the
Boussinesq approximation is relevant in most practical cases.


The next step consists in defining appropriate reference
quantities for both dependent and independent variables and
to render the equations dimensionless in order to highlight
important dimensionless numbers. Here we chose Rin the
inner cylinder radius as reference length, (pC )* R2 / *
as reference time, /R, (pCp)f as reference velocity,
.g*/k(pCp) as reference pressure. We also defined a
dimensionless temperature 0 = (T Tut)/(Tin T0) which
varies between 0 and 1. The number of dimensionless equa-
tions to be solved can be reduced by recognizing that, for 2-D
incompressible fluids, it is possible to define a stream func-
tion (which automatically satisfies the continuity equation).
In dimensionless variables the stream function is defined as:
1 31i 311/ -
vr =-- v- (5)
r a0 =-r"

The two velocity components are thus replaced by just one
independent variable, the stream function Vp. In the govern-
ing equations there is one dependent variable, pressure P,
for which it is not possible to write boundary conditions; the
same is true for the Navier-Stokes equations. In both cases
this dependent variable can be eliminated from the equations
by recognizing the vector identity:
V x VP=0.
The final dimensionless equations to be solved are:
E30 ae v 3 2 E0 1 0 e 1 a2
-+v, -+-+-_ (
3t a3r r 3 3r2 r 3r r2 302
a 32 1W3^ la If ,ve cos9 o .
-q-+--+----= a smn-+ -- (7)
3r rr r r2302 3r r 3A )

The sole dimensionless number appearing in the equations
is Ra* = (pCp)f gp(T.n T t)kR./X*v, the Rayleigh number.
The two above dimensionless equations are to be solved for
increasing (and decreasing) values of the Rayleigh number
and for different values of the radius ratio R = Ro/R.
The domain where the equations (6,7) are to be solved must
be defined first. In other words, is there an axis of symmetry
in this problem? If there is one, then the equations can be
solved either over the entire domain or, preferably, one can
double the accuracy by using the same grid size to cover just
one half of the domain. In the latter case appropriate boundary
conditions must be written at the symmetry axis. The student
must recognize that the governing dimensionless equations
can be solved on a domain that is cut in half by a vertical line.
Why is this not true for a horizontal line?
The dimensionless temperature boundary conditions on the
inner and outer cylinders are:
0(r= 1,0)= 1, 0(r=R,0)=0.
On the symmetry axis the temperature distribution is linear
because both velocity components are zero there. This implies
that the fluid cannot travel from one side to the other of the


Vol.47, No. 1, Winter 2013










symmetry axis. The boundary conditions on the stream func-
tion are very easy to formulate once the student recognizes
that the periphery of the entire half-domain is a streamline,
an arbitrary value of Vp = 0 can be set.

Numerical solution
Depending on whether the numerical solution of partial dif-
ferential equations is part of the transport phenomena course
or not, the instructor can choose between allowing the use of
a commercial CFD code based on a finite volume formulation
or asking the students to develop a finite difference code to
solve the governing equations. When a finite volume code is
employed, the primitive equations are solved and the convec-
tion terms are discretized using an upwind scheme, preferably
of second order. Below we discuss the case where students
develop their own code using a finite difference method. This
method was implemented in our course.
The partial differential equations are converted into alge-
braic equations by an appropriate discretization of the deriva-
tives. When a finite difference code is employed, students
should use second order, central difference Taylor series
formulas for spatial derivatives and a first order time marching
scheme for the time derivatives. The transient conservation
of energy equation can be solved numerically in 2-D by an
implicit alternating direction scheme. The solution of a tri-
diagonal system of equations at each half step is required.
If a very fine grid is employed, for example when half the
tangential direction is totally defined by 200 grid points, the
student could use an iterative scheme instead of the Thomas
algorithm to solve the tri-diagonal system of linear equa-
tions. There is no roundoff error when iterative methods of
solution are employed and the user can control the accuracy
of the obtained solution via a convergence test. The stream
function equation can be solved using an iterative method
of solution (Jacobi, Gauss-Seidel, under/over relaxation) or,
alternatively, one can add a transient term to the equation and
solve it using an ADI scheme.
Finally, the code will require several convergence tests. At
each time step the stream function equation is solved by an
iterative scheme such as the Gauss-Seidel method. The con-
vergence criterion here does not have to be very strict since
this equation is solved at each time step. The convergence
criterion on the heat equation should be based on the fact that,
at steady state, the average heat flow into the inner cylinder qi:

qin r V f _, dO

should be equal to the average heat flow out of the cylinder q.:
-X* f 9aT dO.
d0 ar rRu
'i.--x jR,~d...

This leads to the definition of the Nusselt number which is
simply the ratio between the heat flow into the porous layer


Figure 1. Streamlines and isotherms in an annular po-
rous medium, Ra = 100 and R = 2. For this value of the
Rayleigh number there are two possible hydrodynamic
regimes, a two-cell regime (left) and a four-cell regime
(right). This figure is taken, with permission, from
Reference 8.

4.8-
Nu
4.0- .

3.2

2.4 ,




0.8.
1 10 R 100 1 00

Figure 2. Average Nusselt number Nu as a function of
Rayleigh number Ra in an annular porous medium, R =
2. The additional cell leads to a Nusselt number increase.
This figure is taken, with permission, from Reference 8.

(by convection) and the heat flow into the layer by conduction,
i.e., when there is no motion of the fluid inside the annulus.
Both local and average Nusselt numbers were calculated by
the students.

RESULTS AND DISCUSSION
The developed numerical code is first run for a small value of
the Rayleigh number until convergence is attained. The results
obtained are used as initial conditions to calculate the profiles
for a slightly higher Rayleigh number. This procedure was rec-
ommended to the students in order to speed up the calculations.
For a radius ratio Rot/Rn = 2 and a Rayleigh number of
100, Figure la shows the streamline pattern and the isotherms
within the annular region on increasing the Rayleigh number.
The cell is rotating in a clockwise direction. For lower values
of the Rayleigh number the streamline pattern and the form
of the isotherms is similar; the center of the vortex moves
upwards as the Rayleigh number increases.


Chemical Engineering Education










When the Rayleigh number is increased beyond a certain
limit, a secondary cell appears on the top of the layer (Figure
lb), the secondary cell rotates in a counter-clockwise direc-
tion. Experiments where the temperature field in the layer
was visualizedu' have clearly shown that this multi-cellular
flow regime does indeed exist. Now, if the two-cell regime
is used as an initial condition and if the Rayleigh number
is decreased slowly, one observes that this two-cell regime
remains in the layer until the Rayleigh number drops below
a value of about 65 2.
In other words, for R = 2 and for a Rayleigh number between
65 2 and a value of about 120, there are two possible flow
regimes in the layer. This is a hysteresis loop. Although the
upper limit value of the Rayleigh number in the hysteresis
loop is not clearly established (the transition value depends
on the fineness of the grid employed), experiments16,71 and a
hydrodynamic stability analysis (to be discussed in a later
paper) confirm the lower limit value of 65 2.
Figure 2 shows a plot of the Nusselt number as a function
of the Rayleigh number. The dotted line corresponds to the
two-cell regime (one cell per cylinder half) and the black line
to the four-cell regime. When the flow regime changes from
two cells to four cells, the additional circulation at the top of
the layer leads to an increase in the average Nusselt number.
The experimental Nusselt numbers obtained by Caltagirone 71
have also been included in the figure.
When the radius ratio Ro/R in is close to unity (for example
R=l .1), additional cells are formed at the top of the annular
region; this is true in both porous and fluid media. This can be
explained by recognizing that as the radius ratio R decreases
to 1, the cylindrical geometry tends toward the two parallel
flat plate geometry and additional cells appear if the Rayleigh
number is high enough. Figure 3 shows the streamlines and
the isotherms in a porous medium for Ro/Ri = 1.2, a 6 cell
flow appears at around Ra = 300 and an 8 cell hydrodynamic
regime appears at Ra = 800.
We did not specifically ask our students to calculate the
pressure distribution in the porous layer in this project.
Taking the divergence of Darcy's law and recognizing that
V V = 0, the obtained result is:
V2P = V.- p (l-P(T- T0))g. (8)

This equation can be used to calculate the pressure field
(see Reference 8).

STUDENT RESPONSE
The above project was given in our senior/graduate student
course on numerical transport phenomena. The accompanying
textbooks for this course are Reference 9 or 10 depending on
the mother tongue of the student. The students in our gradu-
ate program come from different countries of Europe and
South America, from Northern Africa, and from the Middle


East. Obviously they have very different mathematical and
computer backgrounds and some have to put in quite an initial
effort. In order to compensate for this, we asked the students
to work in groups of four. We also asked the students to form
cosmopolitan groups if possible; this worked quite well. The
choice of computer language/software was open; all groups
used MATLAB.
The students had one full semester to work on the project
and they could (and did) consult the instructors outside the
classroom all along. The other courses that were taught to
our students during the semester did not require too much
outside work and were graded via exams. The students were
required to write a report that had to include the way they
proceeded, the numerical methods chosen, their analysis
of results, and proposals for improvement as well as the
program itself.
As mentioned above, the problem presented here is in the
spirit of what W.M. Kays wrote in his textbook. This problem
could also be included in a future edition of the excellent
chemical engineering/numerical methods textbook by Car-
nahan, Luther, and Wilkes.121

CONCLUSIONS
Different aspects of transport phenomena can be taught to
senior/graduate students via a project requiring the numerical
solution of the appropriate conservation equations. The study
of natural convection in enclosed surfaces is one example of
such a project. After finishing the project described in this
paper, the student should feel much more confident in several
important aspects of transport phenomena such as vector
analysis, the physics of the phenomenon of natural convection,
the development of a code to solve the coupled pdes, and the
analysis of results. As we hope to show in a later paper, this
project is also an excellent method to introduce more difficult
but important related subjects such as hydrodynamic stability,
heat loss reduction, and choice of geometry.


Figure 3. Streamlines and isotherms for a porous
annular layer, Ro/Ri = 1.2. a) 6 cell regime, Ra=300,
8 cell regime, Ra=800. This figure is taken, with permis-
sion, from Reference 8.


Vol.47, No. 1, Winter 2013











REFERENCES
1. Bird, R.B., WE. Stewart, and EN. Lightfoot, Transport Phenomena,
John Wiley and Sons, New York (1960), 2nd edition (2007)
2. Carnahan, B.,H.A. Luther, and JO.Wilkes,Applied Numerical Meth-
ods, John Wiley and Sons, New York (1969)
3. Barbosa Mota, J.P., and E. Saatdjian, "Natural convection in a
porous, horizontal cylindrical annulus," J. Heat Transfer, 116,
621-626 (1994)
4. Kays, W.M., Convective Heat and Mass Transfer, McGraw-Hill, New
York (1966)
5. Nield, D., and A. Bejan, Convection in Porous Media, Springer-Verlag,
New York (1992)


6. Charrier-Mojtabi, M.C., et al., "Numerical and experimental study of
multi-cellular free convection flows in an annular porous layer," Int.
J. Heat Mass Transfer, 34(12), 3061 (1991)
7. Caltagirone, J.P., "Thermo-convective instabilities in a porous medium
bounded by two concentric horizontal cylinders," J. Fluid Mech., 76(2),
337(1976)
8. Roache, PJ., Fundamentals of Computational Fluid Dynamics, Her-
mosa Publishers, Albuquerque, N.M. (1998)
9. Saatdjian, E., Transport Phenomena: Equations and Numerical Solu-
tions, John Wiley and Sons, Chichester, UK (2000)
10. Saatdjian, E., Les Bases de la Micanique des Fluides et des Transferts
de Chaleur et de Masse pour l'lnginieur, Editions Sapientia, Paris,
(2009)


Chemical Engineering Education











[MM laboratory


TECHNOLOGY IN THE CLASSROOM:

Transitioning Lab and Design

To an All-Digital Workflow


DANIEL ANASTASIO, ARAVIND SURESH, AND DANIEL D. BURKEY
University of Connecticut Storrs, CT 06269


Although students may not appreciate it during the
course of their undergraduate program, they will
spend a large portion of their professional lives en-
gaged in technical writing almost every day.11[ To prepare stu-
dents for this reality, many chemical engineering curriculums
use either their laboratory courses or their design courses to
also teach technical writing. 24] At many universities, includ-
ing the University of Connecticut, these courses are also used
to at least partially fulfill the university's writing requirement.
In such classes, guidelines as to number of pages, revisions,
and assignments are often influenced by a higher authority
in the university. The draft-revision-final report structure
(sometimes with multiple drafts) can result in instructors deal-
ing with numerous versions of the same work, multiplied by
the number of students taking the class. Managing the sheer
amount of paper can become a burden on instructors and
students alike. While there have been numerous studies of
the advantages and pitfalls of incorporating new technologies
(i.e., laptops, iPods, iPads, tablet computing, cloud comput-
ing) into the classroom on the student side of the equation,'51
there has been less work done on the impact that some of
these newer technologies have on the faculty/instructor side.
In the world of iPads, PDFs, and online collaboration tools,
we wondered whether the technology had advanced suffi-
ciently to allow us to do away entirely with the paper copies
of lab reports and design reports. Murphy describes multiple


Daniel Burkey is the associate head of the
Chemical and Biomolecular Engineering
department at the University of Connecticut.,
He received his B.S. in chemical engineer-
ing from Lehigh University in 1998, and his
M.S.C.E.Pand Ph.D.in chemical engineering V
from the Massachusetts Institute of Tech-
nology in 2000 and 2003, respectively. His
primary areas of interest are chemical vapor "
deposition and engineering pedagogy. ., i,.?


Daniel Anastaslo received his B.S. in chemi-
cal engineering from the University of Con-
necticut in 2009. He is pursuing a Ph.D. in
chemical engineering at the University of
Connecticut while acting as an instructional
specialist for the chemical engineering un-
dergraduate laboratory. His research interests
include osmotically driven membrane separa-
tions and engineering pedagogy.


Aravind Suresh is an assistant professor-
in-residence in the chemical engineering
program at the University of Connecticut. He
received his B. Tech in chemical engineering
from the National Institute of Technology in
India in 2004, and his Ph.D. in chemical en-
gineering from the University of Connecticut
in 2011. His primary areas of research interest
are synthesis, structural, and functional char-
acterization of ceramics.


Copyright ChE Division of ASEE 2013


Vol. 47, No. 1, Winter 2013









typologies for iPad/tablet use in the college environment,
focusing on the technology's ability to grant "ubiquitous"
access to course materials and foster peer-to-peer as well as
peer-to-instructor collaboration, as well as the productivity
enhancement generated by the use of these devices, not only
for the students, but for faculty as well.(61 Variations on these
advantages are also noted by Park, Melhuish, and Falloon,
and Economides and Nikolaou.17-91
Prensky notes that students are ever more becoming "digital
natives," having grown up using computers and, increasingly,
the Internet and portable computing devices.J1] Many faculty,
on the other hand, pre-date the technological explosion and
must often play catch-up with the latest abilities and tools that
their students take for granted. While many faculty are often
slow to adopt new technologies, due to time constraints, lack
of interest, and aversion to change, among other reasons,111
those that do typically do so because they believe it will im-
prove student learning, as well as bring about efficiencies in
their workflow, allowing them to rededicate that "found time"
to improve their teaching in other ways.J12,131
For our application of technology to the writing course, we
sought the flexibility of easier reading, mark-up, and correc-
tion that these types of assignments generally require, while
simultaneously reducing the copious amount of paper that
the students were using (and we, the instructors, were haul-
ing around). One thing that we didn't want to do was to have
students clogging our e-mail with reports and attachments, nor
did we want to be tethered to a computer to read lab reports.
We also wanted to avoid making corrections with a feature
such as Microsoft Word's "Track Changes," which we felt
would enable students to edit their reports by simply selecting
"Accept Changes" without reading any critique-defeating
the iterative process of editing and revising between student
and instructor. Given these caveats, we hypothesized we could
develop a workflow that would:
Allow students to submit reports electronically, but not
via e-mail, and keep a record of all of the transactions
between student and instructor.
Allow course instructors to easily read, comment on, and
correct reports without being tethered to a computer or
making the revision process too trivial for the students.
In order to accomplish these goals, we needed to establish
the following: a file format, a computing platform, and a
collaboration platform.

FILE FORMAT
Perhaps the easiest of the three choices to make, we wanted
a format that was near-universally recognized, generally
platform-agnostic, and not able to be trivially edited once
comments have been made. The PDF format easily met all
of these requirements. PDF files are common in both the PC
and Macintosh environments, and both platforms have either


the built-in ability or free software to output to the PDF for-
mat. In our implementation, students can use any platform
that they want (PC/Mac/mobile) for document creation, as
long as the final format for submission is a PDF- students
weren't required to purchase anything (hardware or software)
in transitioning to online submission. Additionally, once cre-
ated, the PDF is generally not editable in the same way as a
traditional word-processing file. This difference ensures that
any corrections or suggestions that we, the instructors, made
on the document would have to be incorporated through
manual student revision of the original document, not by
quickly re-editing the electronic copy we returned. We wanted
the students to have to read and reflect on our comments and
suggestions in the same way they would have to if they had
received a series of comments written in red ink on a printed
page. This process was also facilitated by the PDF format,
since, while the original content is typically locked once the
document has been produced, there are numerous pieces of
software that can be used to "mark-up" or annotate a PDF,
adding content on top of the existing document.

PLATFORM
As mentioned above, the experience of reading, comment-
ing on, and grading physical lab reports is very different than
that same action performed sitting in front of a computer. For
many faculty, reading and interacting with a document via
computer screen, mouse, and keyboard is an awkward and
unpleasant experience. We decided that we wanted to mimic
the traditional grading experience as much as possible, so
we decided to use tablet computing as a platform. Tablets
are generally much smaller than laptops, and, like e-book
readers, are more akin to a traditional reading experience
than reading a document on a laptop or desktop machine.
While there are many tablet platforms available, we chose to
use the Apple iPad due to the large existing market and the
numerous tools for interacting with documents on the device,
although similar arguments can be made for the Android
mobile platform. There are a number of applications on the
Apple App Store, some of which are free, that allow users to
view and annotate PDF documents on the device. As the iPad
and many other tablets have an interactive touch screen, it is
possible to use one's finger or a capacitive stylus to interact
with the screen, providing a natural analog to correcting a
physical document with a pen or marker. There is also the
added benefit of being able to have all report documents with
you at all times, avoiding the need to carry around a stack
of papers, while facilitating grading or reviewing when you
have a few minutes of time.

SOFTWARE
A simple search of Apple's App Store will turn up dozens of
applications that have the ability to interact with PDFs. We ex-
amined a number of these for cost, usability, and overall feel.


Chemical Engineering Education










Of particular use are programs that can integrate and interact
with one of the numerous cloud storage options available,
which facilitates easy collaboration and avoids collection of
student documents through e-mail. Most of the applications on
the App Store for PDF annotation are relatively inexpensive,
especially when compared to the cost of the tablet itself. We
found a number of options, ranging between free and about
$10. One of the simplest is neu.Annotate PDF ( neupen.com/>), which is free to download. This application is
fairly bare-bones, but it does allow the user to import PDFs,
mark them up with a finger or stylus, then save the marked-up
document to a variety of online storage solutions or send it
via e-mail. For a free application, it is fairly robust, but not
as full-featured as some of the other options. It is, however,
a great application for quickly signing documents and has
been useful at the University of Connecticut for electronically
signing forms or letters.
The solution we settled upon for our use was iAnnotate PDF
by Aji LLC ($9.99 on the App Store, com/iannotate/> for more info). iAnnotate has a host of mark-
up tools that are useful during the grading process, including
easily accessible tools for underlining, striking through,
and highlighting text in addition to allowing the insertion
of handwritten notes and text boxes, all in a variety of sizes
and colors. It also has integration with numerous cloud-based
storage solutions for easy moving of annotated files. iAnno-
tate is also specifically mentioned in several studies on tablet
technology, with one specifically stating that the "majority of
students perceived electronic course materials on an iPad in
iAnnotate to be as good as or better than printed course ma-
terials."6.141 iAnnotate is currently only available on the iPad,
although a version for Android-based tablets is in production
at this writing, according to the software's publisher. Figure
1 (next page) shows a typical document with annotations
created in iAnnotate.
The last piece of the workflow is the collaboration software.
We wanted to avoid the inconvenience of students e-mailing
us their documents, which would only serve to fill inboxes
and make keeping track of submissions needlessly time-
consuming. We decided to use the freely available Dropbox
() to create an online space where all
of the student submissions would live. The benefits of this
system are numerous:
Free 2GB storage space (more than adequate for our
purposes)
Centralized storage and organization of all student work
Available across multiple platforms (PC, Mac, web inter-
face, and mobile)
Ability to keep a time-stamped record of all submissions!
deletions from the Dropbox
Ability to natively link with many PDF annotation tools,
including iAnnotate
Vol. 47, No. 1, Winter 2013


We wanted the students to have to read

and reflect on our comments and sugges-

tions in the same way they would have to

if they had received a series of comments

written in red ink on a printed page.



An additional advantage of Dropbox is that copies of
all files are kept on the user's local machine, and are only
synchronized when an Internet connection is available. As
such, a persistent connection isn't required, and in the case
of a large-scale failure of the service, students could resort
to e-mail or a hard copy. It should be noted that Dropbox is
one of several online cloud-storage collaborative tools, and
that others (Microsoft SkyDrive, Google Drive, etc.) may
also be used. Indeed, if the university computing technical
services supports it, it may be possible to deploy a shared-
folder approach using entirely internal resources, which may
allay worries about dependency on an free, external service.
For our laboratory course, we created an individual folder
for each student in the class and invited the student to be a
shared user on that folder. In this way, any time the student
completed a draft or a finished report, they would place it
in their personal Dropbox folder on their computer. That
file would instantly appear in that student's folder on the
instructor's computer, tablet, or other linked mobile device.
In this way, we were able to see submission times to guar-
antee on-time work while organizing all of a student's work
in one place. We also adopted a naming convention to keep
the files organized and to differentiate between different
versions of student work. For example "LastNameExperi-
mentNameVersion.pdf," where the "Version" indicated the
current iteration of the work, e.g., "Draft," "Draft_Reviewed,"
"Final," and "Final_Graded." In this way, all versions of the
student's work could live together in the same folder, and we
as instructors could easily differentiate and compare versions.
Once the student submitted work for review (in PDF for-
mat), the instructors would use the iAnnotate software to
read, review, and comment on the work, and then return it to
the student's folder alongside the original work. At the end of
the semester, the student's folder was essentially a portfolio
of work for the semester, containing all of their drafts, final
reports, and other graded material. Having all of this data
for all students, easily accessible in a single place, makes it
incredibly easy to collect examples of student work and the
revision process for evaluations like internal reviews or ABET
accreditation visits. Garmon indicates that this cloud-based
approach facilitates the instruction of writing as a process,
rather than a one-shot effort, as students and instructors can














Apparatus and Procedure: 11 Page + 1 Page Diagramj 77 /
The bottles were filled with tap water and the thermocouple inserted into the bottle with a rubber
What types of bottles? What are the relevant dimensions9
stopper. The end of the thermocouple that collects temperature information should lie on the
bottles imaginary-axis of symmetry and not too close to any sides or the bottom of the bottle to
What is too close?
get the most accurate reading possible. s th
Iti sue htonc thi s point is
This is kind of awkward sentence construct
/2
cool enough, the entirety of the bexerage is cool en(ogi*B 1/
__ ~ "4V - l tis cool enouqh.?

T(.MV-'_ Lhis probably isnt important y..
_o enough to include in the bad i'i
The refrigerator had a thermometer in it, so the temperature should be recorded every time the
refrigerator is used. Six bottles can be tested at one time, two of each material type (glass, ai
--' 7 plastic, aluminum). The cooling method was tested fEuL.4laci ttne bottle of each type in the
I =b
refrigerator, and the remaining three in a prepared ice water bath: It is important to put water in AiV
with the ice so the types of heat transfer are comparable. Using only ice would be heat transfer"A

hatni i j CS 9 "l imheS 1 iS S ho in total contact?
Sosimulate an actual party
This sentence is confusing; ou talk about the fridge then switch to
e\pqren e, ice ealer warmer fy natural can'eciion wIt he adir and no additional ice was
icetwaler.
added as data was collected. It was assumed that this heat transfer from the solid and air was
negligible to make calculations and simulations simpler. !i
The heating methods were tested by having the bottles pre-chilled in the refrigerator for at least a i
day. The water bath was prepared the day before as well to let it equilibrate with room <(
temperature. One bottle of each type was placed on a countertop, and the remaining three in a
bucket of water. The heat effects compared the effect of air and water when warming the bottles


7


Figure 1. An annotated student report, with different highlights, strikethroughs, comments, and other edits during the
revision process.
8 Chemical Engineering Education










easily compare versions, corrections, and the like without
being physically co-located.0151 We would like to point out,
however, that this methodology was meant to streamline the
grading and organization process for the faculty, and to cre-
ate an easy system for students to submit work-not to act
as a substitution for meaningful interaction with students. As
instructors, we found that we spent about the same amount
of time actually reading and commenting on drafts as we did
with pen and paper, and still spent significant time reviewing
our comments and suggestions with students in person. The
comments and feedback to students will only ever be as good
as the time and effort we put into it, regardless of the way we
provide that feedback.

STUDENT RECEPTION
At the end of the term, after submitting and receiving their
work in this format for the entire academic year, we asked the
students about their experience, focusing on the effectiveness
and the convenience of the workflow. Figure 2 shows a sum-
mary of their responses. The number one positive comment
we received was that the electronic workflow significantly cut
down on their printing budget, either personally or through the


cost-per-page of using the university printing resources. This
sentiment, whether driven by financial motivators or green
ones, was echoed in numerous studies on the advantages of
the digital workflow.'2'161 Additionally, students appeared to
enjoy the features of Dropbox, independently creating new
folders in order to share information between group members
for their lab reports and design projects.

SUMMARY AND CONCLUSION
We set out to create a paperless, online workflow for our
senior laboratory class, which has succeeded beyond our
expectations. Students liked the flexibility of submitting
everything electronically as it saved them time (and printing
costs!), and the course instructors liked the convenience of a
lightweight, mobile platform for receiving, organizing, grad-
ing, and returning student work. We've implemented a work-
flow that is reasonably close to the experience one would get
grading paper materials by hand, but adds the conveniences
described above without trivializing the editing process stu-
dents must go through. We tried to keep costs manageable
for this project. The iPads (for faculty) were by far the most
expensive part ($499 for the least expensive model), but this


"Eliminating paper reports and moving to online submission, grading,
and return of your drafts and reports was effective/convenient?"
50

45




o 35
CL



" 25* Effective

20 Convenient
0
.0 15___
E
Z 10




0
Strongly Agree Agree Neutral Disagree Strongly
Disagree

Figure 2. Student responses on the effectiveness and convenience of moving to an all-electronic workflowfor the
submission, grading, and return of their lab work. The responses were uniformly positive.


Vol. 47, No. 1, Winter 2013











cost can be amortized over several years, and the devices are
useful to the instructors as computing platforms outside the
class. Software costs are either minimal, in the case of iAn-
notate, or free, in the case of Dropbox. For anyone looking
to streamline their workflow for courses in which there is a
lot of student writing and revision, we recommend giving
this approach a try.

REFERENCES
1. Paradis, J., D. Dobrin, and R. Miller, "Writing at Exxon ITD, Notes
on the Writing Environment of an R&D Organization," in Writing in
Non-Academic Settings, Odell, L., Guswami, D., eds., Guilford Press,
New York (1985) pp. 281-307
2. Herrington, AJ., "Writing in Academic Settings: A Study of the Con-
texts for Writing in Two College Chemical Engineering Courses,"
Research in the Teaching of English, 19(4), 331 (1985)
3. Baren, R., "Teaching Writing in Required Undergraduate Engineering
Courses: A Materials Course Example," J. Eng. Ed., 82(1), 59 (1993)
4. Ludlow, D.K., K.H. Schulz,"Writing Across the Chemical Engineering
Curriculum at the University of North Dakota," J. Eng. Ed., 83(2), 161
(1994)
5. Brookshire, R.G., "The iPod Revolution: Coming to a Classroom Near
You," in Proceedings of the 26th Annual OSRA Research Conference,
San Diego, (2007)
6. Murphy, G.D., "Post-PC devices: A summary of early iPad technology
adoption in tertiary environments," E-Journal of Business Ed. and
Scholarship of Teaching, 5(1), 18 (2011)


7. Melhuish, K., and G. Falloon,"Looking to the future: m-learning with
the iPad. Computers in New Zealand Schools," Learning & Leading
with Technology, 22(3), 1 (2010)
8. Park, Y., "A pedagogical framework for mobile learning: categoriz-
ing educational applications of mobile technologies into four types,"
International Review of Research in Open and Distance Learning,
12(2),78 (2011)
9. Economides, A., and N. Nikolaou, "Evaluation of handheld devices
for mobile learning," Int. J. Eng. Ed., in press
10. Prensky,M.,"Digital natives,digital immigrantst' On the Horizon,9(5),
1, Retrieved from %20Digital%20Natives,%20Digital%20Immigrants%20-%20Partl.
pdf> (accessed September 2012)
11. Friel, T., J. Britten, B. Compton, A. Peak, K. Schoch, and W.K. Van-
Tyle, "Using pedagogical dialogue as a vehicle to encourage faculty
technology use," Computers & Education, 53(2), 300 (2009)
12. Tuttle, H.V., "The Lived Experiences of Faculty who use instructions
technology: A Phenomenological Study," Ph.D. Thesis, University of
Nebraska, Lincoln, NE, June 2012
13. Xu, Y., and K. Meyer, Factors explaining faculty technology use and
productivity," The Internet and Higher Education, 10(1), 41 (2007)
14. Bush, M.H., and A.H. Cameron, "Digital Course Materials: A Case
Study of the Apple iPad in the Academic Environment," Ph.D. Thesis,
Pepperdine University, Malibu, CA, 2011
15. Garmon, S.C., "Writing with Others: The Rhetoric of Cloud Technolo-
gies In the Workplace," MA. Thesis, Clemson University, Clemson,
SC, 2011
16. Kilgore, K., "Less Paper, More Learning: The Future of Education,"
M.S. Thesis, Western Connecticut State University, Danbury, CT, May
20120


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PS Form 3526, September 2007 (Page 2 of 3)
72


Chemical Engineering Education










GUEST EDITORIAL




The Case Against the Use


of Solution Manuals


Ask any student, and they'll likely make some of the fol-
lowing arguments in favor of the use of illicitly obtained
solution manuals:
Everyone uses solution manuals. I have to do itjust to level
the playing field.
You can Google "solution manual" and come up with lots of
hits. What's wrong with using freely available documents?
Students who rely too heavily on solution manuals will do
poorly on the exam, so it evens out in the long run.
If the objective of education is to learn the material, then
I should be able to use any tool available to improve my
personal performance.
I only use it when I really need it- when I'm stuck the night
before homework is due and need to figure out how to get
started.
Ifprofessors are lazy enough to assign problems from the
textbook every semester, it serves them right when students
use solution manuals to gain an advantage.
A recent study highlights the mismatch between the
views of faculty and students on this topic; 77% of faculty
vs. 11% of students view the use of solution manuals as
cheating.111 Another study confirms that the percentage
of students who are unsuccessful in a course rises when
students have access to solution manuals, refuting the ar-
gument that solution manuals improve student learning.121
Addressing academic integrity issues can be painful,
however, and many faculty would rather avoid dealing
with a form of cheating that has gained widespread student
acceptance.
One recommended approach is for faculty to set clear
expectations about use of solution manuals to complete
graded homework.J' My department has decided to include
the following statement within the Academic Integrity sec-
tion of all course syllabi:
The use of a solution manual or equivalent (e.g., solutions
posted to the web or from previous class offerings) in the
preparation or submission of homework will be considered
cheating and dealt with accordingly.
Solution manual copying is typically detected when a stu-


Lisa G. Bullard, North Carolina State University

dent transcribes a solution verbatim, especially if it contains
an error; when a narrative response is copied word for word;
or when there is significant overlap between the sequence
of operations or equations in a long, complex problem. Our
typical penalty for students found responsible for using il-
licitly obtained solution manuals is a zero on the homework
portion of the student's grade, since all of their homework
becomes suspect once they are known to have access to an
off-limits resource. Other approaches to mitigate the use of
solution manuals include assigning original projects or open-
ended homework problems, writing original problems (or
using problems from other texts), or using online homework
systems provided by textbook publishers.
Whatever approach we decide to take, we cannot ignore
the issue. When faculty look the other way or implicitly
condone the use of solution manuals, we send a message
about the culture of the department with regard to integ-
rity-that shortcuts are winked at, that students have to
fend for themselves to level the playing field, that the ends
justify the means. Patterns of behavior that are formed in
college become accepted behavior in the workplace (and
life in general); the headlines confirm that there are ample
opportunities to take shortcuts in the business and regulatory
arenas. Chemical engineers are responsible for the health,
safety, and welfare of their co-workers and their community,
and the consequences of taking a shortcut or fudging the facts
can be devastating. Students need to learn how to take the
harder road of self discipline that leads to authentic learning
and accomplishment. Setting clear expectations and holding
students accountable for unethical behavior will make its
occurrence less likely after graduation, when the potential
consequences of integrity violations are much more severe.
REFERENCES
1. Minechiello, A., L. McNeill, and C. Hailey, "Compar-
ing Engineering Student Use of Solution Manuals and
Student/Faculty Perceptions of Academic Dishonesty,"
ASEE Proceedings (2012)
2. Karimi, A., and R. Manteufel, "Does Student Access to
Solution Manual Pose a Challenge?," ASEE Proceed-
ings (2011) 0


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