Memory The contribution of working memory capacity ...

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Memory

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The contribution of working memory capacity to foreign language comprehension in children Ulf Andersson a a Linköping University, Sweden

First published on: 14 April 2010

To cite this Article Andersson, Ulf(2010) 'The contribution of working memory capacity to foreign language

comprehension in children', Memory, 18: 4, 458 — 472, First published on: 14 April 2010 (iFirst) To link to this Article: DOI: 10.1080/09658211003762084 URL: http://dx.doi.org/10.1080/09658211003762084

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MEMORY, 2010, 18 (4), 458472

The contribution of working memory capacity to foreign language comprehension in children

Downloaded By: [Linkopings University] At: 06:50 18 May 2010

Ulf Andersson Linko¨ping University, Sweden The present study examined the contribution of working memory processes in children’s foreign language processing of sentences and short stories. A total of 95 children were given measures of working memory when 910 years old. One to two years later at ages 1112, tasks tapping foreign language literal comprehension (English) and native language inferential comprehension (Swedish) were administered. Regression and correlation analyses demonstrated that both central executive and phonological loop processes predicted foreign language comprehension, whereas central executive processes but not phonological loop processes predicted native language reading comprehension. These findings show that children’s foreign language processing is supported by their working memory capacity tested in their native language. Some of these working memory resources appear to be unique for foreign language. The strong association between native language and foreign language processing suggests that an important factor in becoming proficient in foreign language is the child’s general language aptitude. Possible mechanisms for the contribution of working memory to children’s foreign language comprehension are discussed.

Keywords: Foreign language comprehension; Native language reading comprehension; Working Memory; Central executive; Phonological loop.

It is well documented that working memory is critically involved in language comprehension (e.g., Adams, Bourke, & Willis, 1999; DeDe, Caplan, Kemtes, & Waters, 2004; Swets, Desmet, Hambrick, & Ferreira, 2007). This involvement is theoretically logical as language processing is a high-order cognitive activity that involves a number of processes above and beyond decoding and identification of separate words. During story processing the relevant propositions extracted from the processed sentences are integrated into mental structures that contain the central theme of the story (Gernsbacher, 1990; Just & Carpenter, 1992; Kintsch, 1998). This creation of a mental proposition structure involves bridging inferencedrawing processes where information from

different sentences are related and integrated. Elaborative inferences provide additional information to the mental proposition structures by using information not explicitly stated (e.g., context; Singer, 1994). In order to integrate propositions into a mental proposition structure the different propositions must be held activated simultaneously in working memory (Baddeley, 1986; Daneman & Carpenter, 1980; Kintsch, 1998). Furthermore, inference drawing requires that previous language input and/or contextual information is maintained in working memory concurrently with recent language input (Calvo, 2001). Syntactic and semantic analyses of single sentences also appear to be affected by the

Address correspondence to: Ulf Andersson PhD, Associate Professor, Department of Behavioural Sciences and Learning, Linko¨ping University, SE-581 83 Linko¨ping, Sweden. E-mail: [email protected] This research was partially supported by a grant from the Bank of Sweden Tercentenary Foundation (J2002-0210: 2) and partially supported by a grant from the Swedish Council for Working Life and Social Research (2003-0158) awarded to Ulf Andersson.

# 2010 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business http://www.psypress.com/memory DOI:10.1080/09658211003762084


WORKING MEMORY AND FOREIGN LANGUAGE

individual’s working memory capacity (Swets et al., 2007; Waters & Caplan, 2005). During processing of syntactically ambiguous sentences, individuals with high working memory capacity, in contrast to individuals with low capacity, might try to retain multiple interpretations until disambiguating language input is presented, resulting in better comprehension (DeDe et al., 2004; Just & Carpenter, 1992). However, considerable controversy exists regarding the involvement of working memory capacity in syntactic processing. According to Just and Carpenter (1992) a single (general) verbal working memory resource pool is involved in all aspects of language processing including syntactic parsing (see also Miyake, Carpenter, & Just, 1994; Pearlmutter & MacDonald, 1995) whereas Waters and Caplan (1996; see also Martin, Shelton, & Yaffee, 1994) have proposed two separate verbal working memory resource pools. The first resource pool is involved in automatic aspects of language processing such as lexical access, syntactic parsing, and thematic role assignment, the second resource pool is used during controlled processing such as verbal reasoning, planning actions, controlled retrieval of information from semantic long-term memory. Both the single-resource pool view (Kolk, Chwilla, van Herten, & Oor, 2003; Moser, Fridriksson, & Healy, 2007; Vos, Gunter, Kolk, & Mulder, 2001) and the dual-resource pool view (DeDe et al., 2004; Friedmann & Gvion, 2003; Swets et al., 2007; Waters & Caplan, 2004) have received empirical support, which makes it difficult to put one before the other. Nevertheless, individuals with high working memory capacity are, in general, better at focusing and allocating their capacity to relevant information and inhibiting irrelevant information during language processing than those with low capacity (Adams et al., 1999; Kaakinen, Hyo¨ na¨ , & Keenan, 2003; see also Gernsbacher, Varner, & Faust, 1990). In contrast to native language processing there has been much less effort to systematically examine the role of working memory in foreign language processing. Foreign language processing should impose higher demands on the working memory system, because foreign language processing is slower, less automatised, and more effortful than native language processing (Dornic, 1980; Geva & Ryan, 1993; Harrington & Sawyer, 1992; McDonald, 2006; Miyake & Friedman, 1998; Segalowitz, Segalowitz, & Wood, 1998; Service, Simola, Metsa¨ nheimo, & Maury, 2002).

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One challenge for foreign language learners is the lack of fit between their phonological system (representations) and the phonological structure of the foreign language (Chiappe, Glaeser, & Ferko, 2007; Flege, 1995). Until the learners have developed a foreign language phonological system, they have to rely on their native language phonological system when phonologically decoding foreign language words presented orally (Cutler, Mehler, Norris, & Segui, 1992; for reviews see Eckman, 2004; Flege, 1995; Navarra, Sebastia´ n-Galle´ s, & Soto-Faraco, 2005; Werker & Tees, 1984) or in writing (Brauer, 1998; Chiappe et al., 2007; Jongejan, Verhoeven, & Siegel, 2007). Even when a foreign language phonological system is established it is affected by the individual’s native phonological system (Flege, 1995; Meador, Flege, & MacKay, 2000; Navarra et al., 2005). Furthermore, the established foreign language phonological system may not be as efficient as their native language phonological system, because the phonological representations are probably less segmented, resulting in slower and less accurate word identification and sentence processing during foreign language processing (Metsala, 1997, 1999; Segalowitz et al., 1998). It is well established that a limited vocabulary has a negative effect on native language reading comprehension skill and spoken word recognition (Carroll, 1993; Metsala, 1997, 1999; Stanovich, 1986). As most individuals have a less-developed foreign language vocabulary compared to their native language vocabulary, it is reasonable to assume that this factor constrains the processing of a foreign language more than the processing of native language (Laufer, 1992; Laufer & Goldstein, 2004; Schoonen, Hulstijn, & Bossers, 1998; van Gelderen, Schoonen, Stoel, de Glopper, & Hulstijn, 2007). Another potential factor making foreign language processing slower and more effortful is if the foreign language has a different syntactic structure from the individual’s native language. In such a case, the individual has to acquire knowledge about foreign language syntactic structure and use it during syntactic parsing of sentences (McDonald, 2006; Miyake & Friedman, 1998). It is reasonable to assume that syntactic parsing of sentences during these conditions is less automatic compared to native language syntactic parsing. Thus, due to the unfamiliarity with the syntactic structure and the phonological structure of the language, as well as a limited vocabulary, foreign language processing (word identification, sentence processing) should


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consume more working memory resources compared to native language processing, thereby leaving fewer resources available for language comprehension processes such as inference making, and establishing and developing a mental proposition structure (Ardila, 2003; Cheung, 1996; Chiappe et al., 2007; Geva & Ryan, 1993; Masoura & Gathercole, 2005; Miyake & Friedman, 1998; Service et al., 2002; Walter, 2004, 2007). Previous studies on children have provided evidence consistent with the assumption that working memory plays an important role in foreign language processing (e.g., Ellis & Sinclair, 1996; Lehto, 1995; Papagno, Valentine, & Baddeley, 1991; Service, 1992). However, a large majority of the available studies have examined foreign language vocabulary in relation to phonological working memory, whereas few studies have focused on the processing of sentences or stories and other working memory resources such as executive control processes. The present study was therefore conducted to examine the role of different working memory processes in children’s foreign language comprehension. A number of studies show that the phonological loop supports the learning of new (foreign) linguistic material by providing a temporary phonological code while a more permanent long-term memory phonological representation is constructed (Baddeley, Gathercole, & Papagno, 1998; Ellis & Sinclair, 1996; Palladino & Ferrari, 2008; Papagno et al., 1991; Service, 1992). These phonological loop processes appear to be most critical in the initial stages of acquisition, but are less critical in later stages, for example after 35 years of learning. In later stages, the learning of new words appears to be mediated by existing foreign vocabulary knowledge already in the learner’s lexicon (Masoura & Gathercole, 2005; Service, 1992). Evidence of the importance of phonological loop processes in foreign language learning has also been provided by studies examining children with foreign language learning difficulties (FLLD). These studies suggest that a defective phonological loop contributes to the children’s foreign language learning difficulties (Palladino & Cornoldi, 2004; Palladino & Ferrari, 2008; see also Sparks & Ganschow, 1993). In addition, several studies have demonstrated that the phonological loop, measured by non-word repetition, predicts children’s concurrent or future foreign language vocabulary skills (Dufva & Voeten, 1999; Gathercole & Baddeley, 1993; Masoura & Gathercole, 1999; Service, 1992).

A few studies examining foreign language skills in children have focused on listening and reading comprehension (Dufva & Voeten, 1999; Service, 1992; Service & Kohonen, 1995). Dufva and Voeten (1999) and Service and colleagues (Service, 1992; Service & Kohonen, 1995) showed that non-word repetition predicted concurrent and future foreign language listening and reading comprehension skills. These findings suggest, according to the researchers, that the phonological working memory store also contributes to foreign language comprehension by temporarily storing sentences or clauses while the individual is generating and processing inferences. Moreover, assuming that syntactic analysis (parsing) is slower (i.e., less automatic) and more effortful during foreign language processing, the ability to create accurate phonological representations in WM of sentences should be an important function of the working memory system (see also McDonald, 2006). Studies reported by Geva and Ryan (1993) and Walter (2004, 2007) indicate that the role of working memory during children’s foreign language comprehension is not only restricted to phonological storage and rehearsal processes, but also involves executive control processes. These researchers assessed children’s working memory capacity both with native and foreign language material by using versions of Daneman and Carpenter’s (1980) classical reading span task. This working memory task taps the ability to coordinate performance of two separate operations; that is, simultaneous storage and processing of verbal information. This complex dual task captures both central executive processes and phonological storage processes. The demands on the central executive are especially high, as it requires, among other things, a shift in attention between the storage and the processing components of the task (Baddeley, 1996; Engle, Tuholski, Laughlin, & Conway, 1999; Gathercole, Pickering, Ambridge, & Wearing, 2004; Towse & Hitch, 1995). Geva and Ryan (1993) found that native and foreign language reading span performance predicted individual differences in performance on a measure of foreign language reading comprehension, whereas Walter (2004, 2007) found that native and foreign language reading span performance correlated with performance on a foreign language comprehension task that was specifically developed to tap the individual’s ability to create a mental proposition structure of short stories (see above). In all three studies,



foreign language reading span performance showed stronger associations with foreign language processing than did native language reading span performance. Thus the child’s capacity to simultaneously process and store foreign language information in her/his working memory system is crucial during foreign language comprehension. These findings are also corroborated by studies performed on adults (McDonald, 2006; Miyake & Friedman, 1998; Service et al., 2002). In sum, prior research demonstrates that working memory contributes to children’s foreign language processing of sentences and stories, probably by providing a flexible multi-purpose mental workspace capable of coordinating and executing the multiple processing and storing demands during foreign language processing. This flexible workspace would probably be most critical in foreign language comprehension processes, such as inference making, building a mental proposition structure, and syntactic parsing of sentences. Phonological working memory plays a critical role in children’s acquisition of foreign language vocabulary by temporarily storing a phonological representation of the new word while a more stable and detailed representation is established in long-term memory (Baddeley et al., 1998). The phonological working memory store may also contribute to foreign language processing by temporarily storing whole or parts of sentences while the individual performs inferences and syntactic analysis (Service, 1992). The contribution of working memory may not be limited to the functions of monitoring, and coordinating multiple processes and temporary storing linguistic material. Activating and accessing task-relevant information from long-term memory (e.g., semantic and syntactic information), inhibiting task-irrelevant information from gaining access to working memory, and shifting between different levels of language processing (e.g., single words; whole sentences), and mental proposition structures (Adams et al., 1999; St Clair-Thompson & Gathercole, 2006; Walter, 2004, 2007) are other plausible working memory executive processes during foreign language comprehension. One important finding obtained by previous studies is that it is usually working memory capacity tested in foreign language and not native language that contributes to adults’ and older children’s foreign language proficiency, suggesting that the individual’s capacity to simultaneously process and store foreign language information in

461

her/his working memory system is particularly crucial during foreign language processing (Service et al., 2002; for exceptions see also Geva & Ryan, 1993; Miyake & Friedman, 1998). Thus, to become proficient in a foreign language the individual must have a capacious working memory system that can adapt to the processing of new (foreign) language-specific information and this seems, according to data provided by Miyake and Friedman (1998), to be determined by the individual’s general working memory capacity; that is, the capacity to processes native language information (see also Geva & Ryan, 1993; Service et al., 2002; Walter, 2007). The lack of, or weak, relationships between native language working memory measures and foreign language proficiency in adults and older children (13 years or older) found in prior studies might be due to the fact that they possess a sufficiently effective working memory system capable of processing foreign language information. Another factor that probably contributes to the individual’s ability and need to process foreign language information in working memory is the size of the foreign language knowledge base established in long-term memory, which in turn is related to experience with that specific foreign language (Service et al., 2002). Younger inexperienced foreign language learners whose working memory capacity is less well developed might have to rely more on their general working memory capacity; that is, their capacity to process native language information during the processing of a foreign language (Geva & Ryan, 1993; Swanson, Sa´ ez, & Gerber, 2006). Thus the aim of the present study was to examine if and how different working memory resources tested in native language of 10-year-old children predict their future foreign language comprehension when 12 years old. When discussing foreign language comprehension it is important to make a distinction between literal and inferential comprehension. During literal comprehension the listener or reader merely has to access semantic information to interpret the exact literal meaning of a word or sentence (Gibbs, 2002). Inferential comprehension, on the other hand, requires the individual not only to consider contextual information and adjust the literal meaning of word and sentences to that context, but also take into account irony and sarcasm (Gibbs, 2002; Singer, 1994). Comprehension of discourse and stories is mainly inferential as it involves establishing


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coherence between the different parts of the story or discourse through bridging and elaborative inferences (Garnham, Oakhill, & JohnsonLaird, 1982; Gernsbacher, 1990; Kintsch, 1998; Warren, Nicholas, & Trabasso, 1979). It should be noted that previous studies on foreign language processing in children do not provide any empirical data concerning inferential comprehension, as they have only used tasks tapping literal comprehension due to the children’s low proficiency in the foreign language (for exceptions see Walter, 2004, 2007). The present study used the Baddeley and Hitch (1974; for revisions see Baddeley, 1986, 1990, 1997) three-component model as a theoretical account of the working memory construct. According to this model, the structure of working memory consists of a domain-general attentionalcontrolling system called the central executive, which is supported by two domain-specific storage components for verbal and visuospatial information called the phonological loop and the visuospatial sketchpad. The central executive itself has no storage capacity (Baddeley, 1993). This original three-component model has been revised by Baddeley (2000), and a fourth episodic buffer component has been added to the model. The episodic buffer is a system that can integrate information from the phonological loop, the visuospatial sketchpad, and long-term memory, and temporarily store this information in the form of an episodic representation. The present study employed the three-component model, because research regarding the episodic buffer is still sparse. Based on this framework, the present study was conducted in an attempt to further our understanding of how working memory predicts children’s future understanding of sentences and short stories in a foreign language. The following two general hypotheses were addressed, something that has not been done in previous studies. 1. It was hypothesised that central executive processes would predict future foreign language (English) comprehension at 12 years of age (grade 5), independent of the contribution of phonological loop processes. 2. Phonological loop processes were expected to predict future foreign language (English) comprehension at 12 years of age (grade 5), independent of the contribution of central executive processes.

To address the present hypotheses, children’s working memory central executive processes and phonological loop process were assessed in grade 3 or 4 (age 9 to 11 years) and their foreign language skills (i.e., English) and native language reading skills were assessed in grade 5 (12 years of age). The selection of the tasks was guided by previous research providing a theoretically motivated set of tasks that have been commonly used to assess working memory resources in children. Two complex working memory tasks (the animaldual task and the counting span task; Daneman & Carpenter, 1980; Engle et al., 1999; Gathercole et al., 2004; Passolunghi & Siegel, 2001; Swanson, 1992), the trail-making task (Baddeley, 1996; Lehto, Juujarvi, Kooistra, & Pulkkinen, 2003; McLean & Hitch, 1999; Miyake et al., 2000; Zoelch, Seitz, & Schumann-Hengsteler, 2005), and Raven’s Progressive Matrices test (Chen & Li, 2007; Conway, Cowan, Bunting, Therriault, & Minkoff, 2002; Engle et al., 1999; Kane, Hambrick, & Conway, 2005) were used to tap central executive processing. The word span, the digit span, and the phonological verbal fluency tasks were used to tap phonological loop processes (Alloway, Gathercole, & Pickering, 2006; Baddeley, Thomson, & Buchanan, 1975; Gathercole, Alloway, Willis, & Adams, 2006; Swanson & Beebe-Frankenberger, 2004).

METHOD Participants A total of 95 children (33 boys) participated in this study. When in grade 3 or 4, the total sample had a mean age of 125 months (SD6), and when in grade 5 the mean age was 141 months (SD3). All children were fluent speakers of Swedish, and had normal or corrected-to-normal visual acuity and no hearing loss. The children were recruited by means of a letter of consent that the children brought home to their parents from school. The participating children started to study English in grade 3, thus they had studied English for almost 3 years, when their foreign language processing skills were assessed in grade 5.

General procedure In grade 3 or 4 a test battery including seven tasks was administered to tap functions of the central



executive and the phonological loop (Baddeley, 1997; Baddeley & Hitch, 1974). All tasks, except for Raven’s Progressive Matrices test (Raven, 1976; sets B, C, and D), were performed individually and the test order was the same for all children. The tasks were conducted in a fixed order: digit span, phonological verbal fluency, word span, trail-making task, animal dual task, and counting span. In all tasks there was at least one practice trial before the testing phase to ensure that the children understood the task. All instructions regarding the tasks were presented orally. Testing took approximately 110 minutes, divided into two 45-minute sessions with a 20-minute break in between.

Tasks and procedure Standard Raven’s Progressive Matrices test. The test was administered in groups of four to five children. The test consists of a series of visual pattern designs with a piece missing. The task is to select the correct piece to complete the designs from a number of options (six to eight) displayed beneath the design. The complete test includes five sets of designs (A, B, C, D, E), and each set consists of 12 items (Raven, 1976). In the present study only sets B, C, and D were used, thus the maximum score was 36. For set B six response options were displayed and for sets C and D eight response options. Each child received a test booklet that included 36 test items and 2 practice items. The children responded by checking one of the six to eight options on a separate answer sheet. After the two practice items had been completed, the children completed their booklets at their own pace. The specific instructions and administration procedures followed those specified in the test manual (see Raven, Court, & Raven, 1996). Animal dual task. This task (Passolunghi & Siegel, 2001) indexed the capacity to coordinate performance of two separate operations (e.g., simultaneous storage and processing of verbal information). The child was presented with lists of four 1- and 2-syllable words. The first span size employed was two, the next was three, and the last four. Three different sequences were presented for each span size. The experimenter read the words to the child from the computer screen at a rate of one word per second, and with a 2-second interval after each list. The Microsoft PowerPoint software program (10.1.5) was used

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to administer the presentation of the words to the experimenter. The child had to decide whether the word was the name of an animal or not. If the word was an animal name, the child had to tap the table. At the end of the sequence of word lists the child had to recall the last word in each word list orally. The child was instructed that the recall should be in correct serial order. The child received all 27 sets of stimuli. The total number of recalled words was the dependent measure. Counting span task. This task (Siegel & Ryan, 1989) tapped the ability to coordinate performance of two separate operations (e.g., store and process numeric information). The task was administered by the SuperLAB PRO 1.74 software program. The stimuli consisted of four black and a varied number of red dots (two to seven), arranged in a random pattern. The purpose of the black dots was to prevent the child from using a subitising strategy when counting the red dots. The task was to count the red dots in each pattern and then recall the number of red dots from each pattern in the sequence in correct serial order. The first span size employed was two, the next was three, and so on up to six patterns. Two sequences were presented for each span size. Testing stopped when the child made a mistake in both trials of the same span length. The sum of completely and perfectly recalled sequences was the dependent measure (cf. Baddeley et al., 1975). Trail-making task. This task was used to measure shifting ability and consisted of two parts, A and B. In part A the material consisted of 25 encircled numbers on a sheet of paper. In part B half of the circles had a number in the centre (1 13), and half had a letter (AL). The task in the A part was to connect the 25 circles in numerical order, and in the B part to make a trail with a pencil so that each number alternated with its corresponding letter (i.e., 1-A-2-B-3-C . . . 12-L13). The difference in solution time for the B condition and A condition (i.e., B A) was used as dependent measure. Phonological verbal fluency task. The verbal fluency task required the children to generate as many words as possible from two initial phoneme categories (/f/, /s/); 60 seconds were allowed for each category. The total numbers of words correctly retrieved for the two phonological categories were used as a measure of the capacity


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to retrieve phonological-lexical information from long-term memory.

day are Chris and Debbie going to the computer club?, On ________.) The maximum score was 21.

Word-span task. This task (cf. Baddeley et al., 1975) required the child to recall and repeat sets of words (one to nine) that had been spoken by the experimenter, in correct serial order. The test material consisted of semantically unrelated and phonologically dissimilar CVC words (e.g., car, sun, leg). The first span size employed was three, the next was four, and so on up to eight words. Three sequences were presented for each span size. Testing stopped when the child made a mistake in all three trials of the same span length. The sum of completely and perfectly recalled lists was the dependent measure.

English reading comprehension. This question and answer test was a short reading comprehension task involving dialogues with different everyday phrases. The child had to read a question and then select the best answer to that question from four options*e.g., What was the weather like yesterday? (a) Warm but cloudy. (b) On the radio, I think. (c) Short and thin. (d) I long for snow. The child was allowed 15 minutes to read and answer the 16 questions (three to nine words long). The maximum score for this multiple choice test was 16.

Digit span task. The task required the child to recall and repeat sets of digits (one to nine) that had been spoken by the experimenter in correct serial order. The first span size employed was three, the next was four, and so on up to eight digits. Two sequences were presented for each span size. Testing stopped when the child made a mistake in both trials of the same span length. The same test and scoring procedure as in the word span task was used.

Foreign and native language tasks All schools in Sweden are required to follow a national curriculum. In grade 5, national assessment tests are administered, by the Swedish National Agency for Education, to evaluate the child’s progress towards the educational goals. Performance on the national assessments in English (first foreign language) and Swedish in grade 5 was used as the criterion measure of future skills in foreign language skill and native language reading skill (i.e., Swedish). It should be noted that the foreign language (English) tasks tapped literal comprehension, whereas the native language (Swedish) task were more complex and tapped inferential comprehension skills. English listening comprehension. The task was to listen to a conversation between two friends and the leader of a computer club (from a CD), and to answer 16 questions (5 to 10 words long) about the conversation over 25 minutes. The questions were of multiple choice type or only required one or two words as answers (e.g., What

English story reading comprehension. The child had to read a short story (527 words in length) about the friendship between a boy and a dog called Sandy. The story was divided into four sections (101 to 180 words long). After reading a section the child answered four to five questions (four to nine words long) about the text section. Most questions required a whole sentence as an answer (e.g., Where does Sandy sleep?) whereas other questions were of multiple choice type* What time of the year was it? (A) Spring, (B) Summer, (C) Autumn, (D) Winter*or only required one word as an answer. The total number of questions was 18 and the maximum score was 21. The child was allowed 25 minutes to work with the test. Native language reading comprehension. Two tasks assessed the child’s native language reading comprehension skills. In the first task the child read a short excerpt from a literary text, and then answered 10 questions about the text in writing over 40 minutes. The maximum score was 10. The second task required the child to read a short story, and to answer five questions about the text in writing over 25 minutes. The maximum score was 5. These two tasks were combined into a composite score. The correlation between the two tasks was r.40, pB.05.

RESULTS Descriptive statistics for and correlations among all tasks used in the study are displayed in Table 1. The different measures of foreign language processing were significantly correlated with almost all cognitive tasks used in the study. The correlations ranged in size from .17 to .40. The


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TABLE 1 Descriptive statistics and correlations among the tasks used in the study Tasks


1. Foreign language composite score 2. Foreign language listening 3. Foreign language reading (questions) 4. Foreign language reading (story) 5. Native language reading score 6. Raven’s 7. Animal dual task 8. Counting span task 9. Trail-making$ 10. Phonological verbal fluency 11. Word span task 12. Digit span task

M

SD

40.50 12.95 14.75 11.54

4.77 3.80

14.21

5.82

1

2

3

4

5

6

7

8

9

.87

.88

.94

.63

.37

.37

.35

.40

.36

.31

.24

.64

.70 .78

.52 .56

.37 .28

.39 .33

.40 .31

.40 .34

.36 .28

.28 .26

.25 .25

.61

.33

.30

.25

.33

.34

.28

.17

.46

.42 .40

.34 .39 .42

.32 .38 .22 .25 .61 .19 .28 .18 39 .22 .41 .39 .42 .27 .42 .45 .24 .26 .20 .34 .40 .61

11.39 2.39 22.20 6.93 18.27 5.16 15.17 7.52 74.23 40.43 17.38 6.66 17.76 7.34 19.06 6.94

10

11

12

n 95, df93, Correlation coefficients larger than .20 are significant at the 5% level. $ time measure resulting in a negative correlation.

correlations between the cognitive tasks and native language reading measure were of similar magnitudes as for the foreign language measures, ranging in size from .22 to .46. The native language reading measure correlated significantly with all foreign language measures (ranging from r.52 to r.63) indicating some kind of shared underlying general language processing, but also that language-specific processing is involved in the different languages. As all seven cognitive tasks were significantly correlated, a principal component analysis with varimax rotation was performed to examine the underlying structure of the present cognitive data. Factors with eigenvalues greater than 1 were retained. As can be seen in Table 2, a two-factor model (eigenvalues of 3.17 and 1.20) emerged that accounted for 62% of the variance. As expected, the word span, the digit span, and the phonological verbal fluency tasks displayed high loading on the same factor (1), and Raven’s, the animal dual-task, and the trail-making task loaded primarily on the second factor. However, the counting span task showed almost identical loadings on both factors (.520 versus .517) suggesting that this task includes both central executive processes and phonological loop processes. The unexpected high loading on the phonological loop component is probably because this task, in addition to storage, involves counting, which draws upon phonological loop (Ashcraft, 1995; Geary & Hoard, 2005; Logie & Baddeley, 1987). It was decided to include the counting span task

into the phonological loop component in order to obtain a central executive component that was relatively free of phonological processing. Thus, after the tasks have been standardised into zscores, four tasks (word span, digit span, counting span, phonological fluency) were combined into a phonological loop component, and the remaining three tasks into a central executive component. The correlation between the two components was r.50, pB.05.

The contribution of working memory to future foreign language comprehension To examine the two hypotheses of the current study, multiple regression analyses were calculated for each foreign language measure displayed in Table 1. The two predictors, the central executive component and the phonological loop component, were entered simultaneously in all analyses. The results of the analyses are presented in Table 3. Both components turned out to be significant predictors of performance on the foreign language composite measure (model 1). The complete model 1 accounted for a total of 27% of the individual differences in the composite measure. The squared part correlations displayed in Table 3, which represents the unique contribution for each variable, show that the central executive component contributed 9% variance and the

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TABLE 2 Factor loadings from principal component analysis of the cognitive tasks Tasks


Raven’s Animal dual task Counting span Trail-making Phonological fluency Word span Digit span

Factor 1

Factor 2

.081 .452 .520 .108 .625 .795 .868

.865 .545 .517 .857 .111 .199 .084

phonological loop component accounted for 5% variance. The central executive component and the phonological loop component predicted 28% of the variance in foreign language listening comprehension (model 2). The unique contribution for each one of the two components was 10% and 5%, respectively. The two components also emerged as significant predictors of the foreign language reading task, which involved reading questions and selecting the correct answers to the questions. The central executive component predicted 6% variance and the phonological loop component predicted 4% variance. The complete model 3 accounted for 19% of the variability. The second foreign language reading task that required the child to read a story was significantly predicted by the central executive component, 7% unique variance, whereas the prediction of the phonological loop component did not quite reach significance (pB.08). This model (model 4) accounted for a total of 19% variance. These regression models demonstrate that working memory central executive and phonological loop processes tested in the native language independently predict children’s future foreign language comprehension. To examine whether central executive and phonological loop processes would predict native language reading skills a multiple regression analysis was also performed on the native language composite measure. This model 5 (see Table 3) accounted for 27% variance, and the central executive component predicted a significant amount of unique variance (11%) but the phonological loop component did not (p.05). The results of regression models 15 show that both central executive process and phonological loop processes predict future foreign language comprehension, whereas future native reading performance only is predicted by central executive process.

To further examine the relationship between working memory resources, foreign language processing, and native language reading performance, partial correlations were calculated between the two working memory components and the foreign language measures when controlling for the influence of native language reading performance. These correlation analyses would reveal if central executive and phonological loop processes predict foreign language comprehension above and beyond those involved in native language reading. Significant partial correlations were obtained between the central executive component and the foreign language composite score, r.25, pB.05, and the foreign language listening comprehension measure, r.30, pB.05. The phonological loop component also showed significant relationship with the composite score, r.24, pB.05, and the listening comprehension measure, r.28, pB.05. No other partial correlations reached significance (p.05). To examine if the two working memory components predicted performance on the composite score, independent of the contribution of native language reading skill and the other working memory component, a multiple regression analysis was performed which included the native language reading measure as a predictor in addition to the two working memory components. The complete model (6) for the composite score accounted for a total of 45%, F(3, 91)25.06, pB.05, of the variance, but only the native language reading measure, (b.50, pB.05), emerged as significant predictor accounting for 18% of the variance.

DISCUSSION AND CONCLUSIONS The aim of the present study was to examine if and how different working memory resources tested in native language predict children’s future foreign language comprehension of sentences and short stories. The overall results of the regression analyses provide clear evidence that working memory capacity assessed in grade 3 and 4 accounts for individual differences in foreign language processing in grade 5. This finding corroborates previous studies demonstrating an association between working memory and foreign language proficiency in children and adults (Geva & Ryan, 1993; Miyake & Friedman, 1998; Service et al., 2002; Walter, 2004, 2007), but more importantly it extends our knowledge by showing


467

TABLE 3 Multiple regression analyses of foreign and native language processing ß

t

pr2$

Central executive Phonological loop

.35 .25

3.40* 2.40*

.09 .05


.36 .25

3.49* 2.43*

.10 .05


.28 .23

2.58* 2.10*

.06 .04


.30 .20

2.80* 1.82

.07 .03


.38 .20

3.71* 1.98

.11 .03

Central executive Phonological loop Native reading score

.16 .14 .50

1.65 1.58 5.51*

.02 .01 .18

Predictors Model 1

Model 2

Model 3


Model 4

Model 5

Model 6

Foreign language composite score F(2, 92) 16.98, pB.05, R2 .27

Foreign language listening F(2, 92) 17.74, pB.05, R2 .28

Foreign language reading (questions) F(2, 92) 11.01, pB.05, R2 .19

Foreign language reading (story) F(2, 92) 10.82, pB.05, R2 .19

Native language reading score F(2, 92) 16.77, pB.05, R2 .27

Foreign language composite score F(3, 91) 25.06, pB.05, R2 .45

$

pr2 Squared part correlations, represents the unique contribution for each variable *p B.05.

that children’s central executive and phonological loop processes provide independent prediction of future foreign language comprehension. These are important results, as previous studies have typically demonstrated links between foreign language proficiency and general measures of working memory capacity (e.g., reading span) tested in native and foreign language (Geva & Ryan, 1993; Walter, 2004, 2007). In addition, the present findings suggest that to become proficient in a foreign language the child must have a capacious working memory system that can adapt to the processing of new (foreign) languagespecific information (Geva & Ryan, 1993; Miyake & Friedman, 1998; Service et al., 2002; Walter, 2007). Consistent with the first hypothesis, the central executive process component predicted individual differences on all four measures of foreign language comprehension independent of the contribution of phonological loop processes (Geva & Ryan, 1993; Walter, 2004, 2007; see also Daneman & Carpenter, 1980; Just & Carpenter, 1992). Thus foreign language proficiency in young children (912 years old) is to some extent supported by working memory

executive processes (cf. Geva & Ryan, 1993; Swanson et al., 2006). This finding is theoretically reasonable as the dominant conceptualisation of the construct of working memory considers (central) executive control processes to be domain general (Baddeley, 1986; Engle et al., 1999) and should therefore contribute not only to native language but also to foreign language comprehension. The second hypothesis, stating that phonological loop processes should predict future foreign language comprehension in 12 year-old children independent of the contribution of the central executive, was supported in relation to three out of four measures of foreign language ability. These results are consistent with previous research demonstrating that the phonological loop supports foreign language processing by temporarily storing whole or parts of sentences while the individual performs inferences and syntactic analysis (cf. Dufva & Voeten, 1999; Service, 1992; Service & Kohonen, 1995) and by temporarily storing a phonological representation of new words while a permanent representation is established in long-term memory (Baddeley et al., 1998; Palladino & Ferrari, 2008). As the


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phonological loop measures were performed in native language, the present results suggest that foreign language comprehension in young children is to some extent supported by languagegeneral phonological loop processes (cf. French & O’Brien, 2008). Important findings regarding the relationship between different working memory resources and foreign language processing were also obtained by the partial correlations performed between the central executive, phonological loop, and foreign language ability when controlling for the influence of native language comprehension. The analyses demonstrated that central executive and phonological loop processes predicted individual differences in future foreign language comprehension above and beyond those predicted by native language reading. Thus foreign language processing of sentences and short stories in young rather inexperienced children appears to some extent to draw on working memory resources that are not involved in native language reading comprehension. These working memory resources are probably related to the fact that foreign language processing is slower, less automatised, and more effortful than native language processing due to the unfamiliarity with the syntactic and phonological structure of the language and a limited foreign language vocabulary (Geva &Ryan, 1993; Harrington & Sawyer, 1992; McDonald, 2006; Miyake & Friedman, 1998; Segalowitz et al., 1998; Service et al., 2002). Since the participating children only have rather basic skills in English it is reasonable to assume that they have to allocate a lot of central executive resources in order to perform syntactic parsing of sentences in a foreign language, especially when the syntactic structure is not exactly the same as the structure of the child’s native language (cf. McDonald, 2006; Miyake & Friedman, 1998). Inexperienced foreign language learners might also have a rather poorly developed foreign language phonological system or even lack such a system. Due to this, phonological decoding of foreign language words should theoretically impose especially high demands on the child’s phonological loop resources (cf. Chiappe et al., 2007; Cutler et al., 1992; Eckman, 2004; Flege, 1995; Metsala, 1997, 1999; Segalowitz et al., 1998). Speculatively, in order to comprehend a message presented in a foreign language the child has to employ central executive resources to decode and translate (into their native language) one word at a time, while storing the already

decoded words, in the phonological loop, until all words in a sentence are decoded and parsed (Brauer, 1998; Chiappe et al., 2007; McDonald, 2006; Miyake & Friedman, 1998; Swets et al., 2007). At this point the child can obtain the meaning of the message presented to her/him. A similar but reversed process is probably taking place when the child speaks English or writes in English (Swanson & Berninger, 1996). Furthermore, due to the child’s limited English vocabulary, he/she probably has to infer the meaning of unfamiliar words by using sentence context (already identified words) and story context, which draws on the working memory capacity to simultaneously store and process information (Cain, Oakhill, & Lemmon, 2004; Calvo, 2001; Laufer, 1992; Laufer & Goldstein, 2004; Stanovich, 1986; Sternberg & Powell, 1983). However, the reliance on working memory resources may gradually decrease as the foreign language processing successively becomes more automatised and less effortful due to the development of a larger foreign language knowledge base (vocabulary, phonological representations, syntax) in the long-term memory (Service et al., 2002). Although the present results (models 14) demonstrate that both working memory central executive processes and phonological loop processes predict future foreign language comprehension, the sixth regression model showed that the strongest predictor of foreign language is native language reading skill. This finding suggests that perhaps the most important cognitive factor in becoming proficient in foreign language is the child’s general language aptitude (Gesi Blanchard, 1998; McLaughlin, 1990; Sparks & Ganschow, 1993; van Gelderen et al., 2007). Finally, the result of model 5 demonstrated that central executive process but not phonological loop processes predict future native reading skill. The lack of significant association between phonological loop processes and native reading is not unexpected, considering the fact that the present sample of children (grade 5) were rather experienced readers, and as such they should employ an automatised orthographic reading strategy that does not impose any heavy demands on the phonological loop (Gathercole et al., 2006; Swanson & Jerman, 2007; Wagner et al., 1997). In addition, the significant prediction of the central executive component was expected, as it is well established that working memory executive processes support complex cognitive tasks such as reading comprehension in many ways (e.g.,



Gathercole & Baddeley, 1993; Just & Carpenter, 1992; Swanson & Jerman, 2007) In summary, the present study demonstrated that working memory central executive processes and phonological loop processes provide independent prediction of future foreign language comprehension of sentences and short stories in children. These working memory resources are to some degree unique for foreign language processing. A strong association between native language and foreign language processing suggests that an important factor in becoming proficient in foreign language is the child’s general language aptitude. Manuscript received 18 March 2008 Manuscript accepted 26 February 2010 First published online 14 April 2010

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