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Normative Analysis of Internet-Mediated Distance Education Policies in Selected Large Community Colleges and Their Relat...

Permanent Link: http://ufdc.ufl.edu/UFE0021772/00001

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Title: Normative Analysis of Internet-Mediated Distance Education Policies in Selected Large Community Colleges and Their Related State Systems
Physical Description: 1 online resource (179 p.)
Language: english
Creator: Amason, Robert F, Jr
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: diffusion, distance, elearning, electronic, internet, online, policy
Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Distance education in the United States, particularly online technology-mediated education, has grown rapidly in post-secondary institutions. The fusion of computer, television, telecommunications, publishing, and other print media with technology-mediated education will likely result in three-dimensional experiences that may supplant the classroom, as it is currently known. Despite increasing acceptance of distance education and distance education technologies, some educators and many employers have expressed skepticism regarding nontraditional offerings. This study was a normative analysis of policies and practices regarding technology-mediated distance education in community colleges. The study examined the current condition of distance education policy at three levels state, consortia, and institutional. The study sought to identify the diffusion of such a policy by triangulating policy directives and program attributes at the state, consortium, and institutional levels to factors derived from policy analysis frameworks and acknowledged best practices. Thirty-seven community colleges and 15 states were included in a purposive sample. In 13 states where a state-level distance education consortium was identified, the consortium policies were analyzed. The study indicated that state-level guidance was not consistent across states, and low policy diffusion across all factors was observed at state-level. This finding suggested that state directors of community colleges may need to reexamine statutory, strategic, and funding guidance to encourage more complete oversight of educational access, student success, infrastructure, and planning for Internet-mediated distance education. In this study, institutional-level policy diffusion for students was near unity, suggesting that Internet-mediated distance education was moving toward a high level of consistency among institutions. The diffusion of policy appeared to increase in proportion to the policy-organization s proximity to students. States were farthest from students and had lower policy diffusion; institutions were closest to the student and had the greatest diffusion of distance education policy. Faculty rewards were largely ignored at all levels, with overall low policy diffusion in the faculty factors. This may be interpreted as setting the stage for faculty resistance to more complete implementation of Internet-mediated distance education. States and institutions may find it advantageous to create more faculty rewards for engaging in online teaching.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Robert F Amason.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Honeyman, David S.
Local: Co-adviser: Quinn, David.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2008-06-30

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Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021772:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021772/00001

Material Information

Title: Normative Analysis of Internet-Mediated Distance Education Policies in Selected Large Community Colleges and Their Related State Systems
Physical Description: 1 online resource (179 p.)
Language: english
Creator: Amason, Robert F, Jr
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: diffusion, distance, elearning, electronic, internet, online, policy
Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Distance education in the United States, particularly online technology-mediated education, has grown rapidly in post-secondary institutions. The fusion of computer, television, telecommunications, publishing, and other print media with technology-mediated education will likely result in three-dimensional experiences that may supplant the classroom, as it is currently known. Despite increasing acceptance of distance education and distance education technologies, some educators and many employers have expressed skepticism regarding nontraditional offerings. This study was a normative analysis of policies and practices regarding technology-mediated distance education in community colleges. The study examined the current condition of distance education policy at three levels state, consortia, and institutional. The study sought to identify the diffusion of such a policy by triangulating policy directives and program attributes at the state, consortium, and institutional levels to factors derived from policy analysis frameworks and acknowledged best practices. Thirty-seven community colleges and 15 states were included in a purposive sample. In 13 states where a state-level distance education consortium was identified, the consortium policies were analyzed. The study indicated that state-level guidance was not consistent across states, and low policy diffusion across all factors was observed at state-level. This finding suggested that state directors of community colleges may need to reexamine statutory, strategic, and funding guidance to encourage more complete oversight of educational access, student success, infrastructure, and planning for Internet-mediated distance education. In this study, institutional-level policy diffusion for students was near unity, suggesting that Internet-mediated distance education was moving toward a high level of consistency among institutions. The diffusion of policy appeared to increase in proportion to the policy-organization s proximity to students. States were farthest from students and had lower policy diffusion; institutions were closest to the student and had the greatest diffusion of distance education policy. Faculty rewards were largely ignored at all levels, with overall low policy diffusion in the faculty factors. This may be interpreted as setting the stage for faculty resistance to more complete implementation of Internet-mediated distance education. States and institutions may find it advantageous to create more faculty rewards for engaging in online teaching.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Robert F Amason.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Honeyman, David S.
Local: Co-adviser: Quinn, David.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2008-06-30

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021772:00001


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1 NORMATIVE ANALYSIS OF INTERNET-MEDIATED DISTANCE EDUCATION POLICIES IN SELECTED LARGE COMMUNITY COLLEGES AND THEIR RELATED STATE SYSTEMS By ROBERT F. AMASON, JR. A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007

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2 2007 Robert F. Amason, Jr.

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3 To my late parents, Robert F. and Pauline Y. Amason, who inspired me to a lifelong pursuit of knowledge. Neither of them had the chance to attend college yet intellectual curiosity drove them to become self-educated, lifelong learners in many disciplines. They demonstrated that one is never too old to learn and no subject is too difficult. I also dedicate this to my children, Danielle and Michael. May my efforts inspire them in the same ways as my parents inspired me.

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4 ACKNOWLEDGMENTS I extend my sincerest gratitude to Dr. David Honeyman for his guidance, encouragement, and concern during the writing of this dissertation. To Dr. David Quinn, I extend special thanks for his mentorship in the areas of qualitative analysis and study design. I am particularly grateful to Dr. Larry Tyree for his personal friendship and support throughout my time at the University of Florida. The kind concern, encouragement, and friendship from Dr. Dale Campbell and Dr. Dr. Andy McCollough were invaluable in assuring the success of this dissertation. These gentlemen were highly responsive to my requests and provided invaluable ideas and criticism that helped immensely in completing the research. I thank each of the other faculty and staff members in the Department of Educational Administration and Policy for their assistance and guidance as I maneuvered through the complexities of a doctoral degree. I also thank my family, loved ones, and friends for their support and inspiration in the lengthy endeavor of pursuing a doctorate. Several paid a personal price for my success, and I owe each of them a debt of gratitudemore than I can ever repay.

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5 TABLE OF CONTENTS Page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................8 LIST OF FIGURES .........................................................................................................................9 ABSTRACT ...................................................................................................................................10 CHAPTER 1 INTRODUCTION ..................................................................................................................12 Introduction .............................................................................................................................12 Statement of the Problem ........................................................................................................13 Purpose ...................................................................................................................................15 Research Questions .................................................................................................................17 Significance of Study ..............................................................................................................18 Conceptual Framework ...........................................................................................................18 Distance Education Theories ...........................................................................................18 Policy Theories ................................................................................................................19 Definition of Terms ................................................................................................................20 Delimitations ...........................................................................................................................22 Overview of Research Methods ..............................................................................................22 Organization of the Study .......................................................................................................24 2 REVIEW OF LITERATURE .................................................................................................25 Introduction and Purpose ........................................................................................................25 A Brief History of Distance Education ...................................................................................25 Correspondence Study .....................................................................................................26 Radio and Television Broadcasting .................................................................................27 Open Universities ............................................................................................................27 Teleconferencing .............................................................................................................28 Internet/Web-mediated Online Education .......................................................................28 Controversies and Critiques ............................................................................................29 Theories of Distance Education ..............................................................................................32 Theories of Industrialization of Teaching .......................................................................32 Theories of Independence and Autonomy .......................................................................34 Theories of Interaction and Communication ...................................................................35 Contemporary Theoretical Concepts in Distance Education ...........................................37 Public Policy Research and Analysis .....................................................................................39 Origins of Policy ..............................................................................................................39 The Policy Cycle and Policy Research ............................................................................40 Policy Analysis and Evaluation .......................................................................................41 Policy Theories ................................................................................................................42

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6 Distance Education Policy ......................................................................................................48 Distance Education Policy Analysis Frameworks (PAF) ................................................51 Distance Education Accreditation Policy and Quality Benchmarks ...............................52 Summary .................................................................................................................................55 3 METHODOLOGY .................................................................................................................63 Introduction .............................................................................................................................63 Assumptions ...........................................................................................................................63 Research Methods ...................................................................................................................65 Research Procedures ...............................................................................................................67 Selection of Participating States and Institutions ............................................................67 Sources of Data ................................................................................................................69 Characteristics of the Sample .................................................................................................69 Overview of the Community College System .................................................................69 Enrollment Characteristics of Institutions in the Sample ................................................70 Community College Districts and Individual Institutions ...............................................70 Analysis of Research Data ......................................................................................................71 Framework for Analysis ..................................................................................................71 Analysis factors ...............................................................................................................71 Data Analysis Protocols ..................................................................................................71 Document Coding Convention ........................................................................................72 Assignment of Classifications to Policy Diffusion .........................................................73 Threats to Validity and Reliability ..................................................................................73 4 FINDINGS ..............................................................................................................................78 Introduction and Purpose ........................................................................................................78 State-level Findings ................................................................................................................78 Patterns in State Policy Elements Related to Management and Organization Policy Analysis Factors .......................................................................................................78 Patterns in State Policy Elements Related to Faculty Policy Analysis Factors ...............81 Patterns in State Policy Elements Related to Students and Participants Policy Analysis Factors ......................................................................................................................82 State Community College Distance Education Consortia Findings .......................................82 State Community College Distance Education Consortia Typology ..............................82 Patterns in State Community College Distance Education Consortia .............................82 Patterns in state consortium elements related to faculty policy analysis factors .............84 Institution-level Findings ........................................................................................................85 Characteristics of Institutions and Districts .....................................................................85 ..........................................85 Institutional Strategic Guidance Analysis .......................................................................88 Summary .................................................................................................................................88 5 SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS .......................................100 Summary of the Study ..........................................................................................................100

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7 Discussion of Findings .........................................................................................................100 Findings Regarding Policy Diffusion in Management and Organization, Finding 1: Relationship Between Formal Guidance Documents and Management Decisions100 Findings Regarding Policy Diffusion in Management and Organization, Finding 2: Relationship Between Accreditation Guidelines and Curriculum and Individual Courses Policy ........................................................................................................102 Findings Regarding Faculty, Finding 3: Relationship Between Faculty Support and Quality ....................................................................................................................104 Findings Regarding Faculty, Finding 4: Relationship Between Faculty Workload Management and Faculty Willingness to Engage in Distance Education ..............104 Findings Regarding Faculty, Finding 5: Relationship Between Intellectual Property Considerations and Faculty Reluctance to Adapt Courses to the Online Modality105 Findings Regarding Students, Finding 6: Relationship Between Accreditation and Institutional Distance Education Policy .................................................................108 Conclusions...........................................................................................................................110 Conclusions Regarding Management and Organization Factors (Moderate Policy Diffusion) ...............................................................................................................111 Conclusions Regarding Faculty Factors (Low Policy Diffusion) .................................112 Conclusions Regarding Student/Participant Factors (High Policy Diffusion) ..............112 Analysis of Policy Transfer Mechanisms ......................................................................113 Suggested Typology for State Community College Distance Education Consortia .....114 Suggested Typology for Institution and District-Level Distance Education Relationships115 Implications for Practice .......................................................................................................116 Issues for Further Study ........................................................................................................117 State-level Policy Analysis Framework ........................................................................117 State Consortia Structures .............................................................................................118 Institutional-level Distance Education Governance Structures .....................................118 Tuition, Fees, and Funding Formulas ............................................................................118 Faculty Rewards and Workload Policy .........................................................................119 Should the United States Adopt National Policy for Internet-mediated Distance Education? ..............................................................................................................119 Conclusion ............................................................................................................................120 APPENDIX A ANALYSIS PROTOCOL ....................................................................................................124 B DOCUMENTS EXAMINED IN THE STUDY ...................................................................136 LIST OF REFERENCES .............................................................................................................166 BIOGRAPHICAL SKETCH .......................................................................................................178

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8 LIST OF TABLES Table page 2-1 Policy development areas for distance learning................................................................... 60 2-2 Convergence of distance education policy analysis frameworks with quality .................... 61 2-3 Distance education quality benchmark categories ............................................................... 62 3-1 Sample states and institutions .............................................................................................. 75 3-2 Populations and Carnegie classifications of sample community colleges ........................... 76 3-3 Factors and levels of analysis. (Unit of analysis: A policy document) ................................ 77 3-4 Document coding legend ..................................................................................................... 77 4-1 Community college state-level governance structures ........................................................ 90 4-2 State statutory distance education guidance summary......................................................... 90 4-3 State-level distance education strategic guidance summary ................................................ 91 4-4 State distance education funding analysis summary ............................................................ 91 4-5 State and institutional distance education funding guidance summary ............................... 92 4-6 Comparison among statutory, strategic and funding guidance and policy analysis factors 93 4-7 Selected e xamples of state statutory guidance .................................................................. 94 4-8 Selected examples of state strategic guidance ..................................................................... 96 4-9 State-level distance learning consortia ................................................................................. 98 4-10 Institution-level distance education strategic guidance summary ....................................... 99 4-11 Pattern synopsis by policy level and factor.......................................................................... 99 5-1 Policy diffusion by level and factor ................................................................................... 122 5-2 State community college online distance education consortia typology ........................... 123 5-3 Institution and district distance education typology .......................................................... 123 A-1 Content analysis protocol ................................................................................................... 125 B-1 States, institutions, document codes and documents reviewed.......................................... 137

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9 LIST OF FIGURES Figure page 2-1 Three-tiered policy analysis framework (King et al., 2000).................................................. 60 5-1 Policy diffusion by level and factor ..................................................................................... 121

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10 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy NORMATIVE ANALYSIS OF INTERNET-MEDIATED DISTANCE EDUCATION POLICIES IN SELECTED LARGE COMMUNITY COLLEGES AND THEIR RELATED STATE SYSTEMS By Robert F. Amason, Jr. December 2007 Chair: David S. Honeyman Cochair: David M. Quinn Major Department: Higher Education Administration Distance education in the United States, particularly online technology-mediated education, has grown rapidly in post-secondary institutions. The fusion of computer, television, telecommunications, publishing, and other print media with technology-mediated education will likely result in three-dimensional experiences that may supplant the classroom, as it is currently known. Despite increasing acceptance of distance education and distance education technologies, some educators and many employers have expressed skepticism regarding nontraditional offerings. This study was a normative analysis of policies and practices regarding technology-mediated distance education in community colleges. The study examined the current condition of distance education policy at three levelsstate, consortia, and institutional. The study sought to identify the diffusion of such a policy by triangulating policy directives and program attributes at the state, consortium, and institutional levels to factors derived from policy analysis frameworks and acknowledged best practices. Thirty-seven community colleges and 15 states were included in a purposive sample. In 13 states where a state-level distance education consortium was identified, the consortium policies were analyzed.

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11 The study indicated that state-level guidance was not consistent across states, and low policy diffusion across all factors was observed at state-level. This finding suggested that state directors of community colleges may need to reexamine statutory, strategic, and funding guidance to encourage more complete oversight of educational access, student success, infrastructure, and planning for Internet-mediated distance education. In this study, institutional-level policy diffusion for students was near unity, suggesting that Internet-mediated distance education was moving toward a high level of consistency among institutions. The diffusion of policy appeared to increase in proportion to the policy-diffusion; institutions were closest to the student and had the greatest diffusion of distance education policy. Faculty rewards were largely ignored at all levels, with overall low policy diffusion in the faculty factors. This may be interpreted as setting the stage for faculty resistance to more complete implementation of Internet-mediated distance education. States and institutions may find it advantageous to create more faculty rewards for engaging in online teaching.

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12 CHAPTER 1 INTRODUCTION Introduction Online learning has taken a prominent place in academia. Distance education in the United States, particularly online technology-mediated education, has grown rapidly in post-secondary institutions. Approximately 3.2 million degree-seeking, post-secondary students were taking one or more online courses in the fall of 2005 (Allen & Seaman, 2006). This number represents an increase of more than 800,000 from the previous year. While this one-year increase is more than double the increase of any prior year, the growth since 2002 has been equally remarkable (Allen & Seaman, 2006). For example, the fall 2002 enrollment of students taking at least one online course was 1,602,970 (Allen & Seaman, 2005). The same statistics for the fall 2003 and fall 2004 enrollments were 1,971,397 and 2,329,783, respectively (Allen & Seaman, 2005). Distance education has grown at an annual rate of more than 18% from 2002 to 2006 (Allen & Seaman, 2006). By contrast, total undergraduate enrollments for all degree-granting institutions during the same period moved upward at a slower pace, increasing from 14.2 million to 14.9 million students or 4.9% (National Center for Education Statistics, 2006). The technologies available to educators appear to change with great Law, expressed by Gordon Moore, cofounder and chief executive officer of Intel Corporation, states that the capacity of computer chips doubles every 18 months, while cost for the same chips will decline by 50% during the same period (McCain & Jukes, 2001). Noted educator William Daggett suggested in 2001 that small portable computers, voice technology, and broadband technologies would converge in the 3 years between 2001 and 2004, and these technologies become features of the modern classroom. To see this prediction in action, observe higher education classrooms to see students linking their increasingly smaller and more powerful laptop

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13 computers to the wireless Internet to research articles and contribute ideas in real time to class discussion. Indeed, the approximate doubling of online enrollment from 2002 to 2006 is testimony in support of the rapidity of technological change in higher education. phenomenon that involves the creation, dissemination, preservation and application of dth availability has been one cyberinfrastructure factor in the increased use of electronic media in distance education. There has been a logarithmic progression of bandwidth increase since 1984, facilitating faster connections and more information-rich online classrooms (Goff, 2002). In 2002, the amount of un-lit (i.e., unused) fiber optic cable in the United States was between 65% and 80% of the installed base, illustrating a significant excess capacity in the broadband Internet delivery mechanism (Langley, 2002). Corresponding to faster, cheaper chips, increasing rapid connections, and excess capacity, the Internet annual growth has been between 100% and 300%, while the cost of fiber optic bandwidth eroded from 6% to 50% annually (Langley, 2002). This erosion would suggest that the cost of using the Internet for education was dropping at a time when reports indicate that multimedia was becoming more in demand in the classroom (McCain & Jukes, 2001). Statement of the Problem The fusion of computer, television, telecommunications, publishing, and other print media with technology-mediated education will likely result in three-dimensional experiences that may supplant the classroom, as it is currently known (McCain & Jukes, 2001). McCain and Jukes asserted Foundation, Arden L. Bement, may well usher

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14 in a new technological age that will dwarf in sheer transformational scope and power, anything technology and education with the rapid onset of Internet-mediated distance education prompted this study. The rapid shift in technologies, coupled with increasing demand for access to higher education (National Center for Education Statistics, 2006), has created pressure on institutions to provide technology-mediated distance education courses in increasing numbers (Dahl, 2003). This trend has put some states into distance education overdrive. For example, California has experienced a three-fold increase in distance education course offerings from approximately 4,000 to 13,500 courses since 1998almost totally due to the increase in online offerings (California Virtual College, 1999-2005). California expects to experience growth in distance education enrollments from approximately 4% in 1998 to nearly 20% in 2016 (California Virtual College, 1999-2005). Additionally, states and institutions have perceived that distance education courses offer a lower cost alternative (Carnevale, 2005). Several cost-benefit analyses have supported distance education courses as less costly, while many studies support the notion that the educational outcomes are not diminished by distance (Irele, 1999). States and institutions were therefore increasingly open to offering distance education options, and senior educators have been more accepting of the medium as providing valid higher education outcomes (Allen & Seaman, 2006). Technology-mediated distance education has become a major feature of collegiate academics in the United States, but it is not evenly deployed among all institutions. Larger institutions had more online education courses and greater online enrollment than do smaller schools (Allen & Seaman, 2006). Two-year institutions had more penetration of distance

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15 education offerings than did 4-year institutions and research universities (Allen & Seaman, 2006). Internet-mediated distance education has rapidly expanded and has grown beyond situations where the student and teacher are widely separated (McCoy & Sorensen, 2003). An increased interest in distributed learninga blend of traditional classroom offerings using distance education technologieshas occurred (Eaton, 2002). Distance education policy therefore had begun to influence traditional classroom education, yet research on such policy was limited (McCoy & Sorensen, 2003). Purpose Despite increasing acceptance of distance education and distance education technologies applied in more traditional settings, some educators and many employers expressed skepticism regarding nontraditional offerings (Allen & Seaman, 2006; Carnevale, 2007; Fogg, 2007). A significant amount of public funding was allocated to Internet-mediated distance education without a corresponding in-depth examination of underlying policies (McCoy & Sorensen, 2003). A study was needed to identify whether or not technology-mediated distance education is coherent across states and institutions so that these quality concerns such as these may be allayed. The purpose of the study was to conduct a normative analysis of policy on technology-mediated distance education in community colleges at state, consortia, and institutional levels to understand the diffusion of policy concepts in this increasingly central medium. Chen (1990a) classified program and policy evaluations into two categories: normative evaluation (focused upon policy and program design) and causative evaluation (focused upon policy and program outcomes). Normative evaluations are prescriptive statements regarding how a program should

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16 be designed, based upon prior knowledge, research, theory, and practice (Scheirer, 1996). A normative evaluation therefore seeks to compare actual practice with the prescribed practice. The thrust of this study was to compare policy directives and program attributes at the state, consortia, and institutional levels to factors derived from policy analysis frameworks and acknowledged best practices. Specifically, the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher Education, 2002) were adopted in 2002 by all six U.S. regional accrediting associations, as well as by two associations that specifically accredit community colleges (Lezberg, 2003). Part of the reason for such widespread adoption of a set of guidelines was the interregional aspect of technology-mediated distance education and the rise of enrollments in online education. In a period of only a few years, it has become possible for students in widely separated locations to enroll in large numbers in degree-granting programs despite significant distances. This shift in enrollment opportunity caused concern about the future viability of regionalism as a core concept for managing quality in American higher education (Lezberg, 2003). The resulting adoption of Interregional Guidelines represented a national-level set of standards with which to evaluate state and local institutional policy and programs. Concurrent with development of the Interregional Guidelines previously described, several scholars broadened policy analysis frameworks for distance education (Simonson & Bauck, 2003). These policy frameworks considered the same topics as those contemplated in the Interregional Guidelines, thus setting the stage for development of factors for this study. This study, therefore, compared state and institutional policies and programs against factors derived from policy analysis frameworks and the Interregional Guidelines. The goal of

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17 the study was to discern the extent of diffusion for Internet-mediated distance education policy among states, consortia, and individual institutions. Specifically, this study sought to analysis factors. s and program guidance with policy analysis factors. Determine the extent of congruence of community college institutional distance education policies and program guidance policy analysis factors. Propose guidelines for state-level model policy for community college online distance education programs. Research Questions This study was a normative analysis of state and institutional policies and practices regarding technology-mediated distance education in community colleges. The study sought to triangulate state, consortia, and institutional policies with policy analysis frameworks, regional accreditation policies, and best practices. Conceptual linkages exist between policies and programs, with policies being the larger in scope (Chen & Rossi, 1992). Therefore, to study one policy is to study the other policy. Research questions included the following: Are there differences in distance education policies among the regional accrediting bodies, the states, consortia, and institutions? To what extent are statframeworks for policy analysis? for policy analysis? To what extent are community college institutional distance education policies congruent with frameworks for policy analysis?

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18 Significance of Study Few ethnographic studies exist regarding the quality in distance education. This study fills that gap with an analysis of policies across state boundaries and at institutions representing the largest group of distance education providersthe community colleges (Allen & Seaman, 2006). The study sought to determine the extent of coherence of distance education policies since the introduction of the Internet as a viable educational medium. Coherence of such policies was seen as a measure of policy diffusion (Berry & Berry, 2007). The study sought to elucidate the current condition of distance education policy at three levelsstate, consortia, and institutional. Since the United States did not pursue national accreditation for institutions of higher learning, preferring instead to allow a largely self-organizing, regional-style system of accreditation, the Interregional Guidelines for Electronically Offered Degree Programs represented a de facto national standard (Lezberg, 2003). Given that enrollments in distance education programs grew at rapid rates, and community colleges represented a major locus of these enrollments (Allen & Seaman, 2006), the need arose for a coherent policy at state, consortium, and institutional levels. This study sought to identify the diffusion of such a policy and offer recommendations regarding creation of policies where gaps exist or where no policy exists. Conceptual Framework The framework for this study is grounded in distance education theory and public policy frameworks. Additionally, the literature regarding distance education policy informed the study. Distance Education Theories Several theories of distance education have been proposed and have been classified into three groups (Keegan, 1996):

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19 Theories of industrialization of teaching Theories of independence and autonomy Theories of interaction and communication A brief overview of these categories is presented here; however, theories of distance education are examined in more detail in Chapter 2. Theories of industrialization of teaching have generally held that management and administration of distance education courses should be centralized (Peters, 2003; Simonson, Smaldino, Albright, & Zvacek, 2003). Theories of independence and autonomy included the Theory of Transactional Distance where distance education interactions are conceptualized as transactions between teacher and learner (Moore & Kearsley, 2005). Theories of interaction and empathy between faculty and student (Holmberg, 1995; Simonson et al., 2003) indicated a shift in distance education emphasis from institution-centered emphasis to student-centered emphasis (Saba, 2003). Contemporary theories of distance education suggested a systems view in which distance education systems were seen as a collection of subsystems, including learning, teaching, course design and materials, and management and policy (Moore & Kearsley, 2005). The many modalities available from the World Wide Web influenced contemporary systems approaches to distance education theory, allowing for complex interactions between teacher and students (Anderson, 2004). Policy Theories Several theories of the policy process are examined in Chapter 2; however, two policy frameworks were found particularly useful in this study. The punctuated equilibrium framework (True, Jones, & Baumgartner, 2007) heldwhile many policies are developed in an incremental fashionthat some policies are driven by rapid shifts in the environment. The onset of the

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20 Internet may be seen as such a shift (Christensen, Aaron, & Clark, 2001). The policy diffusion framework held that successful policies elsewhere may be imported across governmental lines (Berry & Berry, 2007). One thrust of this study was to identify such policy diffusion among the various levels of distance education organizations. Definition of Terms The following terms were used in this study. Asynchronous: communication where interaction between the sender and receiver is not simultaneous (Schlosser & Simonson, 2002). Asynchronous Learning Network (ALN): a form of distance learning in which the teacher and student are separated in both time and space. An ALN uses computer-networking technology for teaching and learning activities (Schlosser & Simonson, 2002). Broadband: a high-capacity, high-speed Internet connection. Constructivism (constructionism): the concept that all knowledge is constructed from the interaction of human beings; constructivism holds that all knowledge exists in a social context (Crotty, 1998). Qualitative methods are generally grounded in the constructivist framework (Crotty, 1998; Glesne, 1999). Correspondence course: oldest form of distance education. Classified as slow asynchronous (Matheos & Archer, 2004). Course management system: computer software that facilitates Web-based distance education (for example, WebCT) (Schlosser & Simonson, 2002). Distance education: -based formal education where the learning group is separated, and where interactive telecommunications systems are used to connect learners,

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21 inclusive term for educational activities where the teacher and student are separated by a distance. Distance learning: a term often used interchangeably with distance education. Popular in the United States, the term places emphasis on the learner (Schlosser & Simonson, 2002). Distance learning system: an integrated combination of technologies designed to support teaching and learning when teacher and learner are separated in time and space (Schlosser & Simonson, 2002). Distributed learning: a newer term that describes a model of education where students and teachers may be collocated for some synchronous activities and separated in space and time for others. The distributed learning concept recognizes the adoption of distance learning technology by traditional institutions in conjunction with classroom-based courses (Schlosser & Simonson, 2002). The concept of distributed learning represents a blending of campus-based and distance education technologies to meet the needs of students (Matheos & Archer, 2004). Interpretivism: See constructivism (Glesne, 1999). Online: interactive computer telecommunications. Policy: a written plan of action providing guidance to govern behavior in a specific area (Simonson & Bauck, 2003). Policy analysis: research done to determine the policy adoption process and the effects of adopted policies (Majchrzak, 1984). Policy research: conducting research or analysis on a fundamental social problem in order to provide policymakers with pragmatic, action-oriented recommendations for

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22 Program Synchronous: real-time communications in which the sender and receiver communicate at the same time (Schlosser & Simonson, 2002). Virtual university: an institution that does not have a campus but grants academic degrees (Wolfe & Johnstone, 1999). Virtual university consortium: accredited academic institutions that are linked online to offer courses with no articulation among consortium members (Epper & Garn, 2004; Wolfe & Johnstone, 1999). Delimitations The study was limited to community colleges that are Board Members of the League for Innovation in the Community College. The study was also limited to those states having community colleges that are Board Members of the League for Innovation in the Community College. Similarly, state distance education consortia were included that had member institutions that were Board Members of the League for Innovation in the Community College. Consortia were excluded if they were sponsored by entities that crossed state boundaries. Therefore, consortia, such as the Southern Regional Education Board (SREB) Electronic Campus Initiatives, were not included. As detailed in Chapter 3, member institutions of the Board Members of the League for Innovation in the Community College were purposefully selected to homogenize the sample, increasing the likelihood of robust distance education programs. The study was limited to written documents; no human subjects were involved. Overview of Research Methods Thirty-seven community colleges and 15 states were included in a purposive sample (Creswell, 2005; Glesne, 1999; Patton, 1990). State documents were examined to determine the

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23 existence of distance education consortia (McCoy & Sorensen, 2003). Where a state consortium was identified, the consortium policies were analyzed using the same qualitative, textual analysis approach (Altheide, 1996; McCullough, 2004) as were used for the state and institutional samples. Many individual community colleges are part of larger community college districts. Within the sample, five districts were identified and these districts provided oversight for 25 of the 37 institutions sampled. The unidocuments from sample states, consortia, and institutions were gathered in electronic form, coded by state, and stored in spreadsheets. The content of the documents was then analyzed to identify patterns indicating policy diffusion. Qualitative research techniques grounded in the constructivist epistemology formed the core of the data analysis. Specifically, ethnographic methods of document review and content analysis techniques were used (Altheide, 1996; Creswell, 2005; Hoepfl, 1997; McCollough, 2004). A three-tiered policy analysis framework (King, Nugent, Russell, Eich, & Lacy, 2000) formed the basis for developing a content analysis protocol. Axial coding techniques (Altheide, 1996; Creswell, 2005) facilitated mapping textual elements of the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (Middle States Commission on Higher Education, 2002) to the three-tiered policy analysis framework, resulting in the content analysis protocol used to analyze sample document data. Data reduction from the protocols fit into three factors, which were identical to the tiers from the policy analysis framework: management and organization, faculty, and students. The levels of analysis were state, consortia, and institutional policies.

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24 Organization of the Study The remainder of this study is organized into four chapters. Chapter 2 examines a review of the relevant literature on distance education theory and practice, policy theory, and distance education policy. Chapter 3 offers a more in-depth review of the research methodology. Chapter 4 presents a detailed analysis of data and findings. Chapter 5 includes conclusions, implications and the summary, as well as recommendations for future research.

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25 CHAPTER 2 REVIEW OF LITERATURE Introduction and Purpose The purpose of the study was to conduct a normative analysis of policy on technology-mediated distance education in community colleges at state, consortia, and institutional levels to understand the diffusion of policy concepts in this increasingly central medium. To accomplish the normative analysis, the study compared policy directives and program attributes at the state, consortia, and institutional levels to factors derived from policy analysis frameworks (PAF). The goal of the study was to determine the degree of diffusion of policy across the levels. Policy and program attributes were also compared to acknowledged best practices. The literature of distance education and policy-related fields informed the study. The history and relevant theories of distance education served to set the scene and provide the evaluation of public policy were instructive in conducting policy research and analysis. Policy theory and policy analysis practice guided the study. Finally, available distance education policy literature informed the study and served to synthesize theory and practice into the selected policy analysis framework. The literature for each of these areas is reviewed below. A Brief History of Distance Education While historians have largely ignored it, distance education has a rich and varied history (Pittman, 2003). The format for distance education has experienced five generations (Moore & Kearsley, 2005). These generations include correspondence, broadcast radio and television, open universities, teleconferencing, and Internet/Web-mediated online education. This section is divided into subheadings along these generational lines. The final subsection visits anticipated

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26 developments and the controversies wrought by rapid change in the distance education environment. Correspondence Study Correspondence study was the first distance education format, and for nearly 120 years it was the sole method of distance education (Pittman, 2003). Correspondence courses date from the introduction in Great Britain of the penny post in 1840 (Simonson, Smaldino et al., 2003; Simpson, 2002). The mail was reliable and the cost of postage to any location in the British Empire was a penny. This development fostered correspondence education in shorthand (Moore & Kearsley, 2005). France and Germany also had correspondence study courses during the same period, using the postal service as a communications medium (Moore & Kearsley, 2005). In 1881, the state of New York authorized the Chautauqua College of Liberal Arts to award academic degrees to students who completed prescribed residence and correspondence study (Simonson et al., 2003). Professor William Rainey Harper of Yale University headed the Chautauqua program. Later, as president of the University of Chicago, Harper created a correspondence institute to deliver university courses via the mail (Moore & Kearsley, 2005; Simonson et al., 2003). Industry was also involved in correspondence study. In 1890, courses were offered in mining methods and safety. The organization that initially offered such courses developed into the International Correspondence Schools (ICS) whose enrollment grew to more than 2 million by 1920 (Simonson et al., 2003). During that same period, some 150 railroad companies offered distance education courses. In Sweden, H. S. Hermod founded a school of the same name teaching English by correspondence (Simonson et al., 2003). By 1930, correspondence courses were offered at 39 universities in the United States (Moore & Kearsley, 1996), with many extension institutes serving as for-profit arms of an

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27 otherwise nonprofit, post-secondary institution (Pittman, 2003). Estimates of enrollment in correspondence courses indicate that approximately 2 million students were engaged in study in 1930, and that number had risen to approximately 3 million by 1968 (Moore & Kearsley, 2005). By the late 1920s, concerns resulting from activities of unscrupulous organizations, which had tainted correspondence study, led to the founding of the National Home Study Council (NHSC) (Moore & Kearsley, 2005). The NHSC was founded in 1926 to assure quality in correspondence education (Moore & Kearsley, 2005). Correspondence study continues today through several institutions, including the University of Wyoming, the University of Florida, and Texas State University. Radio and Television Broadcasting The advent of the reliable radio in the mid-1920s interested educators, but radio proved a daunting medium for education (Moore & Kearsley, 2005). Of 176 radio stations established at educational institutions, few survived the 1920s (Simonson et al., 2003). Television was somewhat more successful with the creation of the Corporation for Public Broadcasting in 1967, as well as several state-run educational television entities, notably in Iowa and Alaska (Moore & Kearsley, 2005; Simonson et al., 2003). Ultimately, this generation of distance education formats reached more than 1,000 higher education institutions and some 600,000 students by the early 1980s and produced successful telecourses (Moore & Kearsley, 2005). While this effort was successful, the history of broadcast education is not well documented (Pittman, 2003). Open Universities In the United States, the Articulated Instructional Media (AIM) Project operated from 1964 to 1967. The project tested the idea of joining multiple communications technologies to offer education to distant students (Moore & Kearsley, 2005). It was the first test of distance education as a whole system (Moore & Kearsley, 2005). The AIM Project suffered from control problems

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28 because there was no control over faculty and curriculum, no control over funds, and no control over credit or degrees awarded (Moore & Kearsley, 2005). The Open University of the United Kingdom was founded in 1971 (Simonson et al., 2003). The Open University was a degree-granting institution that offered complete programs via distance. The Open University avoided the control flaws of the AIM Project (Moore & Kearsley, 2005; Simonson et al., 2003). Where the AIM Project was challenged, the Open University has been a success with annual enrollment of more than 200,000 students (Moore & Kearsley, 2005). The AIM Project and the Open University of the United Kingdom concept were examples of a whole system theory in which television broadcasts and correspondence instruction were integrated (Moore & Kearsley, 2005). Since the advent of the Open University of the United Kingdom, many other large successful teaching universities have opened, primarily in Asia (Moore & Kearsley, 2005). In the United States, distance-teaching universities, such as Nova Southeastern University and the University of Phoenix, have been successful in similar fashion to the Open University of the United Kingdom (Simonson et al., 2003). Teleconferencing In the 1980s fully synchronous distance education resulting from vastly improved communications systems, satellite, and fiber-optic communications moved teleconferencing to a level that allowed true collaboration among students and faculty (Simonson et al., 2003). The early equipment was expensive and institutions formed consortia to reduce the cost (Moore & Kearsley, 2005). Featuring synchronous, real-time, two-way communications, coupled with computers and the Internet, this medium continues in operation today (Simonson et al., 2003). Internet/Web-mediated Online Education While video conferencing became more cost-effective by the advent of the Internet and high-speed connections, the Internet also ushered in Web-based education which has become the

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29 most widely used distance education approach (Moore & Kearsley, 2005). The technology of the World Wide Web (WWW) appeared in 1990 as an offshoot of the 1989 development by Tim Berners-Lee of Hypertext Markup Language (HTML) (Keep, McLaughlin, & Parmar, 2000). The WWW marked a major change in the usefulness of the Internet, affecting the way many Americansand increasingly other nationalssee the world and communicate with one another. The WWW has also resulted in a paradigm shift in higher education (Duderstadt, 2000; Moore & Kearsley, 2005). Approximately 3.2 million degree-seeking, post-secondary students were taking one or more online courses in the fall of 2005 (Allen & Seaman, 2006). This number represented an increase of more than 800,000 from the previous year. While this one-year increase is more than double the increase of any prior year (Allen & Seaman, 2006), the growth since 2002 has been equally remarkable. The fall 2002 enrollment of students taking at least one online course was 1,602,970 (Allen & Seaman, 2005). The same statistics for the fall 2003 and fall 2004 enrollments were 1,971,397 and 2,329,783, respectively. Distance education therefore has grown at an annual rate of more than 18% from 2002 to 2006 (Allen & Seaman, 2006). By contrast, total undergraduate enrollments for all degree-granting institutions during the same period moved upward at a slower pace, increasing from 14.2 million to 14.9 million students or 4.9% (National Center for Education Statistics, 2006). The great majority of distance education students are engaged in asynchronous, online courses (Allen & Seaman, 2006). Controversies and Critiques Distance education has been criticized since its inception (Pittman, 2003). As noted earlier, low standards in correspondence courses led to the founding of the National Home Study Council in 1926 (Moore & Kearsley, 2005). Online technology-mediated distance education is rapidly becoming a ubiquitous feature of post-secondary institutions, and this transition is not

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30 without controversy (Saba, 2005). Disruption in markets has been observed to be a powerful tool for change and has generated resistance among market leaders (Christensen et al., 2001). In addition, institutions such as the University of Phoenix have disrupted the fabric of higher education by targeting an underserved, overlooked market of information-hungry adults who use the Internet (Christensen et al., 2001). Virtual universities and consortia that have focused on increasing access to higher education have been observed to be more successful than those that have focused on fiscal justifications for their existence (McCoy & Sorensen, 2003). Three developments occurred in the closing years of the 20th century that increased interest in distance education: advent of mature information technology and the World Wide Web; the end of the Cold War; and financial challenges to states (Saba, 2005). As a result of these factors, many of the aspects of traditional higher educationlocation, roles, time allocationcentral focus for the shifting roles of colleges, the delivery mode for that learning will be a powerful shapeStudents as consumers are demanding more flexibility and ease of educational access, and these demands have increased the use of technology-driven applicationsa euphemism for online education (Levin, 2001). Knowledgeable higher education leaders have remarked upon the shift of universities into the marketplace, and they commented upon the requirement for higher education institutions to serve the needs of students in innovative, responsive ways (Bok, 2003; Duderstadt, 2000). Therefore, online education and a rapidly shifting technological landscape are undeniable features of the current and future post-secondary education arena.

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31 In contrast, while several studies have indicated value in online education (Lou, Bernard, & Abrami, 2006), faculty members saw little value in deviating from traditional delivery methods (Allen & Seaman, 2006; Levin, 2001). Disruptive innovation enters the market at a low level of performance and customer acceptance, and it is usually disdained by the market leaders (Christensen et al., 2001). Faculty disdain for online education was well documented (Allen & Seaman, 2006; Pittman, 2003), but a distain is not new. Thorstein Veblen and Abraham Flexner were early 20th century critics of correspondence study (Pittman, 2003). The critics of distance education usually are 2005, p. 44). Several researchers have observed that the clash of cultures within academia is based upon conflicting value structures that reflect the functional views of faculty, administrators, and technology managers (Bergquist, 1992; Birnbaum, 1988; Saba, 2005). Saba (2005) stated that faculty exist in a premodern craft culture focused on freedom and autonomy; administrators inhabit a modern culture demanding efficiency and cost-consciousness; and distance education occupies a post-modern information technology culture. Some faculty criticisms were focused upon the cost-reduction attributes of online education. The faculty members claimed that they were oppressed by alliances between the institutions and the technology industry (Pittman, 2003). Still other skeptics have been concerned with the reduction of academic freedom driven by industrial models of asynchronous learning (Pittman, 2003). Finally, faculty members were concerned that working conditions might be affected as the shift in teaching roles continued to play out (Pittman, 2003). Faculty members attacked correspondence study with a vengeance with the onset of the Great Depression, so attacks upon the quality of distance education will likely increase as budgets diminish and expenses at traditional institutions rise (Pittman in Moore & Kearsley, 2005). A major impetus

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32 for this study is to assess the state of policy regarding online learning so that quality concerns might be addressed. Theories of Distance Education Distance education theory informed the study. The approach to distance education in the United States has been highly pragmatic with distance educators, using the prevailing media of the time to accomplish educational goals (Pittman, 2003; Saba, 2003). Despite the pragmatic approach, some theories have arisen from both international sources as well as American scholars (Gunawardena & McIsaac, 2004; Simonson et al., 2003). Best practices have emerged and have been translated into conceptual building blocks that are currently being assembled into new theories (Anderson, 2004; Saba, 2003). However, one scholar suggested that Web-based instruction is a technological enhancement to distance education and did not introduce new pedagogy (Jung, 2001). phenomenon of our field of inquiry and an overarching logical structure of reasoned suppositions which can generate intersubjectively testable hypoteducation have been proposed and have been classified into three groups (Keegan, 1996): Theories of industrialization of teaching Theories of independence and autonomy Theories of interaction and communication This portion of the review of literature examines leading theories of distance education distance education theory and policy analysis frameworks (PAF) for distance education. Theories of Industrialization of Teaching Theories of distance education prior to the introduction of the World Wide Web were focused on defining distance education and on aspects of course delivery. In 1967, Otto Peters

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33 proposed a theory of industrialization that relied upon industrial-age organization, planning, division of labor, mass production, and formalization to distribute educational materials to large numbers of students (Gunawardena & McIsaac, 2004; Moore & Kearsley, 2005; Simonson et al., (Simonson et al., 2003). It was a theory of organization rather than of pedagogy (Gunawardena widely separated distance education students (Simonson et al., 2003). It was a highly influential theory and helped shape the concepts of distance education (Gunawardena & McIsaac, 2004). In recent years, Peters (2003) commented on the significant paradigm shift in distance education wrought by the new media. Peters maintained, however, that students in distance education remained largely autonomous, self-directed learners. The Industrial Theory of Distance Education proposed by Peters (Simonson et al., 2003) stated Planning and organization are critical to success. Course development is important. Courses must be formalized and expectations of students standardized. Teaching is objectified. Distance education can be economically feasible only with centralized administration. Under theories of industrialization, distance education was best administered centrally with concentration of resources (Simonson et al., 2003). s (Gunawardena & McIsaac, 2004; Holmberg, 2003; Keegan, 1996; Simonson et al, 2003): Quasi-permanent separation of teacher and learner Influence of an educational organization Use of media to link teacher and learner and to carry course content Two-way communication Quasi-permanent absence of a learning group Industrialized education

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34 learning groups were made possible using electronic communications (Holmberg, 2003). Keegan (1996) added to his theories by hypothesizing that distance education was indeed a form of education, but that success required teaching and learning to be integrated rather than existing in separate place and time (Simonson et al., 2003). Keegan additionally hypothesized that without integrated teaching and learning, students would drop out and experience educational quality deficits, and the status of distance learning would be questioned (Simonson et al., 2003). Theories of Independence and Autonomy In the 1960s, Charles Wedemeyer developed a theory of learner-centered distance education which influenced Michael G. Moore (Gunawardena & McIsaac, 2004). In 1972, Moore introduced the Theory of Independent Study (Moore & Kearsley, 2005). The theory was a pedagogical approach whereby teachers were required to plan and interact (Moore & Kearsley, 2005; Simonson et al., 2003). Distance education theoryfrom the viewpoint of the individual faculty memberwas opposed to industrial theories of distance education where lessons were largely created by central planners (Simonson et al., 2003). Moore classified distance education as autonomous (determined by the learner) or nonautonomous (determined by the teacher) (Simonson et al., 2003). The theory gauged autonomy by whether the teacher or the learner determined learning objectives, teaching resources, and methods of evaluation (Simonson et al., 2003). Moore elaborated on the theory throughout the 1980s and early 1990s, leading to the development of the Theory of Transactional Distance. In the Theory of Transactional Distance, distance education interactions were conceptualized as transactions between teacher and learner (Moore & Kearsley, 2005). The distance was seen as a continuum of more or less transactional

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35 separation between faculty and student (Moore & Kearsley, 2005). Drawing on earlier theory (Gunawardena & McIsaac, 2004). In more autonomous distance education settings, learners took more responsibility for their own learning (Gunawardena & McIsaac, 2004; distance education theories that were grounded in industrial models focused on organizational structure. Theories of Interaction and Communication The Theory of Transactional Distance blended both industrial and psychosocial constructs in that it measured transactions along dimensions of dialogue and structure (Moore & Kearsley, 2005). One environmental factor for dialogue was the existence and size of the learning group, a departure from earlier (industrial) theories that suggested that learning groups were incompatible with distance education (Gunawardena & McIsaac, 2004; Moore & Kearsley, 2005; Simonson et al., 2003). Interpersonal variables included educational philosophy, personalities of teacher and student, subject matter, and environment (Moore & Kearsley, 2005). Structure referred to the design of the course and the educational philosophy of the teaching organization (Moore & Kearsley, 2005). These various transactions led Moore to postulate a variety of interactions in the distance education environment (Gunawardena & McIsaac, 2004; Moore & Kearsley, 2005; Simonson et al., 2003). Specifically, the Theory of Transactional Distance suggested that three interactions existed (Gunawardena & McIsaac, 2004; Moore & Kearsley, 2005): Teacher-Learner Interactions Learner-Content Interactions Learner-Learner Interactions

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36 The concepts of transactions between and among the various elementsteachers, learners, content, context, and organizationserved to define a distance education system (Gunawardena & McIsaac, 2004; Saba, 2003, 2005; Shaffer, 2005). Systems approaches to distance education theory will be addressed in the next section. Holmberg (1995) developed the Theory of Interaction and Communication in 1986, which suggested that interaction between teacher and student is the core to distance teaching (Simonson et al., 2003). This interaction required emotional involvement with the material and a personal relationship between student and instructor which, in turn, created learning pleasure and student motivation (Simonson et al., 2003). Holmberg (2003) expanded his theory to include more concepts of support and interaction in A Theory of Distance Education Based on Empathy. These concepts included the following: Distance education serves learners who are not able to use or who do not want to use face-to-face teaching. Support from an organization, administration of teaching and learning process, and empathy with students are required elements. Distance education is supported by noncontiguous means, for example, pre-produced course materials. Mediated communications are required, including friendly interaction between students, tutors, counselors, and other staff. The teaching and learning process includes arrangements for student-student interaction facilitating personal relationships, study pleasure, and empathy for students. Quick turnaround of assignments and other communications are also required. p. 360) as a feature of the empathy approach. He also focused upon the importance of dialogue. The industrial theories of Peters (2003) and Keegan (1996) were more organization-centered, focusing on structural issues, while the theories of interaction of Moore and Holmberg

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37 are focused on the individual and were more learner-centered (Holmberg, 2003; Moore & Kearsley, 1996, 2005; Saba, 2003). The complexity in the interface of these two areas gave rise to the contemporary search for a systems-oriented theory of distance education (Saba, 2003, 2005). Contemporary Theoretical Concepts in Distance Education As mentioned earlier, Moore (Moore & Kearsley, 1996, 2005) and Holmberg (1995, 2003) adopted learner-centered views of distance education and cast the concept in terms of social science (Saba, 2003). The social construction of knowledge has been prominent in educational literature and has been seen as important to distance education (Gunawardena & McIsaac, 2004; Saba, 2003; Shaffer, 2005). Social science has been increasingly seen as operating in the realm of systems and complexity (Gharajedaghi, 2006). Distance education facilitated by the Internet was now seen as an emerging post-industrial form of education (Saba, 2003). Therefore, a systems view of distance education became a contemporary interpretation of the field. A system is defined as a group of elements that are organized and arranged so that the elements can act in concert toward a desired outcome (Kerzner, 2003). Elements of input, process, output, and a feedback loop complete the basic system model (Scholtes, 1998). Feedback (communication) is elemental to the functioning of a system (Scholtes, 1998). Moore adopted a systems view of distance education in 1996 (Moore & Kearsley, 1996, 2005). He observed that a distance education system consists of several subsystems and their processes: learning, teaching communications, course design and materials, and management, including organization, andsignificantly for this studypolicy (Moore & Kearsley, 2005). Each of these elements was a component of the whole, and while each subsystem was individually worthy of close analysis, understanding the interrelationships among the component elements was paramount (Moore & Kearsley, 2005). Distance education organization structures

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38 manifested the systems characteristics of complexity, hierarchy, dynamism, self-organization, and chaos (Saba, 2003). Distance education scholars have called for a Systems Theory of Distance Education (Shaffer, 2005). Systems dynamics approaches have been applied to the Theory of Transactional Distance interactions posited by Moore (Moore & Kearsley, 2005; Saba, 2003). These approaches examine the feedback loops in the systems model, and they have been viewed as good modeling tools for distance education (Shaffer, 2005). For example, the feedback loop between Mooredistance (Saba, 2003). Researchers have suggested that additional feedback loops are possible that would model other constructs within distance education systems (Saba, 2003; Shaffer, 2005). Anderson (2004) proposed a contemporary systems model of distance education that accommodates the increase in communications and complexity found in online learning. In addition to recognizing the sociocultural factors in how people learn, the model also accommodated the many modalities of interaction available from the Web (Anderson, 2004). The systems model expanded beyond the Transactional Theory of Distance interactions between student-teacher, student-student, and student-content to include more complex interactions between teacher and content, between content and content, and between teacher and teacher (Anderson, 2004). The model also included an equivalency theorem that allows substitution of one form of interaction for another, as long as one of the three interactions is at a very high level scholars have called for models that similarly reflect the complexity and communications modalities afforded by the Internet (Shaffer, 2005).

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39 Public Policy Research and Analysis Origins of Policy A policy is a written plan of action providing guidance to govern behavior in a specific area (Simonson & Bauck, 2003). The etymology of the term policy is found in ancient Greek, Sanskrit, and Latin words that all mean city or state (Dunn, 1994). Similarly, politics was derived from the Latin politia (state); therefore, in many modern languages, the terms policy and politics are interchangeable (Dunn, 1994). Studies of public administration, political science, and the policy sciences (for example, economic policy, education policy) have been beset with ambiguity resulting from the blurring of meaning of the terms politics and policy (Dunn, 1994). The study of policy is as ancient as the Babylonian Code of Hammurabi. Written in the 21st century BCE, the Hammurabian Code was the earliest known effort to create written public policy (Dunn, 1994; Safriz, Layne, & Borick, 2005). The need to codify government response to environmental factors (for example, crop conditions, economic considerations, international strategy, and conflict with other states) gave rise to specialists educated in governmental management and policy creation (Dunn, 1994). As society became more complex, more division of labor was required. This decision resulted in the evolution of a class of professional politicians The Prince, a treatise on managing affairs of state published in 1532, captured the science of politics, as it existed at the dawn of the 16th century (Machiavelli, 1532/1998). Machiavellian concepts still have value today in predicting human behavior in political circumstances (Kocis, 1998). The Renaissance and the Age of Reason ushered in concepts of scientific empiricism and set the stage for modern policy analysis (Dunn, 1994). Post-industrial society created a much more complex environment for policy (Dunn, 1994; Hird, 2005). By the 1950s, advances in social sciences had added values and ethics as core

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40 elements of policy science in modern industrial societies (Dunn, 1994). The rise of technical knowledge and intellectual technologies, the proliferation of graduate schools of public affairs and policy studies, and a transformation of the United States from a manufacturing economy to a service and knowledge economy all aligned to boost interest in policy studies and policy analysis (Dunn, 1994; Hird, 2005). Therefore, policy studies and analysis have been increasingly important in providing information to decision-makers as they confront complex, modern problems across a spectrum of public goods and services, including higher education (Hird, 2005; Majchrzak, 1984). The Policy Cycle and Policy Research The study of the policy cycle included policy formulation, policy implementation, and policy accountability (Rist, 1995). In the first stage of the cycle, policies were formulated as instructions to implementers in response to a need expressed as a societal or organizational goal (Nagel, 1990; Rist, 1995). Then, policies were translated into programs, procedures, or regulations as part of the policy implementation process (Nagle, 1990; Rist, 1995). The third stage in the policy cycle was policy accountability wherein measures of success were applied to determine the effectiveness of the programs, procedures, or regulations stemming from the policy (Rist, 1995). In response to the complexity of post-industrial society, policymakers and other stakeholders, such as the news media, have become interested in research upon which to ground policy formulation and implementation (Hird, 2005). As a result, four types of research have been seen as useful in assessing social problems (Majchrzak, 1984). Basic social research and technical social research have been useful in informing policymakers but were not focused on problem-solving (Majchrzak, 1984). The remaining two types of research are policy analysis and policy research (Majchrzak, 1984; Weimer & Vining, 2005). Policy research has been

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41 focused on examining a particular social problem and identifying alternative solutions to that problem (Majchrzak, 1984; Weimer & Vining, 2005). Policy Analysis and Evaluation Policy analysis was focused on identifying relationships among variables describing social issues and selecting variables that could be manipulated to achieve societal goals (Majchrzak, 1984; Weimer & Vining, 2005). Policy analysis may be either quantitative or qualitative (Nagle, 2001a ). While both policy analysis and policy research were useful in the policy formulation phase of the policy cycle, policy analysis has also been associated with the process of policy adoption and measuring the success of the policies once adopted (Majchrzak, 1984). Policy analysis included both policy evaluation and policy recommendations (Dunn, 1994). Therefore, policy analysis and program evaluation are closely aligned and make use of many of the same research techniques to reach conclusions regarding public policy (Hird, 2005). Program Evaluation has been a practical research activity whose major purpose is to provide feedback on policy success through program analysis (Chen, 1990b ). Since programs are policy implementation vehicles (Mayer & Greenwood, 1980; Nagle, 1990, 2001a; Rist, 1995), evaluating a program has the effect of evaluating its underlying policy. Measures of success may be normative (a policy program is in place) or causativeactual program outcomes are measured to gauge success of the policy (Chen, 1990a; Chen & Rossi, 1992). Evaluators of policy success may create a theory of the implementation program that is designed to reflect the goals and intent of the policymakers who created the program (Chen, 1990a). Therefore, essing policy utility (Chen & Rossi, 1992; Majchrzak, 1984; Nagle, 2001a, 2001b).

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42 Policy Theories Against the backdrop of empiricism in policy studies, such as increased interest in humanistic factors associated with policy decisions and the expanded complex arena of government, more interest has arisen in public policy theory (Hird, 2005). The Policy Studies Organization (PSO) reported in 2004 that theory development in policy is under way, but no overarching theory of policy formulation exists (Morcol, Rundquist, Reese, & Krone, 2004). The study of policy theory has been undertaken at three levels: frameworks, theories, and models (Ostrom, 2007). A framework identifies universal elements of policy analysis and organizes the elements and their relationships with one another. Frameworks are the most general of the three theoretical levels (Ostrom, 2007). A theory focuses on the framework and enables the analyst to diagnose phenomena, analyze and explain processes, and predict outcomes of manipulation of variables. Theories are more specific than frameworks (Ostrom, 2007). Models are the most specific of the three constructs, and they enable the analyst to make precise assumptions about the variables in a given situation and make narrow predictions about likely outcomes if they are tailored to fit the situation (Ostrom, 2007). Since few fully developed theories of policy have emerged, frameworks are the most common constructs in contemporary policy theory (Morcol et al., 2004; Ostrom, 2007; Sabatier, 2007). Contemporary theoretical policy frameworks (Morcol et al., 2004; Ostrom, 2007; Sabatier, 2007) include the following: Incrementalism approach Stages heuristic Multiple-streams framework Punctuated-equilibrium framework The policy diffusion framework Policy networks framework Social construction framework

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43 Institutional rational choice (IRC) The advocacy coalition framework The incrementalism approach to policy formulation and analysis, proposed by Charles Lindblom in 1959, still has supporters (Gill & Saunders, 1992b; Morcol et al., 2004). The The incremental approach -and-error methodology (Lindblom, 1959). In presenting this approach, Lindblom observed that incrementalism engendered a practice of ignoring possible adverse outcomes of the resulting policy (1959). However, to disjointed incrementalists, a final policy was not final at all, thus allowing redress of unintended consequences (Lindblom, 1979). Incrementalism was still a viable policy analysis concept since it allowed study and adjustment of portions of a larger system that may otherwise be inaccessible (DeLeon, 1999). The stages heuristic asserted that policy development moves through a series of stages: agenda setting; policy formulation and legitimation; implementation; and evaluation (Majchrzak, 1984). The stages heuristic was not a causal theory, and has been largely overcome by other frameworks (Sabatier, 2007). However, the stages heuristic provided a useful, descriptive, textbook approach to the policy life cycle (DeLeon, 1999; Majchrzak, 1984). The multiple streams framework suggested that policy agenda setting and alternative specification under conditions of ambiguity were influenced by three streams in the system. These three streams were problems, policies, and politics (Zahariadis, 2007). Policymaking is accomplished within the context of a social problem (Majchrzak, 1984; Nagle, 1990). Within the multiple streams framework problems were descriptions of conditions highlighted by indicators (measures such as graduation rates), dramatic events (a bridge collapse), or feedback from

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44 existing programs, for example, testimony by administrators (Zahariadis, 2007). Problem conditions converged with the other two streams: policies and the political mechanisms necessary to adopt the policies. Therefore, clarity and understanding of the issues driving a need for policy were important in problem definition for policymaking (Majchrzak, 1984). The punctuated equilibrium framework considered both stasis (equilibrium) and discontinuous change (disequilibrium) in the policy arena (True, Jones, & Baumgartner, 2007). The framework held that most policies are stable and change incrementally, as described by the incrementalism framework (Gill & Saunders, 1992b; Lindblom, 1959). Some policies, however, represent rapid, discontinuous shifts as a result of political conflict and new agenda setting (True et al., 2007). Rapid shifts may be caused by both large and small changes in the environment (True et al., 2007). A large budget change was one example of the change factors that may drive sudden (punctuated) equilibrium shifts (Sabatier, 2007). The policy diffusion framework explained the adoption of similar policies across several states, for example a state lottery (Sabatier, 2007). The policy diffusion framework described processes through which governments adopt new programs. The diffusion framework was grounded in three concepts: states learn from one another; states compete with each other; and citizens and other interested parties press policymakers to adopt effective policies from other states (Berry & Berry, 2007). Underlying models for diffusion at national and regional levels have sought to explain how differing policies are transmitted (Berry & Berry, 2007). The policy diffusion framework maintained that every governmental program has its initial source in a nonincremental innovation (Berry & Berry, 2007). Another state may later voluntarily adopt the same policy as an innovation (Berry & Berry, 2007; King & Mori, 2007). Therefore, policy innovation is not

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45 necessarily the same as innovation in a product development senseit has been common for states to adopt policies from one another and call such adoption an innovation (Berry & Berry, 2007). The innovation in this case would be better referred to as policy transfer from another jurisdiction (Berry & Berry, 2007; King & Mori, 2007). Additionally, policy diffusion may be constrained by political agendas and ideologies with different states arriving at differing polices (King & Mori, 2007). One impetus for policy transfer has been the emergence of a new problem that was solved elsewhere (King & Mori, 2007). Politicians must respond to expectations and ideology of the electorate (King & Mori, 2007). Ultimately, the concept of policy convergence represents regional or national adoption of the 2007, p. 19). When examining the mechanisms that result in policy convergence, several causal factors were identified. Voluntary transfers of policy from one actor to another may result from problem-solving on the part of the adopter (Dolowitz & Marsh, 1996; Knill, 2005). Coersion or imposition of a policy by an outside actor (for example, a state legislature) is another common mechanism for policy adoption (Dolowitz & Marsh, 1996; Knill, 2005). Emulation of other states or institutions and competition among policy actors have been suggested as mechanisms fostering policy diffusion (Dolowitz & Marsh, 1996; Knill, 2005). Of these mechanisms, coercion was the approach with the most rapid rate of adoption, while voluntary or optional transfer was the slowest (Rogers, 2003). Mechanisms of policy diffusion included seven objects of policy transfer (Dolowitz & Marsh, 1996, pp. 349-350): Policy goals Structure and content

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46 Policy instruments or administrative techniques Institutions Ideology Ideas, attitudes, and concepts Negative lessons The concept of policy networks has held that policymaking takes place in subsystems consisting of many actors, such as interest groups, governmental agencies, and institutional leaders (Adam & Kriesi, 2007; Marsh, 1998). The policy networks framework was rooted in the concept that the various actors are interdependent and exchange resources in creating policy outcomes (Adam & Kriesi, 2007; Marsh, 1998). In the policy networks framework, power drive policymaking behavior (Adam & Kriesi, 2007; Marsh, 1998). Policy networks may function as informal governing bodies in that a formal, governmental policy organization may be only one of the many actors in the network (Adam & Kriesi, 2007). In this regard, the policy networks framework has held that contemporary policymaking bodies may be less formal and less centralized with more distribution of power among the actors (Adam & Kriesi, 2007). The social construction framework asserted that policymakers use a policy design approach to account for numerous intervening variables in the policy planning process (Ingram, Schneider, & DeLeon, 2007). Policymakers socially construct target populations to reflect interest groups (target populations) and institutions based upon values held by policymakers (Ingram et al., 2007). Policy designs shape institutions and culture, according to the social construction framework (Ingram et al., 2007). The social construction framework is still evolving; however, it has been used in numerous contemporary studies to explain power relationships, allocation of benefits and burdens, and policy changes (Ingram et al., 2007).

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47 The institutional rational choice framework suggested that institutional rules alter the rational behavior of the individuals making decisions (Sabatier, 2007). Despite the multiple definitions of the term institution and the invisibility of many aspects of the structure of institutions (Ostrom, 2007), the institutional analysis and development (IAD) framework has been widely used in the United States to analyze policy (Sabatier, 2007). The IAD framework was organized in terms of the action arena, or the social space in which the participants interact (Ostrom, 2007). The arena included the situation, participants, positions, outcomes, and linkages (Ostrom, 2007). Factors affecting behavior of the participants included rules, structure, and attributes of the community (Ostrom, 2007). The IAD framework linked rules, conditions and community attributes, individual incentives, and the resulting outcomes in the policy arena (Ostrom, 2007). Units and levels of analysis have been seen as critical variables in IAD-related analysis of policy issues (Ostrom, 2007). The advocacy coalition framework (ACF) focused on advocacy coalitions of actors in a variety of institutions (Sabatier, 2007). A major feature of the ACF included selecting the unit of analysis the policy subsystem(s) that make up the entire policy arena (Sabatier & Wiebe, 2007). The policy subsystem consisted of administrative agencies, governmental committees, special interest groups/political action committees, journalists, policy analysts, and other governmental actors (Sabatier & Wiebe, 2007). In the ACF, the belief systems of these policy elites have been seen as elemental for policy learningthe relatively permanent alterations of thought or behavioracross coalitions. (Sabatier & Wiebe, 2007). When using the ACF for policy analysis, the researcher must remain cognizant of the possibility of the appearance of additional coalitions (Sabatier & Wiebe, 2007).

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48 The policy process has been characterized as complex and interdisciplinary (Majchrzak, 1984; Sabatier, 2007). To understand such a process required theoretical frameworks to simplify it by identifying elements within the process that serve as markers for the observer (Ostrom, 2007; Sabatier, 2007). Scientific theory systematized knowledge by providing a set of several contemporary policy frameworks and then grouped the phenomena observed (Sabatier, 2007). Each of these frameworks appeared to focus on a different aspect of the policy process, arena, or actors. Since there is no single, grand unifying theory for policy analysis, analysts have been required to disaggregate the parts of the policy in question and to select the best fit to one or more of the available frameworks (DeLeon, 1999). Distance Education Policy Elements of distance education policy included its purposes, environment, inputs, processes, and outcomes, as well as a policy community consisting of stakeholders, including administrators, faculty, and students (Pacey & Keough, 2003; Perraton, 2003). For higher education, the purposes for distance education have been in extending educational opportunities for new audiences to allow learner convenience or to foster economic development by expanding learning access (Perraton, 2003). Community colleges in particular have been interested in distance education as a means to foster access for continuous learning and for promoting the -Mumford & Parke, 2000). The environment for distance education policy has been one of economics, educational access, technology, and cost (Perraton, 2003). Educational access and economics are interrelated in that access to higher education has been seen as fostering national economic development and competitiveness; hence, expenditures for distance education are cast as investments (Perraton,

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49 2003). Technology was an enabling element which provided opportunity to expand access and which merited investment (Perraton, 2003). Finally, cost savings provided to institutions from distance education have been documented and were seen as favoring distance education (Carnevale, 2005; Perraton, 2003; Texas Higher Education Coordinating Board, 2000). Inputs to distance education policy included the purposes, resources, and stakeholders. Processes included organizational structures, technologies (for example, learning management systems such as WebCT) and governance, accreditation, and quality assurance (Pacey & Keough, 2003; Perraton & Lentell, 2003). Outcomes were benefits to the student, the workforce, employers, and society (Pacey & Keough, 2003; Perraton & Lentell, 2003). Stakeholders consisted generally of administrators, students, and faculty (Perraton, 2003). Stakeholders, combined with policymakers and other groups and agencies with an interest in distance education policy, made up the policy community (Pacey & Keough, 2003). Students, faculty, and administrators have been considered the targets of distance education policy (Chen, 1990b; Ingram et al., 2007). These elements were highly coincident with frameworks for distance education policy analysis (Berge, 1998; Gelman-Danley & Fetzner, 1998; King et al., 2000; Levy, 2003; Osika, 2006), as well as quality standards for distance education (Phipps & Merisotis, 2000). The following elements were critical issues in policy and planning for distance education (Lentell, 2003, pp. 252-253): Identifying the target population and their needs Choosing the type of system Choosing the appropriate technology of delivery Business planning and costing open and distance learning systems Materialsdeveloping or acquiring Tutoring and supporting students Recruiting and enrolling students Assessing students

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50 Managing and administering the open and distance learning systems Monitoring, evaluating, and quality assurance In relation to other disciplines, such as politics and business, policy analysis in higher education has been a comparatively recent development (Gill & Saunders, 1992a). However, the high value and high impact of higher education in the national context conjoined to make educational policy a critical area of study (Gill & Saunders, 1992a). A wide variety of analytical methods were required to evaluate educational policy since educational institutions had characteristics that are significantly different from business or political institutions (Gill & Saunders, 1992a; Majchrzak,1984). For example, higher education was subject to multiple cultures, such as shared governance, that could influence policymaking behavior and could potentially cause conflict with other parts of the educational subsystem (Bergquist, 1992; Birnbaum, 1988). Therefore, to assure that key elements were examined, analysis of distance education policies required use of a multifaceted framework. Policy analysis in higher education required understanding the issues, the environment, culture, constraints, policy actors, networks, and coalitions (Bergquist, 1992; Gill & Saunders, 1992b; Pacey & Keough, 2003; Perraton & Lentell, 2003). Some higher education policy analysts were adherents of incrementalism to explain policy (Gill & Saunders, 1992b), while other analysts supported the stages heuristic (Majchrzak, 1984). However, the rapid onset of the Internet and its effect on distance learning suggested a more adaptive approach (Pacey & Keough, 2003). Such an adaptive approach aggregated several policy theory frameworks previously discussed while recognizing that development of policy remained an iterative exercise (Pacey & Keough, 2003). An adaptive approach blended social construction of the target population (students) with the distance education policy system to create desired outcomes.

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51 In the case of online distance education, the policy system consisted of resources, educational content, and activities delivered through a telecommunications medium (Pacey & Keough, 2003). Feedback regarding outcomes was via policy network interaction (Pacey & Keough, 2003). Further aggregation of the various frameworks suggested viewing the rapid adoption of online technologies as an example of punctuated-equilibrium that required institutions and state regulatory agencies to shift to more responsive planning models as the environment flexed (Christensen et al., 2001; Pacey & Keough, 2003). The adaptive view of policy theories, as applied to distance education, was reflective of the systems theory of distance education (Moore & Kearsley, 1996, 2005), and served as backdrop for examination of various policy analysis frameworks. Distance Education Policy Analysis Frameworks (PAF) Several frameworks have been proposed for distance education policy analysis. Gelman-Danley and Fetzner (1998, para. 2-3) proposed seven policy development areas for distance learning that included the elements in Table 2-1. These areas formed the basis for several other PAF, as listed in Table 2-2 (Berge, 1998; King et al., 2000; Levy, 2003; Osika, 2006). Additional analyses of the distance education policy arena and quality benchmarks focused on the same factors (Dirr, 2003; Lezberg, 2003; Pacey & Keough, 2003; Phipps & Merisotis, 2000; Sherry, 2003; Simonson & Bauck, 2003). Areas added in revised PAF included technical and cultural factors (Berge, 1998), vision and plans (Levy, 2003) and community (Osika, 2006). The technical area included systems reliability, connectivity and educational access, and infrastructure elements, including hardware, software, and technical support (Berge, 1998). Cultural factors included resistance to innovation and online education (Berge, 1998). Vision and plans were added as part of the need to assure effective management of organizational change and to foster a more rapid rate of adoption

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52 (Levy, 2003). Vision and plans were also related to the need to plan effectively for a change to larger learning community (Osika, 2006). The communitinterests in the other PAF areas (Osika, 2006). After piloting the use of a more compact PAF (King, et al., 1999; Nugent, Eich, Mlinek, & Russell, 1999), King, Nugent, Russell, Eich, and Lacy (2000) proposed collapsing the Gelman-Danley and Fetzner (1998) and Berge (1998) models from nine factors to three factors. The -al., 2000). The three-re management and organization, faculty, and students (King et al., 2000). Management and organization included the subareas of tuition and fees, funding formulas, collaboration among educational organizations, resources, curriculum, and program management (King et al., 2000). The faculty area included rewards, support, learning opportunities, including release time, and it addressed intellectual property (King et al., 2000). The student area retained the elements as found within the larger models (King et al., 2000). The King et al. (2000) Three-Tiered Policy Analysis Framework (Figure 2-1) formed the basis for the analytical framework used in this study. Distance Education Accreditation Policy and Quality Benchmarks Accreditation policy Accreditation policy for distance education also informed the study. The most respected and widely accepted accrediting bodies in the United States were the six regional accreditation associations for higher education (Lezberg, 2003): Middle States Association of Colleges and Schools New England Association of Schools and Colleges North Central Association of Colleges and Schools Northwest Association of Schools and Colleges

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53 Southern Association of Schools and Colleges Western Association of Schools and Colleges Responding to calls from member institutions to provide accreditation policy for technology-mediated distance education, these six regional associations evaluated guidelines for distance-education and adopted those developed by the Western Cooperative for Educational Telecommunications (Middle States Commission on Higher Education, 2002; Lezberg, 2003). Additionally, two community college-oriented associations adopted the Interregional Guidelines (Lezberg, 2003). The resultant guidelines are published on the institutio in print form as Interregional Guidelines for Eelectronically Offered Degree and Certificate Programs (2nd ed., Middle States Commission on Higher Learning, 2002). The Interregional Guidelines (Middle States Commission on Higher Education, 2002) included the following five components: Institutional Context and Commitment: Acknowledgement that electronically offered programs are integral to the academic organization. Curriculum and Instruction: Critical issues are not technological but curriculum and pedagogy oriented. Faculty Support: Faculty roles are changing as technology becomes fully integrated. Student Support: The 21st century student is different from his predecessor and these differences affect all aspects of the college stud Evaluation and Assessment: Student achievement and overall program performance assessment have taken on additional meaning as technology impacts the institution. The five components reflected the same general elements of policy as found in the aforementioned PAF. In addition to utilizing these guidelines, the regional associations adopted the following statements of principle (Middle States Commission on Higher Education, 2002, p. vi):

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54 While endeavoring to maintain balance and flexibility in the evaluation of new forms of delivery the regional commissions are also resolved to sustain certain values. These include among other things: that education is best experienced within a community of learning where competent professionals are actively and cooperatively involved with creating, providing, and improving the instructional program; that learning is dynamic and interactive, regardless of the setting in which it occurs; that instructional programs leading to degrees having integrity are organized around substantive and coherent curricula which define expected learning outcomes; that institutions accept the obligation to address student needs related to, and to provide the resources necessary for, their academic success; that institutions are responsible for the education provided in their name that institutions undertake the assessment and improvement of their quality, giving particular emphasis to student learning; that institutions voluntarily subject themselves to peer review. The associations further state in the Interregional Guidelines (Middle States Commission There can be no doubt that there are challenges in sustaining these important values through technologically mediated instruction. The regional commissions appreciate this reality, and also recognize that these values may be expressed in valid new ways as inventive institutions seek to utilize accreditation associations, as the primary higher education quality organizations in the United States, each issued policy statements of varying strengths regarding compliance with the guidelines (Lezberg, 2003). Quality benchmarks Several authors proposed quality benchmarks for distance education (Phipps & Merisotis, 2000; Sherry, 2003; Simonson & Bauck, 2003). These benchmarks aligned with the same categories, as noted in policy analysis frameworks and accreditation standards (Table 2-3). These

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55 categories were successfully woven into evaluation models for effectiveness of distance education (Baker, 2003; Chapman, 2006). Summary The advent of the Internet and high-speed connections ushered in Web-based education, the most widely used distance education approach (Moore & Kearsley, 2005). The World Wide Web (WWW) marked a major change in the usefulness of the Internet and resulted in a paradigm shift in higher education (Duderstadt, 2000; Moore & Kearsley, 2005). A major impetus for this study was to assess the state of policy regarding online learning so that quality concerns might be addressed. Distance education theory informed the study. Several theories of distance education have been proposed and have been classified into three groups (Keegan, 1996): Theories of industrialization of teaching Theories of independence and autonomy Theories of interaction and communication Theories of industrialization of teaching were descriptive of the organization rather than of pedagogy (Gunawardena & McIsaac, 2004). The theories of independence and autonomy represented a pedagogical approach whereby teachers were required to plan and interact (Moore both industrial and psychosocial constructs in that it measured transactions along dimensions of dialogue and structure (Moore & Kearsley, 2005). Holmberg theorized that interaction between teacher and student was the core to distance teaching (Holmberg, 1995; Simonson et al., 2003). This interaction required emotional involvement with the material and a personal relationship between student and instructor (Simonson et al., 2003).

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56 Distance education scholars have called for a Systems Theory of Distance Education (Shaffer, 2005). Moore observed that a distance education system consisted of several subsystems, and each of these elements is a component of the whole (Moore & Kearsley, 2005). Anderson (2004) proposed a contemporary systems model of distance education that accommodated the increase in communications and complexity found in online learning. In addition to recognizing the sociocultural factors in how people learn, the model also accommodated the many modalities of interaction available from the Web (Anderson, 2004). Policy theory and policy analysis were core underpinnings of this study. The policy cycle includes policy formulation, policy implementation, and policy accountability (Rist, 1995). Policy analysis was focused on identifying relationships among variables describing social issues and selecting variables that can be manipulated to achieve societal goals (Majchrzak, 1984; Weimer & Vining, 2005). Policy analysis may be either quantitative or qualitative (Nagle, 2001a) and was also associated with measuring the success of the policies once adopted (Majchrzak, 1984). The Policy Studies Organization (PSO) reported in 2004 no overarching theory of policy formulation exists (Morcol et al., 2004). Of particular interest to this study were the punctuated-equilibrium framework, the policy diffusion framework, policy networks framework, and the social construction framework (Sabatier, 2007). The punctuated equilibrium framework considered both stasis (equilibrium) and discontinuous change (disequilibrium) in the policy arena (True, Jones, & Baumgartner, 2007). The policy diffusion framework explained the adoption of similar policies across several states (Sabatier, 2007). Ultimately, policy convergence represented regional or national adoption of the

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57 2007, p. 19). The concept of policy networks held that policymaking takes place in subsystems consisting of many actors, such as interest groups, governmental agencies, and institutional leaders (Adam & Kriesi, 2007; Marsh, 1998). Policy networks have functioned as informal governing bodies in that a formal, governmental policy organization may be only one of the many actors in the network (Adam & Kriesi, 2007). The social construction framework suggested that policymakers socially construct target populations to reflect interest groups (target populations) and institutions, based upon values held by policymakers (Ingram et al., 2007). A wide variety of analytical methods were required to analyze educational policy (Gill & Saunders, 1992a; Majchrzak, 1984). Since no single, grand unifying theory existed for policy analysis, the analyst was required to disaggregate the parts of the policy in question and attempt to select the best fit to one or more of the available frameworks (DeLeon, 1999). To assure that key elements are examined, analysis of distance education policies required use of a multifaceted framework. The rapid onset of the Internet and its effect on distance learning suggested a more adaptive approach to distance education policy analysis (Pacey & Keough, 2003). Such an adaptive approach aggregated several policy theory frameworks previously discussed (Pacey & Keough, 2003). In the case of online distance education, the policy system consisted of resources, educational content, and activities delivered through a telecommunications medium (Pacey & Keough, 2003). Feedback regarding outcomes was via policy network interaction (Pacey & Keough, 2003). Further aggregation of the various frameworks suggested viewing the rapid adoption of online technologies as an example of punctuated-equilibrium that required institutions and state regulatory agencies to shift to more responsive planning models as the environment flexed (Christensen et al., 2001; Pacey & Keough, 2003). The adaptive view of

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58 policy theories, as applied to distance education, was reflective of the systems theory of distance education (Anderson, 2004; Moore & Kearsley, 1996, 2005) and served as backdrop for examination of various policy analysis frameworks. Elements of distance education policy include its purposes, environment, inputs, processes, and outcomes as well as a policy community consisting of stakeholders, including administrators, faculty, and students (Pacey & Keough, 2003; Perraton, 2003). These elements were highly coincident with frameworks for distance education policy analysis (Berge, 1998; Gelman-Danley & Fetzner, 1998; King et al., 2000; Levy, 2003; Osika, 2006), as well as quality standards for distance education (Phipps & Merisotis, 2000). Several frameworks have been proposed for distance education policy analysis. Gelman-Danley and Fetzner (1998, para. 2-3) proposed seven policy development areas for distance learning. These areas formed the basis for several other PAF. King et al. (2000) proposed collapsing prior models from nine factors to three factors. The resultant three-tiered PAF turned into a more condensed, but still powerful, approach (King et al., 2000). The three-policy factors were management and organization, faculty, and students (King et al., 2000). The King et al. (2000) Three-Tiered Policy Analysis Framework formed the basis for the analytical framework used in this study. In addition to the convergence of PAF, quality benchmarks and accreditation standards have been developed. Several authors have proposed quality benchmarks for distance education (Phipps & Merisotis, 2000; Sherry 2003; Simonson & Bauck, 2003). These benchmarks aligned with the same categories as noted in PAF, and they represented an additional input to analysis of distance education policy. These categories have been successfully woven into evaluation models for effectiveness of distance education (Baker, 2003; Chapman, 2006). The six regional

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59 accreditation associations for higher education in the United States responded to calls from member institutions to provide accreditation policy for technology-mediated distance education in print form as Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher Education, 2002). These guidelines were also highly coincident with the PAF factors, as well as quality factors, and the elements of distance education policy systems. The regional accreditation associations, as the primary higher education quality organizations in the United States, have each issued policy statements of varying strengths regarding compliance with the guidelines (Lezberg, 2003). The current interest in systems theories of distance education suggested a multifaceted approach to policy analysis for electronically offered courses. Distance education theories and policy theories converged in several online distance education policy analysis frameworks, quality standards for online distance education, and interregional accreditation guidelines. This

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60 Figure 2-1. Three-tiered policy analysis framework (King et al., 2000). Table 2-1. Policy development areas for distance learning PAF Area Elements 1. Academic: Calendar, course integrity, evaluation, admission, curriculum approval, accreditation 2. Fiscal: Tuition ra te, technology fees, FTEs, consortia contracts, state fiscal regulations 3. Geographic: Service area, regional limitations, local versus out of state tuition, consortia agreements 4. Governance: Single versus multiple board oversight, staffing, existing struct ure versus shadow colleges or enclaves 5. Labor management: Compensation and workload, development incentives, intellectual property, faculty training, congruence with existing union contracts 6. Legal: Fair use, copyright, faculty, student and institutional l iability 7. Student support services: Advisement, counseling, library access, materials delivery, student training, test proctoring (Gelman-Danley & Fetzner, 1998) Management and Administration Faculty Students

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61 Table 2-2. Convergence of distance education policy analysis frameworks with quality Po licy analysis frameworks Quality benchmarks and accreditation guidelines Gelman Danley Fetzner, 1998 Berge, 1998 King et al., 2000 Levy, 2003 Osika, 2006 Phipps & Merisotis, 2000 Interregional guidelines, 2002 Academic Academic Management and organizati on Curriculum Program support Teaching and learning and evaluation and assessment Institutional context and commitment Fiscal Fiscal Management and organization Vision and Plans Program support Not addressed Institutional context and commitment Geographi c Geographic Management and organization Vision and Plans Program support Not addressed Institutional context and commitment Governance Governance Management and organization Vision and Plans Program support Course development Institutional context and co mmitment Labor management Labor management Faculty Staff training and support Faculty and program support Faculty support Faculty Legal Legal Faculty Copyright and intellectual property Content Not addressed Faculty support Student support services Stu dent support services Students/ participants Student services and student training and support Student support and program support Student support and course structure Student support Not addressed Technical Management and organization Student training su pport and staff training and support Technology and course manage ment system Institutional support Institutional context and commitment Not addressed Cultural Management and organization Vision Community Not addressed Institutional context and commitmen t

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62 Table 2-3. Distance education quality benchmark categories Phipps & Merisotis, 2000 Sherry, 2003 Simonson & Bauck, 2003 Institutional support Institutional guidelines Fiscal Course development Institutional guidelines Academic Teaching/learning Inst itutional guidelines Academic Course structure Institutional guidelines Academic Student support Student guidelines Student Faculty support Faculty guidelines Faculty Evaluation and assessment Institutional guidelines Academic Technical Philosophical

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63 CHAPTER 3 METHODOLOGY Introduction The purpose of the study was to conduct a normative analysis of policy on technology-mediated distance education in community colleges at state, consortia, and institutional levels to understand the diffusion of policy concepts in this increasingly central medium. The intent was to analyze congruence at each level with factors identified in policy analysis frameworks (PAF) associations. This chapter details the assumptions and research rationale for the study to analyze the condition of distance education policy at state, consortium, and institutional levels. This chapter presents research methods and procedures used to conduct the study and describes factors, levels, and data collection protocols. In addition, the chapter provides a detailed explanation of data collection approaches used in selecting samples of state, consortia, and institutional policy documents. Chapter 3 culminates with a discussion of the threats to validity and measures adopted to reduce the impact of these threats. Assumptions The study was based on four suppositions regarding distance education policy and document accessibility. First, it is assumed that states, consortia, and individual institutions are interested in distance education policy. States are believed to find value in policy as statements of intent, as well as governance over institutions. Consortia are similarly believed to govern ehavior through similar statements of policy and other policy-like guidelines. Institutions are assumed to create governing directives that focus departmental leadership, faculty, staff, and students on expected distance education methods, systems, and outcomes.

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64 Second, following the policy diffusion framework (Berry & Berry, 2007), it is believed that states, consortia, and institutions apply policies in similar ways to achieve similar outcomes. This assumption is grounded upon several distance education policy analysis frameworks converging upon the same core elements, as discussed in Chapter 2 (Table 2-2). Similarly, because institutions are highly focused upon regional accreditation as evidence of quality, it is assumed that the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (Middle States Commission on Higher Education, 2002) are important to institutions sampled in this study. In addition, institutions will make strong efforts to meet the various accreditation association guidelines. The Interregional Guidelines also converge on the same core elements as distance education policy analysis frameworks, as discussed in Chapter 2 (Table 2-2). Third, because the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (Middle States Commission on Higher Education, 2002) have been adopted across all six regional accreditation associations (Lezberg, 2003), they have the de facto status of a national standard (King & Mori, 2007). In applying these standards, institutions are assumed to have a common core approach to distance education. Fourth, documents regarding policies are assumed to be accessible at all levels of the study, facilitating a rich dataset. These assumptions lead to the formulation of the following four research questions: Are there differences in distance education policies among the regional accrediting bodies, the states, consortia, and institutions? ruent with frameworks for policy analysis? for policy analysis?

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65 To what extent are community college institutional distance education policies congruent with frameworks for policy analysis? Research Methods The study relied upon qualitative research methodologies to analyze and reduce data. manipulation of variables (Dooley, 2001). The study employed qualitative research methods grounded in constructivism. Ethnographic techniques of document review and content analysis served as data gathering and data analysis approaches (Altheide, 1996; McCollough, 2004). Qualitative inquiry has been seen as valuable in informing the field about issues in technology education (Hoeplf, 1997). The written documents which formed the dataset for this study did not lend themselves to quantitative analysis, thus qualitative analysis was methodologically appropriate to this study (Hoepfl, 1997; Patton, 1990). In choosing a qualitative approach, the researcher hoped to gain perspective on an area where not much is known about distance education policy and also to fully describe the phenomena associated with it (Hoepfl, 1997). Patton (1990) observed that qualitative data collection consists of three approaches: interview data, direct observation, and review of written documents. Review of documents in this study was the data collection method; content analysis was the data analysis excerpts, quotations, or entire passages from organizational, clinical, or program records [and] official publications and repalways specific, qualitative analysis techniques allowed creation of an interwoven view of the various policies and resulting institutional guidelines (Patton, 1990).

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66 artifacts of the policy decisions at state level, among consortia, and at sample institutions. The use of textual analysis was seen as particularly appropriate to policy analysis since concrete, written policies were intended to achieve an end (Hodder, 2000; McCoy & Sorensen, 2003; Weimer & Vining, 2005). Analyzing the content of policy documents was therefore decidedly qualitative. present study intended to identify the state of policy for technology-mediated distance education with the intent to inform decision-makers. To accomplish this end, elements of policy research methodology to policy-and content analysis as formal methodologies therefore intersected with policy analysis. Normative policy analysis was focused on policy and program design to compare actual practice with prescribed practice (Chen, 1990a, 1990b). In order to conduct a normative analysis, a norm must be identified. Distance education policy analysis models have been proposed (Berge, 1998; Gelman-Danley & Fetzner, 1998; King et al., 2000; Levy, 2003; Osika, 2006), and these models have been evaluated in the literature as being useful in analyzing distance education policy (McCoy & Sorensen, 2003; Simonson & Bauck, 2003;). Furthermore, the six regional accrediting bodies in the United States have adopted the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher Education, 2002) as the basis for accrediting technology-mediated distance education programs. The framework proposed by King et al. (2000) was used as a foundation for creating a content analysis protocol by axially coding specific Interregional Guidelines statements to

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67 correspond with the key elements of the framework. This content analysis protocol (Table A-1) served as a normative model for the study. Policy documents at state, consortia, and local levels were examined to determine their congruence with the elements of the content analysis protocol. The specific type of ethnographic content analysis used in the study has been referred to as qualitative content analysis (QCA) where the researcher seeks to translate frequency of occurrence of symbols (words/phrases) to objectively compare content (Altheide, 1996). The research goal of QCA is verification versus discovery of new or emerging patterns as in ethnography (Altheide, 1996). In QCA, protocols are constructed to compare research data against operational definitions, reducing issues of reliability by lessening the requirement to continuously apply judgment when coding. This enhances both reliability and validity (Altheide, 1996). As previously discussed, normative policy analysis seeks to compare existing policy statements to desired policy. The QCA and normative policy analysis are thus compatible, with QCA forming the operative approach to the normative analysis. Research Procedures Selection of Participating States and Institutions Sampling strategy for the study included a purposive sample (Creswell, 2005; Glesne, 1999) of the institutional Board Members of the League for Innovation in the Community education programs. Once the 37 community colleges were selected, their parent states and any state consortial relationships dictated selection of states and consortia for inclusion in the study. The typical case approach to purposive sampling was used (Patton, 1990). The 37 colleges varied in size and were located in 15 states. Furthermore, the institutions sampled covered five of the six regional accreditation bodies in the United States. The sample was purposive because the League Board Members chose to participate in innovation activities at a

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68 higher level than other member colleges (League for Innovation in the Community College, 2004), thus increasing the likelihood of technology-mediated distance education programs in the sample. Since the League for Innovation in the Community College is one of the major proponents of information technology in higher education, League member institutions are exposed to numerous initiatives in technology-mediated distance education (League for Innovation in the Community College, 2004). Purposive sampling includes identifying documents that can help develop detailed understanding of the phenomenon in question, and in this case, distance education policy attributes at several levels (Creswell, 2005; Glesne, 1999; Patton, 1990). By becoming Board Members of the League for Innovation in the Community College, these institutions have expressed an interest in technology and the advancement of community colleges in an array of innovative approaches to postsecondary education. These institutions thus represent a homogeneous sample that could assist in exploring the conceptual landscape of distance education policy (Creswell, 2005). The Board Members total 37 institutions in 15 states. One Board Member college in the United States was excluded since it was no longer a 2-year institution; a Canadian Board Member college was excluded since the PAF used in this study was derived from Interregional Guidelines for Electronically Offered Degree and Certificate Programs (Middle States Commission on Higher Education, 2002), a document accepted for accreditation in the United States. The use of Board Members served to limit the scope of the study in each state to a few institutions, allowing the study to expand beyond the limits of a single state. Analyzing the condition of distance education policy across 15 states and five of six accrediting bodies enhanced the reliability of the study. In addition, having a sample of 15 states increased the

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69 likelihood of consortium membership for the institutions since distance education consortia are an established feature of the online education landscape (Epper & Garn, 2004). Sources of Data Access to primary source documents (McCollough, 2004) was obtained at state, consortium, and institutional level. Documents accessed included state statutes and of Education, each state director of community colleges, consortial policy statements, and institutional distance education strategic plans, governance policies, and program guidance. The listing of the League Board Members was readily available on the League for Innovation in the Community College website ( http://www.league.org ). The documents describing policy for each of the 37 community colleges were generally available on the nveniently accessed through the League for Innovation in the Community College member page ( http://membership.league.org/allimembers.html ). State consortia policies were similarly available on consortium websites. State documents included statutes, administrative code, departmental directives, and strategy and financial documents. Statutes and administrative codes were readily accessed via Lexis/Nexis searches and search of state and institutional websites. Characteristics of the Sample Overview of the Community College System Community colleges were selected as the focus for this study because 59.3% of all undergraduate online education students in 2005 were at associates-granting institutions (Allen & Seaman, 2006). According to the American Association of Community Colleges (2007), the United States has 1,202 community colleges. January 2007 enrollment in U.S. community colleges totaled 11.6 million students (American Association of Community Colleges, 2007).

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70 Enrollment Characteristics of Institutions in the Sample As discussed in Chapter 3, Board Member colleges of the League for Innovation in the Community College were selected as a purposive sample for the study (Table 3-1). Table 3-2 depicts the enrollments at sample institutions and their Carnegie Foundation Classification. With the exception of Delta College, Michigan, all institutions in the sample met requirements for inclusion in the Carnegie Classification Very Large, Two-year (VL2 ). Institutions in this classification had enrollments of at least 10,000 students (Carnegie Foundation for the Advancement of Teaching, 2007). Delta College, with a smaller enrollment of 6,500 students, met the requirements for Carnegie Classification L2 (Large, Two-year). Institutions in this classification had enrollments between 5,000 and 9,999 students (Carnegie Foundation for the Advancement of Teaching, 2007). The total 2005 enrollment for the sample institutions was more than 843,000, a figure that represents approximately 7% of community college students. Community College Districts and Individual Institutions Of the 37 institutions sampled, 25 were associated with five community college districts. The districts were self-identified as such, and constituent institutions were named as colleges versus campuses. Individual institutions totaled 12. While some of the individual institutions had multiple campuses and had a larger enrollment than some of the sample districts (Table 3-2), the individual institutions were not classified as districts. For the purposes of this study, the institutions under district control were aggregated at district level. Since two-thirds of the institutions in the study were under district control, the researcher concluded that treating them as individual institutions would overstate the influence of district policies on the overall sample. Aggregating at district level resulted in a total of 17 individual institutions or districts in the sample.

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71 Analysis of Research Data Framework for Analysis The study focused on the written policy document as the unit of analysis. The three levels of analysis used were state, state consortium, and individual community college. Within states, the sub-levels of analysis were state statutes, state administrative codes, and department of education policy. At the consortium level, written policies and program guidelines were analyzed regarding distance education or distance learning. Within the individual community college, the levels of analysis were written policy and program guidelines. At all three levelsstate, consortium, and individual institutiononly written documents were analyzed. The study was therefore limited to document review and content analysis. No human subjects were involved. Analysis factors Frameworks for management and policy analysis of distance education courses are discussed in Chapter 2 (Gelman-Danley & Fetzner, 1998; King et al., 2000; Levy, 2003; Osika, 2006). These frameworks suggest several dimensions of analysis corresponding to distance education subsystems (Moore & Kearsley, 2005). The convergence of analytical elements found in various distance education policy analysis frameworks is discussed in Chapter 2. These elements were reduced to three factors of analysis: Management and Organization, Faculty, and Students (King et al., 2000). Table 3-3 depicts factors and levels of analysis adopted for the study. Data Analysis Protocols The documentary data were compared against a content analysis protocol, as described in this chapter (Table A-1). The content analysis protocol (McCullough, 2004) was developed based upon the policy analysis framework proposed by King et al. (2000) and the Interregional

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72 Guidelines for Electronically Offered Degree and Certificate Programs (Middle States Commission on Higher Education, 2002), as adopted by the six U.S. regional accreditation associations. To accomplish this comparison, the objective content of documents was determined by a serial progression of sampling, data coding, and analysis and interpretation using the policy analysis framework protocol as a guideline (Altheide, 1996). Table A-1 depicts the content analysis protocol for analyzing the content of sample documents. Documents found at each level were interpreted as having the PAF factor and coded with PAF factors with a numeral 1 allowed use of spreadsheet functions to calculate total numbers and percentages by factor and level for each of the PAF elements. Spreadsheet functions were also employed to array data to facilitate pattern analysis at each levelstate, consortium, institution. Document Coding Convention To facilitate identification of the documents included in the study, a document coding protocol was established (Creswell, 2005). Each state was assigned a capital letter designation (Arizona = A, California = B, and so on). The letters I, J, O, and Q were excluded to avoid confusion with numerals. State-level documents and state consortium documents were then encoded with the corresponding state letter (e.g., Arizona = A) and a number beginning with 100 (indicating a state-level document) and ending with two digits corresponding to the specific document. Institution-level documents were similarly coded with the first three digits corresponding to the specific institution. See Table 3-4 for the complete coding legend. Document codes were included in each state table following the format in Table 3-4. Since there were more than 300 individual documents were reviewed for the study, use of individual

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73 document codes facilitated the management of data arrays to a more convenient size. Table B-1 is a listing of the states, institutions, document codes, and specific documents addressed in the study. Assignment of Classifications to Policy Diffusion Once protocols in Appendix A were completed, the various data elements in each protocol were summed to create a total and a percentage. This created a set of tables that were used to discover patterns in the data at state, consortium, and institutional levels. The aggregate pattern data were also translated into a table where percentages of the occurrence of certain patterns at all three levels and for each factor were examined and classified as low (less than 34%), moderate (34%-68%), or high (greater than 68%) policy diffusion. Threats to Validity and Reliability The sample of Board Member institutions of the League for Innovation in the Community College (n=37) represents approximately 5% of the 800 members of that organization; however, the sample may not be reflective of the broader group of community colleges. For example, community colleges with limited enrollment may have highly limited distance education programs because of funding limitations. The findings therefore apply only to the institutions sampled. In addition, because of their interest in technology, all Board Member institutions of the League for Innovation in the Community College are also Alliance Advantage members. Alliance Advantage Members of the League may be inherently more interested in distance education when compared to regular members of the League or to nonmember institutions. This distinction could serve to bias the study. Institutions with a commitment to technology might skew the findings toward concluding that the level of diffusion of online distance education policy and practice is stronger than is actually the case.

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74 While the sample of states (n=15) represents 30% of the 50 states, it is possible that this sample overlooked states having either robust or limited distance education policies. To account for these potential limitations and thus increase validity (trustworthiness) of the analysis, the study sought to triangulate policies at state, consortium, and institutional levels (Glesne, 1999; Kirk & Miller, 1986). Purposive sampling also can be subject to three sampling errors (Hoepfl, 1997). These are distortions due to insufficient breadth of the sample, maturation, and shallow data collection for each site sampled. The study guarded against these three errors by sampling documents across a variety of institutions (breadth) and by examining complete documents (depth). Maturation, or changes in the sample over time, was addressed by taking the most current document available as the date of the sample. According to Altheide (1996), document reviews are subject to limitations to the retrievablility and access of the documents themselves. Bureaucracies, reproduction technologies, and cultural restrictions regarding the use and availability of key documents can of the Internet and other information technologies have made many institutional guidelines and state policies readily available. Since the documents for this study are public records, access restrictions are considerably fewer than if the documents were private (McCollough, 2004). Furthermore, purposive sampling of several states and community colleges reduced the impact of restricted access to documents by a single state or institution (Patton, 1990).

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75 Table 3-1. Sample states and institutions State Institution Arizona Maricopa Community College District Chandler Gilbert Community College Estrella Mountain Community College Gateway Community College Glendale Community College Mesa Community College Paradise Valley Community College Phoenix College Rio Salado College Scottsdale Community College South Mountain Community College California Foothill D e Anza Community College District De Anza College Foothill College San Diego Community College District San Diego City College San Diego Mesa College San Diego Miramar College Florida Santa Fe Community College Illinois Morane Valley Commu nity College Iowa Kirkwood Community College Kansas Johnson County Community College Maryland Anne Arundel Community College Michigan Delta College Missouri St. Louis Community College New York Monroe Community College North Carolina Central Piedmon t Community College Ohio Cuyahoga Community College Sinclair Community College Oregon Lane Community College Texas Dallas County Community Colleges Brookhaven College Cedar Valley College Eastfield College El Centro College Mountain Vie w College North Lake College Richland College Washington Seattle Community College District North Seattle Community College Seattle Central Community College South Seattle Community College

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76 Table 3-2. Populations and Carnegie classifications of sample community colleges Institution Institutional demographics Carnegie classification (Note 1) Source document identifier Maricopa Community College District, AZ 250000 + VL2 (Note 2) A11011 Foothill De Anza Community College District, CA 44000 VL2 B11003 San Diego Community College District, CA 47395 VL2 B12006 Santa Fe Community College, FL 15855 VL2 C11109 Moraine Valley Community College, IL 47000+ VL2 D11108 Kirkwood Community College, IA 15064 VL2 E11112 Johnson County Community Colle ge, KS 34000 + VL2 F11105 Anne Arundel Community College, MD 20920 VL2 G11106 Delta College, MI 6500 L2 (Note 3) H11104 St. Louis Community College, MO 27460 VL2 K11013 Monroe Community College, NY 11815 VL2 L11105 Central Piedmont Community College, NC 70000+ VL2 M11106 Cuyahoga Community College, OH 55000+ VL2 N11103 Sinclair Community College, OH 24000 VL2 N11208 Lane Community College, OR 36000 VL2 P11105 Dallas County Community Colleges, TX 84000 VL2 R11006 Seattle Community College District, WA 54000 + VL2 S11002 Note 1. The Carnegie Foundation for the Advancement of Teaching (2007). Note 2. VL2 classificationVery Large, Two-Yearis for institutions with fall enrollment data of at least 10, 000 at a 2-year institution. Note 3. L2Large, Two-yearclassification is for institutions with fall enrollment data of 5,000-9,999 at a 2-year institution.

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77 Table 3-3. Factors and levels of analysis. (Unit of analysis: A policy document) Factors Levels Management and organization Faculty Students State Statutes Administrative code Departmental regulations Other distance education documents State consortia policies and practices Institutional Policies and Practices Community college district or individual college Table 3-4. Document coding legend State State c odes State level and consortium codes Community college district codes Individual community college codes Individual document codes Arizona A 100 110 111 01 California B 100 110 112 02 Florida C 100 110 113 03 Il linois D 100 110 114 04 Iowa E 100 110 115 05 Kansas F 100 110 116 06 Maryland G 100 110 117 07 Michigan H 100 110 118 08 Missouri K 100 110 119 09 New York L 100 110 120 10 North Carolina M 100 110 121 11 Ohio N 100 110 122 12 Oregon P 100 110 12 3 13 Texas R 100 110 124 14 Washington S 100 110 125 15 Examples: A10001 First Arizona state-level document. B11001 First Foothill-De Anza Community College (CA) District document. B11101 First De Anza College (CA) document.

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78 CHAPTER 4 FINDINGS Introduction and Purpose The purpose of the study was to conduct a normative analysis of policy on technology-mediated distance education in community colleges at state, consortia, and institutional levels to understand the diffusion of policy concepts in this increasingly central medium. To accomplish the normative analysis, the study compared policy directives and program attributes at the state, consortia, and institutional levels to factors derived from policy analysis frameworks (PAF). The goal of the study was to determine the degree of diffusion of policy across the three levels. Policy and program attributes were also compared to acknowledged best practices. This chapter presents the findings from the comparisons of the content of policy documents and program directives to the policy analysis factors depicted in Table A-1. The complete dataset for this study is available by contacting the researcher at bob_amason@yahoo.com A pattern was identified in the data when the factor was exhibited by more than 50% of the sample (McCoy & Sorrenson, 2003). State-level Findings Fifteen state community college governance structures were represented in the sample. Community college state governance structures are summarized in Table 4-1. A pattern was & Sorensen, 2003). States in the sample exhibited few patterns when policy documents were compared to the policy analysis factors. Patterns in State Policy Elements Related to Management and Organization Policy Analysis Factors Patterns were identified in two of five Management and Organization PAF categories. Within the collaboration category a single pattern was observed in state-level policy guidance

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79 regarding the organization structure factor. Eight states exhibited a pattern of organizational structure which enables the development, coordination, support, and oversight of electronically offered programs California, Florida, Illinois, Kansas, New York, North Carolina, Ohio, and Texas. Within the resources category, patterns were identified in five factors: Budgets and policy statements reflect commitment to the students (8 states: CA, FL, IL, IA, KS, MI, NC, TX). Commitmentadministrative, financial, and technicalto continuation of the program for a period sufficient to enable all admitted students to complete a degree (8 states: CA, FL, IL, KS, MD, NY, NC, TX). Adequacy of technical and physical plant facilities (9 states: FL, IL, KS, MD, MI, NY, NC, TX, WA). Consistent and coherent technical framework (9 states: CA, IL, KS, MD, NY, NC, OH, TX, WA). Technology appropriate to students and curriculum (10 states: CA, IL, IA, KS, MD, NY, NC, OH, TX, WA). Additional state-level management and organization analysis Underlying elements of state-level distance education management and organization policy were examined to enhance the analysis and to clarify state-level policy. Documents analyzed included state statutes and administrative codes, strategy documents such as strategic plans, and funding documents such as budgets. Table 4-2 depicts a summary of state statutory guidance for Internet-mediated distance education. Statutes or administrative rules regarding Internet-mediated distance education were identified in seven states. Statutory guidance was identified in four categories: (a) access; (b) funding; (c) facilities and infrastructure; and (d) directives to create plans and/or policies governing Internet-mediated distance education. Only three states had statutes that addressed

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80 every category: California, Florida, and Kansas. States that addressed at least one, but not all, of these four categories were Arizona, Oregon, Texas, and Washington. Table 4-3 shows a summary of state-level distance education strategic guidance. Strategic guidance documentswith references to Internet-mediated distance educationwere identified in nine states and in the following four categories: (a) access; (b) student success; (c) enhancement of learning or quality enhancement; and (d) infrastructure. Strategic guidance documents that addressed each category were identified in five states: California, Florida, Maryland, North Carolina, and Washington. States addressing at least one strategic guidance category included Iowa, Kansas, Michigan, and New York. Table 4-4 presents a summary of state distance education funding guidance. Funding documents at state level identified policy regarding Internet-mediated distance education in six states and the following two PAF categories: (a) budget or other funding documents address distance education and (b) statutes address funding for distance education. Three states had funding guidance documents that addressed both categories: California, Florida, and North Carolina. States addressing one of the two categories were Illinois, Oregon, and Texas. The policy analysis factors related to tuition and funding formula were addressed by only three states: California, Illinois, and North Carolina (Document Identifiers: B10001, B10002, B10004, B10005, B10010, D10010, D11101, M10001, M10004). North Carolina employed an external consultant to review state funding for distance education and to recommend policy for such areas as tuition (Rogers, 2001). The consultant recommended against establishing a funding formula, citing the lack of development of the online delivery modality as impeding routine operations and rendering a formula ineffective (Rogers, 2001). A more detailed funding analysis of distance education at both state and institutional level is presented in Table 4-5.

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81 Potential relationship among state-level factors Patterns were observed when comparing the results of the state statutory, strategic, and funding policy analysis to factors in the two Management and Organization policy categories previously identified. Table 4-6 presents this finding in graphic format. States with documented statutory, strategic, and funding policies, which addressed Internet-mediated distance education, also spoke to many of the policy analysis factors. While only a few states had enacted legislation addressing distance learning in post-secondary education and/or published strategic guidance, the guidance was thematically consistent, as evidenced by selected statutory and strategic guidance statements presented in Tables 4-7 and 4-8. The statements illustratedamong states that had published such policythat a general state-level commitment existed to educational access, student success, educational quality, and infrastructure viability. These statements reinforced the potential for a relationship between legal and formal guidance documents, such as statutes, strategic plans and budgets, and management and resource decisions at the state level. Patterns in State Policy Elements Related to Faculty Policy Analysis Factors No patterns were identified, and documents expressing state-level policy regarding faculty were limited. No state-level policy documents were found regarding factors in two PAF categories. In the faculty rewards category, issues of faculty workload and compensation were considered in three policy analysis factors: stipends, promotion and tenure, and merit increases. Additionally, within the opportunities to learn about technology and new applications category, no documents were found that addressed the release time policy analysis factor.

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82 Patterns in State Policy Elements Related to Students and Participants Policy Analysis Factors No patterns were identified for the Students category at the state level; however, some documents indicated partial state-level policy regarding students. Documents having partial state-level student policy for distance education were identified in California, Illinois, Kansas, Maryland, New York, Texas, and Washington. These states were also observed to have elements of statutory, strategic, or funding guidance regarding Internet-mediated distance education. State Community College Distance Education Consortia Findings State Community College Distance Education Consortia Typology Research in virtual universities and consortia has been limited (McCoy & Sorensen, 2003), and the term consortium was used in the distance education literature and in policy documents to mean a variety of arrangements among collaborative partners (Wolf & Johnstone, 1999). For the purposes of this study, a virtual university/college consortium is a nondegree granting collaborative relationship among accredited institutions that are linked online (Wolf & Johnstone, 1999). All state consortia in this study met this definition. Table 4-9 is a listing of state distance education consortia for the sample states. Patterns in State Community College Distance Education Consortia State consortia policy elements and supporting document identification were organized into a table which was then used to discover patterns in the data. Because Arizona and Missouri did not have state distance educational consortia, the sample size for state consortia was 13. s disclosed the same policy characteristic (McCoy & Sorensen, 2003).

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83 Patterns in state consortium elements related to management and organization policy analysis factors Patterns were identified in three of five Management and Organization PAF categories. Within the collaboration category a single pattern was observed in policy guidance regarding the organization structure factor. Eight consortia exhibited a pattern of structure which enables the development, coordination, support, and oversight of electronically and Washington. Within the resources category, patterns were identified in four of six factors: Adequacy of technical and physical plant facilities (9 states: IA, MD, MI, NY, NC, OH, OR, TX, WA). Consistent and coherent technical framework (11 states: CA, IL, IA, MD, MI, NY, NC, OR, OH, TX, WA). Reasonable technical support (10 states: IL, IA, MD, MI, NY, NC, OR, OH, TX, WA). Technology appropriate to students and curriculum (11 states: CA, IL, IA, MD, MI, NY, NC, OR, OH, TX, WA). Within the curriculum and individual courses category, patterns were identified in 7 of 10 factors: Delivery modes (10 states: IL, IA, MD, MI, NY, NC, OH, OR, TX, WA). Course/program selection (8 states: IL, IA, MI, NY, NC, OH, TX, WA). Plans to develop curricula/individual courses (10 states: IL, IA, MD, MI, NY, NC, OH, OR, TX, WA). Individual sequences (11 states: CA, IL, IA, MD, MI, NY, NC, OH, OR, TX, WA). Course development (8 states: IL, IA, MI, NY, NC, OH, TX, WA). Entire program delivery (10 states: IL, IA, MD, MI, NY, NC, OH, OR, TX, WA). Interactivity requirements (10 states: IL, IA, MD, MI, NY, NC, OH, OR, TX, WA).

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84 Many of the consortia exhibited Web-based links that facilitated student search for entire courses, degrees, institutions, and course sequences. Patterns in state consortium elements related to faculty policy analysis factors Patterns were identified in three factors in the faculty support category: Student help (8 states: FL, IL, IA, MD, NY, OH, OR, TX). Technical assistance (9 states: FL, IL, IA, MD, NC, NY, OH, OR, TX). Training (9 states: FL, IL, IA, MD, NC, NY, OH, OR, TX). A preponderance of state-consortia appeared to have addressed faculty members support needs. Similar to the state-level analysis, state consortium level documents did not reveal references to faculty rewards, stipends, merit increases, and release time. Another area in which lack of patterning in the Faculty categories was illustrative was in the intellectual property factor. Only three state consortium documents (M10006, P10004, R10009) identified intellectual property considerations as a policy element. Patterns in state consortium elements related to students and participants policy analysis factors Within the Students and Participants PAF, patterns were identified in every support category. Because 12 factors are within this category, and patterns are supported by 10 to 11 state consortia, they are not individually identified here. States where no documents were found for these factors were Kansas and Ohio. Within the requirements and records category, a single pattern was identified for the residency requirements factor. Nine state consortia identified residency requirements for registration: California, Florida, Iowa, Michigan, New York, Ohio, Oregon, Texas, and Washington. All sample state distance education consortia practiced the distributed service model (Epper & Garn, 2004), and directed the student through the website to select and enroll in

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85 a home institution. Within the requirements and records category, no patterns were identified at the consortium level for factors associated with articulation and transfer. Institution-level Findings Characteristics of Institutions and Districts The sample for this study included 37 community colleges located in 15 states. As noted in Table 3-2, all but one of the institutions were classified by the Carnegie Foundation as Very Large Two-Year (Carnegie Foundation for the Advancement of Teaching, 2007). The sample was further characterized as having 12 independent institutions and 25 colleges that were part of five larger districts. As explained in Chapter 3, for the purposes of this study, the institutions under district control were aggregated at district level. Aggregating at district level resulted in a total of 17 individual institutions or districts in the sample (n=17). Institutional-level and district-level policy elements and supporting document identification were arranged in a table, and the resulting array was used to discover patterns in institutional policy. The pattern was identified when nine or more institution or district documents disclosed the same policy characteristic (McCoy & Sorensen, 2003). The institutional level was notable in that not only were patterns identified in 37 of the 50 policy analysis factors (74%), but in many cases the percentage of institutions exhibiting a particular factor was 100%. Specifically, all 15 of the policy analysis factors regarding students displayed patterns, with only 2 factors having fewer than 17 of 17 institutions represented.

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86 Patterns in institution or district elements related to management and organization policy analysis factors In the Management and Organization PAF, 17 of 24 (70.83%) policy analysis factors exhibited patterns. The patterns were discerned in all three of the five categories under Management and Organization. Within the collaboration category, five of seven factors exhibited institution-level patterns. internal organizational structure which enables the Community colleges or districts not exhibiting this factor were: San Diego Community College District, California Santa Fe Community College, Florida Delta College, Michigan St. Louis Community College, Missouri Monroe Community College, New York Results were similar for the following factors: Organizational units addressed in policy documents (11 institutions) Intended student population, curriculum, modes or venue of instruction (16 institutions) Articulation and transfer policies (15 institutions) Within the resources category, the following factors exhibited 100% policy concurrence: Adequacy of technical and physical plant facilities Consistent and coherent technical framework Reasonable technical support Technology appropriate to students and curriculum However, within the resources category, financial management factors of budget and commitment to program continuation were found at only five and seven institutions, respectively. These two policy elements were examined more closely and results are presented at Table 4-documents with mention of distance education were identified in only two institutions: Moraine

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87 Valley Community College, Illinois, and Delta College, Michigan. Exhibiting the confusing nature of technology-mediated distance education financing is the fact that technology spending at Moraine Valley spiked sharply from 2003 to 2005, while at Sinclair Community College, Ohio, funding for technology showed a net decrease in the same period. In the curriculum and individual courses category, one testing factor and the contact hours definition factor failed to exhibit patterns. The testing factor was examinations are employed (paper, online, demonstrations of competency) take place in circumstances that include firm was identified for only seven institutions. Similarly, a contact hour definition factor was identified in 4 of 17 institutions. The remaining factors in curriculum and individual courses were identified in documents at 16 or 17 institutions, depending upon the factor.. Patterns in institution or district elements related to faculty policy analysis factors Faculty support and training factors exhibited patterns in the Faculty PAF. Faculty support rovides orientation and training including strategies for effective were found in documents at 15 institutions. Factors associated with faculty training were found in 14 documents for chnical, design, and production support rovide training and supporta new technology factor was found in 11 documents. On the other hand, as with state-level and consortium-level findings, faculty rewards and release time were largely not identified at the institution level. Only three institutions identified stipend and release time policies, while only two institutions linked promotion and tenure or merit increases to distance education efforts. Similar to state and consortium level findings, copyright and intellectual property policies did not exhibit patterns at institutional levels.

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88 Patterns in institution or district elements related to students and participants policy analysis factors As mentioned previously, policy documents indicated patterns in 15 of 15 student-oriented policy analysis factors. Furthermore, 13 of the 15 factors had 100% institutional policy participation. Only 2 of the 15 student-oriented factors had patterns with fewer than 17 acceptance of courses from other places and transfer of credit, each of which had documented policy at 14 institutions. Institutional Strategic Guidance Analysis In addition to the institutional funding guidance analysis previously discussed and shown in Table 4-6, institutional strategic guidance was examined. Table 4-10 indicates that 10 of 17 institutions (58.8%) have published strategic guidance for distance education. Similar to the state-level strategic analysis, the identified themes were access to education, student success, enhancement of learning or quality, and infrastructure. Institutional strategic guidance was identified in seven states at institutions where the parent state also had state-level strategic guidance. Summary Table 4-11 presents a summary of the results of the study. In the Management and Organization factors, patterns were identified in the data that indicated policy existed at state, consortium, and institutional levels for organization structure and for resource management for technology-mediated distance education. None of the three levelsstate, consortium, institution evidenced patterns in tuition and funding formulas. Statutory, strategic guidance, or funding documents at state and institutional levels evidenced themes of educational access, student success, educational quality, and infrastructure viability. At consortium and institution levels, patterns were observed in many of the curriculum and individual courses factors.

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89 All state consortia in the sample met the definition of a virtual university/college consortium as a nondegree granting collaborative relationship among accredited institutions that are linked online (Wolf & Johnstone, 1999). These relationships met the definition of decentralized administration (Epper & Garn, 2004). Within community college districts, varying degrees of centralized management and administration of distance education were observed from distributed to highly centralized operations (Epper & Garn, 2004). All but one district, and all individual institutions, exhibited some degree of centralized control. Patterns were identified for faculty support (training and preparation) at consortium and institutional levels. At state and consortium levels, no documents were found regarding faculty rewards (stipends, promotion and tenure, and merit increases) and no release time was found to learn about new technology. At the institution level, few policies were found in the faculty rewards or release time factors. Another area where lack of patterning in the Faculty factors was the intellectual property factors. At all levels, only a few documents identified intellectual property considerations as a policy element. At consortium and institution levels, many patterns were identified in the data for the Students/Participants PAF with 100% of institutions documenting policies for several factors. Patterns at institutional level for Student factors indicated 100% matches for 13 of 15 factors. Two Student factors related to articulation and transfer exhibited patterns, but 3 of 17 institutions policies, the Students factor for intuitions would have reached unity.

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90 Table 4-1. Community college state-level governance structures State Policy making o rganization Arizona No centralized state level governance for community colleges California Board of Governors of the California Community Colleges Florida Stat e Board of Education and Florida Community College System (FLCCS) Illinois Board of Higher Education and Illinois Community College Board (ICCB) Iowa State Board of Education and locally elected boards of directors Kansas Kansas Board of Regents (KBOR) Maryland Maryland Higher Education Commission Michigan Michigan State Board of Education and Michigan Community College Association Missouri Missouri Coordinating Board for Higher Education New York Board of Trustees for City University of New York ( CUNY) or Board of Regents of State University of New York (SUNY) North Carolina North Carolina State Board of Community Colleges Ohio Under revision (Schmidt, 2007) Oregon Oregon Board of Education Texas Texas Higher Education Coordinating Board Washi ngton State Board for Community and Technical Colleges (Melear & Leas, 2006) Table 4-2. State statutory distance education guidance summary State Access Funding Facilities/ infrastructure Create plans/policies Document reference code AZ A10001 CA B10001 FL C10001 KS F10002 OR P10002 TX R10007 WA S10001 S10002

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91 Table 4-3. State-level distance education strategic guidance summary State Access Student success Enhance learning or quality Infrastructure D ocument reference code CA B10002 FL C10003 IA E10001 KS F10003, F10009 MD G10001 MI H10001 NY L10001, L10002 NC M10002 WA S10003, S10004 Table 4-4. State distance education funding analysis summary State Budget or other funding documents address distance education Statutes address funding for distance education Document reference code CA B10004, B10005 FL C11106 IL D10010 NC M10005 OR P10008 TX R10005

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92 Table 4-5. State and institutional distance education funding guidance summary State Distance education funding status Community college or district Distance education funding status Arizona 1 Maricopa 1 California 2, 4 Foothill De Anza 1 San Diego 3 F lorida 2, 5 Santa Fe 3 Illinois 2, 6, 7 Moraine Valley 2, 8 Iowa 1, 9 Kirkwood 3 Kansas 1 Johnson County 3 Maryland 1 Anne Arundel 3 Michigan 1 Delta 2, 10 Missouri 1 St Louis 3 New York 1, 11 Monroe 3, 11 North Carolina 2, 12 Central Piedmont 3 Ohio 1 Cuyahoga 3 Sinclair 1, 13 Oregon 2 Lane 1 Texas 2, 14 Dallas 3 Washington 1 Seattle 3 Note 1. Budget or other funding source documents indicate no mention of distance education, online, e-learning, or technology associated with distance education. Note 2. Budget or other funding source documents address distance education, online, e-learning or technology associated with distance education. Note 3. Budget document not identified. Note 4. California budget documents contained several mentions of distance education (Doc Id: B10004, B10005). Note 5-2008 budget for community colleges included $351,397 for the Florida Distance Learning Consortium. No other distance education funding line items were identified (Doc Id: C11106). Note 6Use educational technology and distance learning, as appropriate, to involve all the participants in the consortium more fully in the Note 7technology (Illinois State Budget, Fiscal Year 2008). No other references to distance education were identified (Doc Id: D10011). Note 8. Moraine Valley Community College expended funds in 2005-2006 to support growth of online classes. FYs 2003, 2004, 2005 showed a sharp spike in technology and equipment expenditures over previous and subsequent years. The expenditure on technology was not broken down into subcategories. Building and land/land improvement expenditures remained relatively steady (Moraine Valley Community College, 2006, Doc Id: D11109). Note 9. Institutions identified technology as an area of deep concern in narratives included in the Iowa Community Colleges Fiscal Year 2007 Certified Budgets (Division of Community Colleges and Workforce Preparation, 2006, Doc Id: E10004).

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93 Table 4-5. Continued Note 10. Delta College (MI) identified a total of $47,000 for distance education in the fiscal year 2006-2007 budget (Delta College, 2006, Doc Id: H11104). Note 11. Monroe Community College is part of State University of New York system. There is no mention of distance education programs in the operating budget for community colleges (State University of New York [SUNY], 2006, Doc Id: L10007). Note 12. North Carolina addresses distance education in the state budget (Blosser, 2007; Office of State Budget and Management, 2007, Doc Id: M10005) and has also conducted studies of funding for distance education (Rogers, 2003, Doc Id: M10004). Note 13. Sinclair Community College (2007) cost analysis indicated a net decrease in technology expenditure from 2002-2007 (Doc Id: N11207). Note 14. The Texas State Budget for Fiscal Years 2008-2009 (Office of the Governor, 2007, Doc Id: R10005) explicitly addresses distance education; however, the legislative overview of higher education finance in Texas does not contain references to distance education, e-learning or online education (Legislative Budget Board Staff, 2007, Doc Id: R10006). Table 4-6. Comparison among statutory, strategic and funding guidance and policy analysis factors States AZ CA FL IL IA KS MD MI NY NC OH OR TX WA Statutes Strategic Guidance Funding Guidance Collaboration: Internal organizational structure Resources Budgets Commitment to continue program Adequacy of technical and fiscal plant facilities Consistent and coherent technical framework Technology appropriate

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94 Table 4-7. Selected Examples of State Statutory Guidance State Statute Guidance Document reference code CA Legislative findings and declarations; Intersegmental working group; Guiding principles, 3 Cal Ed Code 66941 (2007) (f) In expanding the use of distance learning tech nology, the state should emphasize the delivery of education and training services to populations currently not receiving those services, the ease of access by educational institutions to the technology, and the lower cost over time of providing instructio n through distance learning rather than on site. (h) Assurance that the standards for course and program quality applied to distance education are rigorous in meeting accreditation standards, Universal Design Standards, and standards currently applied to traditional classroom instruction at higher educational institutions in the areas of course content, student achievement levels, and coherence of the curriculum. B10001 FL Distance learning duties, Fla. Stat. 1001.28 (2007) (1) Facilitate the implementa tion of a statewide coordinated system and resource system for cost efficient advanced telecommunications services and distance education which will increase overall student access to education. C10001 KS State Boards, Commissions and Authorities,74 K.S.A 74 3202c (2006) (9) Develop and implement a comprehensive plan for the utilization of distance learning technologies. F10002 OR ORS 759.445 (2006) 759.445. Connecting Oregon Communities Fund; School Technology Account; Public Access Account. P 10002 TX Subchapter e. Approval of distance education, off campus, and extension courses and programs for public institutions. 19 TAC 4.106 (2006) (a) Prior to offering any distance education, off campus, or on campus extension courses or programs for the first time, institutions of higher education shall submit an Institutional Report for Distance Education, and Off Campus and On Campus Extension Instruction to the Board for approval. (b) Institutional academic and administrative policies shall reflec t a commitment to maintain the quality of distance education, off campus, and on campus extension courses and programs in accordance with the provisions of this subchapter. R10007

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95 Table 4 7. Continued State Statute Guidance Document reference code WA K 20 educational network board Powers and duties, Rev. Code Wash. (ARCW) 43.105.805 (2007) Adopt, modify, and implement policies to facilitate network development, operation, and expansion. Such policies may include but need not be limited to the follow ing issues: Quality of educational services; access to the network by recognized organizations and accredited institutions that deliver educational programming, including public libraries; prioritization of programming within limited resources; prioritizat ion of access to the system and the sharing of technological advances; network security; identification and evaluation of emerging technologies for delivery of educational programs; future expansion or redirection of the system; network fee structures; and costs for the development and operation of the network. S10001

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96 Table 4-8. Selected examples of state strategic guidance State Document Title Guidance Document reference code CA California community colleges system strategic plan (2006). Expand and sustain an appropriate range of delivery methods to enhance access while maintaining and promoting high standards of academic rigor and excellence (p. 26). B10001 FL Florida Community College Strategic Plan (2005) Priority Goal 7: Expand Learning via Emerging Technologies Issue: Enhancing Learning Technologies Initiative 7.1 Create a statewide repository for reusable, high quality learning objects (digital and non digital) which can be used or referenced in learning environments. Initiative 7.3 Pursue s elected support services for students, educators, institutions, and DOE in support of distance learning. Initiative 7.4 Implement statewide equal access to enhanced electronic library resources and services. C10001 KS A plan for coordination of Kansas p ost secondary education (2000). Goal 3: The Kansas post secondary education system should seek to minimize barriers to access and facilitate institutional missions to encompass lifelong learning. In extending access, the Board seeks proposals that apply 2 1st century information technology solutions to F10009 NC Strategic plan for distance learning 2003 2004 through 2008 2009 for the North Carolina Community College System. An entire separate strategic p lan existed for distance education. Goal 2. Develop high quality, Web based degree programs for use by all colleges in the state (p. 10). M10002

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97 Table 4 8. Continued State Document Title Guidance Document reference code WA The cornerstones report: An educational technology strategic plan for the Instruction Commission (2005). Technology and distance education plan. Cornerstones: A. Access is our heritage. System wide themes: A1. Expand Distance Learning A2. Develop Statewide Portal B. Affordabili ty is our mandate. System wide theme: B1. Develop Statewide Purchasing Processes C. Learning environments are our specialty. System wide themes: C1. Develop Information Literacy Programs C2. Conduct Technology Training D. Infrastructure is our advantage. System wide theme: D1. Develop Online Resource Warehouses E. Quality is our trademark. System wide theme: E1. Determine Best Practices S10001

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98 Table 4-9. State-level distance learning consortia State Consortium n ame Uniform Resource Locator (URL) Ari zona None California Cali fornia Virtual Campus http://www.cvc.edu Florida Florida Distance Learning Consortium http://www.fdlc.org Illinois Illinois Community Colleges Online http://www.ilcco.net/ILCCO/index.cfm Iowa Community College Online Consortium http://www.iowacconline.org/ Kansas Kansas Digital Learning (KANDL) http://www.kansasregents.org/KANDL/inde x.html Maryland Marylandonline Statewide Intersegmental consortium. http://www.marylandonline.org/ Michigan Mich igan Community College Virtual Learning Collaborative http://vcampus.mccvlc.org/index.asp?dir='w elcome'&content Missouri None New York SUNY Learning Network http://sln.suny.edu/index.html North Carolina North Carolina Virtual learning community http://vlc.nccommunitycolleges.edu/ Ohio Ohio Learning Network http://www.oln.org/ Oregon Oregon Network for Education http://oregonone.org/ Texas Virtual College of Texas http://www.vct.org/ Washington Washington Online http://www.waol.org/home/default.asp

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99 Table 4-10. Institution-level distance education strategic guidance summary Institution and s tate Access Student s uccess Enhance learning or quality Infrastructure State level strategic guidance found Document reference code Maricopa CCD, AZ A11001 Foothill De A nza CCD, CA B11001, B12001, B12201, B12301 Moraine Valley CC, MI D11101, D11102 Kirkwood CC, IA E11101 Johnson Coun ty CC, KS F11101 Anne Arundel CC, MD G11101 Monroe CC, NY L11101 Central Piedmont CC, NC M11101 Cuyahoga CC, OH N11101 Sinclair CC, OH N11206 Table 4-11. Pattern synopsis by policy level and factor Fact or Management and o rganization Faculty Students Total patterns identified Factors o bserved % Factors o bserved % Factors o bserved % Factors o bserved % Total factors 24 11 15 50 Levels State level 6 25.00 0 0.00 0 0.00 6 12.00 State consortium 14 58.33 4 36.36 13 86.67 31 62.00 Institutional 17 70.83 5 45.45 15 100.00 37 74.00 Whole system totals and percentages 37 51.39 9 27.27 28 62.22 74 49.33

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100 CHAPTER 5 SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS Summary of the Study The purpose of this study was to conduct a normative analysis of policy on technology-mediated distance education in community colleges at state, consortia, and institutional levels to understand the diffusion of policy concepts in this increasingly central medium. To accomplish the normative analysis, the study compared policy directives and program attributes at the state, consortia, and institutional levels to factors derived from policy analysis frameworks (PAF). The goal of the study was to determine the degree of diffusion of policy across these three levels. Discussion of Findings Findings at all three levels provided insight into the state of policy at state, consortium, and institutional levels across the factors of Management and Organization, Faculty, and Students. Table 5-1 provides an overview of total patterns identified by level and factor. Beyond the patterns indicating existence of policy, instances occurred where absence of a pattern in the data may be seen as a pattern in itself. The findings are summarized and discussed below. Findings Regarding Policy Diffusion in Management and Organization, Finding 1: Relationship Between Formal Guidance Documents and Management Decisions Patterns in the PAF data were identified that indicated that policy existed at state, consortium, and institutional levels for organization structure and resource management for technology-mediated distance education. However, none of the three levelsstate, consortium, institutionevidenced patterns in factors for tuition and funding formulas. This absence of policy suggested a pattern in reverse. Themes of educational access, student success, educational quality, and infrastructure viability existed in statutory, strategic guidance, or funding documents at state and institutional levels. These findings suggested a relationship between statutes and formal guidance documents,

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101 such as strategic plans and budgets, and management and resource decisions for technology-mediated distance education at all levels. For higher education, the purposes for distance education have been in extending educational opportunities for new audiences to allow learner convenience or to foster economic development by expanding learning access (Perraton, 2003). The themes of educational access, student success, educational quality, and infrastructure viability identified in the study were indicative of the strategic nature of the state-level management of Internet-mediated distance education. The literature regarding distance education policy also identified access, economics, technology, and cost (Perraton, 2003). Community colleges in particular have been interested in distance education as a means for fostering access for continuous learning and also for promoting the concept of learning without limitations of -Mumford & Parke, 2000). Educational access was a finding in state statutes in this study for 100% of the states with statutes that addressed distance education (Table 4-2). Similarly, in states with strategic plans that addressed distance education, access to education was a theme in all but one (Table 4-3). Oregon Department of Community College and Workforce Development, 2005, p. 2). Technology (infrastructure) was an enabling element which provided opportunity to expand access and which merited investment (Perraton, 2003). In the same manner as the educational access theme, five of seven state statutes addressing distance education included infrastructure as a feature (Table 4-2). Similarly, infrastructure featured in five of nine state-level strategic plans addressed distance education (Table 4-3). Cornerstones Report identified both access and infrastructure as main goals (IC Planning Taskforce, 2005). North

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102 goals, respectively (Parker, McGraw, Williams, & Randall, 2004). The few examples of tuition and funding policy at all levels (particularly at state level) contributed to confusion in this area. Documents in only three states addressed tuition, fees, and funding formulae. However, this nonpattern was difficult to interpret since seven states (at least briefly) mentioned distance education in their budget or other community college funding documents. A North Carolina management analysis specifically recommended against a funding formula for distance education (Rogers, 2001). It was therefore impossible to arrive at a conclusion regarding the status of Management and Organization policy regarding tuition and fees or funding formulas. With the advent of online learning, the environment for community colleges became more complex and three-dimensional (McCain & Jukes, 2001; Foster, 2004). The confluence of state-level community college governance structures, consortia, individual institutions, community college districts, regional accreditation organizations, and many more policy actors has created a system that requires management (Pacey & Keough, 2003). Strategic planning, as a discipline, moved from a bias for formulation to a bias for implementation (Dooris, Kelley, & Trainer, 2002). Therefore, the findings in Chapter 4 regarding state-level convergence of statutes, strategy, and funding guidance indicated that states with high policy diffusion in Management and Organization factors in Internet-mediated distance education also have strong statutory and strategic guidance (Table 4-6). Findings Regarding Policy Diffusion in Management and Organization, Finding 2: Relationship Between Accreditation Guidelines and Curriculum and Individual Courses Policy At consortium and institution levels, many patterns were observed in the curriculum and individual courses category. Many of the PAF factors for this study were derived from the

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103 Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Higher Learning Commission, 2002). Therefore, a possible relationship existed between accreditation standards and institutional distance education policy regarding curriculum and individual courses. The policy analysis frameworks (PAF) proposed by a variety of researchers were largely focused on institution level factors (Berge, 1998; Gelman-Danley & Fetzner, 1998; King et al., 2000; Levy, 2003; Osika, 2006). Curriculum and instruction factors were features of all these PAF. Moreover, quality benchmarks (Phipps & Merisotis, 2000) and the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Higher Education Commission, 2002) also featured curriculum and instruction factors for evaluation. The second component of the Interregional Guidelines is Curriculum and Instruction. This factor held that critical issues were not technological but were curriculumand pedagogy-oriented (Middle States Commission on Higher Education, 2002). Since the Interregional Guidelines represented accreditation standards for Internet-mediated distance educationand promulgated by all six regional accreditation associations, they had the force of evaluation documents for institutions (Lezberg, 2003). Numerous authors on organizational performance management identified a strong correlation between evaluation measures and organizational behavior (Brown, 1996; Kaplan & Norton, 1996; Pfeffer & Sutton, 2006). Therefore, the focus of institutions and consortia on curriculum and instruction may be viewed as an anticipated response to the literature on the subject, as well as accreditation standards. Finding 2 indicated that state-level policy does not often mention curriculum and instruction. Similar to Findings 1 and 6, that fact suggested that state-level policy was less

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104 focused upon actual operations and more on overarching guidance, such as educational access, student success, educational quality, and infrastructure viability. Proximity to the student appeared to be one driver of policy diffusion. Table 5-1 summarizes policy diffusion by level and by factor. Figure 5-1 graphically depicts the same policy diffusion. Taken together, Table 5-1 and Figure 5-1 demonstrate that state-level policy was less focused on specifics of students, faculty, and educational delivery. Institutions were on the opposite end of the policy spectrum with much greater focus on student and faculty factors. Findings Regarding Faculty, Finding 3: Relationship Between Faculty Support and Quality Patterns were identified for faculty support (training and preparation) at consortium and institutional levels. Administrators were concerned about quality of online education, and faculty members asked for training on student interaction and technical matters (Lezberg, 2003). This finding therefore suggested a high level of policy diffusion in faculty training and instructional quality in technology-mediated distance education. Findings Regarding Faculty, Finding 4: Relationship Between Faculty Workload Management and Faculty Willingness to Engage in Distance Education At state and consortium levels, no documents were found regarding faculty rewards (stipends, promotion and tenure, and merit increases) or faculty release time to learn about new technology. At the institution level, only a few policies were found in the faculty rewards or release time factors. Faculty members were reluctant to adopt Internet-mediated distance education (Allen & Seaman, 2006). This finding therefore suggested a relationship between policy regarding faculty workload management and rewards and faculty willingness to engage in online education.

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105 Findings Regarding Faculty, Finding 5: Relationship Between Intellectual Property Considerations and Faculty Reluctance to Adapt Courses to the Online Modality Another area that showed lack of patterning was illustrative was the intellectual property factors. At all levels, only a few documents identified intellectual property considerations as a policy element. Copyright and intellectual property rights were important to the faculty (Berge, 1998; Lipinski, 2003; Wilson, 1998; Wolcott, 2003), and this finding suggested a lack of policy diffusion regarding intellectual property considerations and faculty adaptation of courses to the online modality (Allen & Seaman, 2006). Discussion of Findings 3, 4, and 5. In 1950, Isadore Rabi of Columbia University publicly explained to then-Columbia tlines a key facet of educational delivery in the post-industrial, online distance education environment: The faculty are critical elements for success. Despite increasing acceptance of distance education and distance education technologies applied in more traditional settings, some educators have expressed skepticism regarding nontraditional offerings (Allen & Seaman, 2006; Carnevale, 2007; Fogg, 2005). While several studies have indicated value in online education (Lou et al., 2006), faculty members saw less value in deviating from traditional delivery methods (Allen & Seaman, 2006; Levin, 2001). For the change from traditional education to Internet-mediated education to fully succeed, all policy actors must be aligned (Kaplan & Norton, 2006; Pacey & Keough, 2003; Thousand & Villa, 2005). Furthermore, the Interregional Guidelines for Electronically Delivered Degrees and Certificates (Middle States Commission on Higher Education, 2002) identified faculty as one of five components in accreditation considerations. Since faculty members had numerous concerns regarding distance educationtraining, rewards and incentives, and legal issues

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106 regarding intellectual property rightspolicy was required to assure them that they will be equipped to do the job and rewarded for doing it (Dalziel, 2003). contributions are not considered in tenure and promotion decisions many faculty members Furthermore, Howell, Williams and Lindsay (2003) reported that a 2000 National Education Association survey had found the top concern of distance education faculty to be added workload with no increase in compensation. As an example of faculty concern regarding adequate rewards and incentives, in a 2006 resolution, Foothill-institution to set aside funds to compensate faculty members for attending distance education training (Faculty Senate, 2006). Several researchers observed a clash of cultures within academia based upon conflicting value structures that reflect the functional views of faculty, administrators, and technology managers (Bergquist, 1992; Birnbaum, 1991; Saba, 2005). Saba (2005) made three observations: (a) faculty exist in a premodern craft culture focused on freedom and autonomy; (b) administrators inhabit a modern culture demanding efficiency and cost consciousness; and (c) distance education occupies a post-modern information technology culture. Aligning such diverse educational cultures in support of a radical change to new educational approaches requires a robust change model that addresses a variety of perspectives (Thousand & Villa, 2005). One change model takes into consideration the need for training (skills), resources (technology and infrastructure), and incentives (rewards) (Thousand & Villa, 2005). Despite resistance based upon these factors, faculty roles are shifting from the traditional craft structure (Saba, 2005), and many of their duties are being assumed by others, such as professional course

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107 designers, resulting in job security concerns among faculty members (Howell, Williams, & Lindsay, 2003). The need for faculty training was increasing (Howell, Williams, & Lindsay, 2003). Faculty members were concerned that adequate training would not be forthcoming and that working conditions might be affected as the shift in teaching roles continued (Berge, 1998; Dalziel, 2003; Pittman, 2003; Wilson, 1998). The study identified patterns in faculty training at consortia and institutional levels. Several sample institutions had training programs that appeared extensive with both academic preparation training opportunities, as well as faculty mentorships to assist new online faculty in succeeding. Examples of institutional faculty training include Mesa Community College, Arizona, Foothill-De Anza College, California, and Moraine Valley Community College, Illinois. Mesa College had a training program that covered numerous Web pages and provided outside links to additional training sources. A Mesa College faculty member created an overview of distance education for faculty members. The overview was organized by several topics, including quality in distance learning; assessment; concerns; characteristics and standards (DeSoto, 2003). Numerous active links were provided. Foothill-De Anza College had an extensive faculty center for distance education training and assistance. Foothill Global Access covered the same topics as Mesa but added technical and course design assistance (Foothill-De Anza College, 2007). practices in e-learning, as well as faculty development online resources (Moraine Valley Community College, 2007). Findings of the study indicated almost no policy documents regarding faculty rewards, yet earlier studies indicated that faculty workloads and compensation were important to the success

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108 of distance education implementation (Hardy & Bower, 2004). Organizational change models indicated that efforts to engender new approaches encounter only gradual change when incentives are not included (Thousand & Villa, 2005). Other change experts recommended creating a guiding coalition to engender new approaches (Kotter, 1996). To create a willing coalition across diverse institutional cultures, incentives were needed in addition to training for faculty. The PAFs used in the study included rewards factors in the form of stipends, promotion and tenure, merit increases and release time. Since patterns were not identified for any of these factors, the adoption of e-learning may be gradual within institutions and coalitions among administrators, and faculty may be uneasy about these workload changes. Faculty members have also been concerned regarding intellectual property rights (Dalziel, 2003; Lipinzki, 2003; Wolcott, 2003), yet no patterns were identified in the study to indicate policy diffusion for this factor. With regard to faculty and institutional ownership issues, the law appears largely settled on the concept that materials created while in the employ of a college are the property of the college (Lipinski, 2003). However, use of copyrighted material in the distance education environment continues to encounter challenges that frustrate faculty members (Hardy & Bower, 2004; Lipinski, 2003). Despite the fact that intellectual property issues are complex, limited state-level, consortium, and institutional policy on such issues is likely to operate as a barrier to faculty willingness to adapt to online teaching (Lipinski, 2003; Wolcott, 2003). Findings Regarding Students, Finding 6: Relationship Between Accreditation and Institutional Distance Education Policy At consortium and institution levels, many patterns were identified in the data for the Students/Participants PAF with 100% of institutions documenting policies for several factors. Many of the PAF factors were derived from the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher

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109 Education, 2002). Since the Interregional Guidelines document is an accreditation standard that cuts across all higher education institutions, the apparent high rate of policy diffusion in the Students and Participants category suggested a relationship between accreditation and institutional distance education policy regarding students. Distance education grew at an annual rate of more than 18% from 2002 to 2006 (Allen & Seaman, 2006). Two-year institutions such as community colleges enrolled proportionately more students than other higher education institutions (Allen & Seaman, 2006). Students as consumers are demanding more flexibility and ease of access, and these demands have increased the use of technology-driven applicationsa euphemism for online education (Levin, 2001). The high level of policy diffusion for student support at institutional levels indicated that 2-year institutions acknowledged student demands and market place realities. Knowledgeable higher education leaders remarked upon the shift of universities into the marketplace, and they commented upon the requirement for higher education institutions to serve the needs of students in innovative, responsive ways (Bok, 2003; Duderstadt, 2000). Others commented on student behavior that reduced physical campus visits to near zero for many (Floyd & Casey-Powell, 2004). Therefore, student support for success was a critical component of online education in responding to the rapidly shifting technological landscape of the current and future post-secondary education arena. The fourth component of the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher Education, 2002) is Student Support. This component acknowledges that the 21st century student is different from Institutions therefore may be expected to focus on students (Floyd & Casey-Powell, 2004).

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110 Furthermore, since the Interregional Guidelines represented accreditation standards for Internet-mediated distance education and were promulgated by all six regional accreditation associations, they have the force of evaluation documents for institutions (Lezberg, 2003). As previously discussed, numerous authors on organizational performance management identified a strong correlation between evaluation measures and organizational behavior (Brown, 1996; Kaplan & Norton, 1996; Pfeffer & Sutton, 2006)an anticipated response. Conclusions The findings in this study suggested overall moderate diffusion of policy for Internet-mediated distance education in community colleges. A review of Table 5-1 indicates a moderate degree of overall policy diffusion across all levels for the entire 15-state sample. Overall policy diffusion in Management and Organization factors was moderate. Overall policy diffusion in Students and Participants factors was also moderate. Driven by extremely limited findings of faculty rewards and incentives, overall policy diffusion for the Faculty factors was low. By levels, overall policy diffusion at state level was low, with the Management and Organization factor the only state-level contributor. At the consortium level, moderate policy diffusion was observed with all factors contributing and with the Students/Participants policy diffusion observed as high. Institutional-level policy diffusion was high, with only the Faculty factor observed as moderate. While an overall moderate level of policy diffusion was observed, a clear overarching pattern of greater policy diffusion was observed as the level of analysis became closer to the student. Policy diffusion was therefore propostudents. Institutions directly serve the student and were much more likely than other levels to have more complete Internet-mediated distance learning policy. Furthermore, the study disclosed

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111 institutional-level student policy to be near unity, confirming this conclusion. Finally, this conclusion is congruent with other study findings and conclusions that state-level policy was focused on educational access and other high-level policy concerns, such as infrastructure, than on students. Figure 5-1 depicts this relationship in graphic form. Conclusions Regarding Management and Organization Factors (Moderate Policy Diffusion) These findings suggested a moderate degree of diffusion of policy in the form of statutory and formal guidance documents, such as strategic plans and budgets, and management and resource decisions for technology-mediated distance education at all three levels: state, consortium, and institution. States with well-developed statutory, strategic, and funding guidance also had more policy diffusion at other levels. Regarding policies on curriculum and individual courses, institutions and consortia were focused on the accreditation standards illustrated in the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher Education, 2002). This apparent relationship between accreditation and institutional distance education policy supported a conclusion of moderate to high policy diffusion in the Management and Organization category at consortia and institutions. In this case, the proximity of consortia and institutions to students may be seen as a variable favoring policy diffusion. All state consortia in the sample met the definition of a virtual university/college consortium as a nondegree granting collaborative relationship among accredited institutions that are linked online (Wolf & Johnstone, 1999). This finding suggested policy convergence at the consortium level (King & Mori, 2007). As discussed in Chapter 2, policy convergence occurs when many policy actors adopt the same approach to managing the same phenomenon.

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112 All but one district and all individual institutions exhibited some degree of centralized control. This finding suggested policy convergence on the centralized model of distance education administration (Epper & Garn, 2004). Conclusions Regarding Faculty Factors (Low Policy Diffusion) Patterns were identified for faculty support (training and preparation) at consortium and institutional levels. This finding therefore suggested a high level of policy diffusion in faculty training and instructional quality in technology-mediated distance education at consortium and institutional levels. Since faculty serve at institutions, this finding is congruent with other findings regarding increased policy diffusion with proximity to students. At state and consortium levels, no documents were found regarding faculty rewards (stipends, promotion and tenure, and merit increases) or faculty release time to learn about new technology. At the institution level, few policies were found in the faculty rewards or release time factors. Moreover, a lack of policy diffusion regarding intellectual property considerations and faculty adaptation of courses to the online modality was observed across all levels. Faculty members were reluctant to adopt Internet-mediated distance education (Allen & Seaman, 2006). This finding therefore suggested a relationship between state policy regarding faculty workload management, rewards and intellectual property considerations, and faculty willingness to engage in online education. Conclusions Regarding Student/Participant Factors (High Policy Diffusion) At consortium and institution levels, many patterns were identified in the data for the Students and Participants PAF with 100% of institutions documenting policies for several factors. Many of the PAF factors were derived from the Interregional Guidelines for Electronically Offered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher Education, 2002). Institutions may be expected to comply with accreditation criteria

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113 as measures of their performance (Brown, 1996; Kaplan & Norton, 1996; Lezberg, 2003; Pfeffer & Sutton, 2006). These findings and conclusions are congruent with the conclusion that Internet-mediated distance education policy diffusion was proportional to the level of analysis proximity to the student (Figure 5-1). Analysis of Policy Transfer Mechanisms As discussed in Chapter 2, coercion was held to be the fastest mechanism for policy diffusion (Rogers, 2003). Two types of coercion have been postulated: direct coercion and indirect coercive transfer (Dolowitz & Marsh, 1996). Regional accreditation standards are powerful forces for compliance for institutions, and failure to comply with accreditation guidelines may result in sanctions to institutions. Little doubt therefore occurs that the high diffusion of most policies at institutions is in direct response to perceived direct coercion. On the other hand, state-level distance education policy actors are not likely to feel coercion either directly or indirectly. At state-level, policy transfer is much more likely to be voluntary in response to some perceived need (Dolowitz & Marsh, 1996; Knill, 2005; Rogers, 2003). Communication among various social system elementsin this case perhaps state directors of community collegesmight lead to emulation and voluntary adoption (Rogers, 2003). The perceived need for policy, the relative advantage of the policy itself, strength of interstate communications, time and (Rogers, 2003). Since voluntary adoption is the slowest policy transfer mechanism, the findings of low diffusion at state-level are consistent with theory (Rogers, 2003). Since state-level Internet-mediated distance education policy actors are not subject to coercion by regional accreditation associations, the adoption of policy may remain at a slow pace (Dolowitz & Marsh, 1996; Knill, 2005; Rogers, 2003). The prevailing state cultural norms

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114 regarding oversight of institutions may act as facilitators or as impediments, depending upon the state (Rogers, 2003). If the federal government adopts a more overarching set of policies for Would a centralized system, either at federal or state-level, enhance student educational success in distance education? The question is difficult at best and merits further study. This study observed state-level strategic guidance to be centered on educational access, student success, and infrastructure. While educational access, student success and infrastructure are not necessarily competing goals (infrastructure fosters access, for example) the focus at federal and state levels would be less on the student and more on structure. Policy diffusion in this study was proportional to student proximity, and regional accreditation guidelines are already coercive in nature. Would a state-level or federal-level set of policies therefore decrease institutional flexibility and ultimately reduce the quality of student outcomes? Furthermore, the availability of Internet-mediated distance education has fostered a much more open market for higher education (Lezburg, 2003). Would federal oversight and guidance serve to stifle competition? On the other hand, such oversight may result in enhanced consistency which would respond to quality concerns (Allen & Seaman, 2006; Carnevale, 2007; Fogg, 2007). Suggested Typology for State Community College Distance Education Consortia Research in virtual universities and consortia has been limited (McCoy & Sorensen, 2003), and the term consortium has been used in distance education literature and in policy documents to mean a variety of arrangements among collaborative partners (Wolf & Johnstone, 1999). For the purposes of this study, a virtual university/college consortium is a nondegree granting collaborative relationship among accredited institutions that are linked online (Wolf & Johnstone, 1999).

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115 All state consortia in the sample met the definition of a virtual university/college consortium (Wolf & Johnstone, 1999). However, the existing typologies for technology-mediated distance education consortia did not identify state-level relationships among distance education entities. Four such relationships were identified, and a new typology for state consortia was proposed. Four types of distance education relationships were identified in the sample state community college distance education consortia. Table 5-2 suggests classifying online consortia Type I relationship indicates no state-level community college distance education consortium. Type II consortia are community-college specific, and Type III are intersegmental consortia, providing services across all educational levels, including primary and secondary schools. A Type IV relationship represents a virtual university with community college linkages, but no primary or secondary education institutions are represented. Table 5-2 classifies sample state consortia according to the suggested typology. Suggested Typology for Institution and District-Level Distance Education Relationships Within community college districts, varying degrees of centralized management and administration of distance education were observed from distributed to highly centralized operations (Epper & Garn, 2004). All but one district and all individual institutions exhibited some degree of centralized control. A typology was proposed to describe the various within-district distance education relationships. Four types of distance education relationships were identified at the institutional and district levels. These relationships are described in the typology in Table 5-3. The typology was arranged to represent the levels of centralized control of distance education with Type I representing no district control (distributed) and Type IV representing highly centralized district

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116 control of distance education programs (centralized). In centralized control models, the district provided both administrative and academic services. In distributed distance education models, the district hosted an online catalog and perhaps provided a portal for student entry, but individual institutions offered the service (Epper & Garn, 2004). These four types of distance education relations include: Individual community colleges not contained within a district are identified as Type I distance education institutions. Twelve sample institutions met Type I criteria. Type II distance education institutions report to districts but appear to exercise autonomy in administration of distance education programs. One sample district met Type II criteria. Type III distance education institutions report to a community college district and share distance education courses in a collaborative or consortium-type arrangement that results in distributed services (Epper & Garn, 2004). Two sample districts met Type III criteria. Type IV distance education institutions report to a community college district where distance education is managed in a centralized manner (Epper & Garn, 2004). Two sample districts met Type IV criteria. Implications for Practice States with strategic plans that addressed distance education appeared to have more policy diffusion at all levels. Therefore, state directors of community colleges may find it useful to include online education as a feature of existing strategic plans or to create independent strategic plans for distance education. State directors of community colleges may also find it useful to discuss voluntary adoption of successful policies from neighboring states, or they can at least open additional channels of communication to allow opportunities for policy transfer (Dolowitz & Marsh, 1996; Knill, 2005; Rogers, 2003). Policy diffusion among factors regarding faculty was overall low, and this condition was largely driven by nearly zero findings of policy documentation regarding faculty rewards. Since faculty members were slow adopters of Internet-mediated distance education (Allen & Seaman,

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117 2006), administrators may find it useful to identify suitable rewards for faculty to encourage professors to engage in online education. With regard to the typologies of centralization of distance education, several institutions in the study had developed highly centralized management of distance education efforts. These institutions were classified as Type III and IV Distance Education Institutions. This approach is more in keeping with the theories of industrialization of distance education (Peters, 2003), and is useful in serving increasing numbers of online students (Allen & Seaman, 2006). Does such centralization benefit the student? Theories of interaction and communication (Moore & Kearsley, 2005) suggest high levels of faculty-student contact, which may be more compatible with decentralized models, as identified in Type 1 and II Distance Education Institutions. middle ground to administrators seeking a balance between low-cost and efficiency on the one hand and high social construction of knowledge opportunities on the other (Gunawardena & McIssac, 2004; Saba, 2003; Shaffer, 2005). Administrators may find it useful to evaluate distance education structures in light of the proposed typologies and these theories. Issues for Further Study State-level Policy Analysis Framework Policy analysis frameworks (PAF), proposed by a variety of authors, have elements that appeared to be focused at institutional level (Berge, 1998; Gelman-Danley & Fetzner, 1998; King et al., 2000; Levy, 2003; Osika, 2006). While one PAF (Levy, 2003) included mission and vision elements, findings in this study suggested that strategic factors of educational access, student success, educational quality, and infrastructure have a larger place in PAF for Internet-mediated distance education. A more complete study of strategy and implementation in the online education environment would shed light on the viability of these two elements as factors

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118 for wider policy analysis, and perhaps set the stage for more complete PAF that include statutory and strategic guidance as factors. State Consortia Structures This study identified four types of state-level consortium structure within the prevalent virtual university or consortium arrangements found in the sample (Epper & Garn, 2004). These types of structures were classified along the lines of community college identity. Analysts may find it useful to complete a study of state-consortia to show the extent of policy convergence for governance structures identified in the proposed typology for state community college distance education consortia. Institutional-level Distance Education Governance Structures This study identified four types of relationships at institution or district level. Proposed types were characterized by more centralized or less centralized control of distance education activities. Analysts may find utility in a study of institutional-level governance to classify the extent of policy convergence in district-level governance with regard to the proposed typology for institutions. Given increasing enrollments in distance education at community colleges, should institutions migrate more toward centralized management models? Tuition, Fees, and Funding Formulas The few examples of tuition and funding policy at all levels (particularly at state-level) suggested a need for further study. Few documents were identified at each level, but this nonpattern was inconsistent with brief mentions of distance education in budget or other community college fuspecifically recommended against a funding formula (Rogers, 2001). Additional study of community college distance education funding structures and budgets appears warranted.

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119 Faculty Rewards and Workload Policy The findings in this study suggested limited consideration at all levels for faculty workload management, compensation, and related factors such as release time. Analysts may wish to study community college faculty attitudes and distance education workload policies in more detail to understand the implications for adoption and success of Internet-mediated distance education in the wider community college system. Additionally, study of faculty attitudes toward distance education workloads may be helpful to administrators and faculty as they negotiate collective bargaining agreements. For example, future studies might examine which rewards and workload accommodations are most valued by faculty members, and the results of such a study could set the stage for productive negotiations between the parties. Should the United States Adopt National Policy for Internet-mediated Distance Education? This study examined policy at state, consortia and institutional levels through the lens of a policy analysis framework developed from regional accreditation guidelines. Lezburg (2003) observed that a de facto national standard for distance education existed in the form of the Interregional Guidelines for Electronically Delivered Degree and Certificate Programs (2nd ed.) (Middle States Commission on Higher Education, 2002). A study of national-level policy would answer the question: Is it in the best interest of the United States to go beyond the regional national-level policy regarding Internet-mediated distance education? Such a study would reveal the level of policy guidance on online education at a level above the ones analyzed in this study and would complete the picture of the policy system associated with U.S. distance education (Pacey & Keough, 2003). Such a study would also respond to several questions posed earlier regarding viability and desirability of more overarching policy.

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120 Conclusion The complex nature of Internet-mediated distance learning has burst upon the scene of higher education, particularly among community colleges (Allen & Seaman, 2006). Internet-mediated distance education was multi-dimensional (McCain & Jukes, 2001), and was characterized by a delivery system that emphasized anytime, anywhere learning as a feature In this study, policy diffusion was observed to be proportional to student proximity. The closer the institution was to the student, the more likely it was to have policy documents regarding Internet-mediated distance education. Moreover, institutional-level policy diffusion for students was near unity, suggesting that Internet-mediated distance education was moving toward a level of consistency among institutions. However, faculty rewards were largely ignored at all levels, with overall low policy diffusion in the faculty factors. This may be interpreted as setting the stage for faculty resistance to more complete implementation of Internet-mediated distance education (Allen & Seaman, 2006). States and institutions may find it advantageous to create more faculty rewards for engaging in teaching online. State-level guidance was not consistent across states, and low policy diffusion across all factors was observed at state level. Since state-level policy actors were furthest from students, this finding reinforced the conclusion that policy diffusion was proportional to student proximity. This finding suggested that state directors of community colleges may need to reexamine statutory, strategic, and funding guidance to encourage more complete oversight of educational access, student success, infrastructure, and planning for Internet-mediated distance education.

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121 Figure 5-1. Policy diffusion by level and factor

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122 Table 5-1. Policy diffusion by level and factor Factors Management and o rganization (24 total factors) Faculty (11 total factors) Students/Participant (15 total factors) Total patte rns identified (50 total factors) Level Factors o bserved % Policy d iffusion Factors o bserved % Policy d iffusion Factors o bserved % Policy d iffusion Factors o bserved % Policy d iffusion State level 6 25.00 Low 0 0.00 Low 0 0.00 Low 6 12.00 Low State conso rtium 14 58.33 Mod 4 36.36 Mod 13 86.67 High 31 62.00 Mod Institutional 17 70.83 High 5 45.45 Mod 15 100.00 High 37 74.00 High Whole System Totals and Percentages 37 51.39 Mod 9 27.27 Low 28 62.22 Mod 74 49.33 Mod Policy Diffusion Legend: Low: < 34% Moderate: 34 68% High: > 68%

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123 123 Table 5-2. State community college online distance education consortia typology Type Description States Total I No distance learning consortium Arizona, Missouri 2 II Community college specific consortium C alifornia, Iowa, Michigan, North Carolina, Texas 5 III Intersegmental university/community college consortium Florida, Illinois, Kansas, Maryland, Ohio, Oregon, Washington 7 IV State university with community college links New York 1 Total State Conso rtia 15 Table 5-3. Institution and district distance education typology Type Description Institutions Total in each category I Individual institution, no district. Santa Fe CC, FL Moraine Valley CC, IL Kirkwood CC, IA Johnson County CC, KS Anne Arundel CC, MD Delta College, MI St Louis CC, MO Monroe CC, NY Central Piedmont CC, NC Cuyahoga CC, OH Sinclair CC, OH Lane Community College, OR 12 II Central community college district, but institutions have distance education autonom y Foothill De Anza CCD (CA) 1 III District consortium arrangement distributed services (Epper & Garn, 2004 ) Maricopa CCD, AZ (1), Seattle CCD, WA 2 IV Central community college district with centralized distance education (Epper & Garn, 2004) San Dieg o CCD, CA; Dallas CCD, TX 2

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124 124 APPENDIX A ANALYSIS PROTOCOL

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125 Table A-1. Content analysis protocol State _______________ Consortium______________ Institution___________________ PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Con sortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Document Codes Institution Institution Document Codes Remark Management and Organization Tuition and fee structure N/A Addressed Funding formula N/A Addressed Collaboration With other Departments 1e Internal organizational structure which enables the development, coordination, support, and oversight of electronically offered programs. Units N/A Organizational units addressed in policy documents. Institutions 1a Program is consistent role and mission.

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Table A-1. Continued 126 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Cons ortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Document Codes Institution Institution Document Codes Remark Institutions 1b Intended student population, curriculum, modes or venue of instruction. Intra and inter institutional 1f Articulation and transfer policies. Service areas 1j Legal and regulatory requirements of the jurisdictions in which [the institution] operates. Resources Financial re sources to support distance education 1c Budgets and policy statements reflect commitment to the students. Financial resources to support distance education 4a Commitment administrative, financial, and technical to continuation of the progra m for a period sufficient to enable all admitted students to complete a degree. Equipment 1d Adequacy of technical and physical plant facilities.

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Table A-1. Continued 127 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Cons ortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Document Codes Institution Institution Document Codes Remark New technologies 1g Consistent and coherent technical framework. New technologies 1h Reasonable technical support. New technologies 1i Technology appropriate to students and curriculum. Curricula/ individual courses Delivery modes 2e Appropriate interaction (synchronous or asynchronous) between instructor and students and among students is reflected in the design of the program. Course/program selection 2b Substance of the program, including its presentation, management, and assessment are the responsibilit y of people with appropriate academic qualifications.

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Table A-1. Continued 128 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Cons ortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Document Codes Institution Institution Document Codes Remark Plans to develop 2c Coherent plan for the student to access all courses necessary. Curricula/ individual courses Individual sequences 2c Coherent plan f or the student to access all courses necessary. Course development 2b Academic qualifications of those responsible for curricular decisions, assessment, and program oversight. Entire program delivery 2a The electronically offe red degree or certificate program is coherent and complete. PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark

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Table A-1. Continued 129 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark Interactivity requirements 2e Importance of appropriate interaction (synchronous or asynchronous) between instructor and students and among students is reflected in the design of the program and its co urses, and in the technical facilities and services provided. Curricula /individual courses Test requirements 5a Assessment of student achievement is conducted in each course.

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Table A-1. Continued 130 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark Test requirements 5b Examinati ons are employed (paper, online, demonstrations of competency), they take place in circumstances that include firm student identification. The institution otherwise seeks to assure the integrity of student work. Contact hour definitions N/A Online contact hours are defined. Faculty (including Continuing Education and Cooperative Extension) Rewards Stipends 3a The institution and its participating faculty have considered issues of workload, compensation. Promotion and tenure 3a The institution and its participating faculty have considered issues of workload, compensation.

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Table A-1. Continued 131 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark Merit increases 3a The institution and its participating faculty have considered issues of workload, compensation. Support Student help 3d Provides orientation and training including strategies for effective interaction. Technical assistance 2d Technical support services, including help desk serv ices. Training 3b Ongoing program of appropriate technical, design, and production support for participating faculty members. 1e Provide training and support.

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Table A-1. Continued 132 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark Opportunities to learn about technology and new ap plications Release time 3a Institution and its participating faculty have considered issues of workload, compensation, ownership of intellectual property. Training 3c Provides to those responsible for program development orientation and training. Intellectual property Copyright 1e Copyright law. 3a Institution and its participating faculty have considered issues of intellectual property. Students/Participan ts Support Access to technology 2d Course management and technology. 2d Technical services. 4c Ongoing technical support.

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Table A-1. Continued 133 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark Library resources 2d Library related services a re available. 4c Library resources. Registration 2d Registration, student records. 4c Accurate and timely information about the institution. 4c Application for admission. 4c Enrollment/registratio n in programs and courses. Advising 2d Orientation, advising, counseling, tutoring. 4c Services must be available for students of electronically offered programs pre registration advising, academic ad vising.

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Table A-1. Continued 134 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark Financial aid 4c Financial aid, including information about policies and limitations, information about available scholarships, processing of applications, and administration of financial aid and scholarship awards. Re quirements and records Residency requirements 4b Registration. Acceptance of courses from other places 1f Articulation and transfer policies the institution judges courses and programs on their learning outcomes, and the resources brought to bear for their achievement, not on modes of delivery.

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Table A-1. Continued 135 PAF Factor (King et al. 2000) IRR Reference Code Analysis factor. State, Consortium, or Institution Policy Attribute State Level State Document Codes Consortium Consortium Documen t Codes Institution Institution Document Codes Remark Transfer of credit 1f Articulation and transfer policies the institution judges courses and programs on their learning outcomes, and the resources brought to bear for their achievement, not on modes of delivery.

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136 APPENDIX B DOCUMENTS EXAMINED IN THE STUDY

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137 Table B-1. States, institutions, document codes and documents reviewed State and institution Protocol Documents Arizona A Title Location URL state and consortium level A100 01 Community college courses; intergovernmental agreement, 15 A.R.S. Sec. 1470 (2007). A100 02 Correspondence and extension courses, 15 A.R.S. Sec. 1606 (2007). A100 04 Arizona Community Colleges. (2003). Fiscal 2003 a ppropriations report. A.R.S. 15 1424. Maricopa community college district A110 01 Maricopa Community Colleges. (2007). Maricopa Community Colleges Strategic plan: Operational plans FY2007 08. N/A A110 02 Maricopa Community Colleges. (2006). Marico pa Online. https://student1.dist.maricopa.edu/mccd home.htm A110 03 Maricopa CCD Blackboard LMS Faculty/Staff Resources Page http://www.maricopa.edu/blackboard/re sourcesFaculty.html A110 04 Maricopa Faculty Online Blackboard Support Page http://help.perceptis.com/maricopa/inde x.php A110 05 Maricopa CCD Blackboard LMS Video Demos http://www.maricopa.edu/blackboard/M ovies/menu.htm A110 06 Maricopa CCD Oline library support: http://libra ry.maricopa.edu/ A110 07 Maricopa CCD Center for Learning and Instruction http://www.mcli.dist.maricopa.edu/ A110 08 Maricopa CCD Faculty Link to Teaching and Learning on the Web http://www.mcli.dist.maricopa.edu/tl/in dex.html A110 09 Maricopa Technology Group Ocotillo http://www.mcli.dist.maricopa.edu/ocoti llo/i ndex.php A110 10 Maricopa Community Colleges. (2007). Adopted budget, fiscal year 2007 08. Retrieved September 3, 2007 from http://www.maricopa.edu/business/budget/adoptbgt.htm http://www.maricopa.edu/business/budg et/fy08bgt/fy08adoptbgt.pdf

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Table B-1. Continued 138 State and institution Protocol Documents A110 11 Maricopa Community College District. (2007). About us: Demographics Retrieved August 30, 2007 from http://www.maricopa.edu/about/index.php A110 12 Distance Learning: A Two Semester Program http://ctl.mc.maricopa.edu/_programs/dl mg/index.html A 110 13 Office of General Counsel. (2007).Intellectual property: Copyright guidelines. http://www.maricopa.edu/legal/ip/guidel ines/distance.htm A110 14 Maricopa Community College District. (2007).Getting Started. Retrieved August 30, 2007 from http://www.maricopa.edu/about/index.php A110 15 Maricopa Community College District. (n.d.). National Center for Teacher Education. Retrieved September 20, 2007 from http://www.maricopa.edu/academic/teachered/Resources. html http://www.maricopa.edu/academic/teac hered/Resources.html Chandler Gilbert Community College A111 01 Chandler Gilbert Community College. (2007). E learning http://webport.cgc.maricopa.edu/publish ed/e/le/elearning/home/1/?__s=nf 20070919064237 10310 Estrella Mountain Community College A112 01 Estrell a Mountain Community College. (2005). Center for Teaching and Learning: E Learning. http://www.estrellamountain.edu/ctl/el_i ndex.asp Gateway Community College A113 01 Gateway Community Co llege. (n.d.). Online Learning. http://distance.gatewaycc.edu/ A113 02 Gateway Community College. (n.d.). Center for Teaching and Learning. http://public.gatewaycc.edu/sites/ctl/def ault.aspx

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Table B-1. Continued 139 State and institution Protocol Documents Glendale Community College A114 01 Glendale Community College. (n.d.). eCourses: Online, hybrid, open entry. http://www.gc.maricopa.edu/online/ Mesa Community College A115 01 Mesa Community College Strategic Plan 2005 2008. A115 02 Report of the comprehensive visit to Mesa Community College: Advancement section (2005). The Higher Learning Commission of the North Centeral Association of Colle ges and Schools. A115 03 DeSoto, M. (2003). Quality in distance learning. http://glory.gc.maricopa.edu/~mdesoto/ quality/index.htm Paradise Valley Community College A116 01 Para dise Valley Community College (2006). Adjunct Faculty Handbook. Phoenix, AZ: Paradise Valley Community College. A116 02 Paradise Valley Community College (2007). Choices at PVC: Center for Distance Learning. http://www.pvc.maricopa.edu/choices/ Phoenix College A117 01 Phoenix College. (2007). PC Online. http://www.pc.maricopa.edu/department s/ltd/new/pconline.php A117 02 Phoenix College. (2007). Learning, Technologies and Development. http://www.pc.maricopa.edu/department s/ltd/training/training.php Rio Salado College A118 01 Rio Salado C ollege Online. (2007). College description. http://www.riosalado.edu/ci/college_des c.shtml A118 02 Rio Salado College Online. (2007). Current Students. http://www.riosalado.edu/current/ Scottsdale Community College A119 01 Scottsdale Community College. (2006). SCC E learning Courses. http://www.scottsdalecc.edu/online/inde x.htm l

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Table B-1. Continued 140 State and institution Protocol Documents South Mountain Community College A120 01 South Mountain Community College. (2007). Other academic areas: Online courses. http://academics.southmountaincc.edu/c ourses/onlineco urses/ California B Title Location URL State and consortium level B100 01 Legislative findings and declarations; Intersegmental working group; Guiding principles, 3 Cal Ed Code 66941 (2007). B100 02 The California Community Colleges System Stra tegic Plan Steering Committee. (2006). California community colleges system strategic plan. Sacramento, CA: The California Community Colleges Board of Governors. N/A B100 04 California Community Colleges Systems Office. (2006a). 2007 08 System budget pr oposal. B100 05 California Community Colleges Systems Office. (2006b). SB 361(Scott)/Community Colleges Funding Formula Reform. B100 06 California Virtual Campus http://www.cvc.edu/ B100 07 California Virt ual Campus. (n.d.). CVC Course Catalog. http://www.cvc.edu/students/courses B100 08 California Virtual Campus. (n.d.). Faculty. http://www.cvc.edu/facu lty/ B100 10 Educational Services Division. (2004). Distance education guidelines (2nd ed.). Academic Affairs and Instructional Resources Unit, Chancellor's Office, California Community Colleges. Foothill De Anza Community College District B110 01 Foothill De Anza Community College District Board of Trustees. (2005). Educational master plan 2005 2015. Los Altos Hills, CA: Foothill De Anza Community College.

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Table B-1. Continued 141 State and institution Protocol Documents B110 02 Educational Technology Advisory Committee. (n.d.). Information technology strate gic plan 2005 2010. Los Altos Hills, CA: Foothill De Anza Community College District. B110 03 Foothill De Anza Community College District. (2007). Welcome: Mission. Retrieved August 30, 2007 from http:/ /www.fhda.edu/about_us/ De Anza College B111 01 De Anza College. (2007). Distance Learning Center. Retrieved August 20, 2007, from http:/distance.deanza.edu/index.shtml B111 02 De Anza College. (2007). De Anza College Main Page. Retrieved August 20, 2007, from http://www.deanza.edu/ Foothill College B112 01 Foothill's Leadership in Online Learning. (2007). Etudes Consortium Project: Leadership in Online I nstruction http://www.foothill.edu/news/fh etudesng.html B112 02 Student Code of Conduct for ETUDES Internet Based Courses Retrieved August 20, 2007 from http://www.foothill.edu/services/honori nt.html B112 03 Foothill Community College. (2007). Virtual Campus Center. Retrieved August 20, 2007 from http://www.foothill.edu/vcc/ B112 04 Apodaca, M., Chenoweth, M., Franco, S., Garrido, D, Noone, L. & Thomas, L. (2006). Foothill College Classified Handbook 2006 2007. B112 05 Foothill Community College. (2007). Welcome to Foothill Global Access (FGA)! Retrieved August 20, 2007 from http://www.foothillglobalaccess.org/ B112 06 Foothill Community College. (2007). Foothill Global Access: Faculty Center. http:/www.foothillglobalaccess.org/mai n/faculty_center.htm B112 07 Foothill College. (2003). Curriculum development handbook. http://www.foothill.edu/staff/curri culum /Curr_Main_Handbook.pdf San Diego community college district B120 01 Educational Master Plan 2000 2005 http://www.sdccd.edu/public/district/ma sterplan.html

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Table B-1. Continued 142 State and institution Protocol Documents B120 02 San Diego Comm unity College District. (2007). Mission and goals. Retrieved June 15, 2007 from http://www.sdccd.edu/public/district/mi ssion.html B120 03 San Diego Community College District. (2007). Principles and priorities. Retrieved September 12, 2007 from http://www.sdccd.edu/public/district/ma sterplan.html B120 04 San Diego Community College District. (2007). Online lear ning pathways. Retrieved September 12, 2007 from http://www.sdccdonline.net/ B120 05 San Diego Community College District. (2007). Procedure 5300.2. Courses of instruction and educational program approval. Retrieved September 12, 2007 from http://instsrv.sdccd.edu/policiesframe.ht m B120 06 Office of Institutional Research. (2004). Fact Book. San Diego, CA: San Diego Community College Distric t. San Diego City College B120 07 San Diego Community College District. (2007). San Diego Community College District Main Web Page. http://www.sdccd.edu/ San Diego Mesa College B121 01 San Diego City College. (2 004). Master Plan Update 2004 2005 http://www.sdcity.edu/mp/PDF/MasterP lanInternet2004 2005.pdf San Diego Miramar College B122 01 San Diego Mesa College. (2006). Five year educa tional master plan 2006 07 to 2010 2011 http://www.sdmesa.edu/educational master planning/pdf/Educational Master Plan Outline.pdf B123 01 San Die go Miramar College. (2006). Strategic Plan http://www.miramar.sdccd.cc.ca.us/dept s/president/strategicplan/2006%20Strate gic%20Plan.doc B123 02 S an Diego Community College. (2003). SDCCD Online Handbook. Retrieved June 15, 2007, from http://www.miramar.sdccd.net/depts/pd c/SDCCDonline/outline.htm Florida C Title Locat ion URL State and Consortium Level C100 01 Distance learning duties, 48 Fla. Stat. 1001.28 (2007).

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Table B-1. Continued 143 State and institution Protocol Documents C100 02 Definitions, 48 Fla. Stat. 1005.02 (2007) C100 03 Florida Community Colleges and Workforce Education. ivision of community colleges and workforce education strategic plan 2005. Tallahassee, FL: Department of Education C100 04 Florida Distance Learning Consortium. http://www.distancelearn.org/ma inPage. cfm C100 05 Florida Distance Learning Consortium. Administrative Page. http://www.fldlc.org/ C111 06 Policy and budget recommendations fiscal year 2007 08: Community college programs (Florida). Retrieve d September 6, 2007 from http://peoplesbudget.state.fl.us/BDServiceDetail.aspx?Pol icyID=&Policy Level=&ServiceID=48400600 Santa Fe Comm unity College C111 01 Santa Fe Community College. (2007). Mission and goals. Retrieved July 24, 2007 from http://www.sfcc.edu C111 02 Santa Fe Community College Open Campus Portal. (2007). http:/www2.sfcc.edu/~OpenCampus/ind ex.htm C111 03 Santa Fe Community College. (2007). Welcome to the open campus. http:/www2.sfcc.edu/%7EOpenCampus/ visitor .htm C111 04 Santa Fe Community College. (2007). Open campus: Student services. http://www2.sfcc.edu/%7EOpenCampus /studserv.htm C111 05 Santa Fe Community College. (2007). Online Facu lty Teaching Excellence Network. http://inst.sfcc.edu/~often/index.htm C111 06 Santa Fe Community College. (2007). Academic resources. http:/inst.sfcc.edu/~often/ar_index/ar_in dex.htm C111 07 Santa Fe Community College. (2007). Center for academic technologies. http://cisit.sfcc.edu/%7Ecat/INDEX.HT M

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Table B-1. Continued 144 State and institution Protocol Documents C111 08 Santa Fe Communi ty College. (2007). Educational media. http://cisit.sfcc.edu/%7Eedumedia/distle arn/index.htm C111 09 Santa Fe Community College. (2007). Current data for closing Fall 2005. Retrieved August 30, 2007 from http://admin.sfcc.edu/~ir/factbook.htm C111 10 Santa Fe Community College. (n.d.). Main Web Page. http://www.sfcc.edu/ C111 11 Santa Fe Community College. (n.d.). Lawrence W. Tyree Library, Santa Fe Community College: Distance Learning. http://cisit.sfcc.edu/~library/distance.ht m Illinois D Title Location URL State and Consortium Level D100 01 Definitions. 105 ILCS 425/1 (2006) [Prior to 1/1/93 cited as: Ill. Rev. Stat., Ch. 144, para. 136] D100 02 HIGHER EDUCATION (110 ILCS 805/) Public Community College Act. no reference to de or elearning D100 03 Illinoi s Community College Board. (n.d.). 2005 2006 Biennial report. Springfield, IL: Illinois Community College Board. D100 04 Illinois Community College Board. (2006). Administrative rules. Springfield, IL: Illinois Community College Board. D100 05 Holohan, R., Fischbach, R. Fisher, R. Campbell, T. & Rohr, T. (2005). ILCCO Research report 2005: Quality, retention and expansion of online courses and programs in Illinois community colleges. Illinois Community Colleges Online. Retrieved August 20, 2007 from http://www.ilcco.net/ILCCO/index.cfm?page=Resources. D100 06 Illinois Community Colleges Online (ILCCO). (2004). Consortium main page. http://www.ilcco.net/ILCCO/index.cfm D100 07 e learn ing in Illinois http://elearning.illinois.net/

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Table B-1. Continued 145 State and institution Protocol Documents D100 08 State of Illinois. (2007). E learning in Illinois. http://www.illinois.gov/learning/el earni ng.cfm D100 09 Illinois virtual campus http://www.ivc.illinois.edu/ D100 10 Illinois Community College Board. (2007). Fiscal Year 2008 Illinois tech prep consortium grant guidelines. Springfield, IL : Illinois Community College Board. D100 11 Illinois state budget, fiscal year 2008. Retrieved September 6, 2007 from http://www.state.il.us/budget/FY08%20Operating%20Bu dget. pdf D100 12 Consortium of Academic and Research Libraries in Illinois (CARLI). 2007). Main Webpage. http://www.carli.illinois.edu/ Morane Valley Community College D111 01 Moraine Valley Community C ollege. (2005). Strategic Priorities. Retrieved July 24, 2007 from http://www.morainevalley.edu/gen_info/strategic.html http://www.morainevalley.edu/gen_info /strategic.html D111 02 Moraine Valley Community College. (2007). Academic Quality Improvement Program (AQIP). Retrieved July 24, 2007 from http://www.morainevalley.edu/AQIP/action_projects.htm http://www.morainevalley.edu/AQIP/act ion_projects.htm D111 03 Moraine Valley Community College. (2007). Alternative Learn ing http://www.morainevalley.edu/Alternati veLearning/ D111 04 Moraine Valley Community College. (2007). E learning. http://my.morainevalley.edu/webapps/p ortal/frameset.jsp D111 05 Moraine Valley Community College. (2007). Online general information. http://www.morainevalley.edu/academic s/exam.html D111 06 Moraine Valley Community College. (2007). Student support. http://my.morainevalley.edu/webapps/p ortal/frameset.jsp?tab_id=_10_1 D111 07 Moraine Valley Commun ity College. (2007). Faculty support (Center for Teaching and Learning) http://www.morainevalley.edu/CTL/res ources.htm

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Table B-1. Continued 146 State and institution Protocol Documents D111 08 Moraine Valley Community College. (2007). Facts and Figures, 2005. Retrieved August 30, 2007, from http:/www.morainevalley.edu/gen_info/facts.html D111 09 Moraine Valley Community College. (2006). Comprehensive annual financial report, fiscal years 2005 2006. D111 10 Moraine Valley Community College. (2007). Home Page. http://www.morainevalley.edu/default.a sp D111 11 Moraine Valley Community College. (2007). Library/Learning Reso urces Center: Services for Faculty. http://www.morainevalley.edu/lrc/instru ctionform_display.asp Iowa E Title Location URL State and Consortium Level E100 01 Division of Co mmunity Colleges and Workforce Preparation. (2006). Shaping the future: Five year plan for the community colleges of Iowa 2006 2111. Des Moines, IA: Iowa Department of Education. N/A E100 02 Bureau of Community Colleges and Career and Technical Educatio n. (2005). Instructions for submitting program approval requests, Community college programs. Des Moines, IA: State of Iowa, Department of Education E100 03 Iowa Community College Online Consortium http:// www.iowacconline.org/ E100 04 Division of Community Colleges and Workforce Preparation. (2006). Iowa community colleges fiscal year 2007 certified budgets. Des Moines, IA: Iowa Department of Education. E100 05 Iowa Department of Education. (2006). Details for Minimum Faculty Standards. Retrieved August 20, 2007 from http://www.iowa.gov/educate/componen t/option,com_docman/task,doc_details/g id ,213/Itemid,55/

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Table B-1. Continued 147 State and institution Protocol Documents Kirkwood Community College E111 01 Kirkwood Community College (2005). 2005 2006 Strategic goals: Distance learning five year vision. Retrieved July 24, 2007 from http://www.kirkwood.edu/pdf/uploaded/643/distance_lear ning.pdf http://www.kirkwood.edu/pdf/uploaded/ 643/distance_learning.pdf E111 02 Distance Learning Student Reso urces http://www.kirkwood.edu/site/index.php ?p=3659 E111 03 Advising and Transfer Center http://www.kirkwood.edu/advising/ E111 04 Kirk wood Community College Distance Learning. (2006). http://www.kirkwood.edu/distancelearni ng E111 05 Kirkwood CC Distance Learning Costs and Policies. (2006). http://www.kirkwood.edu/site/index.php ?p=10018 E111 06 Kirkwood Faculty and Staff Policies. (2006). http://www.kirkwood.edu/facultystaff.p hp E111 07 Kirkwood Commun ity College Board Policy Manual http://www.kirkwood.edu/board/policie s/ E111 08 612 Educations Programs http://www.kirkwoo d.edu/site/index.php ?d=194&p=2117&t=2 E111 09 Kirkwood Community College Board Policy 675 Development of Copyrightable Materials and Media by the KCC Personnel http://www.kirkwoo d.edu/site/index.php ?d=194&p=2119&t=2 E111 10 Kirkwood Community College Distance Learning Instructor Resources. (2006). http://www.kirkwood.edu/site/index.php ?p=10099 E111 11 Kirkwood Community College Distance Education Instructor Resources. (2006). ATAW Course Design Guideline http://www.kirkwood.edu/pdf/uploaded/ 134/atawcoursedesignguideline.pdf E111 12 Kirkwood Community College. (2007). Enrollment 2006 7. Retrieved August 30, 2007 from http://www.kirkwood.edu/site/index.php?d=589

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Table B-1. Continued 148 State and institution Protocol Documents E111 13 Kirkwood Community College (2006). Main Webpage. Retrieved August 30, 2007 from http://www.kirkwoo d.edu/ Kansas F Title Location URL State and Consortium Level F100 01 Definitions. K.S.A. 74 32,163 (2006) http://www.kslegislature.org/legsrv statutes F100 02 State Boards, Commissi ons and Authorities,74 K.S.A. 74 3202c (2006). http://www.kslegislature.org/legsrv statutes F100 03 Kansas Board of Regents. (1995). Policy and procedures manual. Topeka, KS: Kansas Board of Regents. http://www.kansasregents.org/download /aca_affairs/policymanual/policymanual .pdf F100 04 Kansas Board of Regents. (2000). Kansas four year state plan: Adult education and family literacy. Topeka, KS: Kansas Board of Regents. F100 05 Distance education means any course delivered primarily by use of correspondence study, audio, video or computer technologies. retrieved July 24, 2007 from http://www.kansasregents.org/KANDL/ index.html F100 06 Kansas Digital Learning (KANDL) Advisory Council for Higher Education. (2004). Retrieved July 24, 2007 from http://www.kansasregents.org/download /kandl/KansasDigitalLearning.pdf F100 07 Welcome to Kan ed. (2004). Topeka, KS: Kansas Board of Regents. Retrieved July 24, 2007 from http://www.kan ed.org/index.htm F100 08 Kan ed. (2006). Annual report 2006. Retrieved September 12, 2007 from http://www.kan ed.org F100 09 Kansas Board of Regents. (2000). A pl an for coordination of Kansas postsecondary education. Retrieved August 1, 2007 from http://www.kansasregents.org/download/agency/coordina tion.pdf http://www.kansasregents.org/download /agency/coordination.pdf

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Table B-1. Continued 149 State and institution Protocol Documents F100 10 Kansas Board of Regents. (2003). Kansas Digital Learning. http://ww w.kansasregents.org/KANDL/ index.html F100 11 Kansas Board of Regents. Unified operating budget request for higher education, FY 2007. Retrieved August 30, 2007 from http://www.kansasregents.org/download/Finance/Unified %20Budget%20Document%20FY%202007%20webpage. pdf F100 12 COMMUNITY COLLEGES K.A.R. 88 26 4 (2006) 88 26 4. Credit. Johnson County Community College F111 01 Strat egic Planning Council. (2006). Johnson County Community College strategic plan assessment matrix FY 07. Retrieved August 1, 2007 from http://www.jccc.net/home/download/14 921/Oper ationalPlan.pdf F111 02 Johnson County Community College. (2006). Distance learning at JCCC. Retrieved July 24, 2007 from http://web.jccc.net/academic/dl/ F111 03 Johnson County Community College (2006). Distance learning policies. Retrieved July 24, 2007 from http://web.jccc.net/academic/dl/policies. htm F111 04 Johnson County Community College. (2006). Mission of the distance lea rning coordinating council. Retrieved July 24, 2007 from http://web.jccc.edu/dlcc/ F111 05 Johnson County Community College. (2007). Friends and Visitor s. Retrieved August 30, 2007 from http://www.jccc.net/home/groups.php?which=5 F111 06 Johnson County Community College. (2006). Current Students. http://www.jccc.edu/home/groups.php? wh ich=2 F111 07 Johnson County Community College. (2007). CTL Distance Learning Mentor / Coordinator http://web.jccc.net/academic/ctl/fa culty_ support/distance_learning.html#Distanc e_Learning_Resources

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Table B-1. Continued 150 State and institution Protocol Documents F111 08 Johnson County Community College. (2007). Distance learning testing. http://www.jccc.net/home/depts.php/53 02/site /dl F111 09 Johnson County Community College. (2006). Distance learning coordinating council: Handouts, checklists and general documents. http://web.jccc.edu/dlcc/resources/index .html F111 10 Johnson County Community College. (2006). Series 400: Personnel, Section 422 .11 Copyrights and patents. http://www.jccc.net/home/depts.php/11 02/site/facultyresources/toc_faculty_han dbook/toc_hr_policies/422.11_copyrigh ts_patents F111 11 Johnson County Community College. (2001). Distance learning development process. http://web.jccc.net/edtech/projects/instru ctions.pdf Maryland G Title Location URL State and Consortium Level G100 01 Maryland Higher Education Commission. (2004). Maryland state plan for post secondary education. Ann apolis, MD: MHEC. http://www.mhec.state.md.us/higherEd/ 2004Plan/2004StatePlan.asp G100 02 Maryland Online. (2007). Welcome to Maryland Online. http://www.marylandonline.org/ G100 03 Maryland Online. (2007). Mission and vision. http://www.marylandonline.org/about/vi sion_mission G100 04 Maryland Online. (2 007). Students. http://www.marylandonline.org/students G100 05 Maryland Online. (2007). Faculty. http://www.marylandonline.org/facult y/ resources G100 06 Filipp, L. (2005). Distance learning at Maryland colleges and universities, Academic year 2003 2004. Annapolis, MD: Maryland Higher Education Commission. Summary of Operating Budget Appropriations for the Fiscal Year Ending June 30, 2008. (Maryland). Retrieved September 6, 2007 from http://dbm.maryland.gov/dbm_publishing/public_content/ dbm_search/ budget/toc_fy2008_fiscal_digest/fisdig08exc .pdf

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Table B-1. Continued 151 State and institution Protocol Documents Anne Arundel Community College G111 01 Anne Arundel Community College. (2006). Continuum: Anne Arundel Community College Strategic Plan 2006 2115. Arnold, MD: Anne Arundel Community College. http://www.aacc.edu/aboutaacc/file/AA CCStrategicPlan.pdf G111 02 Anne Arundel Community College. (2007). Distance learning at AACC. ht tp://www.aacc.edu/distancelearning/ G111 03 Anne Arundel Community College. (2007). Progressive technology at AACC. http://www.aacc.edu/technology/ G111 04 Anne Arundel Community College. (2007). T ruxal library for distance learners. http://www.aacc.edu/library/DLResourc es.cfm G111 05 Anne Arundel Community College. (2007). AAAC Policies. http://www.aacc.edu/aboutaacc/policies. cfm G111 06 Anne Arundel Community College. (2007). Enrollment Statistics and Student Profile; Credit FY 2005 Enrollment in headcount. Retrieved August 30, 2007 from http://www.aacc.edu/aboutaacc/enrollmentstats.cfm G111 07 Anne Arundel Community College. (2006). Student services at AACC. http://www.aacc.edu/studentservices / Michigan H Title Location URL State and Consortium Level H100 01 Strategic Planning Committee. (2007). M ichigan Community College Association 2007 2010 strategic plan. Lansing, MI: MCCA. H100 02 Michigan Community College Association. (2007). V irtual learning collaborative. http://vcampus.mccvlc.org/index.asp H100 03 Michigan Community College Network. (n.d.). http://www.michigancc.net/mc cdeci/ H100 04 FY 2007 08 Community colleges budget. (Michigan). Retrieved September 5, 2007 from http://www.senate.michigan.gov/sfa

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Table B-1. Continued 152 State and institution Protocol Documents Delta College H111 01 Delta College. (2006). Delta College 2006 2010 strategic plan. Retrieved August 3, 2007 from www.delta.edu/aqip/attachments/DeltaCollege20062010S trategic%20Plan%20December122006.do c www.delta.edu/aqip/attachments/DeltaC ollege20062010Strategic%20Plan%20D ecember122006.doc H111 02 Delta College. (2005). Delta College Di stance Learning. http://www.delta.edu/broadcasting/disle arnprog.html H111 03 Delta College. (2005). Delta College Distance Learning: Elearning. http://www.delta.edu/elearning/ H111 04 Delta College. (2006). FY 2006 2007 Strategic planning and budget. University Center, MI: Delta College. H111 05 Delta College. (2005). Delta College: Experience the Delta Difference. http://www.delta.edu/ H111 06 Delta College. (2005). Delta College eLearning Office: Michigan Community College Virtual Learning Collaborative. http://www.delta.edu/ elearning/mccvlc. html H111 07 Edwards Ham, P. (2003). Delta College Academic Assessment Plan 2002 2006. http://www.delta.edu/assessmt/Academi c%20Asses sment%20Plan%20revise%2 0june%2006.doc Delta College. (2005). Delta College Distance Learning. http://www.delta.edu/aqip/attachments/ DeltaCollegeAQIPApplication.p df Delta College. (2004). The academic testing center. http://www.delta.edu/acadtest/ Missouri K Title Location URL State and Consortium Level K100 01 Missouri Department of Higher Education. (2 006). FY2006 Strategic planning documents. Jefferson City, MO: MDHE. K100 02 Missouri Department of Higher Education. (2007). Policy for the review of academic program proposals. http://www.d he.mo.gov/policyforreview .shtml K100 03 Missouri Department of Higher Education. (2006). Financial summary. Retrieved September 6, 2007 from http://www.oa.mo.gov/bp/budg2008/HigherEd ucation.pdf

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Table B-1. Continued 153 State and institution Protocol Documents St Louis Community College K110 01 St Louis Community College. (2007). Distance learning. http://www.stlcc.edu/distance/ K110 02 St Louis Community College. (2007). Admissions and regist ration. http://www.stlcc.edu/admreg/ K110 03 St Louis Community College. (2007). Faculty and staff resources. http://www.stlcc.edu/resources/f aculty staff.htm K110 04 St Louis Community College. (2007). Adjunct faculty certificate program. http://www.stlcc.edu/staffdev/adj_fac_c ert_pr.htm K110 05 St Louis Community Colleg e. (2007). Programs: College wide professional development programs. http://www.stlcc.edu/staffdev/programs. htm K110 06 St Louis Community College. (2007). Center for teaching and learning. http://www.stlcc.edu/fv/ctl/ K110 07 St Louis Community College. (2007). Blackboard at St. Louis Community College. http://www.stlcc.edu/blackboard/ K110 08 St Louis Community College. (2007). Blackboard: Student quick start guides. http://www.stlcc.edu/blackboard/student s.html K110 09 St Louis Community College. (2007). Blackboard: Faculty. http://www.stlcc.edu/blackboard/faculty .html K110 10 St Louis Community College. (2006). Distance learning: Intellectual Property Ownership and Copyright Links. http://www.stlcc.edu/distance/text/resou rces/ownership.html K110 11 St Louis CC. (2007). St Louis Community College: Expanding Minds Changing Lives. http://www.stlcc .edu K110 12 Board of Trustees. (n.d.) St Louis Community College Policy. Retrieved July 14, 2007, from http://www.stlcc.edu/pol/slccpolicy.pdf http://www.stlcc.edu/pol/slccpolicy.pdf

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Table B-1. Continued 154 State and institution Protocol Documents K110 13 St Louis Community College. (2007). St. Louis Community College three year completion and persistence rates for first time, full time, degree seeking students: fall 2003 to spring 2006. Retrieved August 31, 2007 from http://www.stlcc.edu/services/consumer/graduate.html St Louis Community College Florissant Valley K111 01 St Louis Community College Forest Park K112 01 St Louis Community College Meramec K113 01 St Louis Community College Meramec. (2007). Center for support of teaching and learning. http://www.stlcc.edu/mc/services/cstl/in dex.htm New York L 5 Title Location URL State and Consortium Level L100 01 The University of The State of New York. (2005). The Board of Regents statewide plan for higher education. Albany, NY: State Education Department L100 02 Office of the Provost. (20 04). The State University of New York Master Plan, 2004 2008. Albany, NY: State University of New York. http://www.suny.edu/provost/txtfiles/M asterPlan2004 2008.txt L100 03 State University of New York. (2007). University wide Policies and Procedures. http://www.suny.edu/sunypp/ L100 04 State University of New York. (2007). SUNY Learning Network. http://sln.suny.edu/index.html

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Table B-1. Continued 155 State and institution Protocol Documents L100 05 Office of College and University Evaluation. (2004). Distance Higher Education. Albany, NY: New York State Education Department. h ttp://web1.nysed.gov/ocue/Distance/de fault.htm L100 06 State University of New York. (2007). SUNY Learning Network: SLN Community. http://pilot.sln.suny.edu/index.php State University of New York (SUNY). (2006). Operating budget for community colleges. Retrieved September 6, 2007 from http://www.suny.edu/sunypp/documents.cfm?doc_id=171 Monroe Community College L111 01 S trategic Planning Team. (n.d.). Strategic Plan: Forging connection: Serving community needs. 2007 2011. Rochester, NY: Monroe Community College. http://www.monroecc.edu/depts/mccad min/stra tpln.htm L111 02 Monroe Community College. (n.d.). Online Learning. http://www.monroecc.edu/depts/distlear n/index.htm L111 03 Monroe Community College. (n.d.). Online Learning: Stu dents. http://www.monroecc.edu/depts/distlear n/students.htm L111 04 Monroe Community College. (n.d.). Online Learning: Faculty. http://www.monroecc.edu/depts/distlear n/faculty.htm L111 05 Monroe Community College. (2007). Statistics. Retrieved August 31, 2007 from http://monroeccny.college lnfo. com/&kid=GOG0010079203 http://monroeccny.college lnfo.com/&kid=GOG0010079203 L111 06 Monroe Community College. (2007). There's More To You. Retrieved August 31, 2007 from http://www.monroecc.edu/index.htm http://www.monroecc.edu/index.htm North Carolina M Title Location URL State and Consortium Level M100 01 Fees for Extension Programs 23 N.C.A.C. 2D.0203 (2006).

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Table B-1. Continued 156 State and institution Protocol Documents M100 02 Parker, D. A., McGraw, D., Randall, B., & Williams, B. (2004). Strategic plan for distance learning 2003 2004 through 2008 2009 for the North Carolina Community College System. Raleigh, NC: North Carolin a Community College System. http://vlc.nccommunitycolleges.edu/abo ut/PDF/DL%20Strategic%20Plan.pdf M100 03 North Carolina Community College System. (2007). Virtual learning community. Retrieved September 13, 2007 from http://vlc.nccommunitycolleges.edu/ M100 04 Rogers, B. (2001). Analysis of funding issues related to distance learning in the North Carolina Community College System. Tallahassee, FL: Management of America, Inc. M100 05 Office of State Budget and Management. (2007). The North Carolina state budget: Recommended operating budget with results based information 2007 2009. Education, Volume 1. Raleigh, NC: State Budget Office. M100 06 North Carolina Community College System. (2007). Intellectual Property Policy for the Virtual Learning Community. Retrieved September 13, 2007 from http://vlc.nccommunitycolleges.edu/abo ut/PDF/VLC_IP_Policy.pdf Central Piedmont Community College M111 01 Central Piedmont Community College. (2007). 2 007 2008 Operational plan. Charlotte, NC: Central Piedmont Community College. http://www1.cpcc.edu/administration/str ategic plan/2007 2008 operational plan/ M111 02 Central Piedmont Community College. (n.d.). Services for students: Cu rrent students. http://www1.cpcc.edu/services/current M111 03 Central Piedmont Community College. (n.d.). Information technology services: ITS for faculty and staff. http://www1.cpcc.edu/its/faculty staff/

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Table B-1. Continued 157 State and institution Protocol Documents M111 04 Central Piedmont Community College. (n.d.). Information technology services: Services for instruction. http://www1.cpcc.edu/its/faculty staff/instructional technologies M111 05 Central Piedmont Community College. (n.d.). Elearning community: eLearning and distance learning. http://www1.cpcc.edu/elearningcommu nity/support/documentation/elearning M111 06 Central Piedmont Community College. (2007). 2005 2006 Annual report. Retrieved August 31, 2007 from http://www1.cpcc.edu/administration/annual report/2005_Annual Report.pdf M111 07 Central Piedmont Community College. (n.d.) Main webpage. http://www1.cpcc.edu Ohio N 6 Tit le Location URL State and Consortium Level N100 01 Ohio Board of Regents. (2003). 2003 Vision, mission, goals, strategies and measures. N100 02 Policy Makers Guide: E learning and distance learning. Retrieved September 13, 2007 from http://regents.ohio.gov/policymakersgui de/elearning.php N100 03 Ohio Learning Network. Retrieved September 13, 2007 from http://www.oln.org/ N100 04 Ohio Learning Network About. Retrieved September 13, 2007 from http://www.oln.org/about_oln/about.php N100 05 E learning Athenaeum of Ohio: Resources for faculty innovators. (n.d.). http://www.cscc.edu/oln/ N100 06 Office of Budget and Management. (2007). State of Ohio Executive Budget Briefing Document, Fiscal Years 2008 2009. Retrieved September 8, 2007 from http:/ /www.obm.ohio.gov N100 07 Task Force on Quality in Distance Learning. (2002). Quality learning in Ohio and at a distance. Ohio Learning Network. Retrieved August 2 0 2007, from http://www.oln.org

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Table B-1. Continued 158 State and institution Protocol Documents N100 08 Ohio Learning Network. (2006). Annual report. Expanding delivery: e learning in Ohio. Retrieved August 20 2007, from http://www.oln.org N100 09 Ohio Learning Network. (2004). The future of distance and e learning in Oh io. http://www.oln.org/about_oln/e_policy_ archives.php N100 10 Ohio Learning Network. (n.d.). Principles of good practice. h ttp://www.oln.org/about_oln/principles .php N100 11 Ohio Learns! (n.d.). Best practices in student services. http://www.ohiolearns.org/bestpractices. php N100 12 Ohio Digital Commons for Ed ucation. (2005). The convergence of libraries, learning and technology. Proceeds of the conference, March 7 8, 2005. http://www.oln.org/conferences/ODCE2 005/ Cuyahoga Community College N111 01 Cuya hoga Community College: Office of Distance Learning. (2007). Student resource center. http://dlc.tri c.edu/resources/ N111 02 Cuyahoga Community College: Office of Distance Learning. (2007). Distance lear ning site map. http://dlc.tri c.edu/sitemap.htm N111 03 Cuyahoga Community College. (2007). Just the facts. Retrieved August 31, 2007 from http: //www.tri c.edu/about/docs/just.htm N111 04 Cuyahoga Community College. (2007). Home Page. Retrieved August 31, 2007 from http://www.tri c.edu/home/default.htm http://www.tri c.edu/home/default.htm N111 05 Cuyahoga Community College. (2005). Strategic Plan 2005 2010. Retrieved August 31, 2007 from http://www.tri c.edu/plan/default.h tm http://www.tri c.edu/plan/default.htm N111 06 Cuyahoga Community College. (2007). Transfer Center. Retrieved August 31, 2007 from http://www.tri c.edu/Articulation/default.htm http://www.tri c.edu/Articulation/default.htm

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Table B-1. Continued 159 State and institution Protocol Documents N111 07 Cuyahoga Community College. (2007). Instructor sites. Retrieved August 31, 2007 from http://instruct.tri c.edu/home/default.htm http://instruct.tri c.edu/home/default.htm Sinclair Community College N112 01 Sinclair Commun ity College. (2006). Distance learning. http://www.sinclair.edu/academics/dis/ N112 02 Sinclair Community College. (2006). Distance learning: Overview of Distance Learning. http://www.sinclair.edu/academics/dis/ OverviewofDistanceLearning/index.cfm N112 03 Sinclair Community College. (2006). Distance learning: Policies of Distance Learning. http://www.sinclair.edu/academics/dis/P oliciesofDistanceLearning/index.cfm N112 04 Sinclair Community College. (2006). Current students. http://www.sinclair.edu/current/index.cf m N112 05 Sinclair Community College. (2007). AQIP Systems portfolio. Retrieved July 24, 2007 from http://ww w.sinclair.edu/about/aqip/2007 systemsportfolio/index.cfm N112 06 Operations Council. (2006). Sinclair strategic plan Goals and objectives by cluster updated 11/27/06. Dayton, OH: Sinclair Community College. http://www.sinclair.edu/about/aqip/pub/ SPlanwAct.pdf N112 07 Sinclair Community College. (2007). Cost analysis (Budget FY 2002 2003 through FY 2006 2007). Retrieved September 8, 2007 from http://www.sinclair.edu/departments/budget/ReportsandA nalyses/index.cfm N112 08 Sinclair Community College. (2006). About Sinclair Retrieved August 31, 2007 from http://www.sinclair.edu/about/index.cfm N112 09 Sinclair Community College. (2006). Distance Learning: Course delivery methods. http://www.sinclair.edu/academics/dis/ OverviewofDistanceLearning/CourseDe liveryMethods/index.cfm

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Table B-1. Continued 160 State and institution Protocol Documents N112 10 Sinclair Community College. (2006). Distance Learning Course Catalog. http://www.sinclair.edu/academics/dis/ DistanceLearningCourseCatalog/index.c fm Oregon P Title Location URL State and Consortium Level P100 01 Advanced technology education and training grants and loans; rules. 3 0 ORS 326.382 (2005) P100 02 Education and Culture Chapter 340. Expanded Options Program, 30 ORS 340.005 (2006) P100 03 Oregon Department of Community Colleges and Workforce Development. (2001). Community college handbook: State approval requ irements and procedures for degrees, programs, courses and instructors Retrieved July 9, 2007 from http://www.odccwd.state.or.us P100 04 Oregon Department of Education. (2007). Web Site Policy. http://www.ode.state.or.us/search/results /?id=275 P100 05 Oregon Network for Education. (n.d.). Oregon's one stop for distance education. http://www.or egonone.org P100 06 Oregon Network for Education. (n.d.). ONE Faculty/Staff Center. http://www.oregonone.org/faculty.html P100 07 Oregon Network for Education. (n.d.). Student services. http://www.oregonone.org/services.html P100 08 Hope and Opportunity Budget 2007 2009, Part B Education. Retrieved September 8, 2007 from http://www.oregon.gov/DAS/BAM/docs/Publications/GR B0709/B_Education.pdf Lane Community College P111 01 Retrieved August 6, 2007 from http://www.lanecc.edu/research/planning/visionmissionco re0408.html http:/ /www.lanecc.edu/research/plannin g/visionmissioncore0408.html

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Table B-1. Continued 161 State and institution Protocol Documents P111 02 Lane Community College. (2007). Distance Learning. http://www.lanecc.edu/distance/ P111 03 Lane Community College. (2007). Distanc e Learning: Faculty and staff resources. http://www.lanecc.edu/distance/staff.ht m P111 04 Lane Community College. (2007). Distance Learning: Getting Started. http://www.lanecc.edu/distance/geninfo. htm P111 05 Lane Community College. (2007). About Lane. Retrieved August 31, 2007 from http://www.lanecc.edu/mpr/aboutlcc.htm P1 11 06 Lane Community College. (2007). Approved budget schedules, Fiscal Year 2007 2008. Retrieved September 8, 2007 http://www.lanecc.edu/budget/0708/Documents/Approve dBudg etFY08.pdf P111 07 Lane Community College. (2007). Students. Retrieved August 31, 2007 from http://www.lanecc.edu/es/students.html http: //www.lanecc.edu/es/students.html P111 08 Lane Community College. (2007). Transfer programs Retrieved August 31, 2007 from http://www.lanecc.edu/stuser/acadinfo/tranhome.htm http://www.lanecc.edu/stuser/acadinfo/tr anhome.htm Texas R Title Location URL State and Consortium Level R100 01 The Texas higher Education Coordinating Board. (2000). Closing the Gaps by 201 5: The Texas higher education plan. Retrieved August 6, 2007 from http://www.thecb.state.tx.us/reports http://www.thecb.state.tx.us/re ports/PD F/0379.PDF R100 02 The Texas higher Education Coordinating Board. (2007). Closing the Gaps by 2015: 2007 Progress Report. Retrieved August 6, 2007 from http://www.thecb.state.tx.us/reports http://www.thecb.state.tx.us/reports/PD F/1377.PDF R100 03 The Texas higher Education Coordinating Board. (2000). Texas Distance Education. http://www.txelectroniccampus.org/inde x.aspx

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Table B-1. Continued 162 State and institution Protocol Documents R100 04 The Virtual College of Texas. (2007). Welcome. http://www.vct.org/ R100 05 Office of the Governor. (2007). Texas State Budget, Fiscal Years 2008 2009. Retrieved September 8, 2007 from http://www.texasgovernment.info/budget.html R100 06 Legislative Budget Board Staff. (2007). Financing higher education in Texas: Legislative pri mer. Retrieved September 8, 2007 from http://www.lbb.state.tx.us/Higher_Education/HigherEd_F inancingPrimer_0107.pdf R100 07 Institutional Report for Dis tance Education, Off Campus Instruction, and On Campus Extension Programs. 19 TAC 4.106 (2007). R100 08 Definitions. Tex. Educ. Code 132.001 (2007) R100 09 Virtual College of Texas. (2007). Operations manual. Retrieved September 13, 2007 f rom http://www.vct.org/opn_manual.htm Dallas County Community Colleges R110 01 Board of Trustees. (2004). Board of trustees system wide strategic plan, 2005 2008 Retrieved August 6, 2007 from https://www1.dcccd.edu/cat0506/about/miss.cfm?loc=1 https://www1.dcccd.edu/cat0506/about/ miss.cfm?loc=1 R110 02 Dallas Cou nty Community College District. (2006). Dallas TeleCollege: eConnect. http://ecampus11.dcccd.edu/webapps/po rtal/frameset.jsp?tab_id=_14_1 R110 03 Dallas County Communi ty College District. (2006). Dallas TeleCollege: Distance Learning. http://dallastelecollege.dcccd.edu/ R110 04 Dallas County Community College District. (2006). Dallas TeleCollege: Faculty/Employees http://dallastelecollege.dcccd.edu/Facult y/ R110 05 Dallas County Community College District. (2006). About DCCD. http://www.dcccd.edu/Abou t+DCCCD/ R110 06 Dallas County Community College District. (2007). Fast facts. Retrieved August 31, 2007 from http://www.dcccd.edu/About+DCCCD/DCCCD+Facts/

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Table B-1. Continued 163 State and institution Protocol Documents R110 07 Dallas County Community College District. (2006). Home page. http://www.dcccd.edu/ R110 08 Branch Campuses and Distance Learning. (2006). Dallas County Community College District 057501 Retrieved September 13, 2007 from http://www.dcccd.edu/ Brookhaven College R111 01 Cedar Valley College R112 01 Eastfield College R113 01 El Centro College R114 01 Mountain View College R115 01 North Lake College R116 01 Richland College R117 02 Washington S Title Location URL State and Consortium Level S100 01 K 20 educational network board Powers and duties, Rev. Code Wash. (ARCW) 43.105.805 (2007) S100 02 State Government Executive Chapter 43.105. Department of Information Services (Formerly: Data Processing and Commun ications Systems), rev. Code wash. (ARCW) 43.105.820 (2006)

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Table B-1. Continued 164 State and institution Protocol Documents S100 03 Washington State Board for Community and Technical Colleges. (2006). Washington state community and strategic plan. Retrieved Augu st 6, 2007 from http://www.sbctc.ctc.edu/docs/education/workforce/wec_ strategic_plan_000.pdf http://www.sbctc.ctc.edu/docs/education /workforce/wec_strategic_plan_000.pdf S100 04 IC Planning Taskforce. (2005). The cornerstones report: An educational technology strategic plan for the Instruction Commission. Retrieved A ugust 6, 2007 from www.sbctc.ctc.edu www.sbctc.ctc.edu S100 05 Washington State Board for Community and Technical Colleges. (2006). Education services: Elearning. http://www.sbctc.ctc.edu/college/e_elea rning.aspx S100 06 Washington Online: A virtual campus of the community and technical colleges. (2006). http://www.waol.org/home/default.as p S100 07 Office of the Governor. (2007). State Board for Community and Technical Colleges: Agency level summary, FY 2008 2009 Budget. Retrieved September 8, 2007 from http://www.ofm.wa .gov/budget07/detail/NL699.pdf S100 08 State Board for Community and Technical Colleges. (2006). Policy manual. http://www.sbctc.ctc.edu/docs/policy_m anual.pdf S100 09 State Boar d for Community and Technical Colleges. (2006). Distance Learning Council Goals. http://www.sbctc.ctc.edu/college/_g dlcgoals.aspx S100 10 State Board for Community and Technical Colle ges. (2001). Academic Year Report, 2000 01, Appendix A. Full time Undergraduate Student Tuition and Fees.

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Table B-1. Continued 165 State and institution Protocol Documents Seattle Community College District S110 01 Seattle Community Colleges. (n.d.). Strategic plan 2005 2010. Retrieved June 17, 2007 from http://www.seattlecolleges.com http://www.seattlecolleges.com S110 02 Seattle Community Colleges. (2007). Our district: Facts at a glance. Retrieved August 31, 2007 from http://seattlecolleges.com/facts.aspx S110 03 Seattle Community Colleges. (2007). Distance learning. Retri eved August 31, 2007 from http://www.seattlecolleges.edu/distance/ http://www.seattlecolleges.edu/distance/ S110 04 Seattle Community Colleges. (2002/2008). Faculty development. Retrieved August 31, 2007 from http://dept.seattlecolleges.edu/fd/ http://dept.seattlecolleges.edu/fd/ North Seattle Community College S111 01 Seattle Central Community College S11 2 01 South Seattle Community College S113 01

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178 BIOGRAPHICAL SKETCH organizational leadership and consulting at all levels. He has an extensive background in a variety of disciplines: program and project management, human resource requirements determination, industrial engineering, operations management, organization development, total quality management, strategic planning, facilitation, benchmarking, performance assessment, education and training, systems management, and whole-system optimization. He has directed organizations charged with managing resources in excess of $320 million, developed academic organizations from the ground up, led major organizational change, and successfully developed client relationships leading to repeat business. Amason holds a bachelor of science degree in economics (1974) and a master of science degree in industrial management (1975), both from Georgia Tech. He earned his doctorate in higher education administration at the University of Florida where he was a Graduate Alumni Professional (PMP). This certification, granted by the world's leading project management organization, places him in the top echelon of the world's 25 million project workers. In addition to owning his own consulting firm, Bob serves as a university professor at the University of PhoeniInternational campus in Ocala, Florida. He teaches management principles, operations management, project management, and a variety of adult education and training courses at both graduate and undergraduate levels. Amason is past program manager of the Center for Project Management at the University of North Florida. He developed highly successful project management training courses and marketing materials that led to the success of the Center for Project Management for more than six years. As a doctoral fellow at the University of Florida,

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179 Amason has served as executive director of the Institute of Higher Education where he coordinated strategic planning for that organization. Amason has written for the Jacksonville Business Journal. He has been an invited speaker Association, and the Jacksonville Information Technology Exposition and Conference. He is author of several training courses and has written a manuscript on project management. In addition to his other professional accomplishments, Amason is also a retired U.S. Air Force lieutenant colonel who served the nation with distinction for more than 21 years. He has over 2,500 flying hours (2,000-plus hours in B-52G and H aircraft) as both crewmember and instructor. During his military career, he directed flying training, conducted human resource requirements studies, managed acquisition projects, and oversaw process improvement efforts for large, high-value operations. His military awards include the Defense Meritorious Service Medal, the Meritorious Service Medal with four oak leaf clusters, the Air Force Commendation Medal, the Air Force Combat Readiness Medal, and the National Defense Service Medal. history, playing and collecting acoustic guitars, and playing golf. He has two children who are pursuing their own higher education at Florida State University.