The influence of native language skills on foreign language learning

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The influence of native language skills on foreign language learning phonological, orthographic, and semantic contributions
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Gilligan, Gerianne Muldoon
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Communication Sciences and Disorders thesis, Ph. D   ( lcsh )
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Thesis (Ph. D.)--University of Florida, 2004.
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Includes bibliographical references.
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by Gerianne Muldoon Gilligan.
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Printout.
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Vita.

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THE INFLUENCE OF NATIVE LANGUAGE SKILLS ON
FOREIGN LANGUAGE LEARNING:
PHONOLOGICAL, ORTHOGRAPHIC, AND SEMANTIC CONTRIBUTIONS










By

GERIANNE MULDOON GILLIGAN


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF





























This dissertation is dedicated to my children,

Benjamin and Audrey Gilligan















ACKNOWLEDGMENTS


I first must acknowledge my parents, Donald and Maureen Muldoon. I do not

think that I could have finished this degree without their support and assistance. I am


eternally grateful.

There are many people at the University of Florida who have helped me to


flourish both academically and personally.


When I moved to Gainesville five years ago


to begin my doctoral program, I could not have imagined the growth and changes that I


have experienced.


I am very grateful to everyone who has been with me along the way


and supported me through this process.


I have learned a great deal from the members of my committee.


Lombardino has been a wonderful mentor.


Linda


Her expertise in the area of reading


disabilities has helped me to refine my assessment and intervention approaches.


also helped me to improve my writing and research skills.


She has


Finally, without her


understanding and encouragement, the completion of this degree would have been a

much less pleasant experience.


Bonnie Johnson has been a role model to me.


Learning from her experience as a


new faculty member will benefit me as I begin my own academic career.


She has also


t 4 4 4 4 4 .4 I A,* I


F








I have great admiration for Holly i

reading disabilities is truly inspirational.


Her commitment to helping children with


I learned a great deal in her courses and hope


that I can use the information and ideas to make a difference in my own way.

I would also like to thank Scott Griffiths for always being available to help me


He usually knew the answer to any question I had or was able to get the answer


quickly.


I also appreciate the ongoing financial support provided to me by the Graduate


Committee in the Department of Communication Sciences and Disorders, of which Dr.


Griffiths was a member.


I thank the chairman of the department, Dr. Brown, as well.


Sharon DiFino provided consultation on item selection for my German testing.


She also was an enormous help in recruiting participants for this study.


I really


appreciate all that she did for me. Additionally, I want to acknowledge Andrea Zilizi for

recording the German stimulus items for me. I would also like to thank the students who

volunteered to participate in this study. Without them, there would have been no data to


analyze.


I thank Marinela Capanu for providing me with assistance with data analysis. S

was very responsive to my numerous requests for "one more analysis" and I appreciate

all of her help.


In the speech and hearing clinic,

leGrand over the past few years. I truly


I have learned a great deal from Henriette


admire her clinical and administrative skills.


also have immense gratitude for the many pearls of wisdom she shared with me.

I don't know what I would have done without the support I received from Idella








procedures of the Graduate School.


I have also enjoyed the friendship we have shared.


Debbie has been very helpful to me, both professionally and personally.


I will miss our


chats. Although I see Addie less frequently, she helped me with the data collection phase


of my dissertation by helping me coordinate the room scheduling.


She also provides a


great dose of humor.

Finally, I wish to acknowledge my fellow students (current and former) for their


support, inspiration, and friendship throughout this lengthy process.


In particular I would


like to thank Sally Giess, Cynthia Puranik, Claudia Morelli, David Efros, Judy Wingate,

Samantha Lewis, Brian Kreisman, Nicole Kreisman, Nadia Abdulhaq, Jaumeiko Brown,

and everyone else who has helped to keep me motivated over the years.

I will miss the people I have met in Gainesville and will always fondly remember

my time at the University of Florida.

















TABLE OF CONTENTS
page
ACKNOW LEDGM ENTS ........................................ ........... ....... ......... ...... .......................... iii

LIST OF TA B IES................. ....... .................. ..... ... ........................................................... viii

LIST OF FIGURES .......................................................................................................... ... .... ix

ABSTRACT.......... ......................................... ....................................................................

CHAPTER


INTRODUCTION


Background of the Study
Rationale and Purpose....
Research Questions........
Hypotheses......................
Significance ....................
Limitations.....................


* t *S***** St t....................................*tSt*a.t*a# t***SC*******lS

*t...StC*St....................taCtStSSt*StStSS S C5..........................

...........~..............~..10


REVIEW OF THE LITERATURE ............... ............................................................ 11


Linguistic Coding Differences..
Triangle Model of Language Pr
The Meaning Processor.............
The Orthographic Processor .....
The Phonological Processor......
Speed of Processing..................
Persistent Deficits in Linguistic


S*#ttt)((taa StS~lttC~lt l) a tSC *t*SCtStl CttC C*~tltlt5~ b~4t*C C


.,..... ................ ...................... ..,,,..,,.............................


Linguistic Processing in Germaa
Summ ary ......., ...... ................


Setting .............................................
Particinants... .....R.............


.g........ 6..o........g ..............m...........O................ a.... ............36
..................at.......... C* et .7.
-317


METHODS ........................................


(









R E SU LTS ................... .............. ................... ................. ........... ....... ........ ............... 49

Sum m ary .... ... .0. ....9........ .... .. .. ...*.......t.S...t.. .. 4...*.........*. ... ... ..*..t.t **.*..* *...e ... 64

DISCUSSION ............................................................................................................66


Overview of Findings ........................................................... ...................................
Linguistic Coding Differences ................................ ....................................
Phonological Task Levels of Difficulty ...............................................................
Cross-Language Transfer of Skills ........................................................................
Summary of Research Questions..............................................................................


Profiles of Select Participants'


Limitations and Future Directions
Clinical Implications.....................
Conclusions...................................


Performance.


APPENDIX


A INSTITUTIONAL REVIEW BOARD (IRB) PROTOCOL .......................................86

B INFORMED CONSENT TO PARTICIPATE IN RESEARCH FORM.....................90

C QUESTIONNAIRE FILLED OUT BY PARTICIPANTS ..........................................92

D ENGLISH STIMULUS ITEMS (VOCABULARY AND SPELLING) .....................93

E GERMAN STIMULUS ITEMS (VOCABULARY AND SPELLING) .....................94

REFERENCES .........................................................................................................................5

BIOGRAPHICAL SKETCH .... ...... ......................................................................................105















LIST OF TABLES


Table

3-1

3-2

4-1


page

Listing and Description of Experimental Tasks in English and German.....................41

Stimulus Items for the Researcher-Designed Spoonerisms Task ................................44

Simple Statistics for the Four English Predictor Variables and the


German Composite.


................................50


Pearson Correlation Coefficients for the Four English Predictor Variables


and the German Composite.........


Contributors to the German Composite Score .... ... .......... ............. ................... ..........52

Simple Statistics for the English Language Measures .......................................................58

Pearson Correlation Coefficients for the English Language Measures .......................58

English Predictors of German Spelling........................................................................62

English Predictors of German Vocabulary .... ......................................................... 62

English Predictors of German RAN ................................................................... ........63


.............................5 1















LIST OF FIGURES


Triangle Model of Language Processing........................... ......... .................................. 18

Hypothesis of Granularity and Transparency.............................................. ..........34

Comparison of the Association between English Spelling and
the German Composite for Differential Ability Levels in
English Vocabulary and English RAN .................................................................54

Simple Linear Regression Plot of the Association between Spelling Clues and


the German Composite ....


Simple Linear Regression Plot of the Association between the Interaction of
English Spelling and Phoneme Reversal and the German Composite ........................60

Relative Contributions of English Predictors to German Dependent Variables..........63


Finure















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

THE INFLUENCE OF NATIVE LANGUAGE SKILLS ON
FOREIGN LANGUAGE LEARNING:


PHONOLOGICAL, ORTHOGRAPHIC,


AND SEMANTIC CONTRIBUTIONS


Gerianne Muldoon Gilligan

August 2004


Chair:


Linda J. Lombardino


Major Department:


Communication Sciences and Disorders


The primary goal of this study was to examine how native language skills


influence foreign language learning.


Additional goals included determining which native


language skills are most predictive of foreign language learning and investigating

whether spelling, vocabulary, and rapid automatized naming skills transfer between


native and foreign languages.


abilities.


These relationships were explored for a range of learning


Sixty-five college students enrolled in a first-semester German course


participated in the study.


Specific English language skills were measured to determine


the degree to which native language skills were predictive of proficiency in the


- -- --








language) and the dependent variables were select German orthographic, semantic, and

rapid naming skills.

Of the four primary predictor variables of English phonological skills, English

spelling, English vocabulary, and English rapid automatized naming, English spelling

was the best predictor of acquisition of select basic German skills (German composite


score).


Several interactions among the predictor variables also made significant


contributions to the German composite score.


English phonological skills of varying levels of difficulty were examined.


phonological tasks that involved elements of orthographic and/or semantic processing


(e.g.,


spelling clues) were more strongly associated with the German composite score


than were the simpler English phonological tasks.


Cross-language transfer of spelling


and vocabulary skills between English and German was also demonstrated in this study.

Data from this study (1) provide support for the Linguistic Coding Differences

Hypothesis, which states that native language skills influence foreign language learning;

(2) underscore the predictive power of phonologically-based skills; and (3) demonstrate

cross-language transfer of specific skills.















CHAPTER 1
INTRODUCTION

Background of the Study

Many colleges and universities in the United States require foreign language

courses for students seeking a bachelors degree in liberal arts (Ganschow, Myers, &


McColl (2000) pointed out that learning a second language enhances


linguistic development, social development, and cultural awareness.

training enhances native language development by improving one's

linguistic structures (words and sentences) of the native language. S


Foreign language


awareness of the

socially students who


study a foreign language are able to practice turn-taking and other social skills in the


language.


Finally, learning another language helps students to understand better the


culture of the countries where the target language is spoken.


Having a broad world view


is important for international relations in the areas of commerce and government.

The Standards for Foreign Language Learning (1996) identify five goal areas for


foreign language education:


communication, cultures, connections, comparisons, and


communities.


"Communication"


includes students understanding written and spoken


language, engaging in conversation, and expressing ideas.


"Cultures"


means


demonstrating an understanding of the culture where the target language is spoken.


if. -- a* a -I -1 -.. -


Roeger, 1989).








the culture where the target language is spoken.


Finally, "communities" relates to using


the foreign language outside of the school setting.

Spolsky (1989) developed a model of second language learning that identified

several conditions that influence the ease or difficulty with which another language is


learned.


First, the learner must be motivated to put forth the effort that is needed to learn


a new language.


Motivation then joins with other key intrinsic conditions including age,


personality traits, and previous knowledge of the target language.


Finally, an individual's


facility with language in general and other cognitive skills also affects the ease with


which he or she will learn a foreign language.


Having stronger skills in the native


language generally aids the acquisition of another language.


While Spolsky'


(1989)


model may have merit, the relative contribution of each element in the model has not

been examined empirically.

In the early 1990s, foreign language educators felt that difficulties learning a

foreign language were caused by affective variables such as anxiety, lack of motivation,


or poor learning strategies.


Several studies (Sparks, Ganschow & Javorsky, 1993;


Ganschow et al


., 1994; Javorsky, Sparks,


& Ganschow, 1992) challenged this view with


support that affective differences are the result of language learning differences, and not

the cause.

Dinklage (1971) was among the first to describe foreign language learning

difficulties when he wrote about students at Harvard University who were unable to pass


the foreign language requirement.


He discussed students'


errors in three areas: spelling








language learning disability did not exist in isolation but co-occurred with native


language deficits.


He reported that some of the students who had experienced difficulty


had been diagnosed with learning disabilities previously although they believed that they


had "overcome" the disability.


We now know that language-based learning disabilities


persist throughout life, although they may look different at different points in time

(Shaywitz, 2003).

The areas of weakness described by Dinklage (1971) reflect, to a large degree,


deficient phonological processing skills.


Difficulty processing information at the


phonological (sound) level is now considered a core deficit in developmental dyslexia.

Shaywitz (2003) suggested that, "Persistent difficulties in learning a foreign language


provide an important clue that a student may be dyslexic"


(p. 116).


During the last 1


years,


the research of Sparks, Ganschow, and colleagues has


supported their hypothesis that an individual's ability to learn a foreign language is

strongly influenced by his or her native language skills. Initially they proposed this idea


as the Linguistic Coding Deficit Hypothesis and claimed that variability in foreign

language acquisition was accounted for by individual differences in phonological,

syntactic, and semantic components of native language, as well as verbal memory


(Sparks,


Ganschow, & Pohlman, 1989; Sparks & Ganschow, 1991).


They argued that


inefficient processing of language codes will manifest across languages and that

problems in one (or more) of the areas of language will be evident in the native language

as well as the foreign language.








belief that there is rarely a strict cut-offpoint for a deficit (Ganschow & Sparks, 1995;


Ganschow, Sparks, Javorsky, Pohlman, & Bishop-Marbury, 1991

1993a; Sparks, Ganschow, Javorsky, Pohlman, & Patton, 1992a).


many other skills, occur on a continuum.


Sparks & Ganschow,

Linguistic skills, like


Thus an emphasis on differences emphasizes


individual variation rather than disability.

As noted above, phonological deficits are present in learning disabilities such as


developmental dyslexia.


Individuals with dyslexia typically have extreme difficulty


learning a foreign language (Shaywitz, 2003,


p. 124).


Phonological differences can also


be subtle (not severe enough to be considered "dyslexia"), but can have an effect on


foreign language learning.


Sparks et al. (1998) found no significant differences in the


profiles of students with diagnosed learning disabilities and those who were not


diagnosed but struggling to learn foreign language (called "at-risk").


At times it is not


until a student exhibits an atypical degree of difficulty learning a foreign language at the

college level that he or she is diagnosed with a learning disability.

Downey and Snyder (2000) described common characteristics of"at-risk" foreign

language learners, who are students that struggle to learn a foreign language but have not


been diagnosed with a learning disability.


Typically these students had academic


difficulties in high school.


They avoided math, science, and foreign language.


Many


began college at the community college or junior college level and then transferred to a


four-year school.


Often these students are "nontraditional"


(over


years old) and have


had a history of foreign language failure.


They typically described themselves as hard





5


Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities


Act protect students with identified disabilities.


access to programs and services.


These laws focus on ensuring equal


Under these laws, colleges and universities are required


to provide reasonable accommodations so that students with disabilities can access the


same programs that are available to their non-disabled peers.


Among the


accommodations that students enrolled in foreign language courses may need are


extended test-taking time, use of a note-taker, and tutoring.


Waivers and substitutions for


the foreign language courses may also be an option in some colleges and universities;


however they are not always available.


In a recent landmark court case, a judge ruled


that a school could determine whether eliminating a required course, such as foreign


language,


"fundamentally alters the nature"


of the degree (Guckenberger v.


Boston


University,


1998, p. 19).


The Americans with Disabilities Act and Section 504 of the


Rehabilitation Act of 1973 do not require postsecondary institutions to eliminate essential


elements of the curricula (Guckenberger v.


Boston University,


1997, p.95).


Guckenberger v. Boston University (1998) reinforced the court's


ruling that a


college or university is not obligated to grant a course waiver for a student with a


diagnosed disability.


Therefore a student who experiences difficulty with foreign


language should take care in selecting a school and/or major that does not require study

of a foreign language or attend a school with a proactive office of disabilities which can


grant a course waiver or substitution.


requirement.


Another option is a modified foreign language


A program of this type has been developed and implemented at the








foreign language courses.


While taking these courses students receive direct teaching of


the phonological/orthographic system, extra time for exams and quizzes, decreased


quantity of content, and extensive pretest preparation.


Enrollment is limited and students


must sign a contract indicating that they agree to attend every class.


Students must also


take a decreased academic load when studying foreign language, participate in class

discussions, and attend weekly tutoring sessions (Downey & Snyder, 2000).

If foreign language learning differences were better understood, more colleges

and universities might be willing to provide courses that are adapted for students who are


struggling.


Students could then avoid some of the stress caused by college-level foreign


language courses; yet still fulfill the degree requirements of the institution.

Rationale and Purpose

Previous work addressing the relationship between native language skills and

foreign language learning has primarily focused on individuals experiencing difficulty


learning a second language.


The Linguistic Coding Differences Hypothesis states that


native language skills are the foundation for foreign language learning and that problems

with one language skill (such as phonological/orthographic processing) will impact both

the native and foreign language learning systems (Sparks, Ganschow, & Pohlman, 1989).


When students who struggled with foreign language courses (sometimes called


were compared with students who did wel


"at-risk")


in foreign language courses, the groups


showed significant differences in performance on measures of phonology-orthography

(such as word recognition and spelling) but not on semantics (Sparks, Ganschow,








The primary goal of the current study was examine how native language skills,


specifically in the areas of phonology


language learning.


orthography, and vocabulary, contribute to foreign


Looking at these native language skills can provide a better


understanding of individual variation among students enrolled in foreign language


courses.


This study examined specific language skills that have been identified as being


correlated with foreign language learning.


This study expands on previous work and


looks at foreign language learners with a wider range of abilities.


If native language


skills are the foundation for foreign language learning, individuals with native language

weaknesses should experience difficulty learning a foreign language while those with

strengths in native language should be very successful foreign language learners.

Examination of students with both strong and weak native language skills helps us to

better understand individual differences in foreign language learning, across the spectrum

of learning abilities.


This study also looked at phonological processing skills in detail.


studies identified phonological processing skills in a broad way (i.e.,


current study included a range of phonological processing skills,


Previous


spelling).


including tasks that


integrated phonological processing with orthographic and semantic processing (e.g.,


spelling clues).


The strongest predictors of foreign language skills are identified.


The third goal of this study was to examine the idea of cross-language transfer of

vocabulary, spelling, and rapid automatized naming skills between native and foreign


language.


Most of the previous research in this area has looked at the correlation of





8

naming skills to determine if the cross-language transfer relationship holds in these areas

as well.


Research Questions


Is there a relationship between native English language skills in (a) phonological

knowledge, (b) orthographic knowledge, (c) semantic knowledge, and (d) speed

of processing; and German foreign language performance, as measured by a

composite score on a battery of tests in German?

Which specific phonological-orthographic skills (elision, nonword repetition,

spelling, spoonerisms, rapid automatized naming, phoneme reversal, spelling

clues, number learning) best predict performance in foreign language (German

composite score)?

Do native English language skills in vocabulary, spelling, and rapid automatized

naming predict foreign language (German) performance in these same areas,

indicating cross-language transfer of skills?

Hypotheses

The research questions motivated several hypotheses, which are listed below.

Based on the Linguistic Coding Differences Hypothesis, it is hypothesized that

native English language phonological skills will be associated with German

foreign language performance after one semester of instruction.

With respect to overall German foreign language proficiency (German composite


score), native English language phonological and orthographic (i.e.,


spelling)








Phonological-orthographic skills which are more difficult (spelling, spoonerisms,

phoneme reversal, number learning, and spelling clues) will be better predictors

of foreign language proficiency (as measured by German composite score) in

college students than easier phonological-orthographic measures (elision,

nonword repetition, and rapid automatized naming).

German spelling skills will be influenced by English spelling skills.

German vocabulary will be influenced by English vocabulary skills.

German rapid automatized naming will be influenced by English rapid

automatized naming ability.

Significance

Previous work in foreign language difficulties has focused on group differences


between students with learning disabilities and their non-learning disabled peers.


Several


differences in native language abilities between the two groups have been identified.

This study will build on previous work by emphasizing the continuum of language skills


and how relative strengths and weaknesses contribute to foreign language learning.


study also takes an in-depth look at the influence of phonological processing skills at


varying levels of difficulty.


Additionally, this study extends the concept of cross-


language transfer of skills to the spelling, vocabulary, and rapid automatized naming


domains.


Previous work focused on cross-language transfer of phonological skills.


Because foreign language is required for many university degrees, it is important


to understand the skills that are necessary for successful completion.


If a student is








also receive a failing grade, which will affect his or her grade point average and may


result in diminished self-esteem.


If the student can better understand the nature of the


learning difference, he or she will be able to be a better self-advocate.

Understanding the contribution of native language skills can help in the


development of modified or remedial foreign language instructional strategies.


foreign language courses can be taught in ways that match students'


maximize their potential for completing the course.


Modified


learning abilities and


When surveyed, 90% of college


students who received waivers for foreign language courses would have enrolled in


'modified'


foreign language courses if the courses were available (Ganschow,


Philips, &


Schneider, 2000).

Limitations

Native language skills are not the only area contributing to success or failure in


foreign language courses.


Good or poor native language skills will not definitively


predict how a student will do in foreign language courses.


As Spolsky (1989) pointed


out, strong native language skills are necessary, but they are not a sufficient explanation

for successful foreign language learning.

Additionally, this study was limited to college students in their first semester of


German


The results may not generalize to younger foreign language learners, those


learning in an immersion environment (versus a classroom environment), or individuals

who are learning a more versus less transparent (one-to-one grapheme/phoneme

correspondences) language.















CHAPTER


REVIEW OF THE LITERATURE

The purpose of this study is to describe how native English language skills


contribute to foreign language learning.


The chapter begins with a review of studies


related to the Linguistic Coding Differences Hypothesis (LCDH).


An overview of


research studies related to semantic processing, orthographic processing, phonological


processing, and processing speed is included.


Finally, a discussion of processing deficits


in English and German is provided.

Linguistic Coding Differences

Background

Individual differences in foreign language learning were described as early as

1959 when Carroll and Sapon developed the Modern Language Aptitude Test (MLAT)


(Carroll & Sapon, 1959).


This test, designed to predict an individual'


strength or


struggle when studying a foreign language, is still in use.


evaluate the strengths and weaknesses of an individual'


English.


The test can be used to

memory and language skills in


The MLAT score may be useful for program placement according to ability.


Further, the MLAT may be an important component of an evaluation for learning

disabilities; however a score on one test is not enough to make a diagnosis.








foreign language, the students had average to above average intelligence and passing


grades in other courses.


The authors hypothesized that deficits in auditory ability (ability


to deal with sounds) were responsible for the foreign language learning difficulties.

Dinklage (1971) suggested that difficulties learning foreign languages were


grounded in native language differences.


He described Harvard University students who


were bright and successful in their other courses, but unable to pass the foreign language


requirement.


He postulated that the students'


difficulties fit into one of three groups.


The first group had problems with written language (reading and spelling).


group had "auditory discrimination"


The second


deficits, which included difficulty telling the


difference between similar sounds, syllables, and words in the foreign language.


third group had problems remembering what they heard (Dinklage, 1971).


several researchers have written about phonological processing (e.g.,


Since 1971


Wagner &


Torgesen, 1987, Wagner,


Torgesen, Laughon, Simmons,


&Rashotte, 1993).


Each of the


groups described by Dinklage appeared to have difficulty with the phonological aspects


of language.


Some of these students had been diagnosed with dyslexia in childhood but


believed that they had "overcome"


it through hard work.


When faced with a new sound


system in the foreign language classroom, the old problems resurfaced.

Prior to the 1980s, discussion of foreign language learning difficulties was limited


to case studies.


The first empirical study on foreign language learning abilities was


published in 1987 when Gajar compared the performance of students with learning


disabilities (LD) with non-LD peers on the MLAT


. Students who had been diagnosed








Sparks, Ganschow, and Pohlman (1989) later introduced the Linguistic Coding


Deficits Hypothesis, which was based on Vellutino and Scanlon's


linguistic coding.


(1986) description of


Linguistic coding consists of three components: phonological


(processing language at the sound/symbol level), syntactic (grammatical and structural


forms of language), and semantic (meanings of words and concepts) (Vellutino, 1987


Vellutino & Scanlon, 1986).


One assumption of the Linguistic Coding Deficits


Hypothesis is that if an individual has difficulty in any of these areas of their native


language, he or she will have problems learning a second language.


The authors assert


that native language phonological problems will have an "immediate and significant


impact" on foreign language learning.


Individuals with syntactic (grammar) problems


(without phonological deficits) are usually able to pass one or two semesters of foreign


language course work before encountering remarkable difficulty.


Students with semantic


(vocabulary) deficits generally experience problems when the course work shifts from

written work to conversation and functional use of the language (Sparks, Ganschow, &

Pohlman, 1989).

Since development of the Linguistic Coding Deficits Hypothesis, Sparks,

Ganschow, and colleagues have demonstrated its efficacy and application by studying


different populations, such as adolescents and adults in academic settings.


They began


by describing the differences between good and poor foreign language learners at the


high school (Sparks,


Ganschow, Javorsky, Pohlman, & Patton, 1992b; Sparks &


Ganschow, 1993b) and college (Ganschow, Sparks, Javorsky,


Pohlman, & Bishop-








similar vocabulary skills and nonverbal intelligence.


However, they differed in


phonological/orthographic skills (word recognition, spelling, pseudoword reading) and


foreign language aptitude (MLAT).


Students who achieved higher foreign language


grades also had significantly stronger native language and foreign language aptitude

skills than students who achieved lower grades, whether or not the students had been


diagnosed with LD (Ganschow et al.,


1991


, 1994; Ganschow & Sparks, 1996).


Sparks, Ganschow, and colleagues published several studies in which they

reported that linguistic skills, not affective characteristics (such as low motivation, high

anxiety, and poor attitude), were responsible for the differences in foreign language

learning ability between LD and non-LD students (Sparks, Ganschow & Javorsky, 1993;

Javorsky, Sparks, & Ganschow, 1992; Ganschow & Sparks, 1996; Ganschow et al.,


1994).


They posited that the affective differences between good and poor foreign


language learners were likely to be the result of difficulties with language skills.


These


studies provided additional support for their hypothesis that foreign language learning

problems are rooted in native language deficits.


As defined by the Individuals


with Disabilities Education Act (1997), diagnosis of


a learning disability typically involves a significant discrepancy between a student's

intellectual ability (as measured by an IQ test) and academic performance in one or more


of the following areas:


oral expression, listening comprehension, written expression,


basic reading skill (such as word recognition and decoding), reading comprehension,


mathematics calculation, and mathematics reasoning.


Without a discrepancy, a student








without a diagnosis who were struggling to learn a foreign language (called "at-risk").

They found no difference between the two groups on most language and foreign language


aptitude measures (Sparks, Ganschow, Javorsky,


Pohlman, & Patton, 1992b).


Because


there are rarely strict cut-off points to determine the absence or presence of a deficit, the

term Linguistic Coding Deficits Hypothesis was changed to Linguistic Coding

Differences Hypothesis (LCDH) to reflect the continuum of difficulties with foreign


language learning (Sparks 1995).


Difficulties can range from mild to severe.


Predictions from Native Language to Foreign Language

Much of the support for the LCDH has come from group comparisons of high-


school and college students enrolled in foreign language courses.


When successful


foreign language (L2) learners were compared with students who did poorly or failed an

L2 course (called "at-risk"), at-risk L2 learners had significantly lower levels of native


language (L1) skill in phonological-orthographic areas and L2 aptitude (MLAT).


At-risk


students (with and without identified learning disabilities) performed significantly worse


than successful students on phonological-orthographic processing and L


aptitude


measures (Ganschow & Sparks, 1995


Ganschow, Sparks,


Javorsky, Pohlman, & Bishop-


Marbury, 1991


Sparks, Ganschow,


Artzer, & Patton, 1997).


Findings from some predictive studies have also been published to support the


idea that native language skills are the foundation for foreign language learning.


Ganschow


Sparks,


, and Patton (1995) observed that eighth grade English course grades predicted


foreign-language learning the following year.


Later, Sparks, Ganschow, Patton, Artzer,





1i

vocabulary, and foreign language word decoding were predictive of overall second-year

foreign language proficiency in high school students.

Recently, Meschyan and Hernandez (2002) studied the language skills of 80

college-age adults enrolled in an introductory Spanish course and observed a relationship


between L1 decoding (a phonological skill), L2 competency and course grade.


They


administered several tests in L1 and L2 and analyzed the data via multiple regression


methodology.


L1 decoding predicted L1 competency (as measured by score on the


verbal portion of the Scholastic Aptitude Test), however the relationship was mediated by


vocabulary skill


Furthermore, they found that L1 decoding predicted L2 decoding as


well as course grade.


Durgunoglu, Nagy,


and Hancin-Bhatt (1993) studied the relationship between


native language (Spanish) skills and foreign language (English) reading in first-grade


children.


They found that Ll phonological awareness and word reading predicted L2


word and nonword reading.


They explained that "cross-language transfer" of


phonological abilities was responsible for the relationship.

Cheung (1996) studied twelve-year-old Chinese children who were learning

English and found that for students with greater L2 vocabulary, phonological ability was


less predictive of L2 vocabulary learning.


For children with weaker L2 vocabulary skills,


there was a strong relationship between phonological ability and L2 vocabulary


They


concluded that new word learning is mediated by both phonological ability and existing

vocabulary knowledge.








foreign language learning.


She followed nine- and ten-year-old children for a three-year


period and found that L2 grades at the end of the period were related to phonological

skills in the area of nonword repetition (typically considered to be a measure of


phonological memory).


Nonword repetition ability correlated with degree of success in


learning a foreign language.

Triangle Model of Language Processing

Seidenberg and McClelland introduced a frequently cited model of language


processing in 1989.


This particular model deals with written language processing (i.e.,


skilled reading), and the connectionist framework of the model underscores the

interdependence of semantics, orthography, and phonology. The model is commonly


referred to as a "triangle model.

of three processing nodes. The


The triangle model focuses on the interconnectedness


meaning processor, orthographic processor, and


phonological processor each share reciprocal connections with the other two processors.

The reciprocal connections between the processors represent sharing of information

(Metsala & Brown, 1998).


Semantics relates to the study of word meanings.


oral communication is to express meaning.


The purpose of any written and


Adams (1990) explained that in order for


meaning to be efficiently processed, the phonological and/or orthographic input must be

of high quality (accurate) and the connections between the meaning processor and the


phonological and/or orthographic processor must be strong.


Semantic processing deficits


affect oral (spoken) and written (reading) language comprehension.








phonological processor are each connected to the meaning processor, and they are also


connected to each other. These two processors receive the visual and auditory input of

written and oral language. After input is received, connections with the meaning


processor help an individual to comprehend the meaning of the transmitted message.

With experience the process becomes refined and more efficient.


Connections between the processors are reciprocal.


are sent both to and from the meaning processor.


Signals about word meanings


The meaning processor sends


information to the orthographic and the phonological processors.


A strong semantic base


helps language to be efficiently processed both orally and in writing.


Print


Speech








Each of the three nodes in the triangle model makes a unique and necessary


contribution to the language processing system.


weaknesses in the system.


The processors can also compensate for


If a deficit exists at the level of one of the processors, the


other two processors can bolster the system so that language can still be understood or


produced.


For example, an individual can compensate for deficits in phonological


processing (such as difficulty sounding out written words) with superior orthographic

processing (familiarity with the visual forms of words) and/or superior meaning

processing (strong vocabulary and overall language skills).

The processors comprising the triangle model will be discussed in greater detail in


the following sections.


The relationship between the three processors will be also be


discussed, as well as the effect of deficits in the processors.

The Meaning Processor


As noted above, semantics relates to the study of word meanings.


Gathercole and


colleagues described a relationship between semantics and some areas of phonological


processmg.


In four- to six-year-old children without language disorders, phonological


working memory (as measured by nonword repetition ability) and vocabulary growth

were highly correlated (Gathercole & Baddeley, 1990b; Gathercole, Willis, Emslie, &


Baddeley, 1992).


Nonword repetition abilities (good and poor) were associated with


receptive vocabulary skill.


This association was also present for children with specific


language impairment (Gathercole & Baddeley, 1989; 1990a; 1993).

To determine the nature of the correlation between phonological short-term





20


measure of phonological short-term memory) at age four accurately predicted receptive


vocabulary skills at age five.

repetition at age five. The ai


However vocabulary at age four did not predict nonword


Ithors concluded that phonological short-term memory


influences long-term storage of phonological information, which is necessary when


learning new vocabulary words (Gathercole, Willis, & Baddeley, 1991).


Gathercole,


Hitch, Service, and Martin (1997) also noted that both phonological short-term memory

and existing vocabulary skills contributed to new word learning in five-year-old children.

They explained that if an individual knows more vocabulary words he or she will be able

to learn a new word by finding phonological approximations in words that are already

known (Gathercole & Baddeley, 1993)

Walley (1993) and Metsala (1999) also discussed the relationship between


semantics and phonology.


The Lexical Restructuring Hypothesis proposed that as


vocabulary develops, phonological representations become increasingly refined


(segmented).


Vocabulary growth improves phonological skills.


This hypothesis is not


supported in the case of individuals with developmental dyslexia who have strong


vocabulary skills.


According to the Lexical Restructuring Hypothesis a poor vocabulary


would imply phonological difficulties, and a large vocabulary would imply an improved


ability to segment words into their component sounds.


However in the case of a dyslexic


child, as Snowling (2000) noted, a large vocabulary is not necessarily associated with


strong phonological representations.


Individuals with developmental dyslexia have


relatively good vocabulary knowledge in the face of poor phonological processing skills.








The Orthographic Processor

The orthographic processor recognizes strings of letters as familiar patterns


(Adams, 1990).


Efficiency of the orthographic processor depends on strong spelling


abilities. Familiarity with spelling patterns helps an individual to recognize words

quickly.

Spelling integrates phonological, morphological, semantic, and orthographic


knowledge (Fischer, Shankweiler, & Liberman, 1985).


Spelling differs from reading in


that spelling requires encoding, which is segmenting sounds into words, translating

phonemes into corresponding graphemes, and then blending the parts into a written word

(Gillingham & Stillman, 1997).

Children who are able to segment words into their component sounds tend to be

better spellers than children who have difficulty with phoneme segmentation tasks


(Tunmer & Rohl, 1991).


Treiman (1997) also found that in kindergarten and first-grade


children learning to spell, early spelling errors reflected use of phonetic strategies.

Children did not rely on orthographic knowledge but on their knowledge of the


phonological structure of the words, producing "errors"


such as 'jres'


for 'dress'


This


underscores the relationship between phonological awareness and spelling orthographicc)

development.

Poor spellers cannot rely on their phonological processing skills to accurately


spell words.


Bruck (1990) compared college students with a history of dyslexia to age-


and reading-matched controls.


She reported that the students with a history of dyslexia








orthographic information they encountered, attempting to rely on their (weak) sound-

spelling strategies to gain meaning.

For younger children learning to read and spell, phonological awareness skills


affect spelling abilities.


In a longitudinal study, Stuart and Masterson (1992) assessed


phonological abilities at age four and found that these abilities predicted spelling


performance at age ten (six years later). Both strong and weak pre-reading phonological

abilities were predictive of later spelling.

The Phonological Processor


Phonological processing is defined as an individual's


mental operations that make


use of the phonological or sound structure of oral language when he or she is learning


how to decode written language (Torgesen, Wagner,


& Rashotte, 1994, p.


276).


It relates


to how a communicator uses sound-level information to produce oral and written


language and make sense of what is heard.


Phonological processing skills include


phonological awareness, phonological recoding in lexical access, and phonological


recoding in working memory (Share,


1995; Stanovich, 1988; Wagner & Torgesen, 1987).


While related to each other, each component represents a different ability.

Phonological awareness


Phonological awareness is a measure of an individual's


ability to judge the


number, order, and identity of phonemes (sounds) in words (Liberman, 1973


Shankweiler, Fischer, & Carter 1974


Liberman,


Individuals who are successful at phonological awareness tasks have access to well-


Lindamood, Bell, & Lindamood, 1992).





23


phonemes together) and children with strong phonological awareness skills typically

acquire phonics skills more efficiently than children with weaker phonological awareness


(Catts & Kamhi, 1999).


Phonological awareness is closely associated with reading


because in order to understand the letter-sound correspondences and to blend the sounds

into words, a reader must understand that words are made up of individual sounds


(Tunmer & Rohl, 1991).


Phonological awareness encompasses skills such as word-level


awareness (number of syllables) and syllabic structure awareness onsetss and rimes).

In young children who are learning to read, phonological awareness skills are


often associated with early reading ability.


Children with stronger phonological


awareness skills prior to reading instruction typically are more successful when reading

instruction begins (Bradley & Bryant, 1983; Stanovich, Cunningham, & Cramer, 1984).

Early reading involves learning how to sound out or "decode" words, which relies on the


ability to analyze (segment) and synthesize (blend) sounds and syllables.


Ball (1996)


explained that at the early stages of learning to read, the relationship between


phonological awareness and reading is causal, but shifts to 'mutual facilitation'


reading develops.


82) as


Experience with reading helps to improve phonological awareness.


Intact phonological awareness skills are a necessary but not sufficient condition for

learning to read (Ball & Blachman, 1988; Bruck, 1993).

Crombie and McColl (2001) explained that phonological awareness problems


affect foreign language learning in the following ways:


pronunciation, recognizing


familiar words and phrases and confusion of similar sounding words, reading aloud.








language should be introduced early and in a multisensory way (visually, auditorally,


written, etc.).


Audio tapes and practice cards are recommended for reinforcement of


pronunciation and vocabulary (Crombie & McColl, 2001).

Phonological Working Memory

Cowan (1996) explained that short-term memory refers to the aspect of memory


that lasts only a few seconds after input is received.


Working memory refers to short-


term memory when it is used to perform a task (such as solving a problem).

Phonological working memory is a component of short-term memory and involves the

retention of phonologically-coded verbal information in a temporary memory system.

Information is stored in memory by sound-based phonological properties (Gathercole,


1998).


Researchers are most interested in measuring the strength of the store of


information.


Phonological memory is typically evaluated in tasks involving non-word


repetition or repetition of a span of digits, letters, or words.


According to Baddeley and Hitch's


(1974) working memory model (revised by


Baddeley in 1986), working memory has three components:

phonological loop, and the visuospatial sketchpad. The ceni


the central executive, the


tral executive controls the


flow of information through the system and the visual and phonological systems


temporarily process and retain the visual and verbal input.


In terms of language learning,


the phonological system is of primary interest.

The phonological loop consists of the phonological store and a subvocal rehearsal


process (Baddeley, 1986).


Verbal information (either auditory or written) enters the








the decaying representations in the phonological store.


develops during childhood.


The subvocal rehearsal process


Gathercole and Hitch (1993) reported that this process does


not emerge until age seven.

Nonword repetition is associated with language abilities in typically developing


children (Baddeley, Gathercole, & Papagno,


1997).


1998; Gathercole, Hitch, Service, & Martin,


In four-year-old children, non-word repetition ability was strongly correlated with


vocabulary knowledge (Gathercole, Willis,


Emslie, & Baddeley, 1992).


Gathercole,


Service, Hitch, Adams, and Martin (1999) also found an association between

phonological memory (as measured by non-word repetition) and vocabulary in adolescent

subjects.

Deficits in short-term memory are associated with the presence of language


impairment (Bishop, North, & Donlan, 1996; Gillam & van Kleeck, 1996).


Children


with specific language impairment performed poorly on non-word repetition tasks


(Gathercole & Baddeley, 1990a).


Dollaghan and Campbell (1998) found that children


enrolled in language therapy did worse on non-word repetition tests than age-matched,


typically developing peers.


Campbell, Dollaghan, Needleman, and Janosky (1997)


suggested that linguistic processing tasks, such as non-word repetition, are a culturally


sensitive way to


assess


language disorders.


Ellis Weismer, Tomblin, Zhang, Buckwalter,


Chynoweth, and Jones (2000) agreed with this suggestion.


They evaluated the nonword


repetition abilities of


1 second graders.


Children with diagnosed language impairment


and children enrolled in language therapy had deficient nonword repetition skills








identify language disorders.


Deficits in phonological memory have also been found to be


associated with severe reading disabilities (Baddeley, 1986).

Gathercole and Thorn (1998) explained that learning the sound structures of new

vocabulary in native and foreign language seems to be mediated by the phonological


loop.


They noted that gifted language learners (i.e., polyglots) have superior


phonological short-term memory skills, as measured by nonword repetition. Vallar and

Papagno (1995) also discussed verbal short-term memory abilities of polyglots. When


they compared native speakers of Italian who knew several other languages with non-

polyglots they found that the groups did not differ in general intelligence, visuo-spatial

short-term memory, or paired-associate learning of Italian (native language) words.

However the polyglots had exceptional abilities in the areas of verbal short-term memory,

measured by auditory digit span and nonword repetition, and paired-associate learning of


new (Russian) words.


The authors concluded that phonological working memory is


closely associated with acquisition of foreign languages.

Limited or inaccurate representations in memory may affect foreign language

learning in the areas of vocabulary learning and repetition of multisyllabic words.

Strategies to deal with these difficulties include presenting/learning information in


smaller chunks and allowing extra time for recall.


Extensive review of new material is


also helpful (Crombie & McColl, 2001).

Rapid Automatized Naming

Although researchers seem to agree that deficits in rapid automatized naming








by processing speech or sequencing.


During the RAN task the examinee must quickly


name an array of familiar items (letters, numerals, objects) during which they are timed.

The task requires rapid access of familiar symbols stored in long-term memory as


phonological representations (Wagner,


Torgesen, & Rashotte, 1994).


Individual with


phonological deficits have poorly specified representations of words and sounds,

resulting in difficulty accessing and articulating the names of familiar symbols

(Baddeley, 1986; Share, 1995; Wagner & Torgesen, 1987).

However, the poor quality of the phonological representations may not be solely


responsible for deficits in RAN.

strictly a phonological skill. In


Some researchers disagree with the idea of RAN as


addition to accessing phonological codes, the task


requires attention, visual recognition, and articulation (Manis, Seidenberg, & Doi, 1999).

Additionally, RAN and phonological awareness have been shown to make independent

contributions to reading ability (Badian, 1993; Bowers, 1995; Torgesen, Wagner, &


Rashotte, 1997).


Processing speed deficits will be discussed in greater detail in the


following section.

Efficient retrieval of phonological codes associated with phonemes and words

influences how phonological information is used during word reading (Baddeley, 1986).

Deficiencies in rapid naming are often associated with reading rate and fluency problems


(Bowers,


Sunseth, & Golden, 1999; Manis, Seidenberg, & Doi, 1999).


Manis,


Seidenberg, and Doi (1999) suggested that RAN (the ability to rapidly


access


arbitrary


associations) may influence early reading skills while phonological awareness affects





28


Speed of Processing

Manis, Seidenberg, and Doi (1999) studied RAN in the framework of Seidenberg


and McClelland'


(1989) connectionist model described above.


According to the


connectionist model, RAN is not an aspect of phonological processing.


RAN relates to


the learning of arbitrary mappings between print orthographicc processing) and sound


(phonological processing).


Rather than tapping into a processing node, the RAN task


corresponds with the connections between the orthographic processing node and the


phonological processing node (Manis,


Seidenberg, & Doi, 1999).


This work agrees with Wolf and Bowers'


(1999) double deficit hypothesis, which


proposes that timing deficits such as slow letter recognition and rapid naming are


independent of phonological deficits.


While there is some overlapping variance, the


correlation between RAN and other phonological skills such as phonological awareness


and phonological memory is weak.


Correlations between phonological awareness and


phonological short-term memory were stronger.

The double deficit hypothesis states that children with reading problems can have


deficits in naming speed and/or phonological awareness. Children with naming speed

deficits did poorly on measures of rate and comprehension. They were not deficient in


nonword reading


Children with phonological awareness deficits did poorly with word


and nonword reading accuracy as well as comprehension.


Children with single deficits


were generally less impaired than children with double deficits (Bowers, 1995


Wolf, 1993


Bowers &


Wolf & Bowers, 1999, 2000).








continuous information.


Extra response time and extra time for examinations are


strategies to deal with deficits in speed of processing.

Persistent Deficits in Linguistic Processing

Individuals with developmental dyslexia have deficits in one, two, or all three


areas of phonological processing.


Deficits in phonological processing are often


associated with difficulty learning to read (Share, 1995


Stanovich, 1988). In a meta-


analysis of several articles related to prediction of reading skill, Siegel (1992) found that

early phonological processing skills are the best predictor of later reading skill.

Phonological processing is a better predictor of reading than are syntactic skills and

working memory.


Wagner, Torgesen, and Rashotte (1994) explained that an individual'


phonological processing skills are relatively stable characteristics that do not vary with


typical academic instruction.


Phonological processing deficits persist in older readers


with a history of reading struggle, although these individuals have learned to read.


According to Gottardo, Siegel, and Stanovich (1997),


these "compensated dyslexics"


continue to have difficulty sounding out unfamiliar words, spelling, and reading fluently.


Problems forming phonological representations (Brady & Shankweiler, 1991


1981) may also affect an individual'

Ganschow, & Pohlman, 1989). Whc


Snowling,


ability to learn a foreign language (Sparks,


en faced with a new code system, the old problems


with sound-level (phonological) information seem to re-surface.

Phonological processing abilities exist along a continuum (Shaywitz, 1992).








individuals with foreign language learning problems have a previous diagnosis of a


learning disability.


However when they compared test performance of individuals with


and without identified learning disabilities, there were no differences in native language

skills and foreign language aptitude between individuals diagnosed with specific learning


disabilities and those considered "at risk.


In general, however, it is not merely the


presence of a phonological deficit but also the severity of this deficit that affects reading

and spelling (Snowling, Goulandris & Stackhouse, 1994).


Over time, phonological awareness is a relatively stable skill.


Poor phonological


awareness persists in compensated dyslexics who have learned to read (Frith, 1997).

Some of the consequences of poor phonological awareness include difficulty sounding


out unfamiliar words and spelling problems.


Wilson and Lesaux (2001) sought to


determine the nature of the phonological processing deficits that persist.


They compared


28 college students with a history of early and persistent reading problems with 31


controls, with no history of reading problems


Although the "dyslexia group


performance on phonological tasks was in the average range, it was significantly lower


that of the control group.


This effect was most pronounced on tasks involving phoneme


deletion, a phonological segmentation and manipulation task, and spoonerisms, which

involves both phoneme segmentation and time.

Snowling, Nation, Moxham, Gallagher, and Frith (1997) found that college

students with dyslexia performed worse than age- and educationally-matched controls on


all measures of phonological processing.


The students with dyslexia had more difficulty





31

find differences in word and non-word repetition in these groups of college students;

however when more demands were placed on short-term memory (e.g., retention of the

novel items), the dyslexic college students had more difficulty.

In a similar study of college students, Downey, Snyder, and Hill (2000) compared

the performance of students enrolled in modified foreign language classes with their


peers in regular foreign language classes.


The students in the modified foreign language


classes either had a diagnosis of a learning disability or repeatedly failed foreign


language courses.


The students in the modified courses performed significantly worse on


language aptitude tests, spelling, and word recognition.


No differences were observed


between the groups on reading comprehension and vocabulary.

Finally, Gallagher, Laxon, Armstrong, and Frith (1996) studied an interesting

group of college-age students who had a history of dyslexia but received early


identification, intervention, and education in private schools.

motivated and had successfully passed rigorous examinations.


These students were highly

I The authors noted that


while these students had well-compensated for their dyslexia, some problems persisted.

When compared with controls, the students with a history of dyslexia performed

significantly worse than age- and education-matched controls in the areas ofnonword

reading and spelling accuracy; and spoonerisms, digit naming, and speech rate.

Linguistic Processing in German

Recently several investigators have examined ways in which phonological


processing deficits (including dyslexia) are manifested in other languages.


German is a








(auditory signals).


Because each sound generally has only one written representation in


German, individuals with phonological processing deficits generally are able to learn to


read quite accurately.


Most education systems in German speaking countries utilize a


straightforward phonics approach when teaching children to read.


Goulandris (2003)


emphasized that both the transparency of a language and the educational methodology

used to teach children to read influence the extent to which a phonological processing

deficit manifests as a disability.

When Landerl, Wimmer, and Frith (1997) compared the reading abilities of

English and German children with dyslexia, the English-speaking children consistently


made more errors than the German-speaking children.


For example, German children


read three-syllable words more accurately than the English children read one-syllable


words.


Also, the German children with dyslexia read real words as accurately as the


German control group.


The authors concluded that orthographic consistency has an


important influence on dyslexic children's


reading performance.


Wimmer and Mayringer (2002) described dissociations between reading and


spelling difficulties in third-grade German-speaking children.


Some children exhibited


deficits in either reading or spelling with stronger skills in the other area.


The authors


explained that poor reading and adequate spelling was associated with a deficit in

processing speed, while spelling deficits in light of normal reading abilities were the

result of phonological processing deficits.

Landerl (2003) discussed the possibility that the phonological deficit hypothesis








influence German reading acquisition. However, German children with dyslexia had


more difficulty reading non-words than real words.


Landerl (2003) interpreted this as


evidence that German speaking individuals with dyslexia do indeed have specific

difficulties with the phonological component of reading.

Wydell and Butterworth (1999) hypothesized that both granularity and

transparency of a language influence how children with dyslexia learn to read in that


language.


Figure


Their hypothesis of granularity and transparency is diagrammed below in


According to the hypothesis, any language that falls into the shaded area


should not pose as much difficulty for individuals with phonological processing deficits.

As noted above, transparency relates to the degree to which the correspondence


between letter-sound mappings is one-to-one.

sound mapping than an opaque language. Ac


A transparent language has stricter letter-


cording to the hypothesis of granularity and


transparency, persons with dyslexia who are learning to read in a language that is more

transparent will not experience as much difficulty as individuals learning in a less


transparent language.


German is a more transparent language than English.


Granularity relates to the smallest orthographic unit represented by the written


language system.


Granularity is represented on a scale ranging from fine to coarse.


languages such as English and German, the orthographic system represents the phonemes


of the spoken language system.


Their granularity is considered to be "fine"


. Other


languages use the orthographic system to represent segments such as syllables or words


("coarse"


granularity).


Japanese Kana and Kanji are examples of orthographic systems






34


transparency and granularity, the manifestation of reading problems (i.e., dyslexia) is rare

in languages with a coarse granular size (Wydell, 2003).



Hypothesis of Granularity and Transparency

GRANULARITY
coarse


Word



Syllable/
Mora


transparent


* opaque


DEGREE OF
TRANSPARENCY


Figure


Hypothesis of Granularity and Transparency, developed by Wydell and


Butterworth (1999) and published in Wydell (2003).


Reprinted with permission.


Summary

This chapter began with a description of the Linguistic Coding Differences


Hypothesis (Sparks, Ganschow, & Pohlman, 1989).


Next, a connectionist model of


language processing was described (Seidenberg & McClelland, 1989).


Semantic


(meaning), orthographic, and phonological processing were then described in detail.


Phonological processing deficits are often associated with reading problems.


relatinnshin was addrelped


Further the T .inmniictie (ndinr 1fifrsnnrc W-irmnnthni ct0+,








Hypothesis will be addressed in this study and phonological processing skills will be


closely investigated.


This study also looks at cross language transfer in the areas of


vocabulary, spelling, and rapid automatized naming.
















CHAPTER 3
METHODS

The primary goal of this study was to determine if specific native language skills

predict foreign language learning ability, addressing the ideas presented as the Linguistic


Coding Differences Hypothesis (Sparks, Ganschow, & Pohlman, 1989).


dimensions of students'


Several


native language skills were measured to determine the degree to


which their native language skills were predictive of their proficiency in the acquisition


of specific skills in German.


Native English skills were measured in the areas of


phonological processing, spelling, vocabulary, and rapid automatized naming and foreign

language skills were measured in spelling, vocabulary, and rapid automatized naming.

Participants in the study were a group of college students enrolled in a first-semester


German course.


The purpose of this chapter is to describe the setting of and participants


in the study, define the dependent and independent variables, and describe the

instrumentation and data collection procedures.

Setting

This study was conducted over three academic semesters at the University of


Florida.


A series of tests in English and German was administered to university students


enrolled in the first semester of German language study (Basic German I).


All courses






3'


procedures used in this study and determined that the research plan adequately addressed

the ethical dimensions of the project (See Appendix A).

Basic German I is an introductory level foreign language course offered through


the Department of Germanic and Slavic Languages.


The objective of the course is to


provide an introduction to reading, writing, speaking, and listening in German.


Basic


German I is a four-credit undergraduate level course with no pre-requisite coursework.


Foreign language study is a requirement in some programs of study.


Some of the


students enrolled in the course were taking the course to fulfill a requirement for their

degree program, while others were taking it because of personal interests.

Participants


The participants were 65 students enrolled in Basic German I.


included 38 males and


Participants


27 females, ranging in age from 18;8 through 42;3 (years;months).


The mean age was 21 years,


months.


Participants had no prior exposure to the German


language, either through coursework or family/friends and all of the participants had


previously studied another foreign language, either in high school or college.


commonly studied language was Spanish.


The most


Most participants reported that they did well


(e.g.,


"As and Bs") in their previous foreign language study.


The following demographic


information was also reported by the participants:


(1) one student reported difficulty


learning to read; (2) two participants reported having been diagnosed with reading,

language, and/or learning problems (one with Dyslexia and one with Attention

Deficit/Hyperactivity Disorder); (3) eight participants reported a history of enrollment in






38

Participation in this study was voluntary and all students enrolled in the course

were given the opportunity to participate. All students participating in the study met the


following inclusionary criteria:


(1) no prior experience with German, (2) free of sensory


deficits in hearing or vision (uncorrected), and (3) enrolled in Basic German I during the


semester of data collection.


Any students who had previously studied German or who


were non-native speakers of English were excluded from the study.

Students who participated in all phases of the study earned five (5) points of extra


credit added to their final examination grade.


Students who chose not to participate were


given the opportunity to earn the extra credit by writing a short paper, as discussed with


the instructor.


This extra credit opportunity was presented to all students enrolled in


Basic German I during the Spring, Summer, and Fall Semesters of 2003.


At the first data


collection session, students read and signed the Informed Consent document (see


Appendix B).


They also filled out a questionnaire, which included questions on basic


demographic information and on demographic and educational history.

Operational Definition of Variables

The primary hypothesis tested in this study is that native English skills will

correlate with performance on a battery of German tasks in students who were enrolled in


a first-semester German foreign language course.

manipulated) by test scores. The independent vari

language in four areas of processing: semantic pr<

phonological processing, and speed of processing.


All variables were measured (not


iables were measures of English

ocessing, orthographic processing,

Some of the tasks tapped into more








phonological skills and processing speed. The dependent variables were German

spelling, vocabulary, and rapid automatized naming. Table 3.1 summarizes the tests


administered to the participants.


"Instrumentation"


Each instrument is described in detail in the


section.


Data Collection Procedures


Data collection took place over three sessions for each of the participants.


first session was a group session during which the English vocabulary, English spelling,


and Number Learning tests were administered.


The next session was an individual


session that involved English language phonological awareness testing (Elision, Phoneme

Reversal, and spoonerisms), English phonological memory, and rapid automatized


naming in English and German.


During Phases I and II of data collection (described


below), the computerized task was also administered during the individual session.


In the


final session, conducted at the end of the semester, a German vocabulary test and a

German spelling test, along with the spelling clues subtest from the MLAT were


administered.


The author conducted all testing.


Data Collection Phases


There were three phases of data collection for this project.

during the Spring 2003 semester, involving 28 participants. Phase

during the Summer 2003 semester and involved seven participants.


Phase I was completed


II was completed

Phase III was


completed in the Fall 2003 semester.


Thirty students participated in Phase III.


After


Phase II


, the test battery was modified.


Rationale will be discussed.





40


spelling measures, and several computerized tests, which examined single-word reading

and spelling accuracy and speed in English. After the first semester of data collection, a


preliminary analysis of the data was conducted.


The computerized instruments were


found not to be predictive of acquisition of select basic German skills.


Consequently


administration of the computerized tasks was discontinued because it appeared to be too


easy for college students and it was a time-consuming task.


Similarly, the phonemic


awareness task of Elision was not predictive of the German composite score, as had been

expected; however the task was retained as part of the battery because it has been used

widely in previous predictive studies of reading skill.

During Phase III, two higher-level phonological awareness measures (phoneme

reversal and spoonerisms) were added to determine if advanced phonemic awareness


tasks might be more predictive of foreign language (L2) learning.


The new phonemic


awareness tasks were believed to be more sensitive to the individual differences in the


population studied because of their higher levels of difficulty.


Rapid automatized naming


in English was also added because speed is often predictive of adolescents and adults


with reading problems who are proficient in phonological decoding.


Finally, the spelling


clues subtest of the Modern Language Aptitude Test was added because the task

combines several elements of language, including semantics and phonological/

orthographic processing, and was believed to be at an appropriate level of difficulty for a

college-age population.








Table 3-1. Listing and Description of Experimental Tasks in English and German


Number of
Area of Linguistic Processing Task Name Description Participants
ENGLISH
Receptive Choose picture to match
Semantic Processing vocabulary word from an 65
Vocabulary array of four
Write spelling word 65
Orthographic Processing Spelling prued by examiner 65
Composite of scores from
Phonological Processing Elision, Nonword
Composite E Nonword65
Composite Score Repetition, and Number
Learning subtests
Sound manipulation task.
Elision Remove phoneme from 65
Elision 65
target word and produce
new word.
Sound manipulation task.
*Phonological Awareness Spoonerisms Reverse initial sounds in 30
two words.
Word is pronounced
Phoneme backward on audiotape. 30
Reversal Reverse sounds to identify
the word.
Nonword Repetition of pseudo-
Repetition words heard on audiotape.
*Phonological Memory Participant learns new
Number number system and 65
Learning produces numbers using
the newly learned #s
Speed of Processing RAN Timed rapid naming of an 30
__array of digits.
Integration of Phonological, Choose correct definition
Orthographic and Semantic Spelling Clues r phonetically spelled 30
Proesigword orthographicc and
Processing semantic
_____________________ _________________ semantic processing)
GERMAN
Receptive Choose picture to match
Semantic Processing vocabulary word from an 65
Vocabulary array of four
1 ,Write spelling word heard
Orthographic Processing Spelling Write selling word heard65
on audiotape 6








Because of the additional tasks, not all tasks were administered to all 65


participants.


The English spelling, English vocabulary, English phonological composite


(elision, nonword repetition, number learning), and the German spelling, vocabulary, and


rapid automatized naming (RAN) measures were administered to all 65 participants.


English spoonerisms, phoneme reversal,


RAN


, and spelling clues were added during


Phase III of data collection and were administered to 30 participants.

Instrumentation

Standardized tests, adaptation of standardized tests, and experimental procedures


were used to collect data on the participants'


language skills in both English and German.


Each measure will be described in detail, including scoring procedures.


English Language Measures:


Five Domains


English semantic processing was evaluated using a receptive vocabulary test.


Items from the Peabody Picture Vocabulary Test

presented on an overhead projector. The research


- Revised (Dunn & Dunn, 1981) were


ler produced the target vocabulary word.


Participants chose the picture that best matched the target word and circled the number


corresponding to that item on their answer sheet.


There were 20 receptive vocabulary


words (selected from items 148-167 from the Peabody Picture Vocabulary Test


These stimulus items are listed in Appendix D.


correct if the appropriate item number was circled.


task was reported (i.e.,


Each item was scored as


Each participant's


low error rate indicates good performance).


error rate on the


This task was


administered to all 65 participants in groups of three to fourteen students.


Revised).








Stimulus items included 25 words selected from the more difficult (end) of the


test (Items 16-40 on the "Blue" form of the Wide Range Achievement Test


list of these stimulus items is included in Appendix D.

word to be spelled and used it in a sentence. Participa


blank on their answer sheet.


The researcher pronounced the


nts wrote the target word on a


Stimulus words progressed in difficulty. Rather than using


the standard correct/incorrect scoring procedure, each word was scored based on the


number of graphemes that were correctly spelled.


to evaluate the participants'


they misspell


This more detailed scoring was used


knowledge of graphophonemic representation in words that


Again, error rates were reported for the spelling task, based on the scoring


procedure just described.


The spelling task was administered to all 65 participants in


groups of three to fourteen students.

English phonological processing was evaluated using several measures of


phonemic awareness and phonological memory.


A composite score was also computed


for analysis purposes.

Phonemic awareness was evaluated with the following three measures.


Elision, a subtest of the Comprehensive Test of Phonological Processing


(CTOPP) (Wagner,


Torgesen, and Rashotte,


1999), is a sound


manipulation task that requires the participant to take out a phoneme from


the target word and say the new word (e


dryer).


"say driver without the /v


Elision was administered during an individual data collection


session.


This subtest has 20 items.


Error rate was determined for each


1984).


- Revised). A








Phoneme reversal, another subtest of the CTOPP


is an 18-item task


during which the participant hears a word pronounced backward on an


audiotape and must reverse the sounds to make a word (e.g.,


"say neves


backwards"


= seven).


Rate of error was reported.


Phoneme reversal has a


test-retest reliability coefficient of r=.81 for individuals 18 years and older.

Spoonerisms, a researcher-constructed task widely used to measure

phonological awareness, requires the participant to reverse the initial


sounds in two words (e.g.,


birthday cake


= kirthday bake).


Accuracy


(error rate) and speed (in seconds) for the entire list were measured.


"Spoonerisms Total" score was calculated by adding each participant's


accuracy and speed. The

task are shown in Table 3


ten stimulus items chosen for the spoonerisms


below.


Table 3-2. Stimulus items for the researcher-designed spoonerisms task.


Stimulus Item Target Response
table lamp "lable tamp"

copy paper "poppy caper"
birthday cake "kirthday bake"
lazy dog "dazy log"
barn door "darn boor"
new car "kew nar"
four men "mour fen"
red chair "ched rair"
potato chips "chotato pips"






45


Phonological memory was evaluated using a commonly used task, nonword repetition, as

well as a second memory task that taps memory in the context of new word learning.

These measures are described in greater detail below.


Nonword repetition, a subtest of the CTOPP

ability to accurately repeat nonsense words.


evaluates an individual'


In the nonword repetition


task the participant hears a nonsense "word" presented on an audio tape.

Stimulus items gradually increase in number of syllables and phonological


complexity (ranging from one to six syllables).


After the word is


presented, the participant must repeat the target word exactly to get credit


for the item.


No partial credit is given.


Items are scored as correct or


incorrect immediately after the participant produces the nonwords.


rates were reported.


Error


This test was individually administered.


Nonword Repetition subtest of the CTOPP has a test-retest reliability

coefficient ofr=.67 for individuals 18 years and older.

Number learning, a subtest of the Modem Language Aptitude Test


(MLAT) (Carroll & Sapon, 1959), evaluates an individual's


quickly learn a new number system.


strategies, and is timed.


ability to


The task involves memory, learning


This test was administered in a group setting.


Participants learned a new number system by listening to an audiotape.

They first learned nonsense words representing the numbers one through


four (1-4), then 10-40,


and finally 100-400.


After learning the number








were rapid.


Participants earned credit for each correct digit (out of 43)


that they wrote on their answer sheet.


Error rates were reported for all 65


participants.


Phonological processing composite was derived for the purpose of data analysis.


order to reduce the number of independent variables, three of the phonological measures


were combined into a phonological processing composite score.

error rates for elision, nonword repetition, and number learning.


This score included the

The three error rates


were added together. A low composite score indicates better performance and a high

composite score indicates weaker performance.

English speed of processing was measured with stimulus materials from the


rapid automatized naming of digits subtest of the CTOPP


Each participant was


presented with an array of numerals on a page and was asked to quickly say the names of


each numeral.


Performance was timed and time (in seconds) was recorded.


A faster


(lower) time in seconds indicates stronger rapid automatized naming ability and a slower


(higher) time indicates weaker performance.


This subtest was individually administered.


English integration of semantic, orthographic, and phonological processing


was measured with the spelling clues subtest of the MLAT


timed.


The spelling clues subtest is


Participants are given 15 minutes to complete 50 items. The participant must


choose the one word out of five printed words that corresponds most nearly in meaning to


the target word.


An example of this task is for the target word "luv"


with the choices:


carry, exist, affection, wash, spy.


The participant circled the word most closely related to









German Language Measures:


Four Domains


German semantic processing was evaluated using a receptive vocabulary test.

The procedure was similar to the English Semantic Processing task and was researcher-


designed and constructed.


Target words were selected from textbook chapters that were


covered over the course of the semester.


Students should have had at least minimal


exposure to each stimulus item. The author consulted with a faculty member from the

German department to confirm that a representative variety of semantic and phonological


forms were selected. To ensure consistency of presentation, the target vocabulary words

were presented via audiotape. The stimulus items were produced and recorded by a


student who had taken several courses in the German department, leading to an academic


minor in German.


Stimulus items are listed in Appendix E.


As in the English semantic processing task, the participants selected the picture

that best matched the target word and circled the number corresponding to that item on


their answer sheet.


There were


stimulus items that were scored as correct/incorrect.


Error rate was recorded.


This task was administered in a group setting to all 65


participants in groups of three to fourteen participants.

German orthographic processing was evaluated using selected items from the


textbook chapters.


The author consulted with a faculty member from the German


department to ensure that a variety of orthographic forms was included.


Like the English


orthographic processing measure, participants were asked to spell the target word that


they heard.


Stimulus items were presented via audiotape, and were recorded by a student








were recorded.


This task was administered to all 65 participants in groups of three to


fourteen participants.

German speed of processing was measured via a rapid automatized naming task.

Each participant was presented with an array of numerals on a page and was asked to


quickly say the names of each numeral in German.


Performance was timed.


Time was


recorded in seconds.


A faster (lower) time in seconds indicates stronger rapid


automatized naming ability and a slower (higher) time indicates weaker performance.

This subtest was individually administered to all 65 participants.

German composite score was computed to represent foreign language


proficiency.


Error rates for German semantic processing (receptive vocabulary) and


German orthographic processing (spelling) were added to the time for German speed of

processing (rapid automatized naming) to obtain a composite score for all German


measures.















CHAPTER 4
RESULTS

The primary goal of this study was to provide data to examine the Linguistic

Coding Differences Hypothesis (Sparks, Ganschow, & Pohlman, 1989), which states that


native language skills influence foreign language learning.


Data were collected and


analyzed to examine the influence of native language skills on the learning of first-

semester German skills in university students.

The results of data analysis are reported for each of the three research questions


shown below.


Data were analyzed using SAS version 9.


Analyses included correlations


and multiple regressions.


Shavelson (1996) describes these analyses as follows.


Correlation analysis identifies the strength of the relationship between variables by


providing an index to quantify this relationship.


necessarily imply causation.


However, correlation does not


Linear regression addresses the predictive nature of the


relationship between the independent variable(s) and the dependent variable.


Linear


regression specifies a functional relationship between the variables by fitting a straight

line to represent how the dependent variable changes as a result of changes in the


independent variable(s).


The fitting of a straight line is done by selecting a model that


best describes the relationship between the independent variable(s) and the dependent








knowledge, and (d) speed of processing; and German foreign language performance,

as measured by a composite score on a battery of tests in German?


For Research Question 1,


the independent (predictor) variables were English


phonological, English spelling, English vocabulary, and English RAN.


(outcome) variable was the German composite score.


The dependent


The German composite score was


comprised of German spelling, German vocabulary, and German RAN.


Descriptive


statistics for the four English predictor variables and the German composite score are

shown in Table 4-1.

To answer this question, a correlation analysis between all independent and


dependent variables was first performed and is reported in Table 4-2.


Multiple regression


analysis was then run to determine which of these predictor variables best predicted

proficiency in German, which was defined as the score on the German composite.


Table 4-


Simple Statistics for the Four English Predictor Variables and the German


Composite


Variable N Mean Std. Dev. Sum Minimum Maximum
Eng. Phon.
65 43.22 24.01 2809 5 104
Composite
English 65 9.15 457 0% 19%
Spelling (error rate) (error rate)
English 0% 60%
English 65 25.88 13.07 1682 0% 60%
Vocabulary _____(error rate) (error rate)
English
RAN 30 11.69 2.75 350.79 8.00 sec. 18.92 sec.
German
65 55.86 21.86 3630.69 25.52 124.30
Composite








Table 4-2.


Pearson Correlation Coefficients for the Four English Predictor Variables and


the German Composite


* The correlation is significant at p


< .05


Correlation analyses showed that three of the four English predictor variables


were significantly correlated with the German composite score.


Significant correlations


were found between the German composite (dependent variable) and the English


phonological (r(60)


=.33, p


.05), spelling (r(60)


.39, p < .05), and vocabulary (r(60) =


.33, p


< .05) scores.


There were also significant correlations among the English


predictors (main effects) in the areas of English phonological and English spelling (r(60)


= .36, p<.05), English phonological and English vocabulary (r(60)


phonological and English RAN (r(60)


.33, p<.05), English


.62, p<.05), and English spelling and English


vocabulary (r(60)


.33, p<.05).


High significance between the main effects implies the


presence of interaction effects.


In fitting a full model through multiple regression


analysis, interaction effects must be taken into account.


For the full model, R2 was equal to .67


, meaning that 67% of the variance for the


Eng. Phon. English English English German
Composite Spelling Vocabulary RAN Composite
Eng. Phon. --- .36* .33* .62* .33*
Composite__________________________________
Englih --- .33* .08 .39*
Spelling____________
English. .02 .33
Vocabulary___________________________________
English .26
RAN_
German
Composite _____________________________








interaction between the variables also produced significant predictors of German


proficiency, measured by a composite of select basic German skills.


When the full model


was considered, including the four predictor variables, there were four significant


predictors of the German composite score, as shown in Table 4-3, below.


The English


vocabulary measure was a significant predictor of the composite of select basic German


skills (B


= 10.02, P = .05).


The interactions between English phonological and English


spelling (B


.40, P


were also significant.


significant.


.01); and English vocabulary and English RAN (B


.73, P


Finally, one three-way interaction between variables was


The interaction between English phonological, English spelling, and English


RAN (f


-.03, P = .02) was a significant predictor of the German composite score.


If the


four-way interaction between all four predictor variables was significant, then the full


model (including all four predictor variables) would have been significant.


However, the


four-way interaction was not significant.


Table 4-3.


Contributors to the German Composite Score


English Predictor Variables
Source Mean Square F-Value P-Value
English Phonological 703.83 2.42 .14
English Spelling 125.78 0.43 .52
English Vocabulary 1335.08 4.59 .04*
English RAN 7.75 0.03 .87
Significant two-way interactions
Source Mean Square F-Value P-Value
E-Phon*E-Spell 2161.31 7.44 .01*
E-Voc*E-RAN 1271.52 4.37 .05*
Significant three-way interaction
Source Mean Square F-Value P-Value
E-Phnn*F.-Snell*F-R AN 1770970 17 I 09*








p=.08, it was selected for plotting because it contained a wide range of English skills


(vocabulary, spelling, and RAN).


This example should provide a clear picture of the


nature of the relationship between English and German skills.


Figure 4-1


below, demonstrates the differences in English spelling performance


trends when English vocabulary and English RAN were held constant at three levels of


performance.


These variables were held constant for vocabulary and RAN scores at the


25th percentile (best performance


= better than 75% of the participants), the 50th


percentile (median performance), and the 75th percentile (poorest performance).


To plot


the trend lines, the vocabulary and RAN values were then inserted into the equation for


the three-way interaction.


With vocabulary and RAN held constant, the trend lines


represent how different English spelling scores affect the German composite score.

Figure 4-1 illustrates the differential performance in the composite of select basic


German skills for participants with strong, median, and poor native language skills.


participants with the strongest native English language abilities, spelling performance did


not influence the German composite score.


Actually, as spelling error rate increased


(i.e.,


spelling performance got worse), the German composite score improved.


For the


group of participants with language abilities in the median range, spelling performance


had no effect on the German composite score.


The German composite score remained


relatively constant as spelling performance decreased (as measured by increasing error


rate) for the group in the median range.


Finally, and most interestingly, for the


participants with the poorest language abilities (those with the highest rate of error), as








performance in foreign language are predicted by different factors.


For example, it is


possible that poor native language skills predict poor foreign language performance,

while strong native language skills do not necessarily predict strong foreign language


performance.


This possibility will be discussed in greater detail in the following chapter.


Spelling Trends by Performance Quartile.


--- Strongest NL Skills


--- Median NL


Skills


--- Weakest NL Skills


1 2


Change


in Spelling Performance (with Vocab.


& RAN held constant)


Figure 4-1


. Comparison of the Association between English Spelling and the German


Composite for Differential Abilities in English Vocabulary and English RAN.

It is important to note that because the RAN task was added during the second


phase of data collection, only 30 scores were recorded.


For the above analysis, only these


30 participants'


scores could be used.


RAN is considered to be a measure of speed of


processing and does not seem to measure the integrity of a particular processor (e.g.,


phonological, orthographic, meaning). RAN interacted with other English variables to

significantly predict the German composite score. To further examine the predictive


relationships between the other three English language measures and the German








vocabulary predicted the German composite score, additional regression analyses were

performed.


As described in Table 4-2


, there were several significant correlations between the


English phonological, English spelling, English vocabulary, and German composite


variables.


Each of the three English measures was significantly correlated with the


German composite score (r(65)


;r(65)


.39; r(65)


, respectively).


There were


also significant correlations between English phonological and English spelling (r(65)


.36),


English phonological and English vocabulary (r(65)


English vocabulary (r(65)


.33).


.27), and English spelling and


Again, high degrees of correlation imply the presence


of interaction effects.

For the full model (including all interactions), none of the coefficients for the

main effects (English phonological, English spelling, or English vocabulary) were


significant.


R2 was


for the full model.


However, there were significant interaction


effects in the areas of English phonological and English spelling Q=.04, P=.05), English

phonological and English vocabulary (/f=-.009, P=.02), and the three-way interaction

between English phonological, English spelling, and English vocabulary (f8=.0005,


P=.002).


When each individual effect was examined (without considering interaction


effects), R2


= .23


, only English spelling contributed significantly to the German


composite score (ft


.24, P=.04).


In summary, when the four English predictor variables were analyzed, all

contributed to the German composite score, either alone or interacting with each other.








composite score than English phonological or English vocabulary skill.


Spelling alone


significantly contributed to the German composite score, as did the interaction between

English spelling and English phonological, the interaction between English phonological

and English vocabulary, and the three-way interaction between English spelling, English

phonological, and English vocabulary.

Hypotheses Related to Research Question 1


Hypothesis:


Based on the Linguistic Coding Differences Hypothesis, it was


hypothesized that native English language phonological skills would be

associated with German foreign language performance after one semester of

instruction.


Result:


This hypothesis was NOT DIRECTLY SUPPORTED by the data.


While the interaction between English phonological skills and English spelling

and English RAN did significantly contribute to the German composite score, the


other English predictor variables also contributed.


However, English spelling,


which incorporates phonological as well as orthographic skills, made a significant

contribution to the German composite score, so this hypothesis was partially

supported by the data.


With respect to overall German foreign language proficiency


(German composite score),


orthographic (i.e.,


native English language phonological and


spelling) skills would more strongly predict German


performance than English language semantic skills would.


Hypothesis:








interaction with the other English predictor variables, English spelling and

English phonological made stronger contributions to the German composite score,

both independently and in interactions.


Research Ouestion 2


Which specific phonological-orthographic skills (elision,


nonword repetition, spelling, spoonerisms, rapid automatized naming, phoneme

reversal, spelling clues, number learning) best predict performance in foreign

language (German composite score)?

Descriptive statistics for the English language measures are shown in Table 4-4,

followed by the Pearson correlation coefficients for all of the English language measures

in Table 4-5.

Because of the strong correlations among the English language measures and

between the English language measures and the German composite scores, multiple

regression analyses were not performed on all of the English phonological predictor


variables.


Due to the large number of predictors, there would likely be too many


significant interactions between variables to make any definitive conclusions.

Interestingly, however, the correlations between English spelling clues and the other


phonological measures were consistently strong.


Spelling clues correlated with the


elision task, r(30)


.66, p


< .01


with the English spelling task, r(30)


< .01


with


the English vocabulary task, r(30)


.54, p


with the English spoonerisms task,


r(30)


< .01


and with the English phoneme reversal task, r(30)


.62, p


English spelling clues task requires integration of phonological,


orthographic, and


< .O 1









Table 4-4.


Simple Statistics for the English Language Measures


Variable N Mean Std. Dev. Sum Minimum Maximum
11.31%
Elision 65 31% 9.65 735 0 40%
(error rate)
Phonological 65 20.72% 10.97 1347 0 50%
Memory_______(error rate) ____
Number 11.18%
S65 12.45 727 0 51%
Learning (error rate)
English 65 9.15% 0 19%
Spelling (error rate)____________
English 25.88%
English 65 25.88% 13.07 1682 0 60%
Vocabulary __ (error rate)
74.63
Spoonerisms 30 74. 41.02 2239 35.1 198.65
_________ _______ (errorttime) ______________
Phoneme 28.03%
35 18.63 981 0 67%
Reversal (error rate)
Spelling 14.89%
Spelling 36 14.89% 12.05 536 2 60%
Clues (error rate)
11.69 sec
RAN-Eng. 30 116 2.75 350.79 8 18.92 sec.
(time)


Table 4-5. Pearson Correlation Coefficients for the English language measures
1 2. 3 4 5 6 7 8 9 10
1 Elision --- .23 .40* .23 .23 .58* .62* .66* .27 .27
2 Nonword rep --- .24 .20 .17 .00 .03 .28 .23 .09
3 # Learn. --- .33* .19 .29 .29 .27 .73* 34*
4 E-Spell. --- .33* .41* .27 .55* .08 .39*
5 E-Vocab. --- .33* .06 .54* .02 .33*
6 Spoon. Total --- .62* .54* .23 .36*
7 Ph. Rev. --- .62* .45* .66*
8 Sp. Clues --- .12 .53*
9 RAN-E --- .26
10 Germ. Comp. ---
* Correlation is significant at the 0.01 level.


Since the spelling clues task integrates linguistic processing skills of interest in

this study, it is not surprising that spelling clues was correlated strongly with many of the


other English language measures.


However, because the English spelling clues task was






.59


on the English spelling clues task (predictor) and the corresponding scores on the German


composite (outcome) to determine if a predictive relationship existed.


Spelling clues


alone contributed to 24% of the variance in the German composite score (r2=.24) with a


P-value of .0024.


Figure 4-2 below illustrates the strength of the predictive relationship


between spelling clues and the German composite scores.

Influence of Spelling Clues on the German Composite Score


0 5 10 15 20 25 30 35


Spelling Clues


Figure 4-


Simple Linear Regression Plot of the Association between Spelling Clues and


the German Composite.

An even stronger predictive relationship emerged when the four predictors that

were most correlated with the German composite were entered into a model. Phoneme

reversal and English spelling stood out as important in describing the variation in the









scores (participants 1 and 13) were removed from the analysis, the predictive power of


this interaction was a very strong r2


.78 d(=.07


P=.0057).


Influence of Spelling*Phoneme Reversal on German Composite


0 5 10 15 20 25 30 35 40


Spelling*Phoneme Reversal


Figure 4-3


Simple Linear Regression Plot of the Association between the Interaction of


English Spelling and Phoneme Reversal and the German Composite.

Hypothesis Related to Research Question 2


Hypothesis:


spoonensms,


Phonological-orthographic skills which are more difficult (spelling,


phoneme reversal, number learning, and spelling clues) will be


better predictors of foreign language proficiency (as measured by German

composite score) in college students than easier phonological-orthographic

measures (elision, nonword repetition, and rapid automatized naming).








phoneme manipulation or knowledge of spelling rules.


They integrate


phonological processing, memory, and semantic knowledge.


Spoonerisms,


number learning, and English spelling were also significantly correlated with the


German composite score.


Elision, nonword repetition, and English RAN were not


significantly correlated with the German composite score.


Although these tasks


are commonly used in predictive studies of reading abilities, the tasks were

probably too easy for college-age students who have reached a proficient level of


literacy.


The spelling clues, phoneme reversal, and spelling tasks were predictive


because they tap into a higher level of literacy skills, involving the integration of


orthographic, phonological,

Research Question 3: Do native


and semantic skills, as well as memory.


English language skills in spelling, vocabulary, and


rapid automatized naming predict foreign language (German) performance in these

same areas, indicating cross-language transfer of skills?

To determine whether cross-language transfer of spelling, vocabulary, and RAN


skills was present, three separate multiple regression analyses were conducted.


For each


analysis, the three independent variables were English spelling, English vocabulary, and


English RAN. The dependent variables were German spelling, German vocabulary, and

German RAN, respectively.


Of the three predictor variables, English spelling was the only variable that made


a significant contribution to German spelling performance (8


.93. P


.0001


Table 4-6).


This indicates that a relationship exists between native language spelling






62


meaning that 54% of the variance in German spelling was accounted for by the English

predictor variables.


Table 4-6.


English Predictors of German Spelling


_English Predictor Variables
Source Mean Square F-Value P-Value
English Spelling 500.38 24.69 <.0001*
English Vocabulary 35.56 1.75 .20
English RAN 49.37 2.44 .13
*The relationship is significant at p .05

The German vocabulary score was significantly associated with the English

vocabulary score (f = -1.17, P = .01) and the interaction between English vocabulary and

English spelling (f = .11, P = .003) (see Table 4-7). While cross-language transfer of

vocabulary skills was evident, spelling skills had a strong enough influence to make a

significant contribution to German vocabulary as well. R2 was .43. Forty-three percent of

the variance in German vocabulary was accounted for by the English predictor variables.

Table 4-7. English Predictors of German Vocabulary
English Predictor Variables
Source Mean Square F-Value P-Value
English Spelling 261.93 3.84 .06
English Vocabulary 597.97 8.76 .01*
English RAN 13.59 0.20 .66
Significant two-way interaction
Source Mean Square F-Value P-Value
E-Spell*E-Voc 721.30 10.57 .003*
*The relationship is significant at p <.05

Finally, English RAN did not make a unique significant contribution to German


RAN (see


Table 4-8).


English vocabulary seemed to make the strongest contribution to


German RAN.


Significant associations with German RAN were found for English









spelling, and English RAN (ft


.03. P


Although English RAN did not make a


significant contribution to German RAN,


when English RAN was dropped, the remaining


predictor variables became slightly less significant, indicating that English RAN did


make a contribution to the German RAN score.


R2 was


The English predictor


variables accounted for

Table 4-8. English Prea


1% of the variance in German RAN.


doctors of German RAN


English Predictor Variables
Source Mean Square F-Value P-Value
English Spelling 94.76 1.20 .29
English Vocabulary 436.16 5.50 .03*
English RAN 183.85 2.32 .14
Significant two-wa interactions
Source Mean Square F-Value P-Value
E-Spell*E-Voc 371.59 4.69 .04*
E-Voc*E-RAN 444.10 5.60 .03 *
Significant three-way interactions
Source Mean Square F-Value P-Value
E-Spell*E-Voc*E-RAN 377.24 4.76 .04*
*The relationship is significant at p .05

This question addressed the issue of cross-language transfer of specific English


language skills to German skills in the same areas.


Figure 4-3,


below, summarizes the


relative contributions (expressed in F-values) of English skills in spelling, vocabulary

and RAN to German skills in these same areas.

Cross-Language Transfer

5 E-Spell.
20^ U E-Vocal
15 E-RAN
10 ESp*E.


b.

Voc
- a *









Hypotheses Related to Research Question 3


Hypothesis:


German spelling would be influenced by English spelling.


Result:


This hypothesis was STRONGLY SUPPORTED by the data.


English


spelling uniquely predicted German spelling.


Hypothesis:


German vocabulary would be influenced by English vocabulary


skills.


Result:


This hypothesis was SUPPORTED by the data.


English vocabulary


predicted German vocabulary; however English spelling skills also predicted

German vocabulary, as did the interaction between English vocabulary and

English spelling.


Hypothesis:


German rapid automatized naming skills would be influenced by


English rapid automatized naming ability.


Result:


This hypothesis was NOT SUPPORTED by the data.


While English


RAN did contribute to the German RAN score, German RAN was better


predicted by English vocabulary


This relationship will be discussed in greater


detail in the following chapter.

Summary

Native English language skills generally predicted foreign language learning, as


measured by the German composite score.


Because some of the English language skills


were related to each other, interactions between the variables resulted in significant


contributions in many cases.


No one native English language variable emerged as a








predictor variables:


English spelling, English vocabulary, English phonological, and


English rapid automatized naming, English spelling was involved in two of the four


significant contributions to the German composite.

from the model and all 65 participants' scores wer


as the strongest predictor of the German composite score.


When English RAN was removed


e analyzed, English spelling emerged


The interactions between


English spelling and English phonological and English spelling and English vocabulary

also significantly contributed to predicting the German composite score.


Level of difficulty for phonological skills was also examined.


phonemic manipulation tasks (e.g.,


The more difficult


phoneme reversal, spoonerisms, spelling clues)


correlated more strongly with the German composite score than did the easier tasks.


college-age students, the simple phoneme manipulation (such as elision) and

phonological memory (nonword repetition) tasks did not appear to be sensitive enough to


differentiate students'


performance.


By far, the strongest predictor ofproficiency in


German (German composite score) was the interaction between the English spelling and

phoneme reversal tasks.

Analyses for examining cross-language transfer of skills revealed that English


spelling uniquely predicted German spelling.


English vocabulary and English RAN did


not contribute to German spelling.


English vocabulary,


English spelling, and the


interaction between the two variables made significant contributions to German


vocabulary


Cross-language transfer of skills was evident.


not predict German RAN,


as had been hypothesized.


However English RAN did


German RAN was best predicted















CHAPTER 5
DISCUSSION

Overview of Findings

This study explored the relationship between native language skills and foreign


language learning ability.


The Linguistic Coding Differences Hypothesis states that


native language skills influence foreign language learning and that deficits in native


language will impact the ability to learn a foreign language.


The primary goal of this


study was to determine how native language skills in phonological processing,

vocabulary, spelling, and rapid automatized naming contribute to the acquisition of select


basic foreign language (German) skills. Ge

vocabulary, and rapid automatized naming.


nrman testing was in the areas of spelling,

The Linguistic Coding Differences


Hypothesis claims that phonological processing deficits will affect first-semester foreign

language learning.

A related goal of the study was to determine if phonological tasks of varying


difficulty were differentially predictive of foreign language skill.


Phoneme manipulation


tasks have been shown to be reliable measures for predicting reading disability in


beginning readers (Catts & Kamhi,


1999).


However, a simple phoneme manipulation


task (elision) was too easy for college students studied who had achieved a relatively high






67


The third goal of this study was to determine whether cross-language transfer of

spelling, vocabulary and rapid automatized naming (RAN) skills was evident between


English and German.


Previous research had looked at cross-language transfer of


phonological skills (Durgunoglu, Nagy, & Hancin-Bhatt, 1993).


This study extended the


concept to determine if similar transfer of skills occurs for spelling, vocabulary and RAN.

Linguistic Coding Differences

The first research question addressed the relationship between native language


skills and foreign language learning.


Understanding this relationship can help to clarify


why some foreign language learners experience great difficulty, in light of strong

performance in other courses.

Previous research on prediction of foreign language proficiency (operationalized

as foreign language grades) identified English (native language) course grades and

foreign language aptitude as predictors of first-year foreign language course grade.

English spelling was also identified as a significant predictor in one of the two


experiments (Sparks, Ganschow, & Patton, 1995).


A follow-up study on the same group


of students after they completed the second year of foreign language study found that end

of first-year foreign language grade and foreign language word decoding ability were the


best predictors of second-year foreign language grades (Sparks et al.,


In the current study, college students'

performance on various experimental measure


1997).


language skills were determined by

es. While testing may not be the most


comprehensive or accurate measure of foreign language proficiency, for the purposes of






68


proficiency because factors such as motivation, class attendance, and participation often

contribute to final grades.

Several significant correlations were identified among a number of English


language skill measures:


(1) English spelling and the English phonological composite,


(2) English vocabulary and the English phonological composite, (3) English RAN and the


English phonological composite, and (4) English vocabulary and English spelling.

correlations underscore the interdependence of the phonological, orthographic, and

semantic processors in English.

Several of the English predictors, either alone or in interaction with other


predictors, showed a significant influence on the German composite score.


These


Significant


two-way interactions were found between English spelling and English phonological


skills and between English phonological skills and English RAN.


A significant three-


way interaction was found between English spelling, English phonological, and English

RAN.

Because the aim of this study was to examine the influence of the predictors on

the German composite score, all four English predictors were included in the data


analysis.


However not all of the predictors contributed to the German composite.


When


developing a model to identify the best predictors, only the strongest contributors are


included.


The following section (Phonological Task Levels of Difficulty) identifies the


best predictors of the German composite score.

Inclusion of RAN in the analysis demonstrated that speed of processing interacts








the four predictors were analyzed, only 30 participants' scores could be used

RAN task was only administered during the second phase of data collection.


RAN, the analysis of all 65 participants'


I because the


Without


scores yielded significant contributions by


English spelling and by the interactions between English spelling and English vocabulary

and between English spelling and English phonological.

It was predicted from the Linguistic Coding Differences Hypothesis that the

English phonological composite would contribute to first-semester German proficiency.

The Linguistic Coding Differences Hypothesis states that deficits in phonological

processing would negatively affect foreign language performance during the first


semester of study.


This relationship was not directly supported.


English phonological


did not uniquely or significantly contribute to the German composite.


One reason for this


is because of the significant correlations between English phonological and the other


predictor variables.


Significant correlations between predictors imply significant


interaction effects between variables.


The English phonological score was involved in


three significant interactions.

Another potential explanation for the result is that the tasks comprising the

English phonological composite were too simple for college students who had a relatively


high level of language and literacy skills.


Although the elision and nonword repetition


tasks are commonly used to predict reading and language abilities in young children, they


were not sensitive enough to predict foreign language learning in adults.


Sparks,


Ganschow, and Patton (1995) reported a similar finding when they had hypothesized that








predictive.


The authors suggested that it was not a good measure because most students


achieved a high score on the test (ceiling effect).

In the current study, the English spelling task was at a more appropriate level of

difficulty for college students, which is likely the reason for the stronger association


between spelling and foreign language learning.


It is important to note, however, that


spelling involves phonological processing, in addition to orthographic processing.

In the English spelling task, the examiner dictated the target word and then used


the word in a sentence.


sheets.


The participants wrote down the target word on their answer


Responses were scored based on the percentage of phonemes


correctly/incorrectly spelled.


Each word was not scored as simply correct or incorrect.


Rather, the participant was given credit for the number of correctly spelled phonemes.

For example, in the word "reasonable" there are eight phonemes to be correctly spelled.

If all eight phonemes were not correctly spelled, the participant would receive a

proportion of credit.

Graphing the relationship between English spelling and the German composite,

with English vocabulary and English RAN held constant, yielded an interesting


relationship.


This analysis suggested that perhaps strong and weak native language skills


contribute to foreign language learning in different ways.


Although only one relationship


was illustrated, it is possible that relatively strong native language skills are a necessary

but not sufficient criterion for successful foreign language learning, while weak native

language skills strongly predict struggle in foreign language learning.








second language vocabulary, phonological ability was less predictive, while in

individuals with weak second language vocabulary, there was a strong relationship

between native language phonological skills and second language vocabulary.

Obler (1989) described the characteristics of an individual with particularly strong


foreign language learning abilities. This indi

few weeks simply by being exposed to them.


contradict the Linguistic Coding Differences Hypothesis.


vidual was able to learn languages within a

Some of his characteristics appear to


First, the subject reported that


his reading is slow and laborious, both in native and foreign language.


On standardized


testing, his intellectual functioning was in the average range (full scale IQ of 107).


did, however, demonstrate significant strengths in vocabulary and any task requiring the


acquisition of a new code system.


His verbal memory was also outstanding.


Sparks, Ganschow, and colleagues do not address the idea of verbal memory at


any great length.


In discussing foreign language learning difficulties, they focus on


phonological and orthographic processing as well as syntax and semantics.


It is possible


that phonological/orthographic processing deficits are associated with foreign language

learning problems, while strong phonological and orthographic skills are a necessary but


not sufficient pre-requisite for successful foreign language learning.


to strong phonological and orthographic skills,


Perhaps in addition


an individual also needs a strong verbal


memory in order to be a successful foreign language learner.


In the current study, there


was some indication that memory played a role, particularly in the area of phoneme


reversal


, which will be discussed in the following section.








success. Results of this study underscored the interaction among several predictor

variables. It is possible that the more strong predictors an individual learner has, the


more successful he or she will be at foreign language learning.


profile of relative strengths and weaknesses.


Each individual has a


Certain strengths can compensate for areas


of weakness; but sometimes an area of weakness is so significant, or there are not enough

strong areas to compensate, that a disability is manifested.

Phonological Task Levels of Difficulty

The second research question examined the effect of task difficulty on the


predictive nature of the phonological measures.


Correlation analysis yielded strong


correlations between several of the English language measures.


The spelling clues task


was significantly correlated with several of the other English language measures and with


the German composite score. Bec

clues was examined more closely.


causee correlation does not imply causation, spelling


A simple regression analysis was conducted.


significant regression analysis has stronger implications for demonstrating predictive


relationships than correlation does.


A significant association was found between spelling


clues and the German composite.

The spelling clues task incorporates spelling, phonological processing, and


semantic abilities, so it is not surprising that the task was correlated with the other

predictor measures. Although this regression analysis was conducted on only 30


participants'


scores, it is likely that analysis of more scores would yield similar results.


A very strong predictor of the German composite score emerged from the








relationship between the sounds and their graphemic representations.


In the phoneme


reversal task, participants heard a word pronounced backward on an audiotape (e.g.,

neves backwards"). They had to identify the target word by reversing the phonemes

("seven"). This task requires knowledge of the phonological system as well as shori


"Say


t-term


verbal memory, particularly as the stimulus words got longer.

The finding that more sensitive phonological skills are associated with foreign


language learning relates to the persistence of phonological processing deficits.


Wilson and Lesaux (2001) noted, individuals with a history of reading problems

performed significantly worse than controls on phonological tasks, particularly on tasks

involving phoneme deletion, a phonological segmentation and manipulation task, and

spoonerisms, a task that involves phoneme manipulation and is often timed.

Snowling, Nation, Moxham, Gallagher, and Frith (1997) also found that students

with dyslexia had more difficulty than controls on nonword reading, phoneme deletion,


spoonerisms, and phonemic fluency tasks.


Similarly, Gallagher, Laxon, Armstrong, and


Frith (1996) found that college students with a history of dyslexia performed worse than


controls on nonword reading and spelling accuracy; and spoonerisms,


digit naming, and


speech rate tasks. Together these studies demonstrate that phonological processing

problems are persistent. Phonological processing problems initially contribute to


difficulties learning how to read and later manifest as difficulties learning foreign

language.

Cross-Language Transfer of Skills


I








others (such as reading vs. writing; listening vs. speaking).


Studying the variables that


contribute to German spelling, vocabulary, and rapid automatized naming provided a

better understanding of the particular predictor variables most strongly associated with

each area.

In the area of spelling, English spelling made a significant and unique


contribution to German spelling. English vocabulary and English RAN did not

significantly contribute to German spelling. German is a more transparent language than


English, meaning that German has a closer to one-to-one system of letter sound


correspondence.


Participants who were better spellers in English were also better able to


learn the spelling rules in German.


The concept of cross-language transfer of


phonological skills had been previously discussed by Durgunoglu, Nagy, and Hancin-


Bhatt (1993).


Spelling involves phonological processing so it follows that English


spelling would be associated with German spelling.

In the area of vocabulary, English vocabulary significantly contributed to the

prediction of German vocabulary; however English spelling and the interaction between

English vocabulary and English spelling also made significant contributions to German


vocabulary.


Perhaps the phonological processing aspect of spelling helps learners of a


foreign language acquire new vocabulary words.


Individuals with strong phonological


skills can more easily learn the new word forms in the target language.


Service (1992)


studied the relationship between phonological and vocabulary skills in younger foreign


language learners.


She noted predictive relationships between native language








Finally, in the area of RAN,


the German RAN was not predicted by English RAN,


as was hypothesized. English vocabulary skills made a stronger contribution to German


RAN.


A possible explanation for this is that the RAN task in German may have less to


do with speed of processing than with an individual'


numerals.


ability to learn the names for the


Individuals with stronger native language vocabulary skills may be better able


to learn the names of new vocabulary words (letter names) and have an easier time


accessing them for production.


Another possible explanation for why English RAN did


not predict German RAN is that after only one semester of foreign language study,

automaticity is not yet established in the new language.

Summary of Research Questions

Consistent with previous findings, English spelling emerged as a somewhat

stronger predictor of the German composite score than English vocabulary, English


phonological, or English RAN were.


However interactions between all predictors


support the idea that phonological, orthographic, and semantic processing are inter-

connected.

Although most phoneme manipulation tasks are predictive of reading skills for

adolescents and adults with learning disabilities, for college students without disabilities,


some tasks were too easy.


Ceiling effects were evident.


For the population in the current


study, phonological tasks which also integrated orthographic processing, semantics,

and/or memory emerged as better predictors of foreign language learning abilities.

This study also looked at the concept of cross-language transfer of skills between








areas of spelling and vocabulary.


the same areas.


English skills in these areas predicted German skills in


The relationship did not hold for rapid automatized naming.


Profiles of select participants'


study.


performance highlight the issues addressed in this


In the following section, the performance of students who demonstrated


particularly weak foreign language learning, particularly weak native language skills,

particularly strong foreign language skills, and particularly strong native language skills


will be discussed.


The performance of students who reported a history of learning


problems will also be described.

Profiles of Select Participants' Performance

This study included a range of foreign language learners, from strong to weak, as


defined by the German composite score.


This section contains in-depth information on


participants who were very successful at the foreign language tasks in this study (i.e.,

"good foreign language learners"), participants who struggled with the tasks, and


participants who reported a history of language learning difficulties.


Salient


characteristics of good and struggling foreign language learners are discussed.

Support for the hypothesis that native language skills underlie foreign language learning

abilities will be discussed, including examples of predictive relationships between the

English and German measures in participants whose scores were high and low.

Profiles of Strong Foreign Language Learners (Low Rate of Error/Fast Time on the
Experimental Measures)


Good German composite score.


Two participants who did well on the tests of








Participant #35 was a 29-year-old male majoring in computer science.


reported studying Spanish and Latin in the past and reported that he did well in these


courses.


This participant was involved in phase 1 of the study, so only the basic


phonological, spelling, and vocabulary tests were administered.


Of particular importance


is that Participant #35 was the only participant who did not make any errors on the


English spelling test.

only one slight error.


He also had the best score on the German spelling test, making

Interestingly, this participant did not do very well on the nonword


repetition task (22% error rate), however as discussed in the Methods and Discussions

sections, this task did not seem to contribute to the performance of college students

learning a foreign language.

Participant #58 was a 22-year-old male double majoring in math and English.


reported a history of studying Spanish, Latin, and Dutch.


He is fluent in Spanish.


student reported high scores on both the verbal and quantitative portions of the SAT (750


and 760 out of 800, respectively).


intelligence.


These high scores are probably indicative of high


All phonological measures were administered to this participant, as he was


involved in phase


of the study.


He did well on most of the English measures, again


with the exception of nonword repetition (33% error rate).


He did particularly well on


the spoonerisms task.


Good English predictor scores.


To examine the influence of English predictor


scores on German composite scores, performance of participants who did exceptionally


well on the English predictor tasks will now be discussed.


As mentioned above,









Participant #38 was a 23-year-old male majoring in classical studies.


that initially he was a physics major but preferred studying language.


He reported


He has studied


Latin, Greek, French, and Spanish and earned grades of"


" in all of these classes.


This


student reported his SAT scores were 800 verbal and 740 math (each out of 800).


On the


English experimental measures, Participant #38 made no errors on the elision, phoneme

reversal, spoonerisms and number learning tasks and had only a 1% error rate on the


English spelling.


In German, he did well on the vocabulary and spelling measures but


was relatively slow on the German RAN task.


His English RAN score was very fast.


a result of the difficulty with the German RAN task, the German composite score was in

the median range (33" out of 65).

Participant #14 was a 22-year-old male double major in philosophy and molecular


biology


He reported that his verbal SAT score was 800 out of 800 and he made no


errors on the English vocabulary test. H

spelling, and number learning measures.


e also did well on the nonword repetition, elision,

His German spelling and vocabulary scores


were strong, however as a consequence of his "average"


#14's


German RAN score, Participant


German composite score was ranked 19th out of 65 participants.


Profiles of Weak Foreign Language Learners (High Rate of Error/Slow Time on the
Experimental Measures)


Poor German composite score.

on the German composite measure. Cha


Participants #3 and #56 did particularly poorly


iracteristics of these participants will now be


described.








all of the English language measures, ranking among the poorest performers in each


measure.


She experienced particular difficulty with vocabulary, elision, and nonword


repetition.

Participant #56 was an eighteen-year-old female majoring in Political Science.

She did not report a history of learning difficulties but rated her own spelling abilities as


"poor"


. She participated in phase 2 of the study, so all of the phonological measures


were administered.


She had particular difficulty with the phoneme reversal task, the


timed aspect of the spoonerisms task (taking over two minutes to complete the 10-item


task), and the English vocabulary measure. German vocabulary and rapid automatized

naming were particularly difficult for this participant, contributing to her poor score on


the German composite measure.


Poor English predictor scores.


Participants #47 and #5


had a great deal of


difficulty with the English spelling test.


Participant #47 will be described in greater


detail below because he reported a history of learning problems.


His difficulty with


English spelling predicted a poor score on the German spelling measure, which


contributed to a poor German composite score.


Participant #


did poorly on the English


spelling and the English vocabulary measures,


as well as the German spelling and


Vocabulary measures.

Participants #10, #16, and #21 struggled with the English vocabulary measure

which corresponded to poor German vocabulary performance.








Reported history of learning problems


Two of the participants reported a history of learning difficulties.


One reported


that he had attention deficit/hyperactivity disorder (Participant #47) and the other

reported a history of difficulty learning foreign languages (Participant #46).

Participant #47 had a great deal of difficulty with the phoneme reversal task, the


spelling clues task, and the number learning task.


These tasks require a certain degree of


concentration.


It is possible that this participant's


attention problems affected his


performance on these tasks.


His German composite score was in the poor range (63" out


of 65).

Participant #46, who reported a history of foreign language learning difficulty,

had difficulty with the phoneme reversal task and the nonword repetition task; however

his German skills were all within the average range, in comparison to the other


participants.


He appeared to be a very motivated student who was taking the course for


personal growth rather than to fulfill the requirements for a degree.


Compared with the


other participants, is German composite score ranked 35th out of 65.

Participant #61 did not report a history of learning problems on her questionnaire

but verbally expressed that she felt that the experimental phonological tasks were difficult


for her.


She also said that she did not understand why she had such a high score on the


verbal SAT (700 out of 800), is getting As in her other courses, and expected to get a B in


German.


She demonstrated good insight into her situation when she said, "I guess it's


too late for Hooked on Phonics."


Compared to the other participants, Participant #61 had








spelling clues test.


However her German composite score was 60th out of 65.


struggled with the German spelling and RAN measures.


Summary


- Anecdotal Reports


These anecdotal reports provide support for the hypothesis that native language


skills influence foreign language learning.


In general, strong skills in English predicted


strong skills in German; and weak English skills predicted weak German learning.

Limitations and Future Directions

Limitations of this study include the fact that only one foreign language was


studied.


Results may not be able to be generalized to other foreign languages that are


more or less transparent than German.


Also, this study involved college students.


Younger learners may learn foreign languages in a different way, so the results of this


study may not apply to younger learners.


Also


, this study only looked at foreign


language learners in a classroom setting.


Criteria for foreign language learning in an


immersion environment may vary.

Future directions for research in the area of foreign language should include study

relationships between English and languages with various sound and syllable structure


(i.e.,


varying degrees of granularity and transparency).


It would also be interesting to


study foreign language learners at different ages to further investigate the idea of a


critical period for foreign language learning.


Comparing predictors of proficiency in


immersion learning versus classroom learning could yield some interesting relationships.

This study touched on the possibility that strong and weak native language skills may





82


Aptitude Test was such a strong predictor of foreign language proficiency, the entire test


should be examined in greater detail and possibly standardized.


outdated and incomplete.


The published norms are


It would be valuable to have updated information on this


instrument.

Clinical Implications

Because foreign language is required for many university degrees, it is important


to understand the skills that are necessary for successful completion.


If a student is


struggling through the foreign language requirement, he or she may spend an inordinate


amount of time on this class, possibly at the expense of other courses.


The student may


also receive a failing grade, which will affect his or her grade point average and may


result in diminished self-esteem.


If the student can better understand the nature of the


learning difference, he or she will be able to be a better self-advocate.

After the Guckenberger vs. Boston University (1998) ruling that gave universities


increased discretionary power in the granting of foreign language course waivers,


institutions are offering this option to students with learning disabilities.

complete foreign language courses with academic accommodations. Un


fewer


Students must


understanding


foreign language learning problems can help institute appropriate course

accommodations so that students with learning problems can successfully fulfill foreign


language requirements


Examples of such accommodations include:


use of note-takers,


audiotaping class lectures, access to textbooks on tape, breaking large amounts of


information into smaller segments,


extended test-taking time,


taking tests in a distraction-








Siegel (1999) emphasized that the accommodations should specifically relate to


the nature of the learning disability.


For example, if a student has trouble processing


auditory information, he or she would benefit from audiotaping class lectures in order to


review the material after class.


On the other hand, for a student who is a slow reader,


extended test-taking time would be an appropriate accommodation.

DiFino and Lombardino (in press) recommended specific strategies to assist


struggling foreign language learners.


An example is the use of color-coded index cards


for students having difficulty memorizing the gender of nouns (i.e., pink for feminine,


blue for masculine, and yellow for neutral).


These authors also developed a checklist to


help foreign language instructors identify "red flags" which could be associated with

foreign language learning problems (e.g., confusion during class, presence of unexpected

spelling errors, and difficulty with memorization).

Understanding the contribution of native language skills to foreign language

learning can also help in the development of modified or remedial foreign language


instructional strategies.


match students'


Modified foreign language courses can be taught in ways that


learning abilities and maximize their potential for completing the course.


Sparks, Ganschow, Kenneweg, and Miller (1991) described how a multisensory,

structured language approach which involves explicit teaching of phonology could be


incorporated into foreign language instruction.


Sparks, Ganschow, Pohlman, Skinner,


and Artzer (1992) extended this work when they compared instructional methodology for


three groups of struggling foreign language learners.


One group received multisensory









foreign language (MSL/S).


The third group of struggling learners received only


traditional instruction without explicit instruction of the phonological system of the


foreign language (NO-MSL).


Both MSL groups made gains in foreign language aptitude


and the MSL/E group also made gains in native language phonology, vocabulary, and


verbal memory.


The NO-MSL did not make gains in either native language skills or


foreign language aptitude.

not discussed (Sparks, Ga


Foreign language performance in these modified courses was


nschow, Pohlman, Skinner, and Artzer, 1992).


Goulandris (2003) explained that the manifestation of dyslexia is less prevalent in


languages that are transparent.


These languages have a strong sound-symbol


correspondence; and instruction typically involves a direct phonics approach.


combination of these two factors helps to minimize the effects of phonological processing


deficits, which are often associated with reading problems.


If foreign language study,


particularly in transparent languages, incorporated a similar emphasis on the sound

system, perhaps foreign language learning problems would be minimized.

Conclusions

In summary, this study provided support for the Linguistic Coding Differences


Hypothesis by examining a range of foreign language learning abilities.


For a sample of


65 college students enrolled in a first-semester German course, native language skills


influenced foreign language learning.

phonological skills was also examined.


The effect of task difficulty in the area of

A simple phoneme manipulation task (elision)


was too easy for college students who had achieved a relatively high level of language





85


this study demonstrated cross-language transfer of skills in the areas of spelling and

vocabulary.














APPENDIX A
INSTITUTIONAL REVIEW BOARD (IRB) PROTOCOL


PROTOCOL # 2003-4-121
REVISED (Tasks, Number of Participants)

1. TITLE OF PROTOCOL: The Influence of Native Language Skills on Foreign
Language Learning: Phonological and Semantic Contributions (Protocol # 2003-4-
121)

2. PRINCIPAL INVESTIGATOR(s): (Name, degree, title, dept., address, phone #, e-
mail & fax): Gerianne M. Gilligan, M.A., Doctoral Candidate, Communication Sciences
and Disorders, 435 Dauer Hall, 392-2041, gerianne@ufl.edu, fax: 846-0243

3. SUPERVISOR (IF PI IS STUDENT): (Name, campus address, phone #, e-mail &
fax): Linda J. Lombardino, Ph.D., Professor, Communication Sciences and Disorders,
336 Dauer Hall, 392-2113, llombard(@csd.ufl.edu, fax: 846-0243

4. DATES OF PROPOSED PROTOCOL: From: 2/3/03 To: 12/31/03

5. SOURCE OF FUNDING FOR THE PROTOCOL (As indicated to the Office of
Research, Technology and Graduate Education): None

6. SCIENTIFIC PURPOSE OF THE INVESTIGATION:
The purpose of this investigation is to describe how native language skills in phonology,
orthography, and semantics contribute to learning a foreign language. By looking at
these areas of native language ability, we hope to better understand the difficulties
experienced by some foreign language learners, as well as the strengths of "good" foreign
language learners.

7. DESCRIBE THE RESEARCH METHODOLOGY IN NON-TECHNICAL
LANGUAGE. The UFIRB needs to know what will be done with or to the research
participantss.

Tir ham nTn U'iAfnn Avnit Pfccnr Prfccnrr Aff errnann 2rd rnnrlinatnr nf 11 terlrhincT





87

orthographic (reading, spelling), vocabulary, and acquisition of code (ability to quickly
learn a new numeric code system). These skills are not influenced by instruction in a
foreign language. Administration of the native language (English) tasks will involve
about 45 minutes of tests administered to a group of students and individually scheduled
sessions of 15 minutes, for a total of 60 minutes of English language testing (across three
sessions). At the end of the semester, acquisition of select basic German skills will be
evaluated by group administration of vocabulary and spelling tests. German language
testing will involve about 15 minutes of testing. The following table describes the tasks.


Language Skill I Description I Time


English


Vocabulary


Group administration. An array of four pictures
will be presented on overhead projector.
Examiner (PI) will say word. Participants will
write the # of the picture that corresponds with t
word.


he


I 10 min.


Spelling Group administration. Examiner will say words 10 min.
for partici ants to write.
Number Group administration. Nonsense words to 10 min.
Learning represent numbers. Participants' ability to learn
(Verbal new "numbers" is evaluated. Example of task:
Working "ba" is 1, "baba" is 2, dee is 3, "tu" is 20, "ti" is
Memory) 30. What is "ti-ba", what is "baba". This is a
subtest from the Modem Language Aptitude Test
(Carroll and Sapon, 1959).
Spelling Group administration. Task taps into vocabulary 15 min.
Clues and phonological knowledge. Participant sees a
(integration word such as "knfrns" and must choose the
of phon. and appropriate definition from a field of five. The
vocabulary) appropriate definition for this example would be
"discussion meeting" (conference). This is a
subtest from the Modern Language Aptitude Test.


Phonological
Awareness


Individual administration. Spoonerisms task.
Examiner will say two words (e.g., Walt Disney)
and participant will be required to switch the
initial sound in each part ("Dalt Wisney").
Individual administration. Elision task (from the
Comprehensive Test of Phonological Processing,
Wagner, Torgesen, & Rashotte, 1999). Participant
says a word such as "driver" and then is asked to
say the word again, without one phoneme (e.g.,
"v"). Participant must say "dryer".


2 min.


4ntxin.
































8. POTENTIAL BENEFITS AND ANTICIPATED RISK. (If risk of physical,
psychological or economic harm may be involved, describe the steps taken to protect
participant.)

No risks are anticipated. Findings of the study are intended to better understand the
difficulties experienced by some students when learning a foreign language. When
difficulties are understood, modifications to traditional foreign language courses can be
developed, rather than granting waivers to all students experiencing difficulty. With
appropriate accommodations and/or modifications, students with disabilities can more
fully participate in the curriculum developed by the University.


9. DESCRIBE HOW PARTICIPANTS) WILL BE RECRUITED, THE NUMBER
AND AGE OF THE PARTICIPANTS, AND PROPOSED COMPENSATION (if
any):
Students enrolled in first-semester German courses in the German Department will be
given the option to participate. For their participation, students will earn 5 points of
"extra credit" to be added on to their final examination grade for the course. 65 students
will participate in the study. aees 18-45. Students who do not narticinate will he rivpn


Language Skill Description Time
English Phonological Individual administration. Phoneme Reversal task 4 min.
Awareness (from the Comprehensive Test of Phonological
(cont.) Processing, Wagner, Torgesen, & Rashotte, 1999).
Participant hears individual phonemes which,
when reversed, make up a word. Participant must
providee the real word.
Phonological Individual administration. Nonword repetition 4 min.
Short-term task (from the Comprehensive Test of
Memory Phonological Processing, Wagner, Torgesen, &
Rashotte, 1999). Participant repeats multi-syllabic
nonwords that are presented on audiotape. Must
be repeated 100% accurately.
RAN Individual administration. Naming a series of 1 min.
numbers in English. Timed task.
German Vocabulary Group administration. Similar to English 8 min.
vocabulary task with German words.
Spelling Group administration. Similar to English spelling 7 min.
task, with German words.
RAN Individual administration. Naming a series of 1 min.
numbers in German. Timed task.





89


10. DESCRIBE THE INFORMED CONSENT PROCESS. INCLUDE A COPY OF
THE INFORMED CONSENT DOCUMENT (if applicable).
Students enrolled in Beginning German I will be invited to participate in this study. For
their voluntary participation they will earn five extra credit points added on to their final
examination grade. A copy of the Informed Consent document is included as Appendix
B.

ATTACHMENTS
Appendix B: Informed Consent
Appendix C: Questionnaire



Principal Investigator's Signature




Supervisor's Signature

I approve this protocol for submission to the UFIRB:


Dept. Chair/Center Director Date