Metacognitions about Language Skill and Working Memory among ...

Metacognitions about Language Skill and Working Memory among Monolingual and Bilingual College Students: When Does Multilingualism Matter? Sarah Ransdell Nova Southeastern University, Ft Lauderdale, FL, USA Marie-Laure Barbier University of Provence, Aix-en-Provence, France Toomas Niit Tallinn University, Tallinn, Estonia Previous research has shown that individual differences in working memory (WM) are highly predictive of a wide range of cognitive behaviours. Until recently, research has focused on monolingual, or undifferentiated, populations. The present research compares metacognitive awareness, as measured by self-ratings of reading, writing, speaking and listening skills in college students of varying language experience backgrounds. Monolingual, bilingual and multilingual university students within three cultural contexts, America, Estonia and France, read for comprehension and remembered sentence final words of comprehended sentences in a reading span task in their native languages. The results show that bilingual and multilingual students have better metalinguistic awareness of their language skills in reading and WM than do students who are monolingual, but who have comparable native language skills. doi:10.2167/beb390.0

Keywords: bilingualism, multilingualism, working memory, reading span, reading comprehension, metacognitive awareness Decades of research has shown that working memory (WM) is closely tied to long-term memory (LTM) and is greatly affected by it. Thus, what we already know has a direct impact on current processing. A special type of WM has even been proposed, long-term WM (LT-WM), to explain how experience develops into expert retrieval from LTM through deliberate practice (Eriksson, 2000; Eriksson & Delaney, 1999; Eriksson & Kintsch, 1995). Those individuals with a lifetime of experience activating and inhibiting language codes may have developed a LT-WM specific to bilingual development and skill (i.e. Ransdell & Arecco, 2001). Others have conceived of knowledge built through experience as metacognitive awareness (i.e. Mokhtari & Reichard, 2002). Metacognitive awareness includes knowledge about cognitive processes 1367-0050/06/06 728-14 $20.00/0 The International Journal of Bilingual Education and Bilingualism

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as well as self-control mechanisms while monitoring and regulating behaviour. Metacognitive skills may also transfer into other domains, even domains outside of verbal processing per se (Kellogg et al ., 2006). The purpose of the present research is to explore the relations among reading comprehension, reading span (RS) and language experiences. Evidence for different relations among WM tasks in those with a heterogeneous set of experiences in language use relative to those who are monolingual may indicate the existence of a LT-WM or metacognitive skill that has arisen from adaptations needed in a bilingual environment. Self-assessment may be one domain in which bilinguals excel. The diglossic characteristic of bilinguals in the South Florida community in particular, where one language is spoken at home and one written and read at university, anticipates an easier separation in the assessment of relative skill. In other words, if bilinguals typically speak one language at home, but write and speak another in the college classroom, these students are more likely to be able to assess skill independently in each language. An American sample, a French sample and an Estonian sample are included in the present study. The French college students have a similar diglossia to the Americans as they know English mainly as a written, formal language used in school. The Estonian sample includes students who read and write several languages within school and university contexts. This study will compare metacognitive knowledge in the form of self-assessments of speaking, listening, reading and writing in the two or more languages that each participant indicates are their current ‘strongest’ languages. Those participants with more diverse and extensive language experience should be better able to predict their skill than those with limited, mostly monolingual, language experiences.

WM as Active Self-regulation One dimension that figures prominently in explaining individual differences is the idea of self-regulation with increasing skill development. WM is essential for the skilled self-regulation of learning and memory. Expertise develops a kind of WM that quickly accesses LTM and adapts to the new demands of skilled performance. The type of skilled performance that is the focus of the present paper is that of bilingual college students. They may read and write well in school and yet have an entire set of vocabulary, grammar and pragmatic details that are separable from those they use in a university context. A form of skilled self-regulation related to the present study is that of professional translators. While most bilinguals are not simultaneous translators, they may have developed skills similar in kind but not degree to those of translators. Research shows that some skills are greatly improved among professional translators compared to non-translators, by definition, listening and comprehending while interpreting (Gerver, 1974), and some are reduced, simple shadowing of a verbatim message in a single language can be harder for interpreters than for those who are not (Moser-Mercer et al ., 2000). Cowan (2000) suggests that interpreters have learned to switch attention rapidly and strategically between speaking and listening tasks, and they have improved

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through deliberate practice to reduce the demands of one or both dual tasks. The present study investigates the self-assessment skills of students with varying language experience. Those with greater experience should have stronger self-assessment skill that covaries with bilingual skill.

WM and Complex Span That WM is responsible for active information processing rather than strictly passive short-term maintenance of information has been at the core of cognitive psychology since Miller’s magical number 7 plus or minus 2 paper (Miller, 1956). Research since then has greatly improved our understanding of WM, especially most recently with the concept of individual differences in RS and other complex WM spans that have shown good predictive power in academic domains (Daneman & Carpenter, 1980; Daneman & Merikle, 1996). RS measures the extent to which a participant can read increasingly larger sets of sentences while storing the final words of each sentence for later recall. Despite remaining controversy over the locus of causal factors linking span and complex behaviour relations, interesting applied questions are now being addressed. For example, Hannon and Daneman (2001) have found the typical strong relation between RS and reading comprehension even when controlling for test-taking strategies related to metacognitive awareness of how to take reading comprehension tests. They further suggest that good self-regulation of central executive functioning could compensate for limits in active maintenance of information in WM. The present study investigates how metacognitive knowledge developed because bilinguals’ need to activate and inhibit language codes could set them apart from monolinguals in terms of reading comprehension and RS relations. There is ample evidence that poor readers are less able to actively suppress irrelevant information than good readers (Gernsbacher, 1993). Perhaps the bilingual who must actively inhibit and suppress language codes has also developed a mechanism that allows them to be more efficient even when processing monolingual information and more accurate in predicting their own behaviour. Whitney et al . (2001) have shown that individual differences in RS can help us understand central executive functioning in general. They found that manipulation capacity and susceptibility to interference are the two factors that underlie the RS task. RS groups are usually based on a simple categorisation of high and low performers taken from the upper and lower quartiles of performance (i.e. Just & Carpenter, 1992). Whitney et al . (2001) suggest that, as manipulation capacity and susceptibility to interference are independent predictors of RS, different people may score better or worse based on different reasons. We take this idea further by suggesting that bilingual speakers will approach even a strictly native language only version of RS as a different task relative to monolinguals and to bilinguals with less experience inhibiting a non-target language.


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Self-assessment of First and Second Language Skill Measuring individual differences in self-regulatory use of more than one language can also be difficult. One of the most common ways, and one with surprising reliability, is the use of self-assessment. Ross (1998) conducted a meta-analysis of over 60 studies comparing self-assessments of first and second language skills and performance on direct measures of those skills. The effect size for the concurrent validity across those studies was 0.63 across all skill domains, 0.61 for reading, 0.65 for listening, 0.55 for speaking and 0.52 for writing. Self-prediction of behaviour was a bit higher for productive rather than receptive skills but was within an acceptable range for all domains. Ross concludes that the episodic memory of specific skills is one of the best bases for self-assessment and that such measures can be accurate reflections of behaviour. The present study employs a Language Experience Questionnaire (LEQ) designed to ask participants to assess specific skills levels in all of the languages they know within specific and well defined domains and against a specific comparison group.

Hypotheses Multilingual experiences will facilitate metacognitive awareness as measured by self-assessments of language skill. Self-assessments of language skill will be better differentiated among bilingual and multilingual relative to monolingual college students. The power of RS to predict reading comprehension will differ among monolingual, bilingual and multilingual college students.

Method American sample

Participants One hundred and six upper-division university students volunteered to participate in their psychology classes at an American university. Of these, 58 participants were primarily monolingual, even though 20% of them had studied Spanish in secondary or postsecondary school, 7% in French and 3% in German. Of the monolinguals, 72% were Americans by birth, while 21% were born in Jamaica. All monolinguals listed English as their native language. See the Appendix for a copy of the complete LEQ on which participant characteristics were based. Students in all three samples were characterised as bilingual if they self-reported a ‘next strongest language’ that was not simply a college course. Forty-eight participants were bilingual students because they listed a ‘next strongest’ language and had learned this language outside of a secondary or postsecondary classroom context. Because of language origins, Jamaican was considered English while Haitian Creole was considered a second language. Of the bilinguals, 46% were born in America and 55% were born in 16 different countries, mostly from Latin and South America and Europe. Within the

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bilinguals, 60% listed English as their ‘strongest’ language, 20% listed Spanish as their strongest, and the remaining listed Haitian Creole and Portuguese about equally often. The bilinguals named English as their next strongest language at a rate of 35% and 45% named Spanish. Languages named as ‘strongest’ were almost always those participants reported as learnt at birth. Next strongest languages were learned equally at birth, in early childhood, and in late childhood and adolescence, but not exclusively in a school setting.

Materials and procedure The first task was a LEQ created by the authors for this study (see the Appendix). The participants were told that their responses would be confidential. They were instructed to follow along with the researcher as he or she read aloud and to answer the questions accordingly. All tasks were conducted in the majority language of the university setting, in this case, English. Next, the Nelson-Denny reading comprehension subtest, Form G, was administered according to the published protocol and participants had up to 20 min to read the passages and answer questions about them (Brown et al ., 1993). They were given directions for Part II of the Nelson Denny Reading Comprehension Test, A, B and C from the removed copy in the researcher’s note book. They were given a response sheet and were instructed to record their answers on it. The researcher begins the timer and says ‘START’; the subject is to read the passage for one minute. After the minute is up the researcher says ‘MARK’. The line number where the subject is currently reading is recorded. The researcher starts the timer again and it is set for 20 min. The subject continues to read the passages and record their answers on the multiple choice answer form. They are stopped after 20 min unless they finish sooner. Finally, a RS test was given to each subject. The RS test was adapted from Hannon and Daneman (2001). This test takes about 15 min. RS stimuli are presented from the researcher’s notebook and the pages are flipped by the researcher. The RS score sheet is organised in three series. There are five blocks in each of the series. The first block starts with two words and the fifth block ends in six words. If the participant said the word correctly the box next to the word was recorded with an X. In each block there is an * on one or more word(s) picked at random to represent non-coherent sentences, which is counted and scored later. In the RS test, each subject is to read the instructions aloud. The instructions were given as follows: ‘In this task, you will be presented with a series of unrelated sentences. You are to read the sentences out loud at your own pace. You should try to remember the last word of each of these sentences. It is important to not make a pause between sentences, nor to interrupt your reading at the middle of any sentences, even if it seems to you that one doesn’t make sense. Keep doing this until you see a blank, colored page. It means that the trial is over, and you have to say back the last word in each sentence in that trial. You can say them in any order, but you should not start with the last word first, unless it is the only one you can remember.’ There are two practice trials so they can grasp the concept. They read aloud the blocks of sentences in each series, they are then to say aloud the


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words they remember, if they get the words right the researcher records it with an X in the correct box.

Results Descriptive statistics for monolingual and bilingual subgroups in all three samples are presented in Table 1. The bivariate correlations by sample are Table 1 Descriptive statistics among bilingual and monolinguals by sample Variable

Mean

Std dev

Min

Max

Nelson Denny

27.2

6.45

12

36

Reading span

35.6

9.8

11

70

Reading span (coh)

17.4

4.15

6

28

Reading span (inc)

17.4

4.7

5

27

0.41

2.5

American monolingual (n!/58)

Eng writ/read

3.81

4

American bilingual (n!/48) Nelson Denny

26.9

Reading span

37.9

Reading span (coh)

18.2

Reading span (inc)

17.4

Eng writ/read

3.65

5.99

13

36

21

78

3.66

10

24

3.7

9

24

0.56

2

4

11.3

French bilingual (n!/31) Nelson Denny

17.6

3.48

11

23

Read span L2

36.8

7.09

26

53

Read span L2 (coh)

18.5

3.79

13

27

Read span L2 (inc)

18.3

3.70

11

27

Read span L1

44.8

5.64

32

53

Read span L1 (coh)

21.8

3.26

14

27

Read span L1 (inc)

22.9

2.90

16

27

Eng writ/read

2.64

0.78

1.5

4

Estonian multilingual (n !/60) Read span L2

34.4

6.36

22

52

Read span L2 (coh)

17.7

3.67

11

27

Read span L2 (inc)

16.7

3.36

10

27

2.9

0.64

Eng writ/read

1.5

4

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presented in Table 2. Table 2 shows that for American monolinguals, reading comprehension was reliably correlated with all predictors but English writing/reading self-assessment. For American bilinguals, reading comprehension was predicted by English writing/reading self-assessment only. Monolingual students do not differ in English reading comprehension skill relative to bilinguals but they do not self-assess their own reading skill as well as bilinguals. For American and French bilingual samples, self-assessment of Table 2 Bivariate correlations among monolingual and bilinguals by sample Variables

Pearson’s correlation 1

2

3

4

5

"

0.33*

0.47*

0.35**

0.12

"

0.86**

0.82**

0.13

"

0.77**

0.16

"

0.05

American monolingual (n!/58) 1. Nelson Denny 2. Reading span 3. Reading span (coh) 4. Reading span (incoh) 5. English writing/reading

-0.14

American bilingual (n!/48) 1. Nelson Denny

"

0.20 "

2. Reading span 3. Reading span (coh)

0.15

0.18

0.52**

0.67**

0.71**

0.21

"

0.67**

0.24

"

0.05

4. Reading span (incoh) 5. English writing/reading

-0.20

French bilingual (n!/31) 1. Nelson Denny

"

0.56**

0.56**

0.49**

0.45**

"

0.94**

0.94**

0.14

"

0.77**

0.12

"

0.14

0.91**

0.89**

0.35*

"

0.77**

0.33*

"

0.30*

2. Reading span 3. Reading span (coh) 4. Reading span (incoh) 5. English writing/reading Estonian multilingual (n!/60) 1. Reading span 2. Reading span (coh) 3. Reading span (incoh) 4. English writing/reading Estonian students did not take the Nelson Denny test

"

"


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Table 3 Stepwise regression for American monolingual and bilinguals, and French bilinguals predicting reading comprehension R

R2

Mean square

F

Sig.

1

0.12

0.01

33.3

0.80

0.37

2

0.33

0.11

131.1

3.41

0.04

3

0.41

0.17

134.7

3.70

0.01

1

0.52

0.26

409.8

16.89

0.00

2

0.53

0.27

233.8

8.63

0.00

3

0.53

0.28

157.2

5.69

0.00

1

0.45

0.20

74.0

7.42

0.01

2

0.67

0.46

166.3

11.82

0.00

3

0.69

0.47

8.00

0.00

Model American monolinguals

American bilinguals

French bilinguals

56.97

Model 1 predictors: Eng Writing/Reading Model 2 predictors: Eng Writing/Reading, RS Model 3 predictors: Eng Writing/Reading, RS, RScoh

Table 4 Stepwise regression for American monolingual and bilinguals, French bilinguals and Estonian multilinguals predicting reading span R

R2

Mean square

F

Sig.

1

0.13

0.01

96.5

1.00

0.32

2

0.33

0.11

312

3.53

0.04

1

0.21

0.05

286.9

2.30

0.14

2

0.24

0.06

177.4

1.41

0.25

1

0.14

0.02

29.4

0.58

0.45

2

0.58

0.33

250.5

6.97

0.00

0.35

0.12

290.6

8.03

0.00

Model American monolinguals

American bilinguals

French bilinguals

Estonian multilinguals 1

Model 1 predictors: Eng Writing/Reading Model 2 predictors: Eng Writing/Reading, ND

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writing/reading skill was a reliable predictor of reading comprehension. Estonian students did not take a reading comprehension test. For both French and Estonian samples, all measures collected predicted reading comprehension, including RS. A stepwise regression predicting reading comprehension scores is presented in Table 3 by sample. RS predicts 7% of the variance in reading comprehension (ND) and self-ratings of reading skill (SR) predict 8% among all 106 participants. Within the monolingual subgroup, RS predicts 11% of ND (r!/0.32), which is in the range of most studies (see Daneman & Merikle, 1996). Within the bilingual subgroup, SR predicts 26% of ND (r!/0.52). RS predicts 10% of ND, but only when it is entered before SR. RS is not reliable when entered after SR and was only measured in the American sample. Self-ratings of listening and speaking skill do not predict reading in any group. RSC (coherent) predicts ND in monolinguals (0.41, 17%), also in the normal range of published studies. Neither RSC nor RSIC (incoherent) predict ND in bilinguals, even when in model before SR and SR now predicts 30%. Table 4 provides the stepwise regression by sample for predicting RS. Only ND contributes to RS in the American monolingual sample. ND contributes reliably to RS in both the French bilingual and the Estonian samples. French sample

Participants Thirty-one upper-division university students volunteered to participate in their language classes at a French university. Of these, all participants were native speakers of French and all of them had studied English in secondary school, on average beginning at the age of 10, and for at least a dozen years. All were French by birth with an average age of about 30. Eleven listed Italian as a third language, 17 listed Spanish as a third language and 12 listed German. Only two participants did not list a third language in addition to French and English.

Materials and procedure As with the American sample, the Nelson-Denny reading comprehension subtest, Form G, was administered according to the published protocol and participants had up to 20 min to read the passages and answer questions about them (Brown et al ., 1993). The RS test was also used as before, adapted from Hannon and Daneman (2001).

Results French students completed RS tests in both English and French, which were correlated with each other (0.59). This means that abilities in WM are transferred from reading in one language to a second one. Moreover, their RS in English contributes reliably to the prediction of reading comprehension (0.56), as is typical in most studies and in the American sample monolinguals (0.33). Unlike among American monolinguals, French students’ reading comprehension was also predicted by self-assessment of reading skills, 0.45. This result suggests that French"English bilinguals are superior to American


737

monolinguals (0.12) in predicting their own reading performance and equal to English-speaking bilinguals (0.52). Estonian sample

Participants Sixty-three upper-division university students volunteered to participate in their language classes at an Estonian university. Of these, all participants were native speakers of Estonian and all of them had studied English in secondary school, on average beginning at the age of 10, and for at least a dozen years. This sample is best characterised as multilingual, as students also knew Russian, German, Finnish, and to a lesser extent, Swedish because of the geopolitical context of the country.

Materials and procedure This sample completed the Language History Questionnaire including self-assessments of language skill as in the other two samples. The RS test was also used as before, adapted from Hannon and Daneman (2001).

Results Estonian students’ RS scores were predicted by self-assessments of reading (0.35), speaking (0.27) and writing (0.33) consistent with the idea that multilingualism aids self-assessment and metacognitive awareness. This sample has an unusually rich set of language experiences, as the average number of languages known well is 3.4, with a range of 2 to 6, and an SD of 0.958. The number of other languages known is also reliably predictive of self-ratings of language skill in all domains. Interestingly, number of other languages is a reliable predictor of RS, 0.27.

Discussion Multilingualism matters for self-assessment of skill and for prediction of a widely used measure of WM, RS. A rich set of language experiences correlates with good metacognitive awareness in three diverse cultural contexts. American monolinguals do not predict their reading comprehension skill as well as American bilinguals, French bilinguals or Estonian multilinguals. These findings are important because most research assumes that monolingual and bilingual research participants will perform equivalently, or assumes that bilinguals will always underperform in their non-native language. RS has the kind of correlation with reading comprehension that it typically does among the American monolingual participants but does not reliably contribute to reading skill among American bilinguals. Bilingual and multilingual French and Estonian participants also have reliable relationships between RS and reading comprehension, indicating the relative important of this measure of WM for their concurrent reading performance. The results show that bilingual and multilingual students have better metalinguistic awareness of their language skills in reading and WM than do students who are monolingual, but who have comparable native language skills. In a related study, Ransdell (2003) has shown that monolingual students

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were reliably better in receptive vocabulary, reading comprehension and writing fluency than their bilingual peers. Monolingual and bilingual students were equivalent, however, in grammar awareness, phonological awareness, expressive vocabulary, vocabulary density and writing quality. The best predictors of reading comprehension skill among monolingual students were grammar awareness, and both receptive and expressive vocabulary. No measures were reliable predictors of bilingual skill. One of the ramifications of the present research is that language experience may interact with basic cognitive assessments, including self-assessments, and that this interaction should be accounted for in research reports. Even research reports not geared to the study of bilingualism will increasingly need to consider language experience because more university students in America and elsewhere are bilingual. While the present correlational data cannot determine the causal mechanisms behind bilingual advantage in self-assessment of language skill and the relative lack of RS relationships with reading comprehension in American bilingual speakers, the data do point to the need to consider different patterns of predictability in research. The best hypothesis thus far about why bilinguals may excel in metacognitive awareness, and therefore do better at selfassessment, lies in the lifetime of experiences bilinguals have in activating and inhibiting language codes. Metacognitive awareness underlies self-control mechanisms while monitoring and regulating behaviour (i.e. Kellogg et al ., 2006) and should be considered a bilingual advantage not just in childhood (i.e. Bialystok, 1988) but in adult university students as well. Recent work by Bialystok (2003) suggests that bilingual adults may maintain an advantage in cognitive control over comparable monolinguals and this skill may even offset age-related losses in executive processing over time. Studies of adults, particularly those experiencing age-related memory loss, should focus on identifying lifetime patterns of bilingualism, and without the assumption that bilinguals will be at a disadvantage. This will take a paradigm shift in many fields as demographic information about bilinguals, if given at all, is often only described as a potentially debilitating condition for native-like performance in English. Miyake and Friedman (1998) have proposed that individual differences in second language proficiency may be related to WM as a general language aptitude. They found that a learner’s WM capacity influences the ability to acquire native-like skill in a second language. Those with higher WM capacity, as measured by RS in a first language, were stronger in using linguistic cues to comprehend complex sentences correctly and efficiently in their second language. Research is beginning to look at the influence of second language expertise in general cognitive processing (i.e. Kroll et al ., 2002; Miyake & Friedman, 1998; Tokowicz et al ., 2004), but more emphasis on the extent to which multilingualism matters has become a necessity for future research. Acknowledgements The authors would like to thank Kwok Au, Tanika Benjamin, Tiara Davis, Mart Kase, Alex Garvey, Charu Jain, Anisha Staton, Zyanya Torres and


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Christina Waddell for assistance in data collection. This project was funded in part by a Collaborative Linkage Grant ref. 979517 from the North Atlantic Treaty Organization. Correspondence Any correspondence should be directed to Sarah Ransdell, College of Allied Health and Nursing, Nova Southeastern University, 3200 S University Drive, Ft. Lauderdale, FL 33328 USA ([email protected]). References Bialystok, E. (1988) Levels of bilingualism and levels of linguistic awareness. Developmental Psychology 24, 560"567. Bialystok, E. (2003) Bilingualism, aging, and cognitive control: Evidence from the Simon task. Psychology and Aging 19, 290"303. Brown, J.I., Fishco, V. and Hanna, G. (1993) Nelson-Denny Reading Test . Boston, MA: The Riverside Publishing Company, Houghton Mifflin. Cowan, N. (2000) Processing limits of selective attention and working memory: Potential implications for interpreting. Interpreting 5, 117"146. Daneman, M. and Carpenter, P.A. (1980) Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior 19, 450"466. Daneman M. and Merikle, P.M. (1996) Working memory and language comprehension: A meta-analysis. Psychonomic Bulletin and Review 3, 422"433. Gernsbacher, M.A. (1993) Less skilled readers have less efficient suppression mechanisms. Psychological Science 4, 294"298. Ericsson, K.A. (2000) Expertise in interpreting: An expert-performance perspective. Interpreting 5, 187"220. Ericsson, K.A. and Delaney, P.F. (1999) Long-term working memory as an alternative to capacity models of working memory in everyday skilled performance. In A. Miyake and P. Shah (eds) Models of Working Memory: Mechanisms of Active Maintenance and Executive Control (pp. 257"297). New York: Cambridge University Press. Ericsson, K.A. and Kintsch, W. (1995) Long-term working memory. Psychological Review 102, 211"245. Gerver, D. (1974) Simultaneous listening and speaking and retention of prose. Quarterly Journal of Experimental Psychology 26, 337"341. Hannon, B. and Daneman, M. (2001) A new tool for measuring and understanding individual differences in the component process of reading comprehension. Journal of Educational Psychology 93, 103"128. Just, M. and Carpenter, P. (1992) A capacity theory of comprehension: Individual differences in working memory. Psychological Review 98, 122"149. Kellogg, R.T., Friedman, A., Johnson, P. and Rickard, T. (2006) Domain-specific knowledge in intellectual skills. In A. Healy (ed.) Experimental Cognitive Psychology and its Applications: Festschrift in Honor of Lyle Bourne, Walter Kintsch, and Thomas Landauer. Washington, DC: American Psychological Association. Kroll, J., Michael, E., Tokowicz, N. and Dufour, R. (2002) The development of lexical fluency in a second language. Second Language Research 18, 137"171. Michael, E. and Gollan, T. (2005) Being and becoming bilingual: Individual differences and consequences for language production. In J. Kroll and A. De Groot (eds) Handbook of Bilingualism: Psycholinguistic Approaches . Oxford University Press. Miller, G.A. (1956) The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review 63, 81"87. Miyake, A. (1998) Individual differences in second language proficiency: The role of working memory. In A. Healy and L. Bourne (eds) Foreign Language Learning: Psycholinguistic Studies on Training and Retention . Lawrence Erlbaum. Miyake, A. and Friedman, N. (1998) Individual differences in second language proficiency: Working memory as language aptitude. In A. Healy and L. Bourne

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(eds) Foreign Language Learning: Psycholinguistic Studies on Training and Retention (pp. 339"365). London: Lawrence Erlbaum. Mokhtari, K. and Reichard, C. (2002) Assessing students’ metacognitive awareness of reading strategies. Journal of Educational Psychology 94, 249"259. Moser-Mercer, B., Frauenfelder, U., Casado, B. and Kunzli, A. (2000) Searching to define expertise in interpreting. In B. Englund Dimitrova and K. Hylenstam (eds) Language Processing and Simultaneous Interpreting (pp. 107"132). Amsterdam: John Benjamins. Ransdell, S. (2003) The care and feeding of monolingual and bilingual university students in South Florida: Implications for assessment and training. Psychology Learning and Teaching 3 (2), 126"130. Ransdell, S.E. and Arecco, M.R. (2001) Bilingual long-term working memory: The effects of working memory loads on writing quality and fluency. Applied Psycholinguistics 22, 117"132. Ross, S. (1998) Self-assessment in second language testing: A meta-analysis and analysis of experiential factors. Language Testing 15, 1"20. Tokowicz, N., Michael, E. and J. Kroll (2004) The roles of study-abroad and workingmemory capacity in the types of errors made during translation. Bilingualism: Language and Cognition 7 (3), 255"272. Whitney, P., Arnett, P.A., Driver, A. and Budd, D. (2001) Measuring central executive functioning: What’s in a reading span? Brain and Cognition 45, 1"14.

Appendix: Language Experience Questionnaire Tell us about you. All responses are coded by subject ID only. Country of Origin __________ Parents’ Countries of Origin __________ Age __________ __________ Male __________ or Female __________ 1. Please list all of your languages, from strongest to weakest, and at what age you learned each of them. Strongest language _____________________________ age learned ______ Next strongest language ________________________ age learned ______ Next strongest language ________________________ age learned ______ 2. If you could choose, in what language would you feel most comfortable taking a reading comprehension test? ______________________ 3. If you could choose, in what language would you feel most comfortable during a 911 emergency call? ______________________ 4. How comfortable are you in going from one language to another when you want to or need to do so? Not very comfortable 1

2

3

Very comfortable 4


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5. In comparison to other FAU students, what are your skill levels in English?

a) Speaking in English b) Understanding spoken English c) Writing in English d) Reading in English

Low 1 1 1 1

2 2 2 2

3 3 3 3

High 4 4 4 4

6. In comparison to other FAU students, what are your skill levels in a language other than English? Name the language here _________________

a) Speaking b) Understanding spoken c) Writing d) Reading Researcher ID # __________

Low 1 1 1 1

2 2 2 2

3 3 3 3

High 4 4 4 4