Age-related differences in learning disabled and skilled readers’ working memory

Journal of Experimental Child Psychology

J. Experimental Child Psychology 85 (2003) 1–31

www.elsevier.com/locate/jecp

Age-related differences in learning disabled and skilled readersÕ working memory H. Lee Swanson* School of Education, University of California, Riverside, CA 92521, USA Received 3 May 2002; revised 19 March 2003

Abstract This study determines whether age-related deficits in learning disabled (LD) readersÕ working memory performance reflect delays in retrieval efficiency and/or storage capacity. The study compared LD and skilled readersÕ working memory performance (N ¼ 226) across four age groups (7, 10, 13, and 20) for phonological, visual-spatial, and semantic information under initial (non-cued), gain (cues that bring performance to an asymptotic level), and maintenance conditions (asymptotic conditions without cues). The important results were that LD readersÕ working memory performance was inferior to skilled readers on verbal and visual-spatial working memory tasks across all age groups and these differences increased on gain and maintenance conditions when compared to initial conditions. These reading group differences remained when age, reading, and mathematics were partialed from the analysis. The results support a general capacity explanation of reading group differences that is not totally dependent on reading skill. These differences in capacity reflect demands placed on both the accessing of new information and the maintenance of old information that extend beyond the phonological system. Ó 2003 Elsevier Science (USA). All rights reserved. Keywords: Working memory; Learning disabilities; Reading; Domain-general processing; Domain-specific processing; Age-related changes

Introduction Several recent studies show that differences between learning disabled (LD) and skilled readers on measures of cognitive function are attributable to limitations in * Fax: +909-787-5799. E-mail address: [email protected].

0022-0965/03/$ - see front matter Ó 2003 Elsevier Science (USA). All rights reserved. doi:10.1016/S0022-0965(03)00043-2

2

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

working memory (e.g., De Beni, Palladino, Pazzaglia, & Cornoldi, 1998; De Jong, 1998; Passolunghi & Siegel, 2001; Siegel, 1994; Swanson, 1993; Swanson & Siegel, 2001). The present study was designed to investigate the source of reading group differences in working memory across various age groups. The central question in this study is whether reading group differences in working memory performance across various ages can be modified and whether the remaining sources of variance can be attributed to retrieval efficiency or the storage of information. A related question is whether age-related differences in working memory between LD and skilled reading children reflect a general or a specialized system. It is of further interest to determine whether LD readers follow a similar developmental trajectory as skilled readers. As in previous studies (e.g., Baddeley & Logie, 1999; Kane & Engle, 2000; Miyake, 2001), working memory is defined in this study as the preservation of information while simultaneously processing the same or other information. Two issues are involved in identifying the sources of working memory differences between LD and skilled readers. First, it is unclear whether developmental differences in working memory between skilled and LD readers across a large age span are related to their processing efficiency or capacity (e.g., see Barrouillet & Camos, 2001; Case, 1995; Halford, 1998; Hitch & Towse, 1995; for a review). A theory frequently cited in the literature is that age-related differences in working memory for normal achieving children are related to processing efficiency (e.g., Case, 1995; Case, Kurland, & Goldberg, 1982; for a review). The assumption of these studies is that although overall capacity may not increase with age, the allocation of capacity is sensitive to variations in age. However, several studies in the developmental literature have attributed age-related changes in working memory to capacity (e.g., Cowan, Nugent, Elliott, & Ponmarev, 1999; Halford, 1998; however, see Towse, Hitch, & Hutton, 1998, for a competing view). No studies, to the authorÕs knowledge, have addressed the issue of whether the sources of age-related working memory deficits in LD readers are a function of limitations in processing efficiency or capacity. Second, there is no consensus whether reading group differences in working memory reflect a domain-specific or common central system (i.e., see Miyake & Shah, 1999, for a review of various models on this issue). Some studies have suggested that limitations in LD readersÕ working memory be attributed to an isolated storage system, holding and maintaining phonological codes (e.g., Shankweiler & Crain, 1986; Siegel & Ryan, 1989; Stanovich & Siegel, 1994). However, other studies (e.g., Bull, Johnston, & Roy, 1999; De Jong, 1998; Passolunghi & Siegel, 2001; Swanson & Ashbaker, 2000) suggest that difficulties in executive processing may also contribute to the poor working memory performance of LD readers above and beyond their deficits in phonological processing. Thus, further research is necessary to isolate the source of working memory deficits in LD readers. The purpose of this study is (a) to determine whether LD readersÕ working memory deficits across age groups are related to processing efficiency and/or storage capacity and (b) to determine if LD readersÕ working memory deficits are domain specific and/or domain general. The contribution of different factors to childrenÕs working memory was investigated by using cues to bring a childÕs performance to an asymptotic level. This approach implicitly assumes that if LD readers are pro-

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

3

vided help in accessing previously presented information, then residual differences between LD and skilled readers are due to the availability of the contents within a limited working memory system. This assumption is bolstered by work on individual differences and working memory. For example, Cantor and Engle (1993) stated that ‘‘the content of WM is information in LTM that has been stimulated or activated above some critical threshold. . . as the activation level of a concept increases, so does its accessibility’’ (p. 1101). Cuing procedures increase activation to stored information, but this activation is limited by working memory capacity. As stated by Cantor and Engle (1993), ‘‘people differ in the total amount of activation available to retrieve information in LTM. This difference will be manifested in any task that makes at least moderate demands for such activation. High- and low capacity participants, as indexed by the WM spans, actually differ in their activation limits (p. 1102).’’ There are also studies (e.g., Howe, OÕSullivan, Brainerd, & Kingma, 1989) using Markov models that characterize LD childrenÕs memory failures, via cuing, as reflecting problems in storage (as well as retrieval). Consistent with these studies, we suggest that storage is a critical aspect to memory failure in LD readers. Adapting systematic cuing procedures to the measurement of working memory does enhance our understanding of why LD readers experience working memory deficits. For example, a retrieval efficiency hypothesis would predict that if LD readersÕ working memory deficits are due primarily to retrieval rather than storage capacity, then cuing procedures should narrow the working memory performance gap with skilled readers. That is, a retrieval efficiency hypothesis predicts that performance differences between LD and skilled readers are greater for tasks that require effortful reconstruction (i.e., noncued condition) than those that do not (i.e., cued conditions). The magnitude of reading group differences is reduced on cued conditions because retrieval demands are lessened by providing contextual support (see Craik & Jennings, 1992, for a related hypothesis in the literature on aging). An extension of this hypothesis predicts that the benefits of contextual support (cues) are greater for LD readers. In contrast, if LD readersÕ working memory deficits are due to storage capacity, then procedures that facilitate access to previously presented information would not bring them to the same level of performance as skilled readers. Therefore, we conducted a study to examine the validity of these assumptions. The present study presented working memory tasks under three conditions. These conditions include: (1) presentation of working memory tasks without cues to assess initial performance (initial condition), (2) presentation of graduated cues to help participants access forgotten information from the initial condition and to continue the use of cues until span scores can no longer be improved upon (referred to as the gain or asymptotic condition), and (3) presentation of the highest span level achieved for the gain condition after a brief interlude, but without the support of cues (referred to as the maintenance condition). We reasoned that individual differences in working memory performance under initial conditions reflect idiosyncratic processing as well as individual differences in accessing items in storage. To obtain an assessment of individual differences in item accessibility, cues were presented to help participants reinstate the memory trace and/or retrieve forgotten items. This condition, referred to as the gain condition, allows participants to use as many cues as necessary to access

4

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

previously forgotten information. Because the number of probes (the terms probes and cues are used interchangeably) used to retrieve information provides an assessment of the status of information in memory, a finding of reading group differences on the gain condition supports the inference that a failure to activate new information in storage is an important determinant of working memory development. The major limitation in interpreting gain performance, however, is that there is no basis for inferring constraints on storage capacity. Thus, it is necessary to reinstate the highest level achieved successfully under gain conditions, but without cues (referred to as the maintenance condition).1 The sources of age-related working memory differences between LD and skilled readers under the aforementioned conditions were assessed in three ways. First, LD and skilled readers in various age groups were compared on measures of processing efficiency and storage. We calculated processing efficiency as the difference in span scores between maintenance and initial conditions divided by the number of cues necessary to reinstate the memory trace. A low score on this measure reflects more efficient processing of information than a high score. The validity of this measure rests heavily on three assumptions. The first is that processing efficiency is partially a function of the maintenance of information in storage and the number of cues necessary to reinstate the memory trace. We assume that the accessing of previously stored information in working memory performance with a minimum number of cues is more efficient than relying upon several cues. The second is that individuals vary in the number of cues necessary to activate a complete set of items recently presented but temporarily forgotten. This is because the extent of the information available in memory places upper limits on an individualÕs performance (e.g., Anderson, Reder, & Lebiere, 1996; Fastenau, Denburg, & Ables, 1996; Kane & Engle, 2000; Rosen & Engle, 1997). That is, if the information has not been stored, it is logically unavailable for retrieval and therefore cues are ineffective. The final assumption is that if working memory deficits in LD readers are partly due to less efficient processing, then the number of cues relied upon to access information should be greater in LD readers than skilled readers. 1 The logic for the conditions is as follows (also see Swanson, 1992, 1999). The initial condition reflects the baseline for each participantÕs self-initiated processes to access information. The gain condition enhances the access to stored items by tailoring cues to help participants reinstate memory traces or to retrieve forgotten items from the initial (or baseline) conditions. Previous studies have shown that the gain conditions improve performance by as much as 1 SD (Swanson, 1992, 1993). This occurs because the systematic cuing procedure emphasizes sequential processing strategies and thereby reduces the number of competing strategies employed. Thus, if the locus of working memory problems is in the retrieval phase, one would expect a reduction in reading group difference for this condition when compared to the initial condition. One reservation in arguing that performance differences between LD and skilled readers are due to enhanced retrieval efficiency (i.e., improved access to items previously forgotten) is that the manipulations between the initial (noncued) and gain (cued) condition are limited to individual differences in the preservation of information during processing. Thus, we implement a maintenance condition that examines whether LD readers are less accurate than skilled readers at maintaining relevant information. For this condition, the same working memory tasks that matched each participantÕs highest working memory span level (gain score) are again administered, but without cues. Thus, participants are presented items calibrated to their asymptotic level of working memory performance. Calibrating this condition allows us to capture processing differences between groups beyond the learning of items.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

5

In contrast, functional storage capacity was investigated by focusing on whether LD readers were less accurate than skilled readers in maintaining information. We assume that storage capacity is related to the preservation of information during conditions that place high demands on processing (cf. Salthouse, 1992). On the assumption that (a) storage in working memory involves the preservation of information during processing and (b) LD readers experience greater constraints in the storage component of working memory than skilled readers, then LD readers should be less accurate at maintaining information than skilled readers when experimental procedures control for processing difficulty (cf. Conway & Engle, 1996, for a related discussion of this paradigm). That is, if working memory differences between LD and skilled readers are driven by processing difficulty rather than storage, then equating the two groups on the difficulty of the task should eliminate reading group differences. However, if span differences between LD and skilled readers are related to storage, then equating them on the difficulty of the span task should not affect the relation. To equate processing difficulty across participants, we first determined each participantÕs highest span level under gain (cued) conditions. Therefore, we identified each participantÕs asymptotic performance with external support. After a brief interlude, we then readministered the same task at the highest span level established under the gain condition, but this time without cues. We assumed that the readministration of working memory tasks at the participantÕs highest span level under noncued conditions (referred to as the maintenance condition) placed more demands on the maintenance (storage) of information than cued (gain) conditions because external support was removed. We further assumed that if (a) the information to be stored between the cued and noncued conditions was exactly the same and (b) the information presented in the noncued (maintenance) condition was previously recalled under cued (gain) conditions, then a failure to recall information under noncued conditions would reflect demands on storage (see Cowan, 2001, for a review of various models to infer storage). We argue that if LD readers have a weaker storage system (i.e., less likely to maintain information) than skilled readers, then they will experience a greater loss of previously accessed information (via the gain condition).2 Thus, the reductions or costs in the preservation of 2 We assume that the maintenance condition reflects the storage capacity left after processing demands are accounted for. In support of this assumption our previous work shows that the maintenance condition captures processes independent of those tapped in the initial and gain conditions. For example, previous studies have shown that the maintenance condition predicts unique variance related to reading beyond that of span scores derived from the initial and gain condition (Swanson, Ashbaker, & Lee, 1996). Furthermore, reading group differences emerge on the maintenance condition when the influence of initial span scores are partialed out (Swanson et al., 1996, Exp. 1). In addition, span scores from the maintenance condition predicts age-related performance in children better than span scores from the initial and gain conditions (Swanson, 1996; Exp. 2). Several studies (e.g., Salthouse, 1992) suggest that deficits in the ability to maintain information are a consequence of a limited capacity system. Therefore, a failure to retrieve information on the maintenance condition can be partly attributed to demands placed on a limited capacity system. Of course, other influences may be operating, but it seems reasonable to assume that if reading group differences are related to working memory capacity, then LD readers will have fewer resources available to them to maintain and/or activate old (previously accessed) information than skilled readers when processing demands are accounted for.

6

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

information from the gain to maintenance condition would be greater in LD readers than skilled readers. Second, to determine whether increases in the information retrieved reflect the involvement of a general or specific system, we determined if a linear relation exists between reading groups as a function of age across working memory tasks and conditions, via a model outlined by Hale (1990) and Kail (1993). According to Hale and Kail the relative contribution of a global system (e.g., central executive system) is revealed by the relative performance of one group to the other across a broad array of tasks and conditions. A general system assumes that all information processing components develop in concert (e.g., similar rates, Hale, 1990). It is also assumed that the absolute quantity of processing resources increases with cognitive maturity (e.g., age). Thus, if a domain general system underlies working memory performance, then overall performance should be predicted without regard to the nature of the working memory task because all components are equally affected by development (cf. Hale, 1990, p. 654). In accordance with this model, one would expect that if LD readersÕ working memory performance is a linear function of a general system, then their performance can be accurately predicted from the performance of skilled readers. In contrast, a nonlinear function implies that residual differences between reading groups are attributable to isolated processes (e.g., verbal vs. visual-spatial working memory systems). Finally, we determine whether working memory performance is a consequence of reading skill. Turner and Engle (1989) (also see Cantor & Engle, 1993; Engle, Cantor, & Carullo, 1992; Kane & Engle, 2000) suggested that people are poor readers because they have a small ‘‘general’’ working memory capacity and that this capacity is ‘‘independent’’ of reading. Poor readers are viewed as having a weaker working memory than skilled readers, not as a direct consequence of their poor reading skills, but because they have less working memory capacity available for performing a reading and nonreading task. As stated by Turner and Engle, ‘‘working memory may be a unitary individual characteristic, independent of the nature of the task in which the individual makes use of it’’ (p. 150). We test this assumption in a hierarchical regression model that partials out the linear trend of reading scores from working memory performance. If reading group differences in working memory across various conditions hold across age, then one may assume that a domain general working memory system is in operation. Alternatively, a domain specific process model would be supported if reading differences in working memory tasks are eliminated once the domain (e.g., reading) is partialed from the analysis. This cross-sectional study also investigates whether age-related differences in working memory performance between skilled and LD readers are more pronounced at younger than older ages. The majority of studies on working memory and LD readers have utilized participants in the primary grades (kindergarten to grade 5) and therefore we are unclear whether working memory problems persist into adolescence and early adulthood. This study determines whether working memory differences between reading groups are statistically comparable at the older ages.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

7

Method Participants One hundred and twenty-six (126) skilled readers and 100 LD readers participated in this study (N ¼ 226). They ranged in age from 6 to 30. Fifty-two of the normal achieving participants were drawn from a standardization study of working memory measures (Swanson, 1995), whereas the LD sample and the remainder of the normal achieving reading sample were tested between 1996 and 2001. Children were drawn from schools in southern California. Adult LD samples were drawn from an education clinic and the adult normal achieving sample consisted of volunteers. The composite characteristics of the total sample were: (a) gender: 106 females and 108 males, (b) ethnicity: N ¼ 154 Anglo, N ¼ 14 Black, N ¼ 4 Asian, N ¼ 45 Hispanic, and N ¼ 9 other (Hispanic and Black, Native American), and (c) community: 90% urban and 10% rural. Inadvertently, the gender of 12 participants was not recorded. Based on schools attended by children, parentsÕ occupational level and/or residence, social economic status of the sample was estimated as 25% low income and 75% middle to high income. The ages for the total sample are shown in Table 1. The difference in gender ratio for the current sample was not significant between skilled and LD readers across the age groups, v2 ð1; N ¼ 214Þ ¼ :02, p > :05, nor was chronological age, F ¼ :57. For LD readers to be included in this study, their Full Scale WISC-R, WISC III, PPVT-R, or Raven scores had to be greater than a standard score of 85. Although the IQ scores reported by school psychologists indicated all LD readers were >85, we did not have access to all these scores. Those that were available to us (N ¼ 81) yielded a mean Full Scale or general IQ of 103.76 (SD ¼ 14:44). General classification of LD children and adolescents followed state guidelines that closely matched the US Federal Register definition (1977). The definition reflected: (1) a learning problem that was specific and confined to one or two cognitive areas; (b) the childÕs achievement was not commensurate with his/her ability as measured by IQ or chronological age; and (c) the learning difficulty was not the result of retardation, poor teaching, or cultural deprivation. An IQ-achievement test score discrepancy was not used because of serious problems with this type of definition (e.g., Siegel, 1993).

Table 1 Characteristics of skilled and learning disabled readers in the total sample Skilled readers

Chronological age Intelligence Word recognition Mathematics

Learning disabled readers

N

Mean

SD

N

Mean

SD

126 — 126 126

14.06 — 112.37 109.14

6.05 — 6.43 10.22

100 81 100 100

13.46 103.76 79.48 84.18

5.78 14.44 8.34 8.81

8

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

To be defined as normal achieving, the participant had to have Reading and Arithmetic subtest standard scores on the Wide Range Achievement Test (WRAT-R) greater than 90. To be defined as a LD reader, the childÕs percentile score on the reading subtest of the WRAT-R had to be less than the 25th percentile. The standardized scores for each reading group are shown in Table 1.3 Separate scores as a function of age groups are shown in Table 2. Working-memory tasks Some researchers view working memory as reflecting a STM task with high attention demands (e.g., see Engle, Tuholski, Laughlin, & Conway, 1999). Attention is used to maintain task relevant information in an active state and to regulate controlled processing. Thus, individuals performing working memory tasks must remember some task elements and ignore or inhibit other elements as they complete task relevant operations. The working memory tasks in this study required participants to hold information of increasing set size in memory while responding to a question about the task. The questions reflected the recognition of both targeted and non-targeted items and therefore served as a distracter (by introducing interference) to item recall. A question was asked for each set of items and task administration for the initial testing condition was discontinued if the question was answered incorrectly. Thus, working memory span reflected a balance between item storage and correct responses to task relevant questions. Consistent with a number of studies, our working memory tasks required the maintenance of some information during the processing of other information. For example, consistent with Daneman and CarpenterÕs seminal working memory measure (1980), the processing of information was assessed by asking participants simple questions about the to-be-remembered material (storage + processing demands), whereas storage was assessed by accuracy of item retrieval (storage demands only). It is important to note, however, that in our tasks the difficulty of the processing question remained constant within task conditions, thereby allowing the source of individual differences to reflect increased storage demands. Furthermore, the questions focused on the discrimination of items (old and new information) rather than deeper levels of processing such as computing mathematical problems (e.g., Hitch et al., 2001). For this study, working memory tasks required the recall of phonological (Rhyming Task), semantic (Semantic Association Task), and visual-spatial information (Visual-Matrix Task). The three tasks were also selected from a standardized battery of 11 working memory tasks because of their high construct validity and reliability (see

3

Although we selected low achieving participants on the basis of their low reading scores and normal intelligence, it was clear that their reading scores were related to their mathematical performance. This finding is more the rule than the exception when identifying LD readers (e.g., Siegel & Ryan, 1989; Swanson, 1993). Perhaps a more appropriate term than LD readers for the targeted sample is low achievers.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

9

Table 2 Means and SDs for span and probe scores as a function of type of task and condition Task

Initial

Maintenance

Probe

M

SD

M

SD

Age 7, skilled readers (N ¼ 25, CA M ¼ 7:71; SD ¼ :96) (Reading zM ¼ 112:81; SD ¼ 5:11; Math M ¼ 112:68; SD ¼ 9:84) Phonological 1.76 .87 2.72 0.84 2.32 Visual-spatial 3.08 1.32 4.40 1.38 3.64 Semantic 1.48 .91 3.16 1.62 2.44

1.06 1.46 1.50

2.20 2.44 3.48

2.38 3.18 3.48

Age 7, LD readers (N ¼ 17, CA M ¼ 7:80; SD ¼ :95) (Reading M ¼ 81:65; SD ¼ 6:35; Math M ¼ 80:68; SD ¼ 9:33) Phonological 1.11 .92 2.17 1.18 1.64 Visual-spatial 2.00 1.11 3.70 2.14 2.52 Semantic .76 .66 1.29 1.15 .76

1.27 1.37 .66

2.23 3.17 1.47

2.63 3.84 3.28

Age 10, skilled readers (N ¼ 38, CA M ¼ 10:66; SD ¼ :87) (Reading M ¼ 112:34; SD ¼ 6:38; Math M ¼ 107:90; SD ¼ 11:43) Phonological 2.39 1.00 3.23 1.51 2.71 Visual-spatial 3.92 1.07 5.34 1.77 4.60 Semantic 1.50 1.03 2.39 1.63 2.02

1.01 1.12 1.47

2.28 2.60 2.05

3.34 3.44 2.76

Age 10, LD readers (N ¼ 43, CA M ¼ 10:66; SD ¼ :81) (Reading M ¼ 79:03; SD ¼ 8:02; Math M ¼ 78:88; SD ¼ 23:11) Phonological 1.51 1.05 1.93 1.27 1.74 Visual-spatial 3.32 1.26 3.55 1.33 3.44 Semantic .79 1.08 .93 1.00 .95

1.15 1.31 1.09

.90 .58 1.11

2.28 1.82 2.53

Age 13, skilled readers (N ¼ 25; CA M ¼ 13:35; SD ¼ 1:04) (Reading M ¼ 112:69; SD ¼ 6:24; Math M ¼ 107:02; SD ¼ 8:67) Phonological 2.60 1.63 3.80 1.65 3.40 Visual-spatial 4.52 1.15 6.08 1.84 5.24 Semantic 1.76 1.20 3.24 2.24 2.68

1.50 1.23 1.81

2.32 3.32 2.44

2.65 3.63 2.81

Age 13, LD readers (N ¼ 15; CA M ¼ 12:86; SD ¼ :92) (Reading M ¼ 80:01; SD ¼ 8:86; Math M ¼ 82:15; SD ¼ 8:55) Phonological 1.40 .73 1.66 1.04 1.60 Visual-spatial 3.46 1.06 3.80 1.08 3.66 Semantic .80 .94 1.00 1.36 .86

.98 1.04 1.25

.66 .73 .93

1.29 1.70 2.08

Age 20, skilled readers (N ¼ 38, CA M ¼ 21:85; SD ¼ 4:69) (Reading M ¼ 119:00; SD ¼ 7:11; Math M ¼ 109:43; SD ¼ 9:89) Phonological 3.36 1.69 4.97 1.90 4.47 Visual-spatial 4.78 1.66 7.39 2.11 6.05 Semantic 3.13 1.52 5.60 1.19 4.44

2.07 1.90 1.81

4.02 4.94 4.76

2.82 3.90 2.99

Age 20, LD readers (N ¼ 25; CA M ¼ 22:47; SD ¼ 3:74) (Reading M ¼ 80:71; SD ¼ 7:37; Math M ¼ 84:06; SD ¼ 8:78) Phonological 2.52 1.35 4.04 1.48 3.52 Visual-spatial 4.00 1.44 5.72 1.56 4.96 Semantic 1.84 1.31 1.84 1.17 1.84

1.58 1.54 1.28

3.20 2.88 4.32

2.21 2.47 2.62

M

Gain SD

M

SD

10

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

Swanson, 1992, 1993).4 The Cronbach a for each task for the present sample, with age partialed out, was .83, .84, and .86, for the Semantic Association, Rhyming, and Visual-Matrix Span measures, respectively. The complete description of administration and scoring of the three tasks is reported in Swanson (1995). A brief description of each task and the probing procedures follows. Rhyming (Phonological Task). The purpose of this task was to assess the participantÕs recall of acoustically similar words. The participant listened to sets of words that rhymed. Each successive word in the set was presented every 2 s. Nine word sets ranged from 2 to 14 monosyllabic words. Specific instructions were as follows: IÕm going to say some words, then ask you a question about the words, and then I would like you to say the words in order for me. For example, I would like you to remember ‘‘mat, cat,’’ but first I would like you to answer a question about those words. Which word did I say ‘‘cat’’ or ‘‘rat’’? (pause for the participantÕs response). ‘‘ThatÕs right. ‘‘Cat’’ was the word I said. Now can you tell me all the words that I said in order (mat, cat). Now letÕs try some other words.

The experimenter said each word in each set with approximately a 1-s interval between word presentations. After the words had been presented in each set, the participant was asked a question about the words in the set, and then asked to recall the words in order. The 11 test items, in order of difficulty, are shown in Appendix A. If a participant failed a discrimination question, testing was stopped for that test. If the participant passed the discrimination question but omitted, inserted or incorrectly ordered the words, a series of probes (cues) was presented. Sample probing instructions were as follows: ‘‘You missed recalling some of the words in order. I think you know the order of those words but may be confused. Let me try giving you some hints. It will help to remember if you divide words that come at the beginning, words in the middle, and words at the end of the list. Now let me give you some hints to help you remember the words I presented to you.’’ Probe 1. ‘‘The last word(s) —————–in the sequence was (were)——-, now can you tell me all the words in order?’’ Probe 2. ‘‘The first word(s) in the sequence is (are)——-now can you tell me all the words in order?’’ Probe 3. ‘‘The middle words in the sequence are——-now can you tell me all the words in order?’’ Probe 4. ‘‘All words in order are———now tell me all the words in order. (See Appendix A items for how lists were divided into first, middle, and last.)

4 A factor analysis of 885 children and adults, (Swanson, 1995, Table 8, p. 106) indicated that the Rhyming Task loaded .86 and the Semantic Association Task loaded .76 on one factor (referred to as the verbal-semantic factor) and the Visual-spatial task loaded (.69) on a separate visual factor (also see Swanson, 1992). In addition, the tasks were correlated with a traditional measure of working memory used to assess comprehension in adults, the Sentence Span Measure. The correlations, partialed for age, between the three working memory tasks and an adaptation of the Sentence Span Task (Daneman & Carpenter, 1980), are .57, .41, and .43 for the Semantic Association, Rhyming, and Visual-Matrix Span measures (see Swanson, 1996), respectively. These correlations are higher than those reported by Salthouse (1990), in which a review of the literature showed correlations between working memory measures were low (rs < :25).

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

11

If fewer than four probes were needed, the experimenter presented the next most difficult set within the subtest. Three examples of the probing procedure are as follows: 1. Suppose the participant was presented the words car-/star-bar-/far (set 3) and the participant responded ‘‘car-bar-far.’’ The participant obviously left out a word in the middle so the experimenter would provide a hint related to the middle words (Probe number 3 in this case). If probe 3 did not provide the correct answer the experimenter would then present Probe 4. 2. If the participantÕs response was ‘‘car-star-par,’’ then an error has occurred at the end and middle of the list. In this case, the participant would start at Probe 1 (hints related to the last word) and move through Probes 2–4. Probe 2 is presented (probe related to the beginning of the list) even though that word was initially in the correct order. 3. If the participant initially responded ‘‘bar-far,’’ then an error has occurred at the beginning of the list. In this case, the hints would start with Probe 2 and, based upon the participantÕs response, move through Probes 3–4. Probing continued until the participant provided the correct response. Probing ceased when the participant could no longer provide the correct response. The maintenance condition was implemented after the other two tasks described below were administered. The participant was presented again the longest set of words that were recalled successfully (gain score), but this time the longest set was presented without the help of probes. The instructions were as follows: ‘‘These words that IÕm going to say for you now were presented earlier. I want to see if the words are now easier for you to remember.’’ For scoring purposes, the last item set recalled in correct sequential order in which the process question was answered correctly and in which a series of probe questions were not implemented, was the participantÕs initial span score. The gain score was the highest number set recalled correctly with probes. The probe score was the number of probes (cues) necessary to achieve the highest level of performance on the gain condition. The maintenance score was either the initial score for the cases where the gain score was not maintained, or it was the gain score if the gain was maintained. These scoring procedures were used for all three tasks. Visual Matrix Task (Visual-spatial Task). The purpose of this task was to assess the participantÕs ability to remember visual sequences within a matrix. The participant was asked to study a series of dots in a matrix for 5 s. After removing the matrix, the participant was shown a blank matrix (with no dots) and asked a discrimination question, that is, ‘‘Were there any dots in the first column?’’ Then the participant was asked to draw the dots in the correct boxes on the blank matrix. The task difficulty ranged from a matrix of 4 squares and 2 dots to a matrix of 45 squares and 12 dots. The dependent measure was the number of matrices recalled correctly (range of 0 to 11). If an error occurred, probe questions were started. Probe procedures followed the same format as the Phonological Task, except that the matrices were represented as columns that reflect recency, primacy, and middle positions. For example, when probing for errors that occurred in the recency

12

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

position, the experimenter drew dots on a blank matrix in the appropriate last columns and said, ‘‘Now can you show me where the rest of the dots go?’’ If the participant failed to correctly place the dots, but correctly passed the discrimination question, then the probe questions were as follows: Probe 1. On the blank matrix, the experimenter correctly draws in the last column(s) of dots. Then the experimenter says, ‘‘Now can you draw where the rest of the dots go?’’ Probe 2. On a blank matrix, the experimenter draws in dots for the first column. Then the experimenter says, ‘‘Now can you draw where the rest of the dots go?’’ Probe 3. On a blank matrix, the experimenter draws in the dots for the middle (between the first and last column) and says, ‘‘Now can you draw where the rest of the dots go?’’ Probe 4. The stimulus card is shown for 2 s. The model matrix is removed and the participant is asked to fill in all the dots on a blank matrix. The scoring of span scores for the initial, gain, and maintenance condition followed the same procedure as the Phonological Task. Semantic Association Task (Semantic Task). The purpose of this task is to determine the participantÕs ability to organize words into abstract categories. The participant is presented a set of words (approximately one every second), asked a process question, and asked to recall the words that go together. The general instructions were as follows: I am going to say words. Some of the words go together. For example, if I say the words Ôcar-baseball-truck-football,Õ you would say Ôcar and truckÕ first because they go together and then you would say Ôbaseball and footballÕ because they go together. This is because a car and truck are something you ride in (a form of transportation for participants 12 and older) and baseball and football are sports. Now remember when I give you the words mixed up, I want you to change the order of the words and tell me the words that go together. I will ask you a question about the words and then you tell me the words that go together.

The stimulus items are presented in Appendix B. If the participant missed a series of words within a category, the probe questions were implemented. The probing sequence followed the temporal-spatial format discussed for other tasks, except that cues also provided information related to the semantic categories: Probe 1. If the participant omitted a final word in any category, the participant is told the categories of all the words and all final words that appeared in the list within each category. The participant was then asked to recall all the words by category. Probe 2. If the participant omitted a beginning word in any category, the participant was told all the category names and the first word that appear in the list within each category. The participant was then asked to recall the words by category. Probe 3. If the participant omitted any word between the first words and last words presented in a category, the participant was told the category names and then all the words between the first and last words presented. Probe 4. The participant was presented all the words in their original order and asked to recall all the words that went together.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

13

The calculation of span scores related to the initial, gain, and maintenance condition and probe scores followed the same format as the other two tasks. Procedure Each participant was tested individually. All examiners were trained in one 2-h session before the testing of participants. Total testing time was approximately 45 min per participant. All participants were first administered tasks in which initial, probe and gain scores were determined. All items for the initial condition were administered until (a) a discrimination question was missed or (b) an error in retrieval occurred. If an error in retrieval occurred (a participant omitted, inserted, or incorrectly ordered the numbers, dots, or words related to the appropriate task), cues were administered. Finally, the maintenance condition was administered. Because pilot testing showed no order effects, tasks were administered in the following order: Rhyming, Visual Matrix, and Semantic Association.

Results The results are organized into four sections. The first section assesses whether age related reading group differences in span scores were greater on memory conditions that varied processing demands and type of material. The second section assesses whether processing efficiency or demands on storage underlie working memory differences between reading groups across age. The third section assesses whether reading group differences in working memory across age were related to domain general processing. The final section assesses whether reading group differences in working memory were an artifact of achievement. This analysis was necessary to determine whether working memory problems were secondary to achievement difficulties or reflected a primary processing deficit. The rejection level for inferring statistical significance for all comparisons was set at a conservative .01 level. Span scores The raw span score means and SDs for performance on the Phonological, Visualspatial, and Semantic tasks as a function of age group, reading group, and memory condition (initial, gain, and maintenance) are reported in Table 2. The general pattern across the three working memory tasks and three memory conditions was (a) adults (20-year-olds) performed better than children and (b) skilled readers performed better than LD readers. These findings were qualified, however, by the interactions discussed below. Because the span scores reflected differences in the range across conditions, it was necessary to convert all span scores to z-scores within memory conditions and type of task, based on the total sample. Prior to conversion, effect sizes were calculated comparing the initial and gain scores. The mean effect sizes across age groups and type of task were 1.19 for skilled readers and .61 for LD readers. Thus, span scores

14

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

for both reading groups for the gain condition improved at least 1/2 SD when compared to the initial condition. The z-scores were submitted to a 4 (age groups)  2 (reading groups: Skilled vs. LD)  3 (memory condition: initial, gain, maintenance)  3 (Task: Phonological, Visual-spatial, Semantic) ANOVA, with repeated measures on the last two factors. It is important to note that because the span scores were transformed to z-scores within memory condition and type of memory task, no significant main effects related to the memory condition or task would emerge. A significant main effect emerged for age, F ð3; 218Þ ¼ 56:50, p < :0001, MSE ¼ 1:98. A Tukey test showed that significant (ps < :01) age effects were related to the superior performance of 20-year-olds when compared with the other age groups (20 > 13 > 10 > 7). A significant main effect showed that skilled readers performed better than LD readers, F ð1; 218Þ ¼ 125:44, p < :001, MSE ¼ 1:98. These age and reading group findings, however, were qualified by interactions related to memory conditions and type of task. Interactions were significant for the reading group  memory condition, F ð2; 436Þ ¼ 5:98; p < :01, the age  memory condition, F ð6; 436Þ ¼ 4:45, p < :001, MSE ¼ :30, and the age  reading group  type of task condition, F ð6; 436Þ ¼ 2:67, p < :01, MSE ¼ 1:24. No other significant effects emerged, ps > :01. The reading group  memory condition interaction is shown in Fig. 1. As shown, larger reading group differences in span scores emerged for the gain and maintenance conditions when compared to the initial condition. This observation was confirmed when effect sizes were analyzed. Effect sizes were computed as g2 (the proportion of variance in the dependent variable that is explained by reading ability group). An effect size of g2 > :13 (for unequal Ns) was equivalent to a standardized mean differ-

Fig. 1. Mean span z-scores for skilled and LD readers as a function of performance on the initial, gain, and maintenance condition. Error bars represent the standard error of the mean.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

15

ence of .5 or a moderate effect as expressed by CohenÕs d (Cohen, 1988), whereas g2 of .25 or greater was equivalent to ds of .8, which Cohen considered a large effect. Effect sizes between the two reading groups were .17, .29, and .26 for initial, gain, and maintenance conditions, respectively. Thus, effect sizes were large on the gain and maintenance conditions and moderate for the initial conditions. The interaction related to age group as a function of memory condition (e.g., initial) is shown in Fig. 2. Span scores for this comparison were z-scores averaged across the type of task within each condition. As shown in Fig. 2, the important finding was that statistical differences in span scores that emerged between 7- and 10-year-olds in the initial condition were eliminated in the gain and maintenance condition. Tukey tests indicated that significant (ps < :01) increases in working memory span occurred as a function of age for the initial (7 < 10 ¼ 13 < 20), gain (7 ¼ 10 < 13 < 20), and maintenance (7 ¼ 10 < 13 < 20) conditions. Effect sizes (g2 ) for age groups were large for all three conditions (.29, .33, and .36 for initial, gain, and maintenance conditions, respectively). Fig. 3 shows the mean span scores for the age  reading group  type of task interaction. The span scores were the mean z-scores collapsed across memory conditions (initial, gain, and maintenance) for each type of task. The top panel shows skilled readersÕ span scores and the bottom panel shows LD readersÕ span scores. As shown when comparing the two panels, the magnitude of differences between 20-year-old skilled and 20-year-old LD readers increased on the semantic and visual-spatial condition when compared to the phonological condition. The top panel of Fig. 3 shows that a clear age-related trajectory in span scores emerged for skilled readers for the Phonological and Visual-spatial task, but not for the Semantic task. For skilled readers, Tukey tests indicated that significant (p < :01) increases in work-

Fig. 2. Mean span z-scores for each age group as a function of performance on the initial, gain, and maintenance condition. Error bars represent the standard error of the mean.

16

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

Fig. 3. Mean span z-scores for skilled (top panel) and LD readers (bottom panel) as a function of the four age groups for the Phonological, Visual-spatial (Visual), and Semantic tasks. Error bars represent the standard error of the mean.

ing memory span emerged as a function of age on the Phonological (7 < 10 < 13 < 20) and Visual-spatial tasks (7 < 10 < 13 < 20). Age related differences for skilled readers on the semantic task, however, were isolated to the older age group (7 ¼ 10 < 13 < 20) tasks. The bottom panel of Fig. 3 shows that the age-related trajectory for LD readers on the verbal working memory tasks did not match skilled readers. For LD readers, Tukey tests indicated that the age effects (p < :01) were isolated to 20-year-olds on the Phonological (7 ¼ 10 ¼ 13 < 20) and Semantic task (7 ¼ 10 ¼ 13 < 20). In contrast, the age-related trajectory for LD readers on Visual-spatial tasks (7 < 10 ¼ 13 < 20) followed a similar pattern to skilled readers. The effect sizes (g2 ) between LD and skilled readers were .13,

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

17

.16, and .27 for the Phonological, Visual-spatial, and Semantic tasks, respectively. Thus, larger reading group differences emerged on the semantic task when compared to the Visual-spatial and Phonological Tasks. Effect sizes were comparable on the Phonological and Visual-spatial task. In summary, three important findings emerged. First, regardless of age, reading group differences were larger on gain and maintenance than initial conditions. Second, working memory differences between reading groups increased relative to Phonological and Visual-spatial tasks as a function of age when the tasks required the processing of semantic information. Finally, no support was found for the assumption that LD readersÕ working memory performance was statistically comparable to skilled readers in the later ages. Processing efficiency A 4 (age)  2 (reader)  3 (type of task) was computed on process efficiency scores, with repeated measures on the last factor. Efficiency scores were calculated as: (maintenance-initial span scores)/number of probes. Gain scores were not used in this calculation because of their high correlation with probes (rs ranged from .60 to .80). Lower scores reflected more efficient processing than higher scores. Because efficiency scores were not scaled equivalently across tasks, efficiency scores were converted to zscores based on the total sample within each task condition. A significant effect emerged for age, F ð3; 217Þ ¼ 13:15, p < :001, MSE ¼ 1:34. No other significant effects emerged (ps > :01). A Tukey Test indicated that processing efficiency was significantly (ps < :01) better (lower scores) for the oldest age group (20-year-olds) when compared to the younger age groups: 7 ðM ¼ :03; SD ¼ :60Þ ¼ 10 ðM ¼ :28; SD ¼ :72Þ ¼ 13 ðM ¼ :13; SD ¼ :71Þ < 20 (M ¼ :42, SD ¼ :63). In summary, the results do not support the hypothesis that reading group differences in working memory can be attributed primarily to processing efficiency. Measures of processing efficiency were statistically comparable between the two reading groups. Demands on storage We assumed that the three memory conditions (initial, gain, and maintenance) varied the demands placed on a limited capacity system in both LD and skilled readers. Specifically, we assumed that (a) gain conditions reflected increased retrieval efficiency relative to initial conditions and (b) greater demands were placed on memory storage in the maintenance condition (see introduction) than the other two conditions. In statistical terms, unique variance was assumed to exist between memory conditions. To test these assumptions, two analyses were carried out. First, we focused on those variables that predicted performance on the gain condition. We assumed that span scores on the gain condition reflected increased retrieval efficiency relative to the initial condition. This was because the probing procedures improved access to stored information not previously retrieved in the initial condition. We also assumed that individual differences in retrieval efficiency were

18

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

related to demands placed on memory storage. Span scores from the maintenance condition assessed demands on storage. However, it could be argued that reading, age and preretrieval processes (such as performance on the initial condition) accounted for all the important variance, suggesting that measures derived from the maintenance condition or probing added no significant variance to our understanding of reading group differences. Thus, we wanted to determine if individual differences in storage (as reflected in the maintenance condition) added unique variance to retrieval efficiency. The contribution of probe scores and performance on the maintenance condition to retrieval efficiency was isolated using hierarchical regression, by statistically controlling for the influence of preretrieval processes (initial scores), reading and age. The results are presented in Table 3. Span scores from the gain condition were the criterion measure. Predictor variables entered first into the regression model were reading level (standard score adjusted for age) and chronological age. This entry was followed by span scores (raw scores) related to initial and maintenance conditions and probe scores. Span scores related to the maintenance condition were always entered last into the equation to partial out the influence of achievement, age, preretrieval processes (e.g., initial scores), and probe scores. As shown in Table 3, the entry of reading scores, age, initial span scores, and probe scores into the regression model did not eliminate the significant influence of span scores related to the maintenance condition. This pattern held across the Phonological, Visual-spatial and Semantic tasks. This finding was important because Table 3 Hierarchical analysis predicting retrieval efficiency (span scores of gain condition) (N ¼ 226) b

B

SEb

R2

Increment R2

F-ratio

Phonological Reading Age Initial Probe Maintenance

.02 .05 .45 .44 .28

.03 .13 .88 .33 .30

.003 .009 .03 .02 .04

.12 .30 .67 .92 .94

— .18 .37 .35 .02

19.38 23.90 36.42 28.74 7.63

Visual-spatial Reading Age Initial Probe Maintenance

.07 .06 .39 .57 .22

.05 .16 .59 .39 .28

.002 .006 .04 .03 .04

.18 .35 .50 .82 .84

— .17 .15 .32 .02

15.85 16.33 13.41 21.33 5.36

Semantic Reading Age Initial Probe Maintenance

.19 .01 .18 .29 .49

.06 .13 .73 .28 .56

.002 .006 .04 .03 .05

.30 .42 .58 .72 .82

— .12 .16 .14 .10

18.66 37.56 13.98 13.28 10.30

*

p < :01. p < :001.

**

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

19

the results showed that performance on the gain condition was not merely a function of preretrieval processes. The analysis showed that span scores from the maintenance condition captured unique variance across Phonological, Visual-spatial and Semantic tasks. This unique variance was independent of reading, age, initial and probe scores. The next analysis determined whether maintenance conditions placed greater demands on processing for the LD readers than skilled readers. We adapted a formula from dual-task studies (see Baddeley, Della Sala, Papagno, & Spinnler, 1997, MU score) to assess the performance costs on the maintenance conditions. To this end, performance costs were calculated using a formula that included the gain span score minus the maintenance span score divided by the gain score plus the maintenance score (gain ) maintenance/gain + maintenance). A low score reflected minimal cost in performance, whereas a high score indicated that performance was reduced as a function of processing demands. A 4 (age)  2 (reading groups)  3 (type of task: Phonological, Visual-spatial, Semantic) MANOVA, with repeated measures on the last factor was computed on cost scores. To compare across the type of tasks, cost scores were converted to z-scores. Significant differences in cost scores were found as a function of age, F ð3; 218Þ ¼ 25:01, p < :001, MSE ¼ 1:94, and reading ability, F ð1; 218Þ ¼ 28:95, p < :01, MSE ¼ 1:94. No other significant effects emerged (ps > :01). The results showed that significantly lower performance costs emerged for skilled readers (M ¼ :24, SD ¼ :74) when compared with LD readers (M ¼ :30, SD ¼ :76). A Tukey Test indicated that performance costs were greater for children than adults (ps < :01): 7 ðM ¼ :05; SD ¼ :61Þ ¼ 10 ðM ¼ :38; SD ¼ :79Þ ¼ 13 ðM ¼ :09; SD ¼ :87Þ < 20 (M ¼ :59, SD ¼ :45). In summary, the results suggested that demands on capacity were greater for LD readers than for skilled readers. These demands were not domain specific because they did not interact with the type of working memory task (Phonological, Visualspatial, and Semantic). In addition, capacity demands (i.e., cost scores) were comparable in the younger age groups (7, 10, and 13-year-olds), but those demands were significantly higher than those placed on 20-year-olds. Domain general vs. specific processing demands Linearity between groups. The previous results were unclear about whether LD readersÕ working memory deficits reflected problems in a single system or separate domains (verbal and visual-spatial). To address this issue the linear relation between reading and age groups across the complete array of working memory measures and conditions was investigated. A mathematical technique (Brinley plot) outlined by Hale (1990) and Kail (1993) was used to compare age and reading groups. According to the hypothesis that a domain general system was responsible for reading group differences in working memory, the correlation across working memory conditions between skilled and LD readers should approximate 1.0. That is, the closer the LD reader gets to their developmental maturity, the higher the R2 between the LD group and the criterion group (skilled readers) for a particular age (e.g.,

20

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

20-year-olds). To test this possibility, the mean performance of each of the LD reading age groups for each of the treatment conditions (initial, gain, maintenance; Phonological, visual-spatial, and semantic working memory tasks) was plotted as a function of the adolescent (13-year-olds) and adult skilled reading group in the corresponding condition. Table 4 shows the fit between comparisons by age and reading groups. Two general comparisons were made: (1) young skilled readers (<20-year-olds) and all LD reading age groups were compared with adult skilled readers (20-year-olds), and (2) LD readers were compared with adolescent (13-year-olds) skilled readers. Two important results are shown in Table 4. First, across all age groups and processing conditions the relation between LD readersÕ working memory performance and the skilled readersÕ working memory performance was linear. The fit was significant and the R2 was excellent (.95), F ð1; 16Þ ¼ 323:95, p < :0001, MSE ¼ :008. The results clearly showed that the processing of LD readers approximated that of skilled readers when all conditions were taken into consideration. Second, the strongest age-related linear relation for LD readers occurred when the criterion was 13-year-old skilled readers. As shown in Table 4, when the criterion group was 20-year-old skilled readers, the R2 for the younger skilled readers (predictor groups) ranged from .71 to .97(M ¼ :83). In contrast, the R2 for the LD predictor groups ranged from .45 to .74 ðM ¼ :55Þ. When the criterion was 13-year-old skilled readers, however, the R2 for the predictor LD reading group varied from .82 to .92 (M ¼ :88). This finding suggested that the developmental maturity of LD readers was best captured in the performance of 13-year-old readers. It could be argued that the strong linear relation across tasks emerged because all tasks tap a common language system. For example, one could argue that the visualTable 4 Fit statistics for age and reading group Parameters Intercept

R2

F-ratio

1.22

.95

323.95

Criterion group ¼ 20-year-old adults—skilled readers Children 7—skilled reader 1.42 Children 7—LD reader 1.19 Children 10—skilled reader .88 Children 10—LD reader .78 Children 13—skilled reader .86 Children 13—LD reader .73 Adults 20—LD reader .67

.93 2.78 2.16 3.31 1.71 3.41 2.64

.97 .74 .71 .45 .81 .48 .54

211.92 20.38 17.59 5.96 29.55 6.72 8.34

Criterion group ¼ 13-year-old children—skilled readers Children 7—LD reader 1.37 Children 10—LD reader 1.12 Children 13—LD reader 1.01 Adults 20—LD reader .88

1.25 1.43 1.63 .72

.93 .87 .86 .86

72.38 42.23 44.10 46.11

Slope Criterion group ¼ skilled readers LD readers

.95

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

21

spatial working memory, like the Semantic and Phonological Tasks, shared variance with a language system and therefore accounted for the strong linear relation between LD and skilled readers. We reasoned, however, that if the linear relation between reading and working memory measures reflected a general language system, then the significant correlations between visual working memory and reading should be eliminated once verbal working memory was partialed from the analysis. To investigate this possibility the span scores from the Visual-spatial tasks were correlated with reading scores (standard scores on the WRAT-R), with performance on the semantic working memory task and age partialed from the results. The semantic task was selected because performance gaps between skilled and LD readers were greater across age when compared to the Phonological Task. Visual-spatial working memory was significantly correlated with reading (N ¼ 226) for initial (r ¼ :24, p < :001), gain (r ¼ :29, p < :001), and maintenance (r ¼ :32, p < :001) conditions when performance on the semantic working memory task and chronological age was partialed from the analysis. Taken together, the results showed that the relation between reading and visual-spatial working memory was significant when verbal working memory was partialed from the analysis. In summary, the results support the notion that inferior working memory performance in LD readers was domain general. Poor working memory performance in LD readers was not isolated to peripheral storage (Phonological, Visual-spatial, and Semantic) systems. Furthermore, the correlation between working memory and reading was not merely a function of a general language system. The significant correlation between reading and visual-spatial working memory was maintained when verbal working memory was partialed from the analysis. In addition, age-related changes in LD readers were best captured by the performance of adolescent skilled readers. The developmental maturity of LD readersÕ working memory performance was better captured by 13-year-old skilled readers than by 20-year-old skilled readers. Processes not specific to reading. Although the previous analysis suggested there was unique variance related to the working memory conditions, we have not determined whether the reading groups differed on working memory processes unrelated to reading. We addressed this issue by reframing the comparison groups in terms of a regression-based design outlined by Stanovich and Siegel (1994). In this design, we partialed from the criterion variable (working memory) the linear trend of WRAT reading standard scores, WRAT mathematics standard scores, and chronological age, thus removing the variance in the criterion measure (working memory) associated with achievement and age. Because no significant interactions emerged related to the memory conditions and the type of working memory task (verbal, visual-spatial), we simplified the analysis by creating composite scores (sum of z-scores for the Phonological, Visual-spatial, and Semantic tasks) for each memory condition to serve as criterion measures. Subsequent to entering reading, math, and age into the regression model, a dummy variable related to reading group ()1 for skilled readers and +1 for LD readers) was also entered into the equation. The b values for the hierarchical regression model are shown in Table 5. A significant negative b weight for the LD vs. skilled reading variable indicated that the performance of

22

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

Table 5 Regression results for working memory conditions Measure

Criterion measures Initial

Gain

Maintenance

Probes

Reading b t-ratio

.28 3.28

.39 4.86

.37 4.68

Mathematics b t-ratio

.12 1.32

.13 1.52

.11 1.46

.10 .94

.47 9.00 .39 46.58

.49 10.12 .50 71.65

.54 11.63 .53 80.32

.32 5.16 .17 14.30

Skilled vs. LD readers b ).24 t-ratio )1.82 R2 .40 F-ratio (4,216) 36.14

).35 )2.95 .52 57.81

).36 )3.10 .55 65.01

).21 )1.33 .17 11.21

Age b t-ratio R2 F-ratio (3,217)

.15 1.50

*

p < :05. p < :01. *** p < :001. **

the skilled readers exceeded the LD readers on the criterion variables (e.g., initial scores). As shown in Table 5, the design first entered reading, math, and age. These variables were entered simultaneously. As shown, the b values were significant for reading and age for all criterion measures. Higher reading scores and older age groups performed better than less skilled readers and younger children. No significant variance was related to mathematics. The b values (partialed for the influence of reading, mathematics and age) for the reading contrast variable were significant for the gain and maintenance scores. As indicated by the negative b weight, skilled readersÕ performance exceeded LD readersÕ even when reading, mathematics and age were partialed in the analysis. In contrast, the reading contrast variable was not significant for the initial scores. Thus, reading group differences in working memory on the initial conditions were mediated by variations in reading and age. The results also showed that when reading, mathematics and age were controlled, no significant differences emerged for the reading contrast variable for the probe composite scores. In summary, the important findings were that skilled readers were superior to LD readers on conditions that enhanced the retrieval of new information (gain scores) and the maintenance of old information (maintenance scores) when reading, mathematics and age were partialed from the results.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

23

Discussion The results of this study support the notion that LD readers suffer working memory deficits. Although both LD and skilled readers show continuous growth in verbal and visual-spatial working memory, the results clearly indicate that LD readersÕ working memory is inferior to skilled readersÕ. These performance differences are domain general because they emerge across verbal and Visual-spatial tasks. The working memory differences between reading groups increase with age, but these differences are especially pronounced on the semantic task. What is unique to our findings compared with others (Siegel, 1994; Swanson, 1992) is that (a) the reading group effect is greater on conditions that enhance retrieval and require the accessing of earlier retrieved information when compared to initial condition and (b) the reading group effect is sustained when reading and math skill are partialed from the analysis. The first finding suggests that providing cues to facilitate previously accessed information is more likely to benefit skilled readers than LD readers. The second finding suggests that the relative inability of LD readers to benefit from cue conditions is due to capacity limitations that may supersede any retrieval inefficiencies and knowledge-based (achievement) deficits. We will address these two findings within the context of the two general issues that motivated this study. Do LD readers primarily suffer from retrieval inefficiencies or capacity deficits? Two findings suggest that the working memory deficits of LD readers are related to processing constraints of a limited capacity system. First, the magnitude of the difference in span scores (effect sizes) increases between reading groups on gain and maintenance conditions in comparison to the initial conditions. Although the results show that cues substantially improve (as suggested by effect size scores) LD readersÕ working memory performance, LD readers remain at a clear disadvantage to skilled readers in working memory performance across gain and maintenance conditions. These low working memory span scores emerge across all working memory tasks, suggesting that the source of reading group differences reflects generalized processing constraints. Second, skilled readers experience less reduction in performance on the maintenance condition than LD readers. Thus, not only did LD readers have smaller working memory spans than skilled readers on initial and gain conditions, they also experienced greater constraints on capacity (i.e., performance costs) under high demand (maintenance) conditions. Furthermore, these constraints were comparable across the Phonological, Visual-spatial, and Semantic tasks. Do age-related deficits in LD readers’ working memory reflect domain specific or domain general processes? Two findings suggest that the working memory deficits of LD readers relate to a domain-general system. First, reading group differences in working memory across age span and verbal and visual-spatial conditions relate to the absolute quantity of processing resources without regard to the nature or specific componential make

24

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

up of the working memory tasks. The results from the Brinley plots show that when we regress LD readersÕ performance across all conditions and tasks on skilled readersÕ performance, the fit is significant and the R2 is excellent (.95). These findings suggest that group differences in working memory are not due to domain specific processes (i.e., different patterns in performance), but to a domain general (i.e., executive) system. Second, the hierarchical regression shows that reading group differences on gain and maintenance conditions are not eliminated when reading, math, and age are partialed from the analysis. These results support the notion that the relation between working memory and reading across age is not merely an artifact of skills within a particular academic domain (i.e., reading). These findings are important because several authors argue that working memory is domain specific in its influence on language processes (e.g., Shah & Miyake, 1996). Our findings are comparable to several studies (e.g., Conway & Engle, 1994) suggesting that the influence of working memory on cognitive measures is independent of academic domains. Given the above findings, we now address the question: ‘‘What does or does not develop adequately in LD readersÕ working memory?’’ The results show that the working memory problems of LD readers are not merely due to a failure of the phonological system to develop. Deficits in working memory also relate to a general system that operates independently of reading. The results show that these deficits are not remedied by bolstering retrieval efficiency. Furthermore, we could not eliminate reading group differences by calibrating task difficulty (readministering items of highest performance possible with cues) for each participant or by tailoring cues to achieve the highest performance possible (gain performance). Taken together, our findings suggest that the level of activation and the total amount of activation of information available in LD readers are limited. These limitations are not eliminated with increasing age. These findings align themselves with a general capacity hypothesis, suggesting that the activation of attentional resources in LD readers is more limited than skilled readers (Swanson & Alexander, 1997), regardless of the nature of the working memory task. There is a theoretical problem in this study when one considers how to reconcile the specific verbal working memory processing deficit (e.g., problems related to the phonological system) hypothesis commonly attributed to LD readers of normal intelligence (Cohen, 1981; Siegel, 1993) with the notion that they also suffer a deficiency in a domain general system. We know from the literature that individuals of high intelligence can vary in working memory (e.g., Daneman & Carpenter, 1980), and these individual differences relate to reading achievement (Engle et al., 1992). What we do not know is how problems in the phonological system relate to problems in the executive system (or vice versa) in individuals with normal intelligence. One possible explanation is that problems in specific activities of the central executive system may exist in LD readers that are independent of their problems in phonological processing (Swanson, 1993; Swanson & Siegel, 2001). Another possibility is to suggest that a generic storage system indirectly accounts for low-order processing deficits (especially on language-related tasks). For example, in BaddeleyÕs (1986; Baddeley & Logie, 1999) model the central executive system is an undifferen-

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

25

tiated generic system that draws resources from long-term memory to support low-order (slave) systems. However, if the executive system is overtaxed, it cannot contribute resources to low-order processing. Given that the phonological loop is controlled by the central executive (Baddeley, 1990), any deficits in phonological functioning may partially reflect deficiencies in the controlling functions of the central executive itself (see Badddeley, 1996; Baddeley et al., 1997; Gathercole & Baddeley, 1993). There are, of course, other interpretations of the present results that must be considered. Four are considered. The first option is related to the participantÕs knowledge base. For example, it may be argued that although probing procedures enhance retrieval, they cannot compensate for a weak knowledge base. This interpretation fits within Ericsson and KintschÕs (1995) long-term working memory model. That is, knowledgeable children (skilled readers in this case) can outperform less knowledgeable children (LD readers in this case) on working memory tasks. This interpretation, however, does not match well with the results. For example, the statistical control of previous knowledge (achievement scores) did not alter the outcomes related to reading group differences. Reading group differences emerged on both the gain and maintenance conditions when achievement scores were partialed from the analysis. It is also important to note that the participants had learned the items in the gain condition and then were again presented the very same items in the maintenance condition, but without help. Thus, all participants were familiar with the items. Regardless of these controls, LD readersÕ span scores were inferior to skilled readers on both the gain and maintenance conditions. A second option relates to recent studies (Jones, Farrand, Stuart, & Morris, 1995; Pickering, Gathercole, & Peaker, 1998) which suggest that the serial recall of verbal and visual-spatial information shares a common level of representation. No doubt, the retrieval of ordinal information was reflected in all three working memory tasks in the present study. Furthermore, all cuing instructions emphasized the temporal order of information. Thus, the finding that LD readersÕ working memory performance is deficient to skilled readers across task and memory conditions is consistent with the notion that working memory tasks reflect the reconstruction of serial order. This reconstruction calls upon a common process, irrespective of whether the storage medium is verbal or visual-spatial. We believe this is a viable alternative hypothesis to the results. The difficulty with this interpretation, however, is that our results show that significant correlations remain between reading and visual-spatial working memory when verbal working memory is partialed from the analysis. If the verbal working memory task and visual-spatial working memory task both relate to a common system that involves the reconstruction of serial order, then partialing out performance that relates to one serial task (i.e., the semantic task) should eliminate the influence of the other serial task (visual-spatial working memory task) on reading. Such was not the case in this study. Thus, it appears to us that the verbal and visual-spatial working memory tasks capture some subsystems or distinct representations other than serial recall. The third option suggests that the storage capacity is comparable between LD and skilled readers, but LD participants are less resistant to interference (see Palladino,

26

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

Cornoldi, De Beni, & Pazzaglia, 2001, for discussion of this model). Clearly, the discrimination questions in the current working memory tasks constitute a temporary competing condition with storage. As a consequence, LD readers may have difficulty preventing unnecessary information from entering working memory and, therefore, consider alternative interpretations of material (such as those asked for in the processing questions) that are not central to the task. This interpretation fits within several models that explain individual differences in memory performance as due in part to inhibitory mechanisms (e.g., Brainerd & Reyna, 1993; Cantor & Engle, 1993; Conway & Engle, 1994). Although we see this model as a viable alternative to the results, we have three reservations. First, only the span levels of participants who answered the process question correctly were analyzed. If a process question was missed, the participantÕs recall of previously stored information was not requested. This procedure is different from previous studies (e.g., Daneman & Carpenter, 1980) that have allowed a dissociation between the process question (i.e., it is not necessary for participants to answer the process question correctly) and the retrieval question in the analyses. Our procedure removes from the analysis irrelevant responses that emerge between the processing of the distracter question and the retrieval question. Second, if LD readers suffer more interference (i.e., diminished inhibition in that a large number of traces are simultaneously active) than skilled readers, then one would expect the cuing to narrow the alternative interpretations of items in memory when compared with skilled readers. In addition, inefficiencies in inhibiting traces or competition effects should be reduced, via cuing, more in LD readers than in skilled readers. Furthermore, one would predict that a procedure which gives feedback on the relevancy of a response should lead to a substantial increase in memory performance in the group with the diminished inhibitory efficiency. Such was not the case in this study. Finally, it seems that the concept of ‘‘interference’’ can be tied to a resource allocation model. Capacity constraints may underlie individual differences in inhibitory efficiency (see Cantor & Engle, 1993, for discussion). In short, LD readers may use more capacity than skilled readers to inhibit or resist potential interference from irrelevant items (see Chiappe, Hasher, & Siegel, 2000, for discussion). A final option for interpreting the results suggests that LD readers suffer functional working memory problems (e.g., a lack of flexibility in coordinating various memory stores) rather than processing constraints. In this view, LD readers may or may not have the same storage capacity as skilled readers, but an important source of individual differences in reading is an ability to coordinate and/or compensate for the processes they have. This option, not unlike the second, differs from the processing vs. storage issue by emphasizing the coordination of processes. The option also differs from the divided attention among relevant and irrelevant information view as discussed above. In support of this coordination model, Yee, Hunt, and Pellegrino (1991) have argued that complex tasks (i.e., dual or multiple task situations) are more likely to reflect the temporal coordination of processes than the more common assumption that they require divided attention between competing memory traces (also see Towse et al., 1998, discussion related to the seriality of performing different tasks). Thus,

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

27

although individual differences in working memory may reflect a situation in which information is poorly encoded and maintained, individual differences also occur in how participants switch between and coordinate sources of information. For example, LD participants may be forced to represent word information in a phonological form, rather than leave it in a semantic form, or vice versa, and this coordination across different representations is difficult for LD participants. This interpretation is appealing because the phonological form of information has been found deficient in LD readers (e.g., Stanovich & Siegel, 1994). We believe, however, that the major limitation of this option in interpreting the present results is that it does not eliminate a resource allocation model. This is because one can speculate that resource tradeoffs can exist between storage and response execution processes (see Carlson, Wenger, & Sullivan, 1993, for a testing of this notion). Simply stated, there is a cost in switching and/or coordinating across multiple memory traces. A possible corollary to this coordination model, however, is that LD readers experience difficulties primarily related to retrieval operations. For example, LD readers may be less adept at benefiting from probes than skilled readers because of problems in executing the ‘‘controlled components’’ of retrieval. One means to assess the benefits of probes in working memory performance is to examine the correlations between probe scores and gain scores. If the LD groups were less likely to benefit from probes, then the correlations should be significantly weaker in LD than skilled readers. A post hoc analysis of correlations between the probe scores and gain scores were .77 for skilled readers and .66 for LD readers, respectively. A Fisher z-score transformation showed that the coefficients were comparable between groups. This finding suggests that the high correlations between probe and gain scores relate to improvement in retrieval efficiency for both reading groups. Because the magnitude of the correlations was comparable between ability groups, it suggests to us that LD readers benefited as much from cues as skilled readers. In summary, the results show that although the LD readersÕ working memory performance can be modified on Phonological, Visual-spatial, and Semantic measures, as suggested by the effect size scores, the LD readers remain at a clear disadvantage across a broad age range when compared to their normal-reading counterparts. The results further suggest that when compared with skilled readers, LD readersÕ working memory deficits are not primarily driven by retrieval inefficiencies, isolated deficits such as the processing of verbal information, and/or overall reading ability. Instead, their working memory deficits reflect constraints on a general capacity system that appears to operate independent of reading skill.

Acknowledgments This research was partially funded by Peloy Funds awarded to the author from the University of California. The author is thankful to several graduate students, but especially Carole Lee, Margaret Ashbaker, and Sue Simmerman, in the data collection. The author is also thankful for the critical comments by Kathy Wilson and Diana Luxenberg, and two anonymous reviewers on an earlier version of this manuscript.

28

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

Appendix A. Items for the Phonological task Test item

Process question

1. lip-slip 2. run-/fun-/gun 3. car-/star-bar-/far 4. shun-/bun-nun-pun-/dun 5. nap-sap/-gap-rap-/cap-lap 6. ear-dear-/sear-fear-gear-year/-clear-near 7. sack-crack-back/-snack-black-shack-track-/mack-jack-flack 8. red-fed-bed-/led-ned-jed-sled-shed-head/-ped-fred-bled 9. care-fare-share-dare/-clare-bare-tare-mare-hare-lare-/pareware-blare-flare

slip or jip sun or fun jar or star nun or hun gap or flap sneer or gear snack or rack fled or fed chair or tare

Appendix B. Items for the Semantic task Set Question Set 1 (vegetables and clothes)* Coat, carrots/gloves, tomatoes Set 2 (fruit and vehicles) Pear, car, prune/bus, apple, truck Set 3 (tools and clothes) Shirt, saw/pants, hammer/belt, nails Set 4 (sports, furniture, weapons) Hockey, rifle, chair/football, sword, table Set 5 (bird, colors, and shapes) Canary, black, triangle/robin, orange circle/sparrow, pink, hexagon Set 6 (transportation, chemicals elements, and animals) Airplane, hydrogen, gorilla/ship, nitrogen, lion, bus, sodium, puma/taxi, carbon, koala Set 7 (American presidents, trees, and occupations) Fillmore, eucalyptus, chemist/Madison, pine, zoologist, Garfield, ash, clerk, Adams, poplar architect/Buchanan, sycamore, machinist Set 8 (authors-world literature, musical instruments, tools, and personalities) Tolstoy, viola, bolts, depressed/Dickens, flute, stapler neurotic, Hemingway, symbols, crowbar, schizophrenic/Homer, cello, sandpaper, and paranoid

Process question ‘‘Which word, Ôcarrot or bananaÕ?’’ Apple or peach? Level or saw? Sword or knife? Red or orange?

Ship or car?

Birch or ash?

Dickens or Twain?

Note. The slashes (/) shown above reflected the beginning, middle, and end sections of each word list.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

29

References Anderson, J. R., Reder, L. M., & Lebiere, C. (1996). Working memory: Activation limitations on retrieval. Cognitive Psychology, 30, 221–256. Baddeley, A. D. (1986). Working memory. London: Oxford University Press. Baddeley, A. D. (1990). Human memory. Oxford, England: Oxford University Press. Badddeley, A. D. (1996). Exploring the central executive. Quarterly Journal of Experimental Psychology, 49A, 5–28. Baddeley, A., & Logie, R. H. (1999). Working memory: The multiple-component model. In A. Miyake, & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 28–61). New York: Cambridge University Press. Baddeley, A., Della Sala, S., Papagno, C., & Spinnler, W. (1997). Dual-task performance in dysexecutive and nondysexecutive patients with a frontal lesion. Neuropsychology, 11, 187–194. Barrouillet, P., & Camos, V. (2001). Developmental increase in working memory span: Resource sharing or temporal decay? Journal of Memory and Language, 45, 1–20. Brainerd, C. J., & Reyna, V. F. (1993). Domains of fuzzy trace theory. In M. L. Howe, & R. Pasnak (Eds.), Emerging themes in cognitive development, Vol. 1.: Foundations (pp. 50–93). New York: Springer. Bull, R., Johnston, R. S., & Roy, J. A. (1999). Exploring the roles of the visual-spatial sketchpad and central executive in childrenÕs arithmetical skills: Views from cognition and developmental neuropsychology. Developmental Neuropsychology, 15, 421–442. Cantor, J., & Engle, R. W. (1993). Working memory capacity as long-term memory activation: An individual-differences approach. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19, 1101–1114. Carlson, R. A., Wenger, J. L., & Sullivan, M. A. (1993). Coordinating information from perception and working memory. Journal of Experimental Psychology: Human Perception and Performance, 19, 531–548. Case, R. (1995). Capacity-based explanations of working memory growth: A brief history and reevaluation. In F. E. Weinert, & W. Schneider (Eds.), Memory performance and competencies: Issues in growth and development (pp. 23–44). Mahwah, NJ: Erlbaum. Case, R., Kurland, D. M., & Goldberg, J. (1982). Operational efficiency and the growth of short-term memory span. Journal of Experimental Child Psychology, 33, 386–404. Chiappe, P., Hasher, L., & Siegel, L. S. (2000). Working memory, inhibitory control, and reading disability. Memory & Cognition, 28, 8–17. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New York: Academic Press. Cohen, R. L. (1981). Short-term memory deficits in reading disabled children in the absence of opportunity for rehearsal strategies. Intelligence, 5, 69–76. Conway, R. A., & Engle, R. W. (1994). Working memory and retrieval: A resource-dependent inhibition model. Journal of Experimental Psychology: General, 123, 354–373. Conway, R. A., & Engle, R. W. (1996). Individual differences in working memory capacity: More evidence for a general capacity theory. Memory, 4, 577–590. Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–185. Cowan, N., Nugent, L. D., Elliott, E. M., & Ponmarev, I., et al. (1999). The role of attention in the development of short-term memory: Age differences in the verbal span of apprehension. Child Development, 70, 1082–1097. Craik, F. I. M., & Jennings, J. M. (1992). Human memory. In F. I. M. Craik, & T. Salthouse (Eds.), The handbook of aging and cognition (pp. 51–110). Hillsdale, NJ: Erlbaum. Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19, 450–466. De Beni, R., Palladino, P., Pazzaglia, F., & Cornoldi, C. (1998). Increases in intrusion errors and working memory deficit of poor comprehenders. Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 51, 305–320.

30

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

De Jong, P. (1998). Working memory deficits of reading disabled children. Journal of Experimental Child Psychology, 70, 75–95. Engle, R. W., Cantor, J., & Carullo, J. J. (1992). Individual differences in working memory and comprehension: A test of four hypotheses. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 972–992. Engle, R., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. (1999). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology: General, 128, 309–331. Ericsson, K., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102, 211–245. Fastenau, P., Denburg, N. L., & Ables, N. (1996). Age differences in retrieval: Further support for the resource-reduction hypothesis. Psychology and Aging, 11, 140–146. Federal Register. (1977). The rules of a regulatory for implementing PL 94–142. US Government Printing Office, Washington, DC. Gathercole, S. E., & Baddeley, A. D. (1993). Working memory and language. Hillsdale, NJ: Erlbaum. Hale, S. (1990). A global developmental trend in cognitive processing speed. Child Development, 61, 653–663. Halford, G. (1998). Development of processing capacity entails repeating more complex relation: Implications for cognitive development. In R. H. Logie et al. (Eds.), Working memory and thinking (pp. 139–157). Hove, England: Erlbaum. Hitch, G. J., & Towse, J. N. (1995). Working memory: What develops?. In F. E. Weinert, & W. Schneider (Eds.), Memory performance and competencies: Issues in growth and development (pp. 3–21). Mahwah, NJ: Erlbaum. Hitch, G. J., Towse, J. N., & Hutton, U. (2001). What limits childrenÕs working memory span? Theoretical accounts and applications for scholastic development. Journal of Experimental Psychology: General, 130, 184–198. Howe, M., OÕSullivan, J. T., Brainerd, C., & Kingma, J. (1989). Localizing the development of ability differences in organized memory. Contemporary Educational Psychology, 14, 336–356. Jones, D. M., Farrand, P., Stuart, G. P., & Morris, N. (1995). Functional equivalence of verbal and spatial information in serial short-term memory. Journal of Experimental Psychology: Learning, Memory, & Cognition, 21, 1008–1018. Kail, R. (1993). The role of global mechanisms in developmental change in speed of processing. In M. Howe, & R. Pasnak (Eds.), Emerging themes in cognitive development: Vol. 1 (pp. 97–116). New York: Springer. Kane, M. J., & Engle, R. W. (2000). Working memory capacity, proactive Interference, and divided attention: Limits on long-term memory retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 336–358. Miyake, A. (2001). Individual differences in working memory: Introduction to special edition. Journal of Experimental Psychology: General, 130, 163–168. Miyake, A., & Shah, P. (1999). Toward unified theories of working memory: Emerging general consensus, unresolved theoretical issues, and future research directions. In A. Miyake, & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 442–481). New York: Cambridge University Press. Palladino, P., Cornoldi, C., De Beni, R., & Pazzaglia, F. (2001). Working memory and updating processes in reading comprehension. Memory & Cognition, 29, 344–354. Passolunghi, M. C., & Siegel, L. S. (2001). Short-term memory, working memory, and inhibitory control in children with difficulties in arithmetic problem solving. Journal of Experimental Child Psychology, 80, 44–57. Pickering, S. J., Gathercole, S. E., & Peaker, S. M. (1998). Verbal and visuospatial short-term memory in children: Evidence for common and distinct mechanisms. Memory & Cognition, 26, 1117–1130. Rosen, V. M., & Engle, R. W. (1997). The role of working memory capacity in retrieval. Journal of Experimental Psychology: General, 126, 211–227. Salthouse, T. A. (1990). Working-memory as a processing resource in cognitive aging. Developmental Review, 10, 101–124.

H. Lee Swanson / Journal of Experimental Child Psychology 85 (2003) 1–31

31

Salthouse, T. A. (1992). Working memory mediation of adult age differences in integrative reasoning. Memory & Cognition, 20, 413–423. Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of Experimental Psychology: General, 125, 4–27. Shankweiler, D., & Crain, S. (1986). Language mechanisms and reading disorder. Cognition, 24, 139–168. Siegel, L. S. (1993). Phonological processing deficits as the basis of a reading disability. Developmental Review, 13, 246–257. Siegel, L. S. (1994). Working memory and reading: A life-span perspective. International Journal of Behavioral Development, 17, 109–124. Siegel, L. S., & Ryan, E. B. (1989). The development of working memory in normally achieving and subtypes of learning disabled. Child Development, 60, 973–980. Swanson, H. L. (1992). Generality and modifiability of working memory among skilled and less skilled readers. Journal of Educational Psychology, 84, 473–488. Swanson, H. L. (1993). Working memory in learning disability subgroups. Journal of Experimental Child Psychology, 56, 87–114. Swanson, H. L. (1995). S-Cognitive processing test. Austin, TX: PRO-ED. Swanson, H. L. (1996). Individual and age-related differences in childrenÕs working memory. Memory & Cognition, 24, 70–82. Swanson, H. L. (1999). What develops in working memory. A life span perspective? Developmental Psychology, 35, 986–1000. Swanson, H. L., & Alexander, J. (1997). Cognitive processes that predict reading in learning disabled readers: Revisiting the specificity hypothesis. Journal of Educational Psychology, 89, 128–158. Swanson, H. L., & Ashbaker, M. H. (2000). Working memory, short-term memory, speech rate, word recognition and reading comprehension in learning disabled readers: Does the executive system have a role? Intelligence, 28, 1–30. Swanson, H. L., Ashbaker, M. H., & Lee, C. (1996). Learning-disabled readersÕ working memory as a function of processing demands. Journal of Experimental Child Psychology, 61, 242–275. Swanson, H. L., & Siegel, L. (2001). Learning Disabilities as a working memory deficit. Issues in Education: Contribution of Educational Psychology, 7, 1–48. Stanovich, K. E., & Siegel, L. (1994). Phenotypic performance profile of children with reading disabilities: A regression-based test of the phonological-core variable-difference model. Journal of Educational Psychology, 86, 24–53. Towse, J. N., Hitch, G., & Hutton, U. (1998). A reevaluation of working memory capacity in children. Journal of Memory and Language, 39, 195–217. Turner, M. L., & Engle, R. W. (1989). Is working-memory capacity task dependent? Journal of Memory and Language, 28, 27–154. Yee, P. L., Hunt, E., & Pellegrino, J. W. (1991). Coordinating cognitive information: Tasks effects and individual differences in integrating information from several sources. Cognitive Psychology, 23, 615–680.