552018

research-article2014

LDXXXX10.1177/0022219414552018Journal of Learning DisabilitiesSumner et al.

Article

The Influence of Spelling Ability on Vocabulary Choices When Writing for Children With Dyslexia

Journal of Learning Disabilities 1­–12 © Hammill Institute on Disabilities 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0022219414552018 journaloflearningdisabilities.sagepub.com

Emma Sumner, PhD,1 Vincent Connelly, PhD,2 and Anna L. Barnett, PhD2

Abstract Spelling is a prerequisite to expressing vocabulary in writing. Research has shown that children with dyslexia are hesitant spellers when composing. This study aimed to determine whether the hesitant spelling of children with dyslexia, evidenced by frequent pausing, affects vocabulary choices when writing. A total of 31 children with dyslexia, mean age 9 years, were compared to typically developing groups of children: the first matched by age, the second by spelling ability. Oral vocabulary was measured and children completed a written and verbal compositional task. Lexical diversity comparisons were made across written and verbal compositions to highlight the constraint of having to select and spell words. A digital writing tablet recorded the writing. Children with dyslexia and the spelling-ability group made a high proportion of spelling errors and within-word pauses, and had a lower lexical diversity within their written compositions compared to their verbal compositions. The age-matched peers demonstrated the opposite pattern. Spelling ability and pausing predicted 53% of the variance in written lexical diversity of children with dyslexia, demonstrating the link between spelling and vocabulary when writing. Oral language skills had no effect. Lexical diversity correlated with written and verbal text quality for all groups. Practical implications are discussed and related to writing models. Keywords dyslexia, spelling, vocabulary, writing

Writing requires integrating cognitive, linguistic, and motor processes. It is consistently reported that children and adults with dyslexia have difficulties with accurate spelling (Ramus, Marshall, Rosen, & van der Lely, 2013), and more generally with the composition of written texts (Berninger, Nielsen, Abbott, Wijsman, & Raskind, 2008; Connelly, Campbell, MacLean, & Barnes, 2006; Gregg, Coleman, Davis, & Chalk, 2007; Sumner, Connelly, & Barnett, 2014). The “simple view” and “not-so-simple” models of writing development (Berninger & Amtmann, 2003; Berninger & Winn, 2006) highlight transcription, text generation, and executive function as the three key components involved when writing, all of which are overseen by working memory resources. The lower-level transcription process (the act of integrating spelling and handwriting to produce a visible trace of the text) must become an automatized skill to free resources to be devoted to the compositional aspect of writing (Berninger & Winn, 2006). With this in mind, and as the models predict, producing spellings while composing a written text will impose a high cognitive demand on poor spellers. The impact of poor spelling on the writing process is of interest in the present study.

In a recent study, children with dyslexia made a higher proportion of spelling errors and tended to pause more frequently while composing a narrative text in comparison to their typically developing same-age peers (Sumner, Connelly, & Barnett, 2013). The amount and duration of pausing while writing were similar to those of a younger spelling-ability-matched group. Pause behavior was not explained by poor motor skills, but rather slow hesitant spelling, linked to poor spelling ability, led to a slower overall writing time and poorer compositional quality (Sumner et al., 2013). Thus, the cognitive demand of spelling directly affects the amount of time that writing takes for children with dyslexia and is linked to the quality of writing produced. Might there be other repercussions for the composing process as a consequence of slow hesitant spelling of words? 1

Goldsmiths, University of London, UK Oxford Brookes University, UK

2

Corresponding Author: Emma Sumner, PhD, Department of Psychology, Goldsmiths, University of London, New Cross, London, SE14 6NW, UK. Email: [email protected]

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

2

Journal of Learning Disabilities 

Words selected for composition are mentally generated and accurately transcribed onto the page through the application of spelling knowledge (Berninger & Winn, 2006; Van Galen, 1991). Transcription is thus closely related to text generation, as transcription is the tool to demonstrate the ideas that the writer wishes to convey. However, to date, studies on children with dyslexia have not yet considered the relationship between the transcription and text generation processes identified in models of writing. Text generation is highly dependent on the selection of appropriate vocabulary from the mental lexicon (Treiman, Clifton, Meyer, & Wurm, 2003). In spoken language, there is a strong link between the diversity of vocabulary and the quality of a spoken narrative (Yu, 2010). Similarly, a greater written lexical diversity has been shown to significantly correlate with the quality of compositions produced by typically developing children (Olinghouse & Leaird, 2009). Studies on adults with dyslexia have also shown that diverse vocabulary choices (lexical diversity) are a key marker of the quality of compositions (Connelly et al., 2006). However, in the literature it has been suggested that children with dyslexia avoid writing words they cannot spell (Berninger et al., 2008), implying that these children restrict their vocabulary when writing supposedly due to their spelling difficulties. Few attempts have yet been made to test this anecdotal report. A text with low lexical diversity points toward frequent repetition of the same words. Connelly et al. (2006) used a written composition task from a sentence prompt and found no difference in the number of different words produced by university students with dyslexia and their same-age peers and spelling-ability-matched peers. This study used a count of the number of different words produced as a proxy for lexical diversity. However, this measure has been criticized for being too simplistic and prone to text length influence (McCarthy & Jarvis, 2010). Certainly in the above study, text length varied across groups. There are ways to examine diversity, such as dividing types of words produced (the number of different words) by the tokens (total number of words in a written sample)— referred to as type–token ratio (TTR). Of interest, when even more stringent measures of lexical diversity are employed (e.g., mathematical transformations of TTR to control for text length) a difference is reported between the written performance of university students with and without dyslexia (Wengelin, 2007, used the vocd measure, a program that uses an algebraic transformation model to estimate diversity). Swedish students with dyslexia that composed a written text (typed) scored significantly below their age-matched peers on this lexical diversity measure. Moreover, the typed compositions were analyzed using keystroke logging, which highlighted that students with dyslexia made a high percentage of within-word pauses

while writing and that their number of within-word pauses and revisions to spelling errors together predicted 55% of the variance in written lexical diversity. Of interest, Wengelin (2007) also reported that these students with dyslexia performed at the same level as their peers on the measure of lexical diversity (vocd) when analyzing verbally produced texts. Findings from adult data suggest a link among spelling, pausing, and written vocabulary choice. The gap between spoken and written lexical diversity in adults with dyslexia (Wengelin, 2007) further highlights their difficulty with writing. However, it is possible that the participants in the Wengelin (2007) study had a more limited oral vocabulary to draw on than their peers (no independent measure of vocabulary was taken). Studies have suggested that due to reduced reading exposure children with dyslexia may have a smaller oral vocabulary in comparison to their peers (Gathercole & Baddeley, 1989). Thus, when investigating vocabulary diversity it is important to measure performance on standardized vocabulary tasks as well as comparing written and oral vocabulary. If spelling difficulties constrain written vocabulary in individuals with dyslexia, then there should be a measurable discrepancy between the diversity of vocabulary in oral versus written tasks. Studies to date that have examined dyslexia and written vocabulary use have primarily focused on adults in higher education. University students may not be typical of the broader range of individuals with dyslexia since they are required to frequently read and write and may have developed more practiced ways of coping with their difficulties. On the other hand, little research has focused on the writing produced by children, which is important to acknowledge as soon as possible to provide necessary support as required. For these reasons, this study examined vocabulary, spelling, lexical diversity, and compositional writing in children with and without dyslexia close to 9 years of age and a younger spelling-ability-matched group.

The Present Study The focus of the present study was on the transcription and text generation (lower-level) processes (Berninger & Winn, 2006). The aim of this study was to investigate whether the hesitant and thus poorer spelling ability that is characteristic of children with dyslexia constrains the written vocabulary choices made and affects the quality of writing produced. The writing process was examined using a digital writing tablet to detect pause locations and durations during the composition task. Pause performance was examined in relation to spelling ability. Within-word pausing is thought to reflect transcription demands (Almond, Deane, Quinlan, Wagner, & Sydorenko, 2012). Similar to Wengelin (2007), it was expected that children with dyslexia would pause frequently

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

3

Sumner et al. within words (reflecting a struggle with the spelling of words already chosen for writing) and that this would be correlated with spelling ability more so than oral vocabulary levels, as dyslexia is a written language problem. Guiraud’s R index (see Vermeer, 2000) was the lexical diversity measure used to assess verbal and written compositions. Other measures of diversity (such as vocd) could not be used as they require a minimum of 50 tokens to compute. Many children with dyslexia did not reach this count in the written compositions. R is a mathematical transformation of TTR and corrects for differing text lengths. R divides the number of different words by the square root of the total number of words (types/√tokens), implying vocabulary size is proportional to the square root of text length. Van Hout and Vermeer (2007, p. 114) state that R is a “happy medium” between TTR and stronger transformations of data, such as vocd, which entails selecting only a sample of words from the whole compositions and mathematically modifying the data set, thus making it more complex to interpret. Mellor (2011) reported that R was useful in defining essays of high and low quality. As is noted in the literature, there are many ways to measure lexical diversity, but no single measure provides a perfect result (Siskova, 2012). Therefore, a syllable count of words produced (used in Gregg et al., 2007) in the compositions was also used to verify the Guiraud’s R diversity findings. It was hypothesized that the written compositions of children with dyslexia and the younger spelling-ability group would reflect a lower lexical diversity than the agematched group and diversity would be lower in the written as opposed to the verbal compositions for children with dyslexia (reflecting the cognitive demands of spelling). Similar group patterns were predicted for syllable count. Spelling ability was expected to predict written lexical diversity for children with dyslexia rather than oral vocabulary ability, demonstrating a relationship between spelling and written word choice. It was also predicted that children with dyslexia would perform better in lexical diversity in the verbal compositions, where spelling demands are eliminated. It might be expected that children with dyslexia would perform better in verbal lexical diversity than the younger spelling-ability-matched group due to more language experience over the years. The final hypotheses relate to compositional quality. Verbal compositions produced by children with dyslexia were expected to be of a higher quality than their written work that requires spelling. Greater lexical diversity was expected to relate to a higher quality of the compositions produced (verbal and written; Olinghouse & Leaird, 2009) by both children with dyslexia and typically developing children, highlighting the importance of using varied vocabulary when composing a narrative.

Method Participants A total of 31 children with dyslexia (15 boys, 16 girls), aged between 8 years 3 months and 11 years 1 month (mean age of 9 years 4 months) were recruited from primary schools in Oxfordshire, United Kingdom. These children were recognized by the school special educational needs coordinators (SENCos) as showing significant difficulties with reading and spelling and in the absence of any additional problems with speech and language, hearing, or neurological disorders. Selection measures were administered to confirm a diagnosis of dyslexia. A discrepancy between nonverbal cognitive ability, on the Matrices task, and their performance on a dictated standardized spelling task was confirmed for children with dyslexia (both tasks from British Abilities Scales–II; BAS-II; Elliott, Smith, & McCulloch, 1996). The discrepancy criterion meant that all children scored within the average range on nonverbal cognitive ability (scaled M = 50) but that children with dyslexia scored more than one standard deviation below the age mean on spelling performance. Table 1 shows the scores from the selection measures and additional measures of reading and vocabulary level, comparing children with dyslexia to two typically developing groups: a chronologically age-matched group (CA) and a spelling-ability-matched group (SA). All children had English as their first language. The CA group were recruited by individually matching children in the same school and year group to the children with dyslexia. CA children were initially identified by the class teacher as of a similar age to the already selected children with dyslexia (±3 months) and of the same gender (15 boys, 16 girls). The CA group differed to children with dyslexia, as they demonstrated a level of spelling knowledge that was age appropriate (±1 SD of the age mean dictated spelling task). The SA comparison group were also individually matched to children with dyslexia by gender and school. The BAS-II spelling task (Elliott et al., 1996) was distributed to whole classes (between 5 and 8 years of age), and those children who performed similar to children with dyslexia on the spelling raw score (±1 point) were recruited for further study. All children were previously identified as typically developing by class teachers. Standardized spelling scores were also recorded to ensure the SA group had age-appropriate spelling. A one-way analysis of variance (ANOVA) revealed a significant difference in participant age across the three groups. Tukey post hoc comparisons revealed that children with dyslexia and the CA group were not different in age. These two groups were older than the SA group. Multivariate analysis of variance revealed there was a significant main effect of group across the remaining measures in Table 1, Pillai’s trace V = 1.56, F(18, 146) = 28.82, p < .001, η2 = .78. Univariate ANOVAs (reported in Table 1)

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

4

Journal of Learning Disabilities 

Table 1.  Group Means and Standard Deviations for the Selection and Additional Profile Measures. Measures

D (n = 31)

M (SD) Age (range) 9;4 (8;3–11;1) Nonverbal abilitya   Scaled score 51.00 (3.83) Spelling abilitya   Raw score 8.09 (3.15)   Standard score 79.06 (5.33) Reading abilitya   Raw score 23.13 (11.70)   Standard score 80.87 (10.56) Phoneme segmentationb   Raw score 6.65 (1.47) Receptive vocabularyc   Raw score 88.09 (11.19)   Standard score 92.71 (7.21) Expressive vocabularya   Raw score 9.06 (3.56)   Scaled score 40.68 (8.42)

CA (n = 31) M (SD) 9;4 (8;4–11)

SA (n = 31) M (SD) 6;6 (5;1–8)

ANOVA

Post hoc

F(2, 90) = 111.17, p < .001, η2p = .71

  (D = CA) > SA

51.74 (6.21)

54.46 (4.87)

F(2, 90) = 7.92, p = .001, η2p = .15

(D = CA) < SA

25.16 (8.34) 110.68 (13.04)

9.26 (2.94) 92.84 (6.58)

F(2, 90) = 54.14, p < .001, η2p = .70 F(2, 90) = 64.28, p < .001, η2p = .57

(D = SA) < CA D < SA < CA

49.86 (8.98) 113.75 (11.68)

26.35 (11.68) 98.19 (13.44)

F(2, 90) = 53.42, p < .001, η2p = .55 F(2, 90) = 37.13, p < .001, η2p = .61

(D = SA) < CA D < SA < CA

11.84 (0.63)

9.29 (1.32)

F(2, 90) = 122.76, p < .001, η2p = .73

D < SA < CA

104.06 (18.63) 104.29 (5.10)

71.03 (11.41) 100.68 (8.48)

F(2, 90) = 40.34, p < .001, η2p = .48 F(2, 90) = 21.80, p < .001, η2p = .41

SA < D < CA D < (CA = SA)

15.00 (3.71) 54.94 (11.40)

9.58 (2.98) 49.65 (6.23)

F(2, 90) = 28.42, p < .001, η2p = .39 F(2, 90) = 20.15, p < .001, η2p = .31

(D = SA) < CA D < (CA = SA)

Note. CA = chronologically age matched; D = dyslexic; SA = spelling-ability matched. a British Abilities Scales–II; scaled score M = 50, SD = 10; standard score M = 100, SD = 15. Raw score = total number of words spelled correctly.bDyslexia Screening Test–Junior; raw score out of a possible 12. cBritish Picture Vocabulary Scale–II; standard score M = 100, SD = 15.

and post hoc comparisons confirmed children with dyslexia and the SA group were matched on raw spelling skill (p = .64), whereas the CA group scored significantly higher. The CA and SA groups scored within the expected range on the spelling task (evidenced by the standardized score), although the CA group performed better overall. The difference between the CA and SA standardized spelling scores was not considered problematic, as the primary concern was comparing children with dyslexia to the two control groups. It is noted that the SA group scored significantly higher than children with dyslexia and the CA group on nonverbal cognitive ability. However, this was only a slight difference, and as the SA group were not performing more than 1 SD above the age mean, it was not considered to have implications for compositional performance. Children with dyslexia performed below the CA and SA groups on the standardized spelling score, reading, phoneme, and vocabulary measures. However, the mean vocabulary scores for children with dyslexia did not reach 1 SD below the expected value. It was noted that those children with dyslexia who had the lowest score in the expressive task were not the lowest scorers in the receptive task.

Measures Nonverbal cognitive ability.  Children completed the Matrices task from the BAS-II (Elliott et al., 1996), which required

using their reasoning skills to identify the correct missing part (out of 5 options) of a visual stimulus. A scaled score was derived from the number of correctly identified answers (M = 50, SD = 10). Internal reliability ranges from α = .78 to .90 for the specified age groups in this study Spelling.  A dictated single-word spelling test from the BASII (Elliott et al., 1996) was administered to all children. A raw score was generated from the number of correct spellings made, and converted to a standard score (M = 100, SD = 15); this task shows high internal reliability for the age groups (α = .84 to .93). Reading.  Each child completed the single-word reading task from the BAS-II (Elliott et al., 1996). Raw scores were converted to a standard score (M = 100, SD = 15). Internal reliability for the age groups ranged from α = .88 to .95. Phoneme segmentation.  To assess each child’s ability to recognize and manipulate speech sounds, the phoneme segmentation task was administered from the Dyslexia Screening Test–Junior (DST-J; Fawcett & Nicolson, 2004). Children were asked to delete specific phonemes from a word and to say the end result out loud. Total possible raw score was out of 12 marks. Receptive vocabulary. The British Picture Vocabulary Scale– II (BPVS-II; Dunn, Dunn, Whetton, & Burley, 1997)

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

5

Sumner et al. assessed receptive vocabulary knowledge. Children had to correctly identify the picture that corresponded to the spoken word read by the experimenter. The raw score was converted to a standard score (M = 100, SD = 15). The median split-half reliability coefficient is .86. Expressive vocabulary.  The word definitions task was administered from the BAS-II (Elliott et al., 1996), requiring each child to verbally describe the meaning of a word. Descriptions were later scored using the criteria in the test manual. Raw scores were converted to a scaled score (M = 50, SD = 10). For this age range, internal reliability ranges from α = .83 to .92. Written compositional task. A narrative prompt from the Wechsler Objective Language Dimensions (WOLD; Rust, 1996) was used, asking all children to describe their perfect place to live. The prompt was typed above the writing paper and read to the child before the task began. Children had 15 minutes to complete this task; no help with spellings or ideas were given. When finished, all children reread their compositions to the experimenter so that misspelled words could be identified. Spelling errors were noted before typing compositions and correcting the errors to prevent bias when scoring. Verbal compositional task.  Verbal compositional skills were assessed using the same narrative prompt as the writing task (WOLD; Rust, 1996), following the same instructions, albeit a few weeks later. Responses were audio-recorded and later transcribed.

Procedure This study was fully approved by the university research ethics committee. Children were tested individually, in a quiet room within their school. Selection measures were administered in the first testing session to determine group membership, and participants later completed the general vocabulary measures and composition tasks. The written and verbal compositional tasks were scheduled at least 2 weeks apart, with the writing task first. It may be considered a limitation that the same narrative task was used for both written and verbal compositions, but this was deliberate so that accurate comparisons of performance could be made. The written task was scheduled first due to concerns over attrition and the hope of getting a full sample of written compositions to fully address the relationship between spelling and lexical diversity. To help prevent repetition, a gap of at least 2 weeks between the sessions was scheduled (over the Christmas school holiday). Of importance, it was observed that children reported something new in the second (verbal) compositional task. As these were not taught sessions and children composed

on the spot, without time to plan, we did not expect the verbal compositions to be influenced by previous knowledge of the written task weeks before (procedure similar to Wengelin, 2007). The writing task was completed on lined paper that was placed on the surface of a digital writing tablet (Wacom, Intuos 4), which recorded the XY coordinates of the pen when writing (Eye and Pen software, version 1; 100 Hz).

Data Analysis Pause analysis.  Eye and Pen software detects temporal characteristics of the execution of text, including pauses (inactivity, on and off the paper) when writing. In the present study, the aim was to identify where children made long interruptions to their text making. A pause threshold of 2 seconds was decided on as reflecting a significant pause from writing and is in accordance to studies that postulate longer pauses reflect a high processing demand (Alves, Castro, & de Sousa, 2007; Wengelin, 2007). Using the software, pauses longer than 2 seconds were coded as either within- or between-word pauses (Alamargot, Chesnet, Dansac, & Ros, 2006). Productivity.  Tokens (number of words) and types (number of different words) were recorded as indicators of productivity. Misspellings were corrected in the written compositions and used in this analysis. Spoken words showing the child thinking aloud, such as “um,” “ahh,” and “what’s the word?,” were excluded from the analyses. Lexical diversity. The Guiraud index (R) was calculated, transforming the often-used TTR to reduce the issue of text length influencing diversity scores. Correlations between Guiraud’s R and text length did reveal a significant relationship (r = .34, at p = .02) for the whole sample. However, this is a relatively small correlation, and the syllable count below was used to further identify patterns of performance across groups and modality. Syllable count.  Compositions were analyzed for the number of words used that had 3 or more syllables. This criterion has been used to determine vocabulary level (Gregg et al., 2007), as words with longer syllables are thought to reflect a more advanced vocabulary, needing more consideration of phonology and morphology. There was a nonsignificant correlation between syllable count and text length (r = –.03, p = .43). Compositional quality.  The WOLD analytical assessment criteria (Rust, 1996) were used to score compositions, covering ideas and development, organization/coherence, vocabulary, sentence structure, grammar usage, and capitalization/punctuation. A score of up to 4 was possible for each

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

6

Journal of Learning Disabilities 

Table 2.  Percentage of Pause Locations > 2 s for the Three Groups. Pause location Within-word pauses Between-word pauses

D (n = 31) (%)

CA (n = 31) (%)

SA (n = 31) (%)

20

 4

20

80

96

80

Note. CA = chronologically age matched; D = dyslexic; SA = spellingability matched. Percentage of pauses made at each location is in relation to the total number of pauses.

component (total raw score possible = 24). It was decided that the full WOLD assessment criteria would not be possible to score from verbal compositions (e.g., punctuation), and therefore only the following three components were scored: ideas and development, organization/coherence, and vocabulary. Reliability checks for the analytical scoring were administered on 50% of the written and verbal samples (randomly selected). Interrater reliability ranged from κ = .716 to .864 (p < .001) for the individually scored components. Pearson’s correlation for the overall raw score revealed an agreement of .96.

Results Pause Performance in the Written Composition A frequency count identified the number of pauses of over 2 seconds and the percentage of those pauses that were made either within or between words (shown in Table 2). Children with dyslexia and the SA group paused more (20%, > 2-s pauses) within words than the CA group. The CA group tended to pause more between words, and children with dyslexia again matched the performance of the SA group. Pauses around spelling errors were analyzed. A one-way ANOVA revealed significant group differences for the number of spelling errors made, F(2, 90) = 15.74, p < .001, η2p = .26. Tukey post hoc comparisons demonstrated no significant difference in the number of errors made by children with dyslexia (M = 15.39, SD = 9.01; 24% of total text) and the SA group (M = 12.56, SD = 8.78; 37% of text), but these two groups made significantly more spelling errors than the CA group (M = 4.87, SD = 4.08; 4%). A Kruskal–Wallis test revealed a significant effect of group on the percentage of within-word pauses (>2 s) made during a misspelled word, H(2) = 25.56, p < .001. Follow-up Mann–Whitney tests revealed children with dyslexia made significantly more within-word pauses on spelling errors (34%; SD = 26.87) than the CA (10%; SD = 23.75) and SA groups (22%; SD = 20.31), whereas the SA group made more of these pauses than the CA group. An effect of group was also found for between-word pauses whereby a spelling error was followed

by a pause, H(2) = 20.92, p < .001. Children with dyslexia (13%; SD = 7.98) and the SA group (12%; SD = 10.73) performed similarly, and made significantly more betweenword pauses following a spelling error than the CA group (5%; SD = 6.61). Additional analyses revealed that for children with dyslexia, a significant negative correlation was found between spelling ability and within-word pausing (r = –.61, p < .001), and spelling and between-word pausing (r = –.55, p = .001); the lower the spelling level the more pauses occurred. These correlations were not found to be significant for the CA or the SA group, although in the SA group it was approaching significance (r = –.32). No significant correlations were found for within-word or between-word pause frequency and the general vocabulary tasks, for any of the three groups.

Lexical Performance in the Written and Verbal Compositions Separate 3 × 2 (group × modality) repeated ANOVAs were conducted for tokens, types, and lexical diversity (Table 3, mean scores). For this and all subsequent analyses requiring multiple comparisons, Bonferroni confidence interval adjustments were applied to control for false positives. Tokens.  There was a significant effect of group, F(2, 90) = 20.39, p < .001, η2p = .31, and modality, F(1, 90) = 16.43, p < .001, η2p = .15; more tokens (words) were produced in the verbal compositions. There was also a significant interaction between modality and group, F(2, 90) = 7.69, p = .001, η2p = .15. Children with dyslexia and the SA group produced fewer words when writing in comparison to the verbal task. However, children with dyslexia were not significantly different to the CA group for this verbal measure. Types.  There was a significant effect of group, F(2, 90) = 28.25, p < .001, η2p = .38, modality, F(1, 90) = 8.99, p = .004, η2p = .09, and an interaction between modality and group, F(2, 90) = 12.62, p < .001, η2p = .22. Mean estimates demonstrated a higher number of different types of words in the verbal compositions. When writing, the SA group had a more restricted vocabulary than children with dyslexia, whereas the CA group wrote a higher number of different types. There was a nonsignificant difference between children with dyslexia and the CA group for the types in the verbal compositions. Guiraud index (R).  There was a significant effect of group membership, F(2, 90) = 20.63, p < .001, η2p = .31, but not for modality, F(1, 90) = 2.01, p = .16, η2p = .02. The interaction between modality and group was significant, F(2, 90) = 4.56, p = .01, η2p = .09. Lexical diversity (R) was lowest for

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

7

Sumner et al. Table 3.  Group Means and Standard Deviations for the Lexical Measures. Lexical measures Tokens  Written  Verbal Types  Written  Verbal R  Written  Verbal

D (n = 31)

CA (n = 31)

SA (n = 31)

M (SD)

M (SD)

M (SD)

Post hoc

70.19 (35.79) 144.42 (108.32)

126.52 (48.64) 122.52 (70.27)

35.19 (20.31) 64.35 (50.68)

SA < D < CA SA < (D = CA)

41.79 (18.25) 67.13 (37.63)

72.52 (22.91) 60.65 (28.12)

22.13 (9.64) 36.55 (23.85)

SA < D < CA SA < (D = CA)

4.93 (1.02) 5.57 (1.23)

6.44 (0.96) 5.90 (3.01)

3.75 (0.75) 4.45 (1.29)

SA < D < CA (D = CA) > SA

Note. CA = chronologically age matched; D = dyslexic; R = Guiraud index of diversity (types/√tokens); SA = spelling-ability matched; tokens = number of words; types = number of different words.

Table 4.  Syllable Count (Three or More) From the Written and Verbal Compositions.

Syllables

D

CA

SA

M (SD)

M (SD)

M (SD)

Post hoc

3+ syllables  Writtena 1.93 (1.96) 4.10 (2.86) 0.73 (0.88) SA < D < CA  Verbalb 4.90 (3.76) 3.71 (4.33) 1.81 (2.09) (D = CA) > SA Note. CA = chronologically age matched; D = dyslexic; SA = spellingability matched. a Only 22 children with dyslexia wrote at least one word of 3 or more syllables, whereas 28 CA and 15 SA children did. b 29 children with dyslexia spoke at least one word of 3 or more syllables, 24 in the CA group, and 22 SA children.

children with dyslexia in the written task, in comparison to their performance in the verbal task, although children in the SA group performed worse overall. Children with dyslexia and the SA group showed a reverse pattern, in comparison to the CA group, of having a higher lexical diversity in the verbal rather than the written. The written R results were computed again with receptive (BPVS-II) and expressive vocabulary (word definitions) as covariates (ANCOVA). The covariates were not significantly related to written lexical diversity, F(1, 88) = 3.33, p = .07, η2p = .04, and F(1, 88) = 0.64, p = .38, η2p = .01, respectively. However, the significant effect of group membership remained as reported above, even after controlling for the lower oral vocabulary levels of the children with dyslexia, F(2, 88) = 59.14, p < .001, η2p = .57, and here the difference in lexical diversity in written texts remained in comparison to their same-aged peers. The number of words composed of three syllables or more was also calculated per text (Table 4). Multivariate analysis of variance revealed a significant main effect of group on syllable length, Pillai’s trace V = .39, F(4, 180) = 11.19, p < .001, η2 = .21.

Univariate ANOVAs and Games–Howell post hocs confirmed that children with dyslexia wrote fewer words of longer syllables than their CA peers, F(2, 92) = 22.36, MSE = 95.88, p < .001, η2 = .33. However, on the verbal compositional task children with dyslexia scored at the same level as the CA group on syllable length, with both groups significantly higher than the SA group, F(2, 92) = 4.02, MSE = 75.62, p = .02, η2 = .18.

Predictors of Written Lexical Diversity Table 5 shows bivariate correlations that were computed individually for the three groups to examine the relationship of pause behavior, spelling ability, and oral vocabulary to written lexical diversity (R) performance. A significant negative correlation was found between more frequent within-word and between-word pausing, being related to a lower written lexical diversity for children with dyslexia; yet only the within-word pauses were significantly related to lexical diversity for the SA group. For children with dyslexia, spelling had a significant positive correlation with written lexical diversity, as did the receptive vocabulary measure, whereas expressive vocabulary did not. In contrast, the verbal lexical diversity measure was the only significant correlation with written lexical diversity for the CA group. Hierarchical regression analyses were computed to focus on the predictors of written lexical diversity. For children with dyslexia, spelling ability was entered first due to the initial predictions made, and both within-word and betweenword pause frequency were entered together in the next step as predictor variables for the outcome variable written lexical diversity (R). Addressing the predictive value of oral language skills, receptive vocabulary was entered into the regression. Table 6 illustrates that spelling ability accounted for 41% of the variance in performance for written R by children

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

8

Journal of Learning Disabilities 

Table 5.  Written Guiraud (R) Correlations With Pausing, Spelling, and Oral Vocabulary Measures. Correlation measures

D (n = 31)

CA (n = 31)

Within-word pausing Between-word pausing Spelling abilitya Receptive vocabularyb Expressive vocabularya Verbal R

−.60* −.59* .64* .45* .38 .18

−.11 −.26 .24 .02 .12 .64*

SA (n = 31) −.48* −.22 −.13 .01 .13 .28

Note. CA = chronologically age matched; D = dyslexic; SA = spellingability matched. a British Abilities Scales–II. bBritish Picture Vocabulary Scale–II. *Bonferroni correction p < .01 (two-tailed).

with dyslexia, with within-word and between-word pausing, significantly predicting a further 12% of the variance. Once spelling ability and within- and between-word pause frequency were accounted for, receptive vocabulary was not a significant predictor. Linear regressions were computed for the two control groups. The correlations in Table 5 demonstrated that spelling would not influence written lexical diversity for the control groups. For this reason, lexical diversity (R) on the verbal compositional task was the predictor variable for the CA group, significantly accounting for 41% of the variance in scores for written lexical diversity, R2 = .41, ß = .64, F(1, 29) = 20.26, p < .001. In contrast, within-word pausing was entered as the predictor of written lexical diversity for the SA group, revealing a significant value of 15%, R2 = .15, ß = –.38, F(1, 29) = 4.80, p = .03.

Quality Ratings of the Written and Verbal Compositions The full WOLD analytical scoring (all six criteria) was first applied to the written compositions produced and revealed a significant effect of group, F(2, 90) = 49.09, p < .001, η2p = .53. Post hoc comparisons demonstrated that children with dyslexia (M = 8.61, out of a possible raw score of 24) matched the performance of the younger SA group (M = 7.52), whereas both of these groups scored significantly below the CA group (M = 13.68). A high percentage of spelling errors in relation to text length were recorded in the compositions produced by children with dyslexia (21%) and the SA group (39%), whereas the CA group made significantly fewer errors (4%), F(2, 90) = 57.54, p < .001, η2p = .56. Table 7 illustrates performance on the three WOLD scoring components that could be compared across both modalities: ideas and development, organization/coherence, and vocabulary. Three separate 3 × 2 (group × modality) repeated-measures ANOVAs were conducted.

Ideas and development.  There was a significant main effect of group, F(2, 90) = 12.84, p < .001, η2p = .22, and modality, F(1, 90) = 19.26, p < .001, η2p = .18, with significantly higher scores for the verbal compositions and a significant interaction between modality and group, F(2, 90) = 8.98, p < .001, η2p = .17. Children with dyslexia and the SA group produced more developed ideas in the verbal compositions, whereas the CA controls showed an opposite pattern. A decrease in the CA ideas from written to verbal meant their performance was no different to children with dyslexia in the verbal compositions. Organization/coherence. A significant effect was found for group, F(2, 90) = 9.28, p < .001, η2p = .17, and modality, F(1, 90) = 42.67, p < .001, η2p = .32, with scores higher in the verbal compositions. There was a significant interaction between modality and group F(2, 90) = 5.56, p = .005, η2p = .11. Children with dyslexia were no different to the SA group in the written modality but performed better in verbal compositions. Conversely, children with dyslexia matched the CA group performance for this measure of the verbal compositions. Vocabulary.  A significant effect was found for group, F(2, 90) = 18.03, p < .001, η2p = .29, and modality, F(1, 90) = 12.00, p = .001, η2p = .12: Vocabulary scored higher in the verbal compositions. There was a significant interaction between modality and group membership, F(2, 90) = 7.36, p = .001, η2p = .14. Children with dyslexia and the SA group scored similarly in both conditions, increasing in vocabulary level when composing a text verbally. There was a significant difference between children with dyslexia and the CA group in the written, but not in the verbal compositions.

Lexical Diversity and the Quality of Written and Verbal Compositions R was used to establish the relationship of written lexical diversity to written text quality (WOLD raw score). Significant positive bivariate correlations (p < .05) were found for children with dyslexia (r = .60) and their CA peers (r = .36): The more diverse the vocabulary was in the written compositions, the higher the compositions were graded. However, this relationship was nonsignificant for the younger SA group (r = .29). The same comparisons were conducted for the verbal lexical diversity (R) and the overall raw score of the three marked verbal WOLD categories. Significant correlations (p < .05) for all groups showed verbal R for children with dyslexia (r = .73), CA (r = .74), and SA groups (r = .77) had a positive relationship with performance in the verbal composition task.

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

9

Sumner et al. Table 6.  Regression Equation Predicting Written Lexical Diversity (R) for Children With Dyslexia. Predictor variables a

Spelling ability Within- and between-word pausing Receptive vocabularyb

ß

R2

R2 change

F

df

.64 −.28 .12

.41 .53 .54

.41 .12 .01

20.09 3.53 0.61

1, 29 2, 27 1, 26

p .000** .044* .44

a

British Abilities Scales–II. bBritish Picture Vocabulary Scale–II. *p < .05. **p < .001.

Table 7.  Group Means and Standard Deviations for the WOLD Assessment of the Written and Verbal Compositions. WOLD criteria Ideas and development  Written  Verbal Organization/coherence  Written  Verbal Vocabulary  Written  Verbal

D (n = 31)

CA (n = 31)

SA (n = 31)

M (SD)

M (SD)

M (SD)

Post hoc

1.84 (0.68) 2.55 (0.77)

2.68 (0.79) 2.55 (0.85)

1.54 (0.57) 2.09 (0.74)

(D = SA) < CA (D = CA) > SA

1.38 (0.55) 2.03 (0.71)

1.94 (0.57) 2.06 (0.77)

1.16 (0.37) 1.77 (0.49)

(D = SA) < CA (D = CA) > SA

1.48 (0.63) 2.16 (0.58)

2.48 (0.67) 2.26 (0.63)

1.52 (0.51) 1.97 (0.71)

(D = SA) < CA D = CA = SA

Note. CA = chronologically age matched; D = dyslexic; SA = spelling-ability matched; WOLD = Wechsler Objective Language Dimensions (each section marked out of a possible 4).

Discussion The present study has confirmed that the poorer lexical diversity in written compositions produced by children with dyslexia is related more to spelling ability than vocabulary knowledge, supported by the correlation and regression analyses that have shown spelling ability has a high predictive value on written vocabulary. Moreover, both the objective (lexical diversity, syllable count) and more subjective (WOLD assessment) measures of vocabulary have demonstrated that the vocabulary choices of children with dyslexia when writing are poorer than their age-matched peers. The extra demands that writing and spelling make on children with dyslexia were highlighted by the gap between verbal and written narrative performance and the age-appropriate lexical diversity shown in the verbal transcripts by these same children. These findings confirm the view that, for children with dyslexia, spelling is a costly cognitive process when writing as predicted by models of writing (Berninger & Amtmann, 2003), further noted by the many spelling errors in the texts of children with dyslexia and the poorer overall quality of the written text. This study also provides evidence of how the cognitive demand of spelling is manifested during the writing process. Showing that written lexical diversity, spelling, and frequent pausing are interlinked demonstrates that spelling difficulties

force the writer to pause frequently within words. The relationships among spelling, lexical diversity, and betweenword pausing also provide strong evidence to show that selection of the next word is highly linked to spelling ability, and actually not to oral vocabulary, which failed to significantly correlate with between-word pausing. The robustness of the lexical diversity results were underlined by a similar finding showing words with less syllables were produced by the children with dyslexia when writing but not in the verbal narrative. Thus, the broken, hesitant style of writing of the children with dyslexia is not associated with the fluent style and appropriate vocabulary choices that are required to keep on track with successful text generation. The use of a spelling-ability match group demonstrated that the children with dyslexia were severely delayed in their writing development but that they were not that substantially different in how they write, notably pausing frequently while making text, which related to written lexical performance. A nonsignificant correlation between spelling ability and within-word pausing was noted for the spelling-abilitymatched group. However, this was approaching significance and the size of the correlation was .32, showing that it was in a very similar direction to those with dyslexia. It may not be as strong as the children are typical for their age for spelling and other factors may also be contributing as

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

10

Journal of Learning Disabilities 

per the typically developing group, whereas the defining feature of the children with dyslexia is the constraint of spelling on writing given their superior oral language skills. Thus, one would expect a stronger relationship between spelling and pausing in the dyslexia group anyway. The difficulties that children with dyslexia experienced are further emphasized by the comparison to their agematched peers. This control group was actually found to produce a more diverse range of vocabulary in the written task, rather than in their verbal composition. Typically developing children of the same age as this study have also been shown in another study to have a higher written lexical diversity when comparing written and verbal compositions (Johansson, 2008). A significant relationship between written lexical diversity and text quality makes a stronger case for the importance of vocabulary when writing (Olinghouse & Leaird, 2009). It could be suggested that as the agematched controls do not have difficulties with spelling, working memory resources are free to be devoted to the generation of ideas (including vocabulary). The higher WOLD quality score in writing demonstrates that these children have reached a more proficient level of writing than children with dyslexia. A potential limitation is that although the WOLD scoring criteria are useful to identify aspects of composition, the limited scoring scale (1–4) could lead to the younger spelling-ability group have a higher floor effect than might be expected. A score of 0 is not allowed but may have been suitable for some of the younger group. For this reason, the objective lexical diversity measures of vocabulary contribute to the present findings substantially. While arguing for the importance of vocabulary skill for quality of writing (as shown for children with dyslexia), it was a surprise that the standardized assessments of vocabulary were not significantly correlated with written lexical diversity (R) for the control groups. This could be related to the idea that standardized assessments of vocabulary knowledge may assess something slightly different to how many words (diverse) children can select and use in their compositions. In fact, a significant correlation was found between verbal lexical diversity (R) and written diversity for the agematched group, so perhaps this was a more appropriate measure of vocabulary knowledge for the assessed task. Moreover, significant correlations were found between diversity measures and quality of writing for both the control groups and children with dyslexia, further supporting this idea. According to the simple view of writing (Berninger & Amtmann, 2003) it could be hypothesized that spelling consumes working memory resources for children with dyslexia, and as a consequence text quality suffers due to restricted vocabulary. Correlational analyses in the present study have shown a positive relationship between spelling ability and written lexical diversity. However, vocabulary

selection receives little attention, neither as a resource (language ability) nor as an active writing component in the simple view of writing or other contemporary developmental models of writing. Our findings suggest that the transcription and text generation are closely related and interactive. This interactivity has important consequences for the efficiency of the writing processes and the end product. A hierarchical level of processing can be hypothesized whereby the mental lexicon is addressed during the online production and execution of writing. For children with dyslexia this process is largely determined by spelling capabilities and the long pauses while writing demonstrate this conflict. These pauses could represent a breakdown of the efficient parallel processing of information (reflecting the required interaction between transcription and text generation) to a slower sequential processing when the cognitive demands are too high (Maggio, Lete, Chenu, Jisa, & Fayol, 2012). Until this study, this processoriented approach had not yet been considered in research on dyslexia and writing performance, and this study has demonstrated that the activation of the writing processes is a recursive process. It has been suggested that children with dyslexia could have poorer vocabularies to draw on when writing through having deeper-seated language problems that may interfere with text generation. However, a number of thorough reviews have emphasized that children with dyslexia are distinct from those with wider language problems (Bishop & Snowling, 2004; Catts, Adolf, Hogan, & Weismer, 2005). A more recent article clearly demonstrates that both dyslexia and specific language impairment can occur independently (Ramus et al., 2013). To ensure the present sample did not have broader language difficulties, additional vocabulary measures were administered and, as part of the initial selection criteria, children recognized by the SENCo as having speech or language problems were excluded. Children with dyslexia did score significantly below their peers on the standardized measures of vocabulary, although this is not unusual (Ramus et al., 2013). On average, their performance did not reach more than one standard deviation below the test mean and differences found between groups in the study remained when the vocabulary differences were accounted for statistically. Unlike studies on the writing of children with language impairments, where both spelling and vocabulary contributed significantly to compositional quality (Dockrell, Lindsay, & Connelly, 2009; Dockrell, Lindsay, Connelly, & Mackie, 2007), it was spelling that was the key constraint on writing in this study when examining children with dyslexia. In terms of implications, it might seem that an appropriate method for children with spelling difficulties to compose a text would be through dictation of their work, as this frees the demands of writing. Productivity has been found to be highest when children compose texts through

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

11

Sumner et al. dictation, rather than writing a narrative (Scardamalia & Bereiter, 1987). However, dictation is only a short-term solution and one that is not always practical. Writing is an important skill for education and life thereafter. Children and adults need to learn to be independently proficient in writing. For these reasons, it is suggested that more practical implications of the present findings would be to focus on the spelling difficulties: the root of the problem with expressing written vocabulary. Further research should be targeted toward how specific spelling instruction can improve confidence in spellings and in turn allow these children to use a wider range of words from their vocabulary when writing. A recent meta-analysis of spelling interventions has shown that gains in spelling also generalized to spelling when writing (Graham & Santangelo, 2014), whereas another study demonstrated improved fluency in writing after a spelling intervention (Berninger et al., 2002). To conclude, the present study provides important data for an area that is largely under researched and has previously focused mainly on adults, rather than children. The findings confirm the original predictions that spelling ability can constrain vocabulary choices when writing, and thus constrain text quality. In parallel with the reading literature that shows a relationship between reading and vocabulary development, a similar pattern is shown between the processing of spellings and written vocabulary. These findings contribute to models of writing, which would benefit from noting the relationships between different processes and how an impairment in one area (spelling) can have repercussions for another aspect of development. Acknowledgments Special thanks go to the children and schools that participated in this study.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Waterloo Foundation and Oxford Brookes University, through a PhD studentship that was awarded to Emma Sumner.

References Alamargot, D., Chesnet, D., Dansac, C., & Ros, C. (2006). Eye and Pen: A new device for studying reading during writing. Behaviour Research Methods, 38(2), 287–299. Almond, R., Deane, P., Quinlan, T., Wagner, M., & Sydorenko, T. (2012). A preliminary analysis of keystroke log data from a timed writing task (Research Report Series RR-12-23). Princeton, NJ: Educational Testing Service.

Alves, R. A., Castro, S. L., & de Sousa, L. (2007). Influence of typing skill on pause–execution cycles in written composition. In G. Rijlaarsdam (Series Ed.), M. Torrance, L. van Waes, & D. Galbraith (Eds.), Writing and cognition: Research and applications (Studies in Writing Vol. 20, pp. 55–65). Amsterdam, Netherlands: Elsevier. Berninger, V. W., & Amtmann, D. (2003). Preventing written expression disabilities through early and continuing assessment and intervention for handwriting and/or spelling problems: Research into practise. In H. L. Swanson, S. Graham, & K. R. Harris (Eds.), Handbook of learning disabilities (pp. 345–363). New York, NY: Guilford. Berninger, V. W., Nielsen, K. H., Abbott, R. D., Wijsman, E., & Raskind, W. (2008). Writing problems in developmental dyslexia: Under-recognized and under-treated. Journal of School Psychology, 46, 1–21. Berninger, V. W., Vaughan, K., Abbott, R. D., Begay, K., Coleman, K. B., Curtin, G.,  . . . Graham, S. (2002). Teaching spelling and composition alone and together: Implications for the simple view of writing. Journal of Educational Psychology, 94, 291–304. Berninger, V. W., & Winn, W. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In C. MacArthur, S. Graham, & J. Fitzgerald (Eds.), Handbook of writing research (pp. 96–114). New York, NY: Guilford. Bishop, D. V. M., & Snowling, M. J. (2004). Developmental dyslexia and specific language impairment: Same or different? Psychological Bulletin, 130, 858–886. Catts, H. W., Adolf, S. M., Hogan, T. P., & Weismer, S. E. (2005). Are specific language impairment and dyslexia distinct disorders? Journal of Speech, Language, and Hearing Research, 48, 1378–1396. Connelly, V., Campbell, S., MacLean, M., & Barnes, J. (2006). Contribution of lower order skills to the written composition of older students with and without dyslexia. Developmental Neuropsychology, 29, 175–196. Dockrell, J. E., Lindsay, G., & Connelly, V. (2009). The impact of specific language impairment on adolescents’ written text. Exceptional Children, 75, 427–436. Dockrell, J. E., Lindsay, G., Connelly, V., & Mackie, C. (2007). Constraints in the production of written text in children with specific language impairments. Exceptional Children, 73, 147–164. Dunn, L., Dunn, L., Whetton, C., & Burley, J. (1997). British Picture Vocabulary Scales (2nd ed.). Windsor, UK: NFERNelson. Elliott, C. D., Smith, P., & McCulloch, K. (1996). British Abilities Scales II: Administration and scoring manual. Berkshire, UK: NFER-Nelson. Fawcett, A. J., & Nicolson, R. I. (2004). The Dyslexia Screening Test–Junior: Manual. London, UK: Psychological Corporation. Gathercole, S. E., & Baddeley, A. D. (1989). Evaluation of the role of phonological STM in the development of vocabulary in children: A longitudinal study. Journal of Memory & Language, 28, 200–213. Graham, S., & Santangelo, T. (2014). Does spelling instruction make students better spellers, readers, and writers? A ­meta-analytic

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014

12

Journal of Learning Disabilities 

review. Reading and Writing: An Interdisciplinary Journal, 27, 1703–1743. Gregg, N., Coleman, C., Davis, M., & Chalk, J. C. (2007). Timed essay writing: Implications for high-stakes tests. Journal of Learning Disabilities, 40, 306–318. Johansson, V. (2008). Lexical diversity and density in speech and writing: A developmental perspective. Working Papers, 53, 61–79. Maggio, S., Lete, B., Chenu, F., Jisa, H., & Fayol, M. (2012). Tracking the mind during writing: Immediacy, delayed, and anticipatory effects on pauses and writing rate. Reading and Writing: An Interdisciplinary Journal, 25, 2131–2151. McCarthy, P. M., & Jarvis, S. (2010). MTLD, voc-d, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behaviour Research Methods, 42, 381–392. Mellor, A. (2011). Essay length, lexical diversity and automatic essay scoring. Memoirs of the Osaka Institute of Technology, 55, 1–14. Olinghouse, N. G., & Leaird, J. T. (2009). The relationship between measures of vocabulary and narrative writing quality in second- and fourth-grade students. Reading and Writing: An Interdisciplinary Journal, 22, 545–565. Ramus, F., Marshall, C. R., Rosen, S., & van der Lely, H. K. J. (2013). Phonological deficits in specific language impairment and developmental dyslexia: Towards a multidimensional model. Brain, 136, 630–645. Rust, J. (1996). The Manual of the Wechsler Objective Language Dimensions (WOLD) UK edition. London, UK: Psychological Corporation. Scardamalia, M., & Bereiter, C. (1987). Knowledge telling and knowledge transforming in written composition. In S. Rosenberg (Ed.), Advances in applied psycholinguistics (Vol. 2, pp. 142–175). Cambridge: Cambridge University Press.

Siskova, Z. (2012). Lexical richness in EFL students’ narratives. Language Studies Working Papers, 4, 26–36. Sumner, E., Connelly, V., & Barnett, A. L. (2013). Children with dyslexia are slow writers because they pause more often and not because they are slow at handwriting execution. Reading and Writing: An Interdisciplinary Journal, 26, 991–1008. Sumner, E., Connelly, V., & Barnett, A. L. (2014). Dyslexia and expressive writing in English. In B. Arfe, J. E. Dockrell, & V. W. Berninger (Eds.), Writing development and instruction in children with hearing, speech, and oral language difficulties. Oxford, UK: Oxford University Press. Treiman, R., Clifton, C., Meyer, A. S., & Wurm, L. H. (2003). Language comprehension and production. In A. F. Healy & R. F. Proctor (Eds.), Experimental psychology (Vol. 4, pp. 527–547). New York, NY: John Wiley. Van Galen, G. P. (1991). Handwriting: Issues for a psychomotor theory. Human Movement Science, 10, 165–191. Van Hout, R., & Vermeer, A. (2007). Comparing measures of lexical richness. In J. Daller, J. Milton, & J. Treffers-Daller (Eds.), Modeling and assessing vocabulary knowledge (pp. 93–114). Cambridge, UK: Cambridge University Press. Vermeer, A. (2000). Coming to grips with lexical richness in spontaneous speech data. Language Testing, 17, 65–83. Wengelin, A. (2007). The word-level focus in text production by adults with reading and writing difficulties. In M. W. Torrance, L. Van Waes, & D. Galbraith (Eds.), Writing and cognition: Research and applications (pp. 67–82). Oxford, UK: Elsevier. Yu, G. (2010). Lexical diversity in writing and speaking task performance. Applied Linguistics, 31, 236–259.

Downloaded from ldx.sagepub.com at TEXAS SOUTHERN UNIVERSITY on December 18, 2014