Examples of such languages are Spanish and Italian. ... Spanish and Italian (Seymour, Aro, & Erskine, 2003). ...... acquisition in European orthographies. ...... naar Nienke Bollen, Renate van der Jagt, en Constantijn Bloemendaal voor hun hulp ...
Orthographic knowledge in children with and without reading difficulties
Vanessa Martens
Orthographic knowledge in children with and without reading difficulties Thesis, University of Amsterdam, Amsterdam, The Netherlands Copyright © 2006 Vanessa Martens Cover design by Vanessa Martens Printed by Digital Printing Partners Utrecht
Orthographic knowledge in children with and without reading difficulties
ACADEMISCH PROEFSCHRIFT
ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. mr. P. F. van der Heijden ten overstaan van een door het college voor promoties ingestelde commissie, in het openbaar te verdedigen in de Aula der Universiteit op dinsdag 24 oktober 2006, te 14.00 uur
door Vanessa Eleanor Gwen Martens geboren te Oostburg
Promotiecommissie:
Promotor:
Prof. dr. D. A. V. van der Leij
Co-promotor:
dr. P. F. de Jong
Overige leden:
Prof. dr. V. H. P. van Daal Prof. dr. K. P. van den Bos Prof. dr. W. van den Broeck dr. J. G. van Hell Prof. dr. F. Wijnen
Faculteit der Maatschappij- en Gedragswetenschappen
Voor mijn ouders
Contents 1
General Introduction Learning to read Difficulty in learning to read Outline of this thesis
2
The effect of word length on lexical decision in dyslexic and normal reading children Introduction Method Results Discussion
7 8 12 15 21
Use of lexical knowledge in naming by dyslexic and normal reading children Introduction Method Results Discussion
27 28 33 37 48
The effect of visual word features on the acquisition of orthographic knowledge Introduction Study 1 Method Results Discussion Study 2 Method Results and discussion General discussion
57 58 63 63 66 74 75 75 76 77
Effects of repeated reading in dyslexic and normal reading children Introduction Study 1 Method Results Discussion Study 2 Method Results Discussion General discussion
81 82 86 86 89 96 97 97 98 102 102
3
4
5
1 1 3 4
6
Epilogue Review of main findings Limitations Reading models The acquisition of orthographic knowledge Specific deficits in dyslexia Conclusion
107 107 111 112 117 120 121
General references
123
Appendices A: Word frequencies and bigram frequencies of the words and pseudowords used in the studies reported in Chapters 2 and 3 B: Pseudowords used in the study reported in Chapter 4 C: Word frequencies and bigram frequencies of the words and pseudowords used in the studies reported in Chapter 5
133 133 135
Samenvatting (Summary in Dutch)
137
Dankwoord (Acknowledgements)
145
Curriculum Vitae
147
136
General introduction
Chapter 1 General introduction
Most people take the ease with which they can read for granted. After all, we do it every day: skimming the newspaper, reading our mail, and so on. We generally take in information at a fast rate, simply ‘seeing’ what it says at a glance, sometimes even without paying conscious attention. ‘Seeing what it says at a glance’ seems simple, but it is actually the result of the intricate interplay of several skills. What happens exactly from the moment a skilled reader perceives a letter pattern to the articulation of the speech sounds represented by the pattern has been described in a number of computational models (e.g., Ans, Carbonnel, & Valdois, 1998; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; Plaut, McClelland, Seidenberg, & Patterson, 1996; Seidenberg & McClelland, 1989). The focus of the present thesis, however, is not on the fully developed skilled word recognition in adults, but on the development of word recognition in children, who are learning to read with varying degrees of success. Learning to read Although skilled word recognition has received far more attention from researchers trying to capture skilled reading in (computational) models, some models have been put forward to describe the development of reading skill (e.g., Ehri, 1992, 1998; Frith, 1985; Marsh, Friedman, Welch, & Desberg, 1981). These models describe how reading skill evolves by postulating a number of different developmental stages. To start with, learning to read entails learning to associate letters (graphemes) with their corresponding sounds (phonemes). This requires children to be aware that the letters or graphemes in a word are connected to different speech sounds, and to grasp that a change in one of the letters can involve a change in meaning (e.g., dog-fog, fog-fig, fig-fit). The awareness that a spoken word can be subdivided into smaller parts, such as syllables and phonemes, is called ‘phonological awareness’ (Byrne, 1998; Liberman, Shankweiler, Fischer, & Carter, 1974; Perfetti, 1985). In the initial stages of learning to read, every grapheme is recoded into its corresponding phoneme and subsequently these sounds are blended together to form a word’s pronunciation. This process of recoding print into sounds 1
Chapter 1 letter-by-letter is slow and laborious, requiring conscious attention. With reading experience, children acquire implicit knowledge of the statistical regularities in their orthography; some letter and sound combinations co-occur often, whereas others are encountered less frequently. This is called orthographic knowledge (Share, 1995). Orthographic knowledge accelerates the word recognition process by extending the associations between single graphemes and phonemes to associations capturing units larger than single letters. Put differently, word recognition develops from being based on associations between single graphemes and phonemes to associations between grapheme and phoneme combinations (Bowey & Hansen, 1994; Ehri, 1998). Eventually, connections between printed words and their pronunciations are established (e.g., Ehri, 1992; Share, 1995; Stanovich, 1993). There is no general definition of orthographic knowledge. Orthographic knowledge has been taken to apply to both a sublexical and a lexical level. At a sublexical level, it includes general knowledge on what letter combinations are permitted in a given language, which ones occur frequently (Perfetti, 1985), and knowledge of syntactic or morphological constraints on letter combinations (e.g., ing, -able) (Assink & Kattenberg, 1995). At a lexical level, orthographic knowledge includes knowledge of specific word spellings (Ehri, 1980) and direct connections from print to meaning that bypass phonological recoding processes (Stanovich, 1993). Whether sublexical orthographic knowledge is acquired before, after, or simultaneously with lexical orthographic knowledge is not a foregone conclusion (e.g., Share, 1995). In the present thesis, the focus is sometimes on orthographic knowledge at a sublexical level, and sometimes on orthographic knowledge at a lexical level. The initial recoding of graphemes into phonemes appears to be a prerequisite in learning to read across (alphabetic) languages (Ehri, 1998). However, the ease with which graphemes are recoded into phonemes varies across different languages, and is partly dependent upon the ‘transparency’ or ‘depth’ of the orthography. In ‘transparent’ or ‘shallow’ orthographies, there is a consistent relation between letters (graphemes) and the sounds they represent (phonemes). Examples of such languages are Spanish and Italian. Other languages, such as English, have less consistent grapheme-to-phoneme correspondences. In these orthographies, the same letter (combination) can represent different sounds. For example, compare the six different pronunciations of the letter combination ‘ough’ in the following English words: tough, though, through, thorough, plough, and lough. It shows that the mapping of graphemes to phonemes can be irregular. In addition, the mapping of phonemes to graphemes can be inconsistent as well: Many 2
General introduction different combinations of letters can represent the very same sound (e.g., to, too, two, flu, flew, blue, queue, pooh, shoe, through, you). Thus, the extent to which the correspondences between letters and sounds are regular and consistent (i.e., orthographic depth) adds to the complexity of acquiring reading skill. Most languages, including Dutch and German, have orthographies that are ‘intermediate’ in orthographic depth, being more consistent than English and less consistent than Spanish and Italian (Seymour, Aro, & Erskine, 2003). Difficulty in learning to read Taking the complexity of reading skill into account, it is surprising that most children learn to read fluently within a few years. However, some 10 % of children do experience difficulties in learning to read. Approximately 4 % of the children have severe trouble in learning to recognize written words accurately and quickly. These children are diagnosed as ‘dyslexic’ (Blomert, 2005; van der Leij, Struiksma, Ruijssenaars, Verhoeven, Kleijnen, Henneman, Pasman, Ekkebus, van den Bos & Paternotte, 2004). Dyslexia often stems from a deficiency in phonological processing (Vellutino, Fletcher, Snowling, & Scanlon, 2004), resulting in slow and inaccurate reading. In transparent orthographies, the highly regular correspondences between graphemes and phonemes can help dyslexics to overcome phonological problems (Ziegler & Goswami, 2005). By relying on the laborious sublexical reading procedure, that is, recoding graphemes into phonemes in a serial way, even dyslexics can reach high accuracy levels. As a consequence, the main characteristic of dyslexia in transparent orthographies is a pervasive slowness of reading (de Jong & van der Leij, 2003; Wimmer, 1993; Zoccolotti, de Luca, di Pace, Judica, Orlandi, & Spinelli, 1999). The chronic slowness of reading in dyslexics has been associated with their persistent reliance on a sublexical reading procedure. Normally developing readers show a gradual shift from a predominant reliance on a sublexical reading procedure (i.e., grapheme-to-phoneme recoding) to a progressively larger contribution of a lexical reading procedure (i.e., relying on connections between larger letter combinations, up to whole words), and thereby speed up their reading. In contrast, dyslexics appear to continue to recode graphemes into phonemes in a serial way. In other words, whereas word recognition becomes increasingly ‘lexicalized’ in normally developing readers, dyslexics stick to a sublexical reading procedure (Share, 1995; Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005). This suggests that dyslexics fail in using or acquiring orthographic knowledge. The 3
Chapter 1 focus of the present thesis was on differences in the use and acquisition of orthographic knowledge in dyslexic children and children without reading difficulties. Outline of this thesis The use and acquisition of orthographic knowledge was examined in four studies. To assess orthographic knowledge, one or both of the following two methods were employed. One method was to compare the effect of word length on reading speed and accuracy in dyslexic and normal reading children. If a word is processed by successively recoding its graphemes into phonemes, each additional grapheme will take extra time. Thus, predominant reliance on a sublexical reading strategy is indexed by slower reading speed with increasing word length. In contrast, if a lexical reading procedure is employed, all letters/graphemes in a word are processed in parallel. In this case, long words are read as fast as short ones. The reliance on sublexical and lexical reading procedures is not assumed to be an all-ornone question, but should rather be thought of as relative contributions of both reading procedures. Thus, the larger the effect of length on reading speed, the more a reader relies on a sublexical recoding reading procedure (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; Weekes, 1997). The effect of length has been shown to decrease with reading experience in normal reading children from the end of first grade onwards, suggesting a progressively larger role of a lexical reading procedure (Zoccolotti, et al., 2005). The second method to assess orthographic knowledge was to disrupt visual word features by presenting (pseudo)words in alternated case (eXaMpLe). Case alternation slows down reading, which has been suggested to be due to the disruption of visual multiletter features (Besner & Johnston, 1989; Mayall, Humphreys, & Olson, 1997). Multiletter features capture visual characteristics of letter combinations, comprising features of units larger than single letters and smaller than whole words. These features include, for example, the shape of the spaces between the letters, and relative size and shape of the letters themselves (e.g., ascenders and descenders). By disrupting these features, a more serial reading procedure is induced (as shown in Chapter 3). In adults, case alternation affects words less than pseudowords (Besner & Johnston, 1989; Mayall & Humphreys, 1996). This has been hypothesized to be due to the availability of lexical orthographic knowledge (Mayall & Humphreys, 1996). The degree to which case alternation affects word- and pseudoword-reading speed in children with and 4
General introduction without reading difficulties was as yet unknown, and was investigated in the present thesis. In Chapter 2, the extent to which dyslexic and normal reading children rely on lexical and sublexical reading strategies in a lexical decision task was examined. This task requires a fast and accurate decision on whether a visually presented string of letters constitutes an existing word or not. As this task does not involve pronouncing the words and pseudowords out loud, the demand on phonological processing – which is often problematic in dyslexics – was assumed to be smaller than in a naming task, in which (pseudo)words do have to be read aloud. To investigate the relative reliance on sublexical and lexical reading strategies, the length of the words and pseudowords was varied from 3 to 6 letters. If readers predominantly rely on a sublexical reading strategy, reading speed will decrease with increasing word length. The performances of dyslexic children, age peers without reading problems (i.e., chronological age controls, CA), and younger children with the same reading level as the dyslexics (i.e., reading age controls, RA) were compared. In the study reported in Chapter 3, the findings of the lexical decision task described in Chapter 2 were extended to the children’s performance in a naming task. Instead of making a lexical decision, the children had to read the words and pseudowords aloud as fast and as accurately as possible. In this study, differences in the availability of lexical orthographic knowledge were examined in dyslexic and normal reading children by comparing the effect of length on reading aloud. In addition to the effects of length, the effects of case alternation in the naming task were examined. Chapter 4 concerns two studies in which the effect of visual word features on the acquisition of orthographic knowledge was examined in normal beginning and advanced readers. The main hypothesis was that repeated presentation in a visually disrupted format (i.e., in alternated case) would attenuate the acquisition of orthographic knowledge compared to repeated reading in normal lowercase format. In the first study, the children repeatedly read a number of pseudowords in either lowercase or alternated case. During the training, pseudowords were presented repeatedly. In the subsequent posttest, the pseudowords were presented in either the same case format as they had been trained in, or in the other case format (i.e., lowercase or alternated case). In addition to the trained pseudowords, a set of untrained pseudowords was presented in the posttest. The effects of reading frequency, case during the training, and case in the posttest on reading speed and accuracy were examined. Although case alternation was shown to slow down word5
Chapter 1 and pseudoword-reading in Chapter 3 and the first study of Chapter 4, these studies did not clarify whether the effect of case alternation was due to a disruption of single letter features or to a disruption of multiletter features. To investigate this, a second study was conducted in which single letter reading in lowercase, uppercase, and alternated case was compared. In Chapter 5, the acquisition of orthographic knowledge in dyslexic children and in normal reading children was investigated in two studies. The acquisition of orthographic knowledge was assessed by changes in the effect of word length on reading speed and accuracy after repeated reading. The assumption was that repeated reading should result in the acquisition of word-specific (lexical) orthographic knowledge (e.g., Share, 1995; Reitsma, 1983b), evidenced by a decrease in the effect of word length on reading speed. In addition, we investigated whether visual word features affected the acquisition of orthographic knowledge in dyslexic children. In the first study, two groups of dyslexics read the same words and pseudowords 15 times. One dyslexic group read in lowercase; the other group read the same words and pseudowords in alternated case. Words and pseudowords varied in length from 4 to 6 letters. To examine how normally developing readers would respond to this training involving the repeated reading of a small set of words and pseudowords, a second study was conducted in which beginning and advanced readers without reading difficulties read the same words and pseudowords 15 times in lowercase. The main findings of the studies reported in this thesis are discussed in Chapter 6. The results of the various studies are connected, consistencies and inconsistencies in the results are reviewed, and alternative explanations are discussed. In addition, limitations of the studies are considered.
6
Word length effect on lexical decision
Chapter 2 The effect of word length on lexical decision in dyslexic and normal reading children1
In the present study, the effect of word length on lexical decision in dyslexic and normal reading children was investigated. Dyslexics of 10 years old, chronological age controls, and reading age controls read words and pseudowords consisting of 3 to 6 letters in a lexical decision task. Length effects were much stronger in dyslexics and reading age controls than in chronological age controls. These results support the contention that dyslexics continue to rely on a predominantly sublexical reading procedure, whereas for normal readers the contribution of a lexical reading procedure increases. The relevance of the findings for current computational models of reading is discussed.
1
Martens, V. E. G., & de Jong, P. F. (2006b). The effect of word length on lexical decision in dyslexic and normal reading children. Brain and Language, 98, 140-149. 7
Chapter 2 Introduction A common finding in reading research is that, in skilled readers, length does not affect the reading speed for high frequent words, whereas longer pseudowords do take more time to recognize than short pseudowords (e.g., Juphard, Carbonnel, & Valdois, 2004; Weekes, 1997). Recent research has shown, however, that in young readers the effect of length applies to both words and pseudowords, and that the influence of length on reading speed is even more pronounced in dyslexics (e.g., de Luca, Borrelli, Judica, Spinelli, & Zoccolotti, 2002; Spinelli, de Luca, di Filippo, Mancini, Martelli, & Zoccolotti, 2005; van der Leij & van Daal, 1999; Ziegler, Perry, Ma-Wyatt, Ladner, & Schulte-Körne, 2003; Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005). Dyslexia refers to a deficient reading development, which often stems from problems in phonological processing (Vellutino, Fletcher, Snowling, & Scanlon, 2004). Due to phonological problems, a lot of errors are made in reading, and reading remains slow. However, in transparent orthographies, the highly regular grapheme-to-phoneme correspondences can help dyslexics to overcome phonological problems (Ziegler & Goswami, 2005). As a consequence, even dyslexic children can read accurately, by relying on a sublexical reading strategy in which letters are successively phonologically recoded. Therefore, in transparent orthographies, dyslexia is mainly characterized by laborious and slow reading (de Jong & van der Leij, 2003; Wimmer, 1993; Zoccolotti, de Luca, di Pace, Judica, Orlandi, & Spinelli, 1999). The influence of length on reading speed is often taken to suggest that word recognition is, at least partly, based on a sublexical reading strategy. The differential effect of length on words and pseudowords in skilled readers, young readers, and dyslexics further suggests that the nature of word recognition might change with the development of reading ability. In a word naming study, Zoccolotti et al. (2005) observed that the effect of word length on vocal response times decreased dramatically from first grade to third grade in normal reading children, whereas in third grade dyslexics, the effect of word length was comparable to that of normal reading first graders. Zoccolotti et al. inferred that dyslexics ‘appear to fail in the transition from a sub-lexical to a lexical procedure’ (p. 372). Until now, most of the studies investigating the effect of length in children have involved silent reading tasks in which eye-movements were registered (Hutzler & Wimmer, 2004; de Luca et al., 2002) or naming tasks (Spinelli et al., 2005; Ziegler et al., 2003; Zoccolotti et al., 2005). However, as words have to be read aloud in naming tasks, phonological processes may be assumed to contribute 8
Word length effect on lexical decision considerably to performance (e.g., Sprenger-Charolles, Siegel, Béchennec, & Serniclaes, 2003). Since phonological processing has often been shown to be problematic in dyslexics (see Vellutino, et al., 2004), we aimed to investigate the effect of length in a reading task in which the contribution of phonology is less important: lexical decision. In this task, which requires a judgment on whether a string of letters constitutes a word or not, the focus is much more on orthography. As a lexical decision task specifically requires lexical knowledge, it may provide additional information about the nature of word recognition in dyslexic children. Given that lexical knowledge is crucial to perform a lexical decision task, but not (or less) for a naming task, this ‘extra’ lexical involvement might result in a processing strategy that relies to a larger extent on a lexical reading procedure. There are at least two reading models that postulate an influence of length on word and pseudoword recognition: the Dual Route Cascaded model by Coltheart, Rastle, Perry, Langdon, and Ziegler, (2001) and the connectionist network proposed by Ans, Carbonnel, and Valdois, (1998). In some other connectionist models developed by Seidenberg and colleagues (e.g., Harm & Seidenberg, 1999; Plaut, McClelland, Seidenberg, & Patterson, 1996; Seidenberg & McClelland, 1989), the effect of word length is not explicitly modeled in word recognition, but is argued to be a consequence of neighbourhood effects. In the Dual Route Cascaded model (DRC, Coltheart, et al., 2001), two reading routes are distinguished: the nonlexical route and the lexical route, which are activated at the same time. In the nonlexical route, the graphemes of a word are decoded into phonemes one-by-one, in a serial way. In the lexical route, all letters of a word are activated in parallel, and these letters activate a word’s entry in the orthographic lexicon. This word entry activates the corresponding word entry in the phonological lexicon, which activates the word’s phonemes (in parallel). From a developmental perspective, novel words will first be read through the nonlexical route. With the development of reading skill, an increasing number of words become represented in the orthographic lexicon, and then for these words the lexical route can be used (Jackson & Coltheart, 2001). The number of words readers can access directly in their orthographic lexicon depends on their reading skill, and consequently, so does the extent to which readers rely on the lexical or the nonlexical route. For reading aloud, the DRC model predicts a smaller length effect on words than on pseudowords. When a word’s pronunciation is accessed via the lexical route, there should be no difference in reading speed for words of different lengths, all letters being processed in parallel. In contrast, when words are read via the
9
Chapter 2 nonlexical route, reading speed decreases with each additional letter. The larger the length effect, the more readers rely on sublexical decoding strategies. For lexical decision, the predictions of the DRC model are different. The model makes lexical decisions on the basis of the contents of the orthographic lexicon, and is thus based on the lexical route only. The lexicon is searched in a serial way, in order of word frequency. As a consequence, a decision (‘yes’) on high frequent words will be reached faster than on low frequent ones. If the search on the lexicon is completed and no lexical match has been found, the model will produce ‘no’ for a decision. As a result, lexical decisions on words will be faster than lexical decisions on pseudowords. The model makes no explicit predictions for word length. Therefore, provided that word frequency is matched across words of different lengths, lexical decisions on long words may be expected to be as fast as on short ones. The predictions of the DRC model with regard to lexical decision, however, bear upon normal adult readers. The model does not specify whether they also apply to children, or whether word length would affect lexical decision in children in a different way than in adults. If children base their lexical decisions solely on the contents of their orthographic lexicons, as outlined by the model, they will only make correct decisions on words they can read using a lexical reading strategy. However, words that are not yet in their orthographic lexicon would be erroneously rejected, possibly leading to high error rates. Even if these words could have been read correctly by a sublexical reading strategy, this would be of no avail, if lexical decision is exclusively based on a lexical reading strategy. As yet, however, it is unclear whether children exclusively rely on a lexical reading strategy in a lexical decision task, like adults do. Another model that can account for the length effect on reading speed for words and pseudowords is provided by Ans, Carbonnel, and Valdois (1998). This model (for short, ACV98) is a connectionist network in which orthography is mapped to phonology by two reading procedures that work successively. First, a global procedure using knowledge about whole words is applied. In this procedure, the so-called ‘focal window’ or ‘visual attentional window’ spans all letters (or syllables) in a word at a time. Within this window, all letters are processed in parallel. If a word is not recognized by this global procedure, however, it will subsequently be processed by the analytic procedure. The analytic procedure is based on the activation of word syllabic segments or smaller segments. Processing is applied to the largest initial segment of the printed letter string that is recognized as familiar, and will proceed to the next familiar spelling pattern(s), up to the end of 10
Word length effect on lexical decision the string. Most often, familiar words are read by the global procedure, whereas unfamiliar words and pseudowords are read by the analytic procedure. For words that are read aloud by the global procedure, no length effect is predicted, as all letters are processed in parallel. In contrast, in the analytic procedure, units are processed sequentially, resulting in slower reading speed for longer words. Lexical decision is exclusively performed by the global procedure in normal readers. Therefore, no effect of word length is expected in lexical decision in normal readers. For dyslexic readers, however, the model’s predictions are different (Juphard, et al., 2004). Developmental dyslexia is assumed to be a consequence of either a problem in the analytic procedure, or a problem in the global procedure (Valdois, Bosse, Ans, Carbonnel, Zorman, David, & Pellat, 2003). In regular orthographies, phonological decoding does not appear to be the major problem in dyslexia, but rather the development of direct print-to-sound connections. Thus, in these orthographies, the problem is seldom located in the analytic procedure, but is much more likely to be situated in the global procedure. Juphard et al. (2004) argued, that ‘when the size of the visual attentional window is reduced, then reading and lexical decision are based on analytic processing whatever the lexicality of the item to be read.’ (p.333). They therefore expected a strong effect of word length in their dyslexic participant, both in reading aloud and lexical decision, which was indeed found. As in other studies (e.g., de Groot, Borgwaldt, Bos, & van den Eijnden, 2002), they did not find a length effect in a group of normal reading adults, which is in accordance with both the DRC model and the ACV98 model. To date, most studies on lexical decision in dyslexics have involved adults (e.g., Milne, Nicholson, & Corballis, 2003; Milne, Hamm, Kirk, & Corballis, 2003) with acquired dyslexia (Arduino, Burani, & Vallar, 2003; Làdavas, Umilta, & Mapelli, 1997). The current study was concerned with the effects of length on the lexical decision performance of Dutch children with developmental dyslexia. The performance of these 10-year-old children was compared to the performance of a group of normal readers of the same age and to the performance of a group of younger normal readers, approximately 8 years of age, with the same level of reading ability. The lexical decision task consisted of words and pseudowords of 3 to 6 letters. Consistent with the results of previous studies on word naming (e.g., de Luca, et al., 2002; Spinelli, et al., 2005; Zoccolotti, et al., 2005) and the performance of the adult dyslexic described by Juphard et al. (2004), we expected that the length effect in lexical decision would be stronger for dyslexic than for normal reading children of the same age. 11
Chapter 2 Method Participants Sixty-six children took part in the study. These children came from 12 regular primary schools in the west and middle part of the Netherlands. Twenty-two children (13 boys, 9 girls) in Grade 4 had a reading lag of at least 15 months (mean 18.8; range 15-28). This group will be called the Dyslexic group (DYS). The Chronological Age control group (CA) consisted of 22 normal readers (15 boys, 7 girls) in Grade 4. These children were individually matched in age, gender, vocabulary and nonverbal reasoning ability to the children with reading problems. The third group, a Reading Age control group (RA), consisted of 22 normal readers (13 boys, 9 girls) in Grade 2, individually matched in reading level and gender to the dyslexic children. Mean ages for each of the three reading groups are presented in Table 1. None of the children had neurological disabilities or problems in hearing, vision, or attention. Permission for all children was obtained from the parents and the school. Screening. The 66 children were selected from 546 children on the basis of their performance on three screening tasks, which had been administered a few weeks prior to the lexical decision task. Word reading ability was assessed with the One Minute Reading Test (‘Een Minuut Test’, Brus & Voeten, 1979), which was administered individually. This test consisted of a list of 116 unrelated words, of increasing length and difficulty. The children were required to read aloud as many words as possible without making errors within one minute. The score was the number of words that were read correctly. On the basis of this raw score, a standardized score was computed, ranging from 1 to 19, with a mean of 10 and a standard deviation of 3. All children in the DYS group scored at or below the 20th percentile. Children were also given a vocabulary test. A standardized sub-test of the Amsterdam Child Intelligence Test Battery (Revisie Amsterdamse Kinder Intelligentie Test, Bleichrodt, Drenth, Zaal, and Resing, 1987) was used. During this test, the test assistant read 60 words of increasing difficulty aloud (one at a time), upon which the children had to choose the matching picture out of four alternatives. To assess nonverbal reasoning, the RAVEN Standard Progressive Matrices (Raven, Court, & Raven, 1986) was administered. Each item consisted of three rows of three geometric patterns each. On each row, the patterns changed from left to right according to some common logic. The third picture on the third row was missing, and children were required to complete this row by choosing the correct alternative. The DYS and CA groups completed all 60 items, whereas the RA group 12
Word length effect on lexical decision completed the first 36 items only, as these items cover their expected nonverbal reasoning abilities. The mean scores on each of the screening measures for each of the selected three groups are presented in Table 1. Table 1 Mean scores on each of the screening measures for the Dyslexic group (DYS), Chronological Age control group (CA), and Reading Age control group (RA) Age
(months)
DYS
CA
RA
124.27 (5.33)
124.27
(4.25)
96.55
(3.97)
Word reading ability Raw score
46.86 (6.51)
74.68
(5.38)
46.86
(6.37)
Vocabulary
Raw score
47.73 (4.63)
48.14
(4.28)
42.55
(2.70)
Non-verbal reasoning Raw score
43.00 (6.01)
42.82
(6.22)
29.14
(2.44)
23.23 (4.26)
51.09
(6.52)
23.18
(4.10)
Reading age
Note. a
a
Between parentheses are the standard deviations.
Reading age reflects the reading level in months. Within one school year, children receive
10 months of reading education, so a reading age of 15 months reflects the expected reading level halfway Grade 2.
Materials The stimulus set consisted of 80 words and 80 pseudowords. The length of the items varied from three to six letters, creating four different length categories. For each length, 20 words and 20 pseudowords were selected. The mean frequencies and mean bigram frequencies of the words for each of the length categories are displayed in Table 2. Words of different lengths did not differ significantly in frequency and bigram frequency. Pseudowords were constructed by changing one or two adjacent letters at either the beginning or the end of the words. Letters that were replaced within a given word were interchanged with the letters of another word. For example, exchanging the final letters in the words ‘straat’, ‘schrik’, and ‘schoon’ [resp. ‘street’, ‘fright’, ‘clean’] resulted in the pseudowords ‘straan’, ‘schrit’, and ‘schook’. As a consequence, the mean bigram frequency of the pseudowords was did not differ significantly from the mean bigram frequency of the words. In addition, the CV structure of the words and pseudowords were similar. Pseudowords of different lengths were also comparable in bigram frequency (see Table 2). (See Appendix A for a complete list of the words and pseudowords.)
13
Chapter 2 Table 2 Mean word frequencies and mean bigram frequencies for words and pseudowords consisting of 3, 4, 5, and 6 letters Length
Words
Word frequency Bigram frequency
Pseudowords
Note.
Bigram frequency
3
4
5
6
195.78
192.81
194.54
198.00
(187.61)
(211.13)
(183.24)
(227.30)
335.63
336.30
331.51
264.14
(517.19)
(351.98)
(128.25)
(92.78)
278.15
317.70
325.08
253.76
(305.15)
(344.59)
(129.51)
(87.67)
Between parentheses are the standard deviations. Mean word frequency is reported
per million (adapted from Staphorsius, Krom, & de Geus, 1988). Mean bigram frequency is reported per 20,000 words (Bakker, 1990).
The stimulus set of 80 words and 80 pseudowords was divided into two comparable subsets of 40 words and 40 pseudowords each. We used two comparable subsets to decrease the chance that results would be obtained that were inherent to a particular stimulus set. This way, we aimed to increase the generalizability of the results. The two subsets did not differ significantly in word frequency and bigram frequency across different word lengths. Each child read one of the subsets, consisting of 40 words and 40 pseudowords. The assignment of the subsets to the children was randomized, such that half of the children in each reading group were presented with one subset, and the other half of the children were presented with the other subset. Apparatus and task procedure The items appeared one by one in the middle of a 14” screen of an Apple Macintosh LC 475 computer. The items were presented in 48-point Amsterdam font, in black letters on a white background. Response times were registered by a voice key. The test assistant marked the accuracy of each response (right, wrong, or invalid if the voice key had not been set off properly or had been triggered by another sound). Children were not given feedback on the accuracy of their response. All trials started with a short beep to focus the participant’s attention. The stimulus appeared 750 ms after the beep and remained on the screen until the voice key was triggered. The test assistant made the next word appear on the screen using the keyboard. One second later, a beep announced the next trial. 14
Word length effect on lexical decision Each child was presented with 40 words and 40 pseudowords, which were presented in two blocks of 20 words and 20 pseudowords each. Within these two blocks, the order of presentation of words and pseudowords was randomized. If a given word was presented in the first block, the pseudoword that was derived from it was presented in the second block, and vice versa. Thus, pseudowords were never presented within the same block as the words they had been derived from. All items were presented once. The task started with eight practice trials. The practice trials familiarized the children with the task, and gave the experimenter the opportunity to adjust the sensitivity level of the voice key, if necessary. Children were instructed to say ‘yes’ if they read a real word, and to say ‘no’ if they read a nonsense word, as quickly as possible, with making as few errors as possible. A verbal lexical decision task has been applied in a few previous studies (Wile & Borowski, 2004; Crosbie, Howard, & Dodd, 2004). We opted for a verbal response because we assumed that this would be easier for the (young) children than to remember which button to push. It seems unlikely that this overt verbal response interferes with the phonological skills in the different reading groups, as the required response was very simple (namely, ‘ja’ or ‘nee’ (yes or no, respectively). The reading groups may be assumed not to differ on the speed with which they can say ‘yes’ or ‘no’. Given the very limited number of words and pseudowords starting with a /j/ or /n/ (no words started with a /j/ and 2 pseudowords started with an /n/), the initial letters of the (pseudo)words are also unlikely to have interfered with the required verbal responses. Children were urged to avoid saying “uh”, as this would set off the voice key, immediately making the word disappear from the screen. General procedure The study consisted of a battery of screening tests and a lexical decision task. First, during screening, a vocabulary test and a nonverbal reasoning test were administered per group. These tests took about 45 minutes each. Next, a word reading ability test was administered individually, taking about 3 minutes per child. A few weeks later, children performed the lexical decision task. For the lexical decision task, children were individually tested in a (separate) room in school where testing could take place relatively quietly, taking about 10 minutes. Results The results are organized in two sections. First, we report the results on accuracy; second, we present the results concerning the response times.
15
Chapter 2 Accuracy The mean error percentages for words and pseudowords of different lengths for the three Reading Groups are displayed in Table 3. In general, the error percentages were very low, ranging from about 1 – 4.5 % for words, and from about 2.5 – 9 % for pseudowords. A MANOVA for repeated measures with Lexicality (words or pseudowords) and Length (3, 4, 5, or 6 letters) as within subjects factors and Reading Group (DYS, CA, or RA) as a between subjects factor was performed. There was a significant difference in the accuracy of the three reading groups, F (2, 63) = 3.51, p < 0.05, η2p = 0.10. We specified two contrasts, which showed that the DYS group made significantly more errors than the CA group, F (1, 63) = 7.03, p < 0.01, η2p = 0.10, whereas there was no difference in accuracy for the DYS group and the RA group, F (1, 63) = 1.76, p > 0.15. The significant main effect of Lexicality, F (1, 63) = 20.65, p < 0.001, η2p = 0.25, was qualified by an interaction of Lexicality and Reading Group, F (2, 63) = 3.83, p < 0.05, η2p = 0.11. In general, words were responded to more accurately than pseudowords. This difference in accuracy for words and pseudowords was larger for the DYS group than for the CA group and the RA group. Length did not affect accuracy, F (3, 189) = 1.77, p > 0.15. There was no interaction of Length and Reading Group either, F (6, 189) = 1.58, p > 0.15, indicating that (pseudo)word length did not affect the accuracy of any of the reading groups. The interaction of Lexicality and Length was significant, F (3, 189) = 3.69, p < 0.05, η2p = 0.06. Table 3 Mean error percentages for words and pseudowords of 3, 4, 5, and 6 letters in lexical decision for the Dyslexic group (DYS, n = 22), chronological age control group (CA, n = 22), and reading age control group (RA, n = 22) Length Reading
3
4
5
6
Group DYS CA RA Note.
16
Words
3.64
(4.92)
2.73
(4.56)
3.18
(6.46)
1.36
(3.51)
Pseudowords
5.45
(8.58)
9.09
(7.50)
7.73
(9.22)
9.09
(9.72)
Words
4.09
(5.90)
2.73
(5.51)
1.82
(3.95)
0.91
(2.94)
Pseudowords
2.27
(4.29)
5.91
(7.96)
3.18
(4.77)
3.18
(5.68)
Words
4.55
(5.10)
0.91
(2.94)
4.55
(5.96)
2.73
(4.56)
Pseudowords
7.73
(6.85)
6.82
(7.16)
2.73
(5.51)
3.18
(6.46)
Between parentheses are the standard deviations.
Word length effect on lexical decision Words consisting of 4 letters were responded to more accurately than pseudowords consisting of 4 letters. For items consisting of 3, 5, or 6 letters, there was no difference in accuracy between words and pseudowords. This interaction was refined by a three-way interaction of Lexicality, Length, and Reading Group, which approached significance, F (6, 189) = 1.90, p = 0.084, η2p = 0.06. As there was no systematic difference among the three reading groups, this effect could not be interpreted. Response times The analyses were based on response times for valid and correct trials only. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials were excluded from the analyses (0 %, 5.28 %, and 5.51 % for DYS, respectively, 0.17 %, 3.01 %, and 5.11 % for CA, respectively, and 0.11 %, 4.15 %, and 7.73 % for RA, respectively). For each child in each condition, a mean response time and a standard deviation were calculated. Response times that deviated more than 2.5 standard deviations from the child’s condition mean were considered outliers and excluded from the analyses (0.57 % for DYS, 1.02 % for CA, and 0.51 % for RA). In all, the outliers, incorrect and invalid trials amounted to 11.36 % of the data for DYS, 9.32 % of the data for CA, and 12.50 % for RA (in total 11.06 % of the data). In Table 4, the mean response times for words and pseudowords of the Dyslexic group (DYS), the Chronological Age control group (CA), and the Reading Table 4 Mean response times for words and pseudowords of 3, 4, 5, and 6 letters in lexical decision for the Dyslexic group (DYS, n = 22), Chronological Age control group (CA, n = 22), and Reading Age control group (RA, n = 22) Length Reading
3
4
5
6
Group DYS CA RA
Note.
Words
1438
(461)
1654
(616)
1793
(823)
1837
(761)
Pseudowords
1867
(558)
2252
(885)
2356
(732)
2562
(801)
Words
1103
(246)
1154
(331)
1114
(259)
1129
(273)
Pseudowords
1199
(297)
1252
(349)
1281
(297)
1320
(327)
Words
1776
(677)
1768
(520)
1870
(727)
1958
(535)
Pseudowords
2012
(738)
2430
(819)
2577
(954)
2678
(784)
Between parentheses are the standard deviations.
17
Chapter 2 Age control group (RA) are displayed. A MANOVA for repeated measures with Lexicality (words or pseudowords) and Length (3, 4, 5, or 6 letters) as within subjects factors and Reading Group (DYS, CA, or RA) as a between subjects factor was performed. There was a significant difference in the speed of lexical decision among the three reading groups, F (2, 63) = 20.09, p < 0.001, η2p = 0.39. We specified two contrasts, which showed that the DYS group was significantly slower than the CA group, F (1, 63) = 24.01, p < 0.001, η2p = 0.28, but as fast as the RA group, F (1, 63) = 1.07, p > 0.30. The significant main effect of Length, F (3, 189) = 34.73, p < 0.001, η2p = 0.36, was refined by a two-way interaction of Length and Reading Group, F (6, 189) = 5.97, p < 0.001, η2p = 0.16. This interaction is shown in Figure 1. Two separate analyses comparing the DYS group with the CA group and the RA group, respectively, showed that Length affected DYS more than CA, F (3, 126) = 13.40, p < 0.001, η2p = 0.24, but affected DYS and RA to the same extent, F < 1. Repeated
2800 2600 Response time (ms)
2400 DYS words
2200
DYS pseudowords
2000
CA words
1800
CA pseudowords RA words
1600
RA pseudowords 1400 1200 1000 3
4
5
6
Length
Figure 1.
Response times (in milliseconds) for words and pseudowords consisting of
3, 4, 5, and 6 letters in lexical decision by the Dyslexics (DYS), Chronological Age controls (CA), and Reading Age controls (RA). The error bars represent 95 % confidence intervals.
18
Word length effect on lexical decision contrasts in the analysis comparing the DYS group with the CA group showed that most of the difference between these two groups was due to a larger increase in response time for the DYS group than for the CA group from 3 to 4 letters, F (1, 42) = 7.73, p < 0.01, η2p = 0.16. The increase in response times from 4 to 5 letters was slightly larger for the DYS group than for the CA group, but this difference only approached significance, F (1, 42) = 3.04, p = 0.089, η2p = 0.07. The increase in response times from 5 to 6 letters was similar for the DYS group and the CA group, F (1, 42) = 1.65, p > 0.20. The interaction of Length and Reading Group in the comparison of the DYS and the CA group indicated that, in absolute terms, the increase in response time due to (pseudo)word length was larger in the dyslexic children than in their normal reading age peers. However, given that the DYS group already responded more slowly than the CA group at the shortest (pseudo)word length, 3 letters, the interaction of Length and Reading Group might merely reflect a proportional increase in response time with each additional letter. Put differently, it is possible that each additional letter might require a similar percentage of additional reading time in both groups. A straightforward method to check whether a significant interaction reflects a proportional effect is to subject the scores in the various conditions to a logarithmic transformation (Levine, 1993; van der Sluis, de Jong, & van der Leij, 2004; Zar, 1999), and subsequently perform the MANOVA on the transformed scores2. If the interaction effect disappears in the analysis on the transformed scores, then the original interaction effect is proportional. However, if the interaction effect remains, then it is safe to conclude that the reading groups are differently affected by the experimental manipulation, such as length. Thus, we performed additional analyses on the logarithm of the response times, to check whether any of the interactions in the analyses on the response times reflected proportional differences. These analyses yielded the same results as those on the response times, indicating that none of the reported interactions reflected a proportional effect.
2
Taking a two by two factorial design with conditions ‘a’, ‘b’, ‘c’, ‘d’, a significant interaction effect would mean that (a – b) is unequal to (c – d). For example, ‘a’ can be dyslexics’ RT for words and ‘b’ for pseudowords, and ‘c’ and ‘d’ can denote the word and pseudoword RT for the normal readers. If this effect is merely a proportional effect than a/b = c/d. Taking logarithms, we test whether ln(a/b) = ln(c/d), which is identical to the test that ln(a) – ln(b) = ln(c) – ln(d). Thus, an algorithmic transformation transforms a multiplicative effect into an additive effect. 19
Chapter 2 The significant main effect of Lexicality, F (1, 63) = 86.17, p < 0.001, η2p = 0.58, was qualified by an interaction of Lexicality and Reading Group, F (2, 63) = 9.99, p < 0.001, η2p = 0.24. Two separate analyses comparing the DYS group with the CA group and the RA group, respectively, showed that words were responded to faster than pseudowords, and that the difference in response times for words and pseudowords was larger for the DYS group than for the CA group, F (1, 42) = 25.02, p < 0.001, η2p = 0.37, but equivalent for the DYS group and the RA group, F < 1. The analyses on the logarithm of the response times yielded the same results, indicating that the difference between the DYS group and the CA group was not a proportional difference. The interaction of Length and Lexicality was also significant, F (3, 189) = 5.32, p < 0.005, η2p = 0.08. The effect of Length was larger on pseudowords than on words. Again, the analyses on the logarithm of the response times produced the same results. There was no significant interaction of Length, Lexicality, and Reading Group, F (6, 189) = 1.32, p > 0.25. The previous analyses have shown that the effect of length was larger on pseudowords than on words. The lack of a three-way interaction with Reading Group indicated that the stronger effect of length on pseudowords than on words applied to all three groups. This implies an effect of length on pseudowords in each of the three groups, including the CA group. In addition, the combination of the Length by Reading Group interaction (and the contrasts we specified for DYS-CA and DYS-RA) and the lack of a three-way interaction with Lexicality indicates that the effect of length was stronger for both words and pseudowords in DYS than in CA, but equivalent for DYS and RA. These results suggest a length effect on both words and pseudowords in the DYS and RA groups alike. What remains unclear is whether length affected words at all in the CA group. In order to investigate this, we conducted a separate analysis on the words for this group. This analysis showed that the CA group was not affected by Length when performing lexical decision on words, F < 1. From the Length by Lexicality interaction and the lack of a three-way interaction with Reading Group in the overall analysis we can infer that length did affect pseudowords in the CA group. To check this, we also conducted a separate analysis on the pseudowords in this group, which indeed showed that length did affect lexical decision on pseudowords in the CA group, F (3, 63) = 3.25, p < 0.05, η2p = 0.13.
20
Word length effect on lexical decision Discussion Length effects are often believed to indicate the use of a serial sublexical decoding strategy instead of a more parallel lexical reading procedure. The latter procedure might be less available to dyslexic readers because of a lack of orthographic knowledge (Ziegler et al., 2003; Zoccolotti et al., 2005). Indeed, in several studies length was found to affect the word and pseudoword naming speed of dyslexic readers more than the naming speed of normal readers. In the current study, we examined the effect of length on dyslexic and normal reading children’s performance in lexical decision, a task that was assumed to be more dependent on the availability of lexical orthographic knowledge than the naming tasks used in previous studies. We found that lexical decisions were highly accurate in both groups of normal readers and the group of dyslexic children. For words, less than 5 % of the responses were incorrect, whereas for pseudowords the percentage of errors was less than 10 % in each of the groups. These high accuracy levels can have two different explanations. One possible explanation is that most of the words were part of the children’s orthographic lexicon, enabling the reliance on lexical processing while performing the lexical decision task. In case of the dyslexics and the younger readers, however, this seems an unlikely explanation. A more likely explanation is that the words were not yet in the orthographic lexicon (and could thus not be recognized by relying on lexical processing alone), and that the (pseudo)words were identified correctly using a serial sublexical processing procedure before making a lexical decision. If we assume that in dyslexic and younger normal readers many words are not yet part of the orthographic lexicon, this seems a sensible strategy to enable accurate performance in a lexical decision task. If these readers had relied on lexical processing (only) while performing the lexical decision task, that is, searching their orthographic lexicon without previous sublexical decoding, this would have led to high error rates. The predominant use of a sublexical reading procedure in the dyslexic (and younger normal readers) is further suggested by the substantial increase in their response times with each additional letter compared to the normal reading 10-yearold children in this study (see Figure 1). Overall, the increase in response time was larger for pseudowords than for words. The smaller effect of length on words than on pseudowords suggests that, in addition to a sublexical reading procedure, also lexical knowledge was used in lexical decision. Interestingly, most of the difference in the effect of length on reading speed between the dyslexics and their normal reading age peers could be ascribed to a 21
Chapter 2 larger increase in response time for the dyslexics from 3 to 4 letters. Although items of different length were matched in consonant-vowel structure as much as possible, the increase in response time from 3 to 4 letters may have been caused (partly) by the much higher frequency of occurrence of consonant clusters (e.g., ‘gr..’ and ‘..ms’) in items consisting of 4 letters (and more). Thus, the introduction of consonant clusters may have complicated reading for dyslexics more than for chronological age controls, despite the matching of 3-letter items to those consisting of 4, 5, and 6 letters in word frequency and bigram frequency. However, as the current study was not designed to examine possible specific difficulties in dyslexics with processing consonant clusters, an extended discussion falls beyond the scope of the current study. In contrast to the dyslexic and younger readers, the 10-year-old normal reading children did not appear to be affected by length when performing lexical decisions on words, consistent with what has typically been found in normal reading adults (e.g., de Groot, et al., 2002; Juphard et al., 2004). This suggests that, when performing the lexical decision task on words, they predominantly relied on a lexical/global reading procedure. For pseudowords, however, length did appear to affect the speed of lexical decision. This result pattern is different from what is generally observed in adults, whose lexical decisions do not appear to be affected by length on either words or pseudowords (de Groot, et al., 2002; Juphard et al., 2004). Thus, adults seem to stop processing as soon as an item is not recognized as part of the orthographic lexicon and seem to base their lexical decision on lexical processing only. However, this finding is not undisputed; Balota, Cortese, SergentMarshall, Spieler and Yap (2004) reported an interaction between length and word frequency: length had an effect on low frequency words but not on high frequency words. The latter result raises the possibility that adults, too, read the complete word or pseudoword before making a lexical decision. Summarizing, adults generally base their lexical decisions on a quick familiarity check, at least for high frequency words, rejecting the item when it is not recognized by a lexical reading procedure. Our results suggest that when the 10-year-old normal reading children encountered an item that was not in their orthographic lexicon, typically a pseudoword, they subsequently identified the item using a sublexical reading procedure before giving a ‘no’-response. The results on lexical decision in the current study are remarkably similar to the findings on the effects of length on the naming performance of normal and dyslexic readers (e.g., Spinelli, et al., 2005; van der Leij & van Daal, 1999; Ziegler et al, 2003; Zoccolotti, et al., 2005). In addition to stronger length effects in 22
Word length effect on lexical decision dyslexic readers than in normal readers, also stronger effects on pseudoword naming than on word naming have been found regularly. The latter effect has even been reported often for the naming performance of skilled readers, and has been interpreted as the (partial) reliance on a sublexical reading strategy (e.g., Juphard et al., 2004). In the present study, the reliance on a sublexical reading strategy enabled accurate performance in a lexical decision task for children with orthographic lexicons of limited size. This strategy might explain why the results of the current study on lexical decision in dyslexic and normal readers closely resemble the results of studies on naming. It might be argued that the children performed the lexical decision task by first silently naming all (pseudo)words, followed by a lexical decision. However, this seems unlikely for two reasons. The first reason is that, in naming studies, length did affect word-naming speed both in English and in German normal reading 10-year-olds (Ziegler et al, 2003), and in Dutch normal reading 10-year-olds (Martens & de Jong, 2006c). The lack of a length effect on words in lexical decision in normal reading 10-year-olds suggests that these children did not silently phonologically recode the words before making a lexical decision. The second reason is that the relation between lexical decision speed on words and word reading speed has been reported to decrease from first grade to sixth grade (Gijsel, van Bon, & Bosman, 2004). This suggests that, with the development of reading skill, lexical decision becomes increasingly based on a lexical reading strategy, performed by means of a quick familiarity check on the orthographic lexicon. These findings support our contention that the 10-year-old normal readers first performed a familiarity check on the item (like adults do), and only when it was not in their orthographic lexicon did they identify it using a sublexical reading procedure before giving a ‘no’-response. More generally, the combined results on accuracy and reading speed suggest that when children encountered a (pseudo)word that was not in their orthographic lexicon (i.e., an item that was not recognized using a lexical reading procedure), they proceeded by identifying the (pseudo)word relying on a sublexical reading procedure to reach a correct lexical decision. This seems a sensible strategy, given that there is a large discrepancy in the phonological lexicon and the orthographic lexicon in dyslexic children and in normal beginning readers. Our findings for children with varying levels of reading skill and the results obtained for adults in other studies suggest that lexical decision becomes based on the orthographic lexicon to an increasing extent with the development of reading skill. The influence of length on the lexical decision performance of the dyslexic children in the current study is in accordance with the results that were found by 23
Chapter 2 Juphard et al. (2004) in their study of the lexical decision performance of one dyslexic adult. As in our dyslexic children, this adult showed a substantial effect of length, which was stronger in pseudowords than in words. However, the inclusion in the current study of a younger group of children of the same reading age revealed that the dyslexics were affected to the same extent as this reading age control group. This result suggests that reading level or the size of the orthographic lexicon might determine the extent to which readers can rely on the lexical route in word recognition. Consequently, the length effect on words and pseudowords in a lexical decision task should be considered primarily as an indicator of reading level rather than as a cause of the reading problem. An important note to add here is that the present study was conducted with readers of a shallow orthography (Dutch); different results might be obtained with (beginning, advanced, and dyslexic) readers of a deep orthography, such as English. Possibly, the effects of length on lexical decision will be less pronounced in these readers (cf. Ziegler, Perry, Jacobs & Braun, 2001). Given that there were no time constraints in the present study, as the (pseudo)words remained on the screen until a response was given, it is unclear whether the strong reliance of the dyslexic children on a sublexical reading procedure was (primarily) generated by habit or necessity. However, in a speeded version of a lexical decision task (Yap & van der Leij, 1993) in which CVC words and pseudowords were presented for only 200 ms, accuracy rates dropped in dyslexic children, compared to an unspeeded version of the lexical decision task. In reading age controls, accuracy rates also dropped in the speeded version, whereas the time constraint did not affect the accuracy of the chronological age controls. Although the presentation time might have been very short, especially for dyslexic children, these results suggest that the limited size of the orthographic lexicon in dyslexics and reading age controls precludes (strong) reliance on a lexical reading procedure. Thus, the adoption of a sublexical reading procedure by dyslexics is probably generated by necessity. The length effect we found in dyslexics’ lexical decision can be accounted for by the ACV98 model (also see Juphard et al., 2004). This model predicts that, in dyslexics, the size of the attentional window is reduced, forcing them to use the analytical reading procedure instead of the global reading procedure. The analytic reading procedure is characterized by a smaller attentional window. Thus, not all letters of a (pseudo)word are processed at the same time, but in a serial way, resulting in slower reading speed for longer (pseudo)words.
24
Word length effect on lexical decision In the DRC model, lexical decision is based solely on the lexical route, performed by a search in the orthographic lexicon. Word length is not expected to affect lexical decision. However, our results showed highly accurate performance by young children and dyslexic children, who may both be assumed to have orthographic lexicons of limited size. Had these children based their lexical decisions on the lexical route only, this would, as said, have resulted in high error rates. This suggests that readers with orthographic lexicons of limited size at least partly rely on sublexical processing to perform a lexical decision task. The contribution of sublexical processing was also suggested by the effect of length on lexical decision speed. Thus, the DRC model may need some adaptations to enable an account of the lexical decision performance in beginning and dyslexic readers. Similar to what is found in adult lexical decision (e.g., de Groot, et al., 2002; Juphard et al., 2004), words were responded to faster than pseudowords. The DRC model and the ACV98 model provide similar explanations for this finding. Both models state that (in normal reading adults) lexical decision is based on the lexical or global route only. A printed (pseudo)word is compared to internal representations of known words, until a match is found. As soon as the search of the internal representations (or the orthographic lexicon) is complete and no match has been found, the model produces a ‘no’ response, and the search is stopped. Thus, as the search of the entire orthographic lexicon precedes a ‘no’ response, words are necessarily responded to faster than pseudowords. However, our results suggest that in children the sublexical/analytic procedure also contributes to the lexical decision process. Both models might explain the difference in lexical decision speed for words and pseudowords in children by stating that the contribution of the lexical/global procedure may be larger for words than for pseudowords. Summarizing, we found that length affected dyslexics more than chronological age controls in lexical decision. To enable accurate performance, dyslexics predominantly relied on a sublexical reading strategy. These results support the notion put forward by Zoccolotti et al., (2005), that dyslexics fall short in the development of a lexical reading procedure. This pattern of results is compatible with the ACV98 model, whereas the DRC model cannot (yet) fully account for these findings.
25
26
Use of lexical knowledge in naming
Chapter 3 Use of lexical knowledge in naming by dyslexic and normal reading children3
The aim of the current study was to investigate relative differences in the use of lexical knowledge by dyslexic and normal reading children. Lexical knowledge was examined by the effects of word length and cAsE aLtErNaTiOn on word and pseudoword naming. Dyslexics were more affected by length than normal readers. In both dyslexics and normal readers, length affected reading speed for words less than for pseudowords, suggesting that both groups at least used some lexical knowledge. Case alternation affected dyslexics more than normal readers. Overall, however, case alternation affected words and pseudowords to the same extent, in all three groups. These results suggest that in children of this age, no lexical feedback is available to compensate for the visual disruption caused by case alternation. The results are discussed in terms of two current computational models of reading.
3
Martens, V. E. G., & de Jong, P. F. (2006c). Use of lexical knowledge in naming by dyslexic and normal reading children. Manuscript submitted for publication. 27
Chapter 3 Introduction Children learning to read in a transparent orthography often identify written words by decoding graphemes into phonemes and subsequently blending these phonemes together to form a word’s pronunciation. With practice, children acquire orthographic knowledge at a lexical and, possibly, at a sublexical level (Ehri, 1992, 1998; Share, 1995). Lexical orthographic knowledge refers to direct connections between written and spoken forms of words. Sublexical orthographic knowledge concerns sensitivity to statistical regularities in the orthography, that is, implicit knowledge about what letter and sound combinations co-occur frequently. The acquisition of orthographic knowledge is assumed to enable fast and accurate reading. Sublexical orthographic knowledge is further evidenced by sensitivity to bigram frequency: high frequent bigrams are read faster than low frequent ones (e.g., Arduino & Burani, 2004). Lexical orthographic knowledge is indexed by faster recognition of high frequent words than of low frequent words (e.g., Andrews, 1989; Forster & Chambers, 1973), which, in turn, are recognized faster than pseudowords (e.g., Rastle & Coltheart, 1999). Most children acquire orthographic knowledge within the course of some years of reading instruction, evidenced by progressively faster and more accurate reading of an increasing number of words. Dyslexic children, however, continue to read slowly, although in transparent orthographies the highly regular grapheme-tophoneme correspondences enable even dyslexic children to read accurately (e.g., de Jong & van der Leij, 2003; Wimmer, 1993; Zoccolotti, de Luca, di Pace, Judica, Orlandi, & Spinelli, 1999). A dominant hypothesis for dyslexics’ pervasive inability to speed up their reading process is that they have severe difficulties in the acquisition of orthographic or lexical knowledge. As a consequence, dyslexics have to rely relatively more heavily on the slow and laborious strategy of phonological decoding (e.g., Hogaboam & Perfetti, 1978; Reitsma, 1989). The main aim of the current study was to examine in more detail the presumed differences in lexical knowledge, and consequently in reading strategy, between dyslexic and normal readers. Two methods were employed to reveal these relative differences in the availability of lexical knowledge. One method was to examine the effects of length on naming speed. Generally, the effect of word length decreases as word recognition becomes less dependent on a serial phonological decoding process and the effect disappears when all the letters of a word are identified in parallel. In the latter case, word recognition is assumed to be completely based on lexical knowledge. The second method to examine differences in the availability of lexical knowledge consisted in changing the more parallel 28
Use of lexical knowledge in naming lexical reading strategy of the normal readers into a more serial phonological decoding strategy, by breaking up letter combinations that can usually be processed in parallel. This was done by applying cAsE aLtErNaTiOn. A straightforward prediction would be that the normal readers become more similar to the dyslexic readers in terms of the availability of a particular reading strategy if words are presented in alternating case. In other words, case alternation will reduce the difference between normal and dyslexic readers regarding the effect of length by imposing the same (serial) reading strategy. However, as will be outlined below, the availability of lexical knowledge may modify the effect of case alternation on words. First, the effect of length will be discussed. The effect of length on the naming speed of words and nonwords can be easily described in terms of at least two computational models of reading: the Dual Route Cascaded model by Coltheart, Rastle, Perry, Langdon, and Ziegler (2001), and the connectionist network proposed by Ans, Carbonnel, and Valdois (1998). In the Dual Route Cascaded model (DRC, Coltheart, et al., 2001), two reading routes are postulated: the sublexical route and the lexical route. These two routes are activated in parallel. In the sublexical route, the graphemes of a word are decoded into phonemes one-by-one, in a serial way. In the lexical route, all letters of a word are activated in parallel, and these letters subsequently activate a word’s entry in the orthographic lexicon, the corresponding word entry in the phonological lexicon, and finally the word’s phonemes. Novel words and pseudowords will predominantly be read through the sublexical route, although it should be stressed that the lexical route is also involved. Words that have been repeatedly read will predominantly be processed through the lexical route, provided that they have been included in the orthographic lexicon (Jackson & Coltheart, 2001). The number of words readers can access directly in their orthographic lexicon depends on their reading skill, and consequently, so does the extent to which readers rely on the lexical or the sublexical route. In the model by Ans, Carbonnel, and Valdois (1998, for short, ACV98), also two reading procedures are distinguished, but in this model the procedures work successively. First, a global procedure using knowledge about whole words is applied. In this procedure, the so-called ‘focal window’ or ‘visual attentional window’ spans all letters (or syllables) in a word at a time. Within this window, all letters are processed in parallel. If a word is not recognized by this global procedure, it will subsequently be processed by the analytic procedure. The analytic procedure is based on the activation of word syllabic segments or smaller segments. Processing is applied to the largest initial segment of the printed letter string that is 29
Chapter 3 recognized as familiar, and will proceed to the next familiar spelling pattern(s), up to the end of the string. Most often, familiar words will be read by the global procedure, whereas unfamiliar words and pseudowords will be read by the analytic procedure. Despite the differences between these two computational models, they are similar in their claim that the magnitude of the length effect is due to the amount of lexical knowledge that is involved in word and pseudoword naming. In the DRC model, a larger length effect signifies a larger involvement of the sublexical route. In the ACV98 model, such an effect indicates a larger role for the analytic procedure. Both models predict that if sufficient lexical knowledge of a set of words is available no length effect will occur as all letters are processed in parallel due to the use of the lexical (DRC) or global (ACV98) routine. These predictions have been supported in a number of studies with proficient adult readers. Length did not influence the reading speed of (high frequent) words, but did have an effect on the reading speed of pseudowords that, by definition, do not have a lexical representation (e.g., Juphard, Carbonnel, & Valdois, 2004; Weekes, 1997). In beginning and dyslexic readers, effects of length have predominantly been examined for words. Generally, for these readers the reading speed of words is heavily affected by length, thereby suggesting that words are mainly read by a sublexical reading procedure (Spinelli, de Luca, di Filippo, Mancini, Martelli, & Zoccolotti, 2005; Ziegler, Perry, Ma-Wyatt, Ladner, & Schulte-Körne, 2003; Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005). In normal reading children, the length effect tends to decrease considerably from the end of first grade onwards (Zoccolotti et al., 2005). To date, the only study examining the effect of length on both word and pseudoword naming in children has been a study by Ziegler et al. (2003). In line with the results of other studies, dyslexic children were more affected by length than normal readers. Unexpectedly, however, Ziegler et al. (2003) did not find a length by lexicality interaction, indicating that effects of length on word and on pseudoword reading did not differ. This suggests that all children used the same strategy for word and pseudoword reading, a result that is not in accordance with the predictions of the DRC and the ACV98 model in which pseudowords are assumed to be more dependent on a sublexical or analytical reading procedure. The result is also at odds with the findings of eye movement studies with dyslexic and normal reading children in which the number of saccades, indicating the amount of sublexical processing within a (pseudo)word, was found to increase more for longer
30
Use of lexical knowledge in naming pseudowords than for longer words in normal reading children (e.g., Hutzler & Wimmer, 2004; de Luca, Borrelli, Judica, Spinelli, & Zoccolotti, 2002). In the current study, we examined the effect of length on the reading speed for words and pseudowords in normal and dyslexic readers. We also included a group of younger readers with the same reading age as the dyslexic children. Except for the study by Ziegler et al. (2003), such a reading age control group has not been included in previous studies on length effects in dyslexic and normal reading children. As a second method to examine differences between normal and dyslexic readers in their use of lexical knowledge, we employed case alternation. Case alternation is the alternating use of lowercase and uppercase letters within a (pseudo)word, e.g., eXaMpLe. Case alternation slows down reading, which has been suggested to be due to the distortion of the visual multiletter features (Besner & Johnston, 1989; Martens & de Jong, in press; Mayall, Humphreys, & Olson, 1997). Multiletter features are features larger than single letters and smaller than whole words, such as the relative shape and size of letters, and the shape of the spaces between the letters. Case alternation is assumed to elicit a more serial reading strategy, by breaking up letter combinations that can usually be processed in parallel. If this is indeed the case, then the decelerating effect of case alternation should increase for longer words (see Mayall, Humphreys, Mechelli, Olson, and Price, 2001, for a similar hypothesis). One aim of the current study, although not its main aim, was to test this interaction of case alternation and length in (pseudo)word naming speed, which, to our knowledge, has not been examined yet. As said, assuming that case alternation induces a more serial reading strategy, a straightforward prediction would be that dyslexics are less hampered by case alternation than normal readers, because case alternation would interfere less with dyslexics’ predominant serial/sublexical reading procedure than with normal readers’ predominant parallel/lexical reading procedure. Following this line of reasoning, however, case alternation would be expected to affect pseudowords less than words, since pseudoword reading requires more sublexical processing (which is serial in nature) than word reading does. Put differently, case alternation might be expected to interfere less with the reading procedure typically involved in pseudoword reading than with the reading procedure typically involved in word reading. Yet, research has shown the opposite: case alternation affects pseudowords more than words (e.g., Besner & Johnston, 1989; Mayall & Humphreys, 1996). In addition, high frequent words are less affected than low frequent ones (e.g., Besner & McCann, 1987; Mayall & Humphreys, 1996). 31
Chapter 3 Besner (1990) argued that case alternation affects word reading less than pseudoword reading, because words can be read by both a lexical and a sublexical reading procedure, whereas pseudowords can only be read by a sublexical reading procedure. According to Besner, the lexical reading procedure is based solely on letter identification, whereas in the sublexical reading procedure also multiletter visual units are used. As these multiletter units are disrupted, the sublexical reading procedure is more hampered by case alternation than the lexical reading procedure. However, several findings have been reported that are not in accordance with the hypothesis of a stronger disruption of the sublexical reading procedure (for an overview see Mayall, 2002). In an alternative account, Mayall and Humphreys (1996) suggested that words are less affected by case alternation than pseudowords, because the visual processing of words benefits from top-down effects of lexical knowledge. Thus, case alternation decreases reading speed because the disruption of visual multiletter features induces a more serial reading strategy. However, the effect of case alternation is reduced by the top-down feedback provided by the availability of lexical knowledge. The more lexical knowledge is available, the more top-down lexical information helps to compensate for the visual disruption. Accordingly, words, especially high frequent ones, are less affected by case alternation than pseudowords (see Mayall, 2002). Following the account of Mayall and Humphreys (1996), the effects of case alternation should be different in groups of readers that are presumed to differ in their amount of lexical knowledge (Mayall, 2002). More specifically, in dyslexics, who are presumed to have acquired relatively less orthographic knowledge, the effects of case alternation on words and pseudowords should be more similar than in their normal reading peers. The latter are assumed to have more orthographic knowledge, which is hypothesized to be particularly helpful in reducing the effects of case alternation on words. To summarize, the main aim of the present study was to examine differences between normal and dyslexic readers in their use of lexical knowledge during reading. Words and pseudowords of different length were read by dyslexic children, their normal reading age peers, and a group of younger normal readers with a similar reading level as the dyslexic children. Since dyslexic readers are hypothesized to have less lexical knowledge and accordingly rely relatively more on sublexical processing, we expected a larger effect of length in the dyslexic children than in their normal reading peers. In addition, words and pseudowords were presented under two conditions: lowercase and alternated case. Through case alternation we aimed to create a condition in which the availability of lexical 32
Use of lexical knowledge in naming knowledge would become more important. We had two expectations. The first, a more general one, was that case alternation would have a larger effect with increasing (pseudo)word length. The second expectation was that normal reading children would be relatively less hampered by case alternation in word naming, whereas the effect on pseudoword naming would be more similar in normal and dyslexic readers. We did not have specific hypotheses with respect to differences between the dyslexic and the younger normal readers. Method Participants Sixty-six children participated in the study. They were selected from 12 regular primary schools in the west and middle part of the Netherlands. The Dyslexic group (DYS) comprised 22 children (13 boys and 9 girls) in Grade 4 who had a reading lag of at least 15 months (mean 18.8; range 15-28). Twenty-two normal readers (15 boys and 7 girls) in Grade 4 were selected for the Chronological Age control group (CA). These children were individually matched in age, gender, vocabulary and nonverbal reasoning ability to the children in the DYS group. The third group, a Reading Age control group (RA), consisted of 22 normal readers (13 boys and 9 girls) in Grade 2, individually matched in reading level and gender to the dyslexic children. Permission for all children was obtained from the parents and the schools. The 66 children were selected from 546 children on the basis of their performance on three screening tasks: Word reading ability, vocabulary, and nonverbal reasoning. These three tasks were administered a few weeks prior to the naming task. Word reading ability. To assess word reading ability, the One Minute Reading Test (Een Minuut Test) (Brus & Voeten, 1979) was administered individually. This test consists of a list of 116 unrelated words of increasing length and difficulty. Children are required to read aloud as many words as possible without making errors within one minute. The score was the number of words that were read correctly. On the basis of this raw score, a standardized score was computed, ranging from 1 to 19, with a mean of 10 and a standard deviation of 3 (van den Bos, lutje Spelberg, Scheepsma, & de Vries, 1994). All children in the DYS group scored at or below the 20th percentile. All children in the normal reading control groups scored within the normal range.
33
Chapter 3 Vocabulary. Vocabulary was assessed with a standardized sub-test of the Amsterdam Child Intelligence Test Battery (Revisie Amsterdamse Kinder Intelligentie Test) (Bleichrodt, Drenth, Zaal, and Resing, 1987). During this test, the test assistant reads 60 words of increasing difficulty aloud (one at a time), upon which the children have to choose the matching picture out of four alternatives. On the basis of the number of correctly chosen pictures (the raw score), a standardized score was computed, ranging from 0 to 30, with a mean of 15 and a standard deviation of 5. Children with a standardized score of more than 2 standard deviations below or above the population mean were excluded from the study. Nonverbal reasoning. To assess nonverbal reasoning, the RAVEN Standard Progressive Matrices (Raven, Court, & Raven, 1986) were administered. Each item consists of three rows of three geometric patterns each. On each row, the patterns change from left to right according to some common logic. The third picture on the third row is missing, and children are required to complete this row by choosing the correct alternative. The DYS and CA groups completed all 60 items, whereas the RA group completed the first 36 items only, as these items cover their expected nonverbal reasoning abilities. The score, consisting of the number of correct answers, was matched to a percentile score (comparing a child’s score to that of children of comparable age). In Table 1, the mean scores on each of the screening measures for each of the selected three groups are presented. Table 1 Mean scores on each of the screening measures for the Dyslexic group (DYS), Chronological Age control group (CA), and Reading Age control group (RA) CA Age
(months)
DYS
RA
124.27
(4.25)
124.27 (5.33)
96.55
(3.97)
Raw score
48.14
(4.28)
47.73 (4.63)
42.55
(2.70)
Non-verbal reasoning Raw score
42.82
(6.22)
43.00 (6.01)
29.14
(2.44)
Word reading ability Raw score
74.68
(5.38)
46.86 (6.51)
46.86
(6.37)
Reading age a
51.09
(6.52)
23.23 (4.26)
23.18
(4.10)
Vocabulary
Note. a
Between parentheses are the standard deviations.
Reading age reflects the reading level in months. Within one school year, children receive
10 months of reading education, so a reading age of 15 months reflects the expected reading level halfway Grade 2.
34
Use of lexical knowledge in naming
Naming task Materials. The stimulus set included 80 words and 80 pseudowords. The items varied in length from three to six letters. For each length, 20 words and 20 pseudowords were selected. The mean frequency of the words was 195.28 per million (SD 199.23) (Staphorsius, Krom, & de Geus, 1988). Mean bigram frequency was 309.06 per 20,000 words (SD 439.65) (Bakker, 1990). Words of different lengths were matched in frequency and bigram frequency. Pseudowords were constructed by changing one or two adjacent letters at either the beginning or the end of the words. Letters that were replaced within a given word were interchanged with the letters of another word, e.g. exchanging the initial letters in the words ‘lucht’, ‘markt’, and ‘helft’ [resp. ‘air’, ‘market’, ‘half’] resulted in the pseudowords ‘hucht’, ‘larkt’, and ‘melft’. As a result, the mean bigram frequency of the pseudowords was equal to the mean bigram frequency of the words. In addition, the CV structures of the words and pseudowords were similar. Pseudowords of different lengths were also matched in bigram frequency. (See Appendix A for a complete list of the words and pseudowords.) For both words and pseudowords, presentation format was varied: For each length, half of the items were presented in lowercase; the other half were presented in alternated case, that is, alternating lowercase and uppercase letters (e.g., aLtErNaTeD cAsE). To avoid confusion between capital ‘I’ and lowercase ‘l’ in the alternated-case items, ‘i’ was only presented as a lowercase letter and ‘L’ was only presented as an uppercase letter. Half of the alternated-case items started with a lowercase letter; half started with an uppercase letter. Whenever a word presented in alternated case started with a lowercase letter, the pseudoword derived from it started with an uppercase letter, and vice versa, in order to make the word shape of a word-pseudoword ‘pair’ as distinct as possible (e.g., sLeChT - VrEcHt). Items that were presented in lowercase to the one half of the children, were presented in alternated case to the other half of the children, and vice versa. Every word was presented only once to a child, in either lowercase or alternated case. Apparatus and task procedure. The items appeared one by one in the middle of a 14-in. screen of an Apple Macintosh LC 475 computer. The items were presented in 48-point Amsterdam font, in black letters on a white background. Children were seated at a 60-cm distance from the screen. A voice key registered response times. The test assistant marked the accuracy of each response by pressing the appropriate key on the keyboard (right, wrong, or invalid if the voice key had not been set off properly or had been triggered by another sound). Children were not given feedback on the accuracy of their response. All trials started with a short beep 35
Chapter 3 to focus the participant’s attention. The stimulus appeared 750 ms after the beep and disappeared from the screen as soon as the voice key was triggered. The test assistant made the next word appear on the screen using the keyboard. One second later, a beep announced the next trial. Items were presented in four separate blocks according to case type (lowercase or alternated case) and lexicality (words or pseudowords). Half of the children first named all lowercase items, and subsequently (after a short break) the alternated-case items. The order of the lowercase and alternated-case blocks was reversed for the other half of the children. The first block (which could be either lowercase or alternated case) started with either words or pseudowords, which was also balanced across children. If a child started with pseudowords within the first block, the third block started with words, and vice versa. The order of presentation of the words or pseudowords was randomized within each of the four blocks, with a different random order for each child. Children were told that they would read real words and nonsense words on the computer, and they were asked to read these words aloud as quickly as possible and with as few errors as possible. Before each block, the experimenter announced the type of words (words or pseudowords) and type of case (lowercase or alternated case). Each of the four blocks started with four practice trials. Children were explicitly encouraged to refrain from speaking until they knew the entire word, to make sure any sounding out of the word occurred silently. Furthermore, they were urged to avoid saying “uh”, as this would set off the voice key, immediately making the word disappear from the screen. The practice trials familiarized the children with the task, and gave the experimenter the opportunity to adjust the sensitivity level of the voice key, if necessary. General procedure The study consisted of a screening and a naming task. During screening, a vocabulary test and a nonverbal reasoning test were administered to complete classes. Each of these tests lasted about 45 minutes. Subsequently, a word reading ability test was administered individually, taking about 3 minutes per child. A few weeks later, the naming task was administered individually in a (separate) room in school where testing could take place relatively quietly. The naming task took about 25 minutes.
36
Use of lexical knowledge in naming Results Previous studies on the effects of length on naming have involved only lowercase words and pseudowords. To keep in line with these studies, we will first present the results on the naming of (pseudo)words in lowercase. Subsequently, we will report the results on the effects of case alternation. Lowercase Accuracy. The mean error percentages for naming words and pseudowords of different lengths in lowercase for the three reading groups are displayed in Table 2. Due to difficulties in recording response times, half of the data for one child in the Reading Age control group was missing. This child was excluded from the analyses. Overall, few errors were made, especially in the CA group. As the CA group made very few errors, they were not included in the analysis on the error scores. A MANOVA for repeated measures with Lexicality (words or pseudowords) and Length (3, 4, 5, or 6 letters) as within subjects factors and Reading Group (DYS or RA) as a between subjects factor was performed. The effect of Reading Group was not significant, F < 1. The DYS group read as accurately as the RA group. A significant effect of Lexicality was found, F (1, 41) = 47.597, p < 0.001, η2p = 0.54. Words were read more accurately than pseudowords. The effect of Length was also significant, F (3, 123) = 11.098, p < 0.001, η2p = 0.21, showing that shorter (pseudo)words were read more accurately than longer ones. In addition, an Table 2 Lowercase naming: Mean error percentages for words and pseudowords of 3, 4, 5, and 6 letters for the Dyslexic group (DYS), Chronological Age control group (CA), and Reading Age control group (RA) Length Reading
3
4
5
6
Group CA
Words
0.00
(0.00)
1.36
(3.51)
0.91
(2.94)
1.36
Pseudowords
1.36
(3.51)
5.00 (10.12)
6.36
(9.02)
7.73 (11.10)
DYS
Words
2.27
(5.28)
3.64
4.09
(5.03)
5.91
Pseudowords
5.45
(8.00)
9.55 (11.33)
RA
Words
1.90
(4.02)
4.76
Pseudowords
6.67
(7.96)
7.62 (12.61)
Note.
(7.90) (6.80)
16.36 (15.60) 2.86
(4.63)
15.71 (17.20)
(3.51) (9.08)
17.27 (18.04) 3.33
(5.77)
14.29 (10.28)
Between parentheses are the standard deviations.
37
Chapter 3 interaction of Lexicality and Length was found, F (3, 123) = 7.21, p < 0.001, η2p = 0.15. With increasing length, accuracy for pseudowords decreased more than accuracy for words. None of the other interactions reached significance. Although we did not include the CA group in the analysis due to their very low error percentages, the same Lexicality by Length interaction was observed for this group (see Table 2). Response times. The analyses were based on response times for valid and correct trials only. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials were excluded from the analyses (0.17 %, 8.07 %, and 3.18 % for DYS, respectively, 0.40 %, 3.01 %, and 3.30 % for CA, respectively, and 0.24 %, 7.14 %, and 2.62 % for RA, respectively). For each child in each condition, a mean response time and a standard deviation were computed. Response times that deviated more than 2.5 standard deviations from the child’s condition mean were considered outliers and excluded from the analyses (0.51 % for DYS, 0.85 % for CA, and 0.77 % for RA). In all, the outliers, incorrect and invalid trials amounted to 11.93 % of the data for DYS, 7.56 % of the data for CA, and to 10.77 % for RA (in sum 10.08 % of the lowercase data). In Table 3, the mean response times of words and pseudowords that were read correctly in lowercase by the Dyslexic reader group (DYS), the Chronological Age control group (CA), and the Reading Age control group (RA) are displayed. For an overall analysis, we conducted a MANOVA for repeated measures with Lexicality (words or pseudowords) and Length (3, 4, 5, or 6 letters) as within subjects factors and Reading Group (DYS, CA, or RA) as a between subjects factor. Significant main effects were found for Reading Group, F (2, 62) = 15.147, p < 0.001, η2p = 0.33, Lexicality, F (1, 62) = 118.736, p < 0.001, η2p = 0.66, and Length, F (3, 186) = 76.250, p < 0.001, η2p = 0.55. These main effects were qualified by three two-way interactions. The interaction of Length and Lexicality indicated that the effect of Length was larger on response times for pseudowords than on those for words, F (3, 186) = 20.423, p < 0.001, η2p = 0.25. The interactions of Lexicality and Reading Group, F (2, 62) = 9.335, p < 0.001, η2p = 0.23, and the interaction of Length and Reading Group, F (6, 186) = 7.532, p < 0.001, η2p = 0.20, will be inspected in more detail in two subsequent analyses comparing the DYS group with each of its control groups. The three-way interaction of Length, Lexicality and Reading Group approached significance, F (6, 186) = 1.869, p = 0.088, η2p = 0.06. In a subsequent analysis, we compared the DYS group with the CA group, to reveal the differences between these two groups. We will focus on the differences between the reading groups that were indicated in the overall analysis. In the 38
Use of lexical knowledge in naming Table 3 Lowercase naming: Mean response times for words and pseudowords of 3, 4, 5, and 6 letters for the Dyslexic group (DYS), Chronological Age control group (CA), and Reading Age control group (RA) Length Reading
3
4
5
6
Group CA DYS
Words
632
(111)
645
(91)
666
(92)
Pseudowords
711
(139)
763
(155)
829
Words
750
(152)
913
(286)
969
1026
(357)
1219
(353)
Words
739
(126)
805
Pseudowords
897
(205)
1076
Pseudowords RA
Note.
699
(112)
(240)
900
(308)
(337)
1001
(299)
1439
(513)
1631
(603)
(145)
803
(152)
895
(196)
(325)
1189
(425)
1387
(461)
Between parentheses are the standard deviations.
analysis comparing the DYS group with the CA group, the significant main effect of Reading Group showed that the DYS group read significantly slower than the CA group, F (1, 42) = 26.708, p < 0.001, η2p = 0.39. The Lexicality by Reading Group interaction indicated that the difference in response times for words and pseudowords was larger for the DYS group than for the CA group, F (1, 42) = 19.252, p < 0.001, η2p = 0.31. The Length by Reading Group interaction showed that the length effect was stronger for the DYS group than for the CA group, F (3, 126) = 18.505, p < 0.001, η2p = 0.31. Repeated contrasts indicated that most of this difference was due to a larger increase in response time from 3 to 4 letters for the DYS group than for the CA group, F (1, 42) = 27.476, p < 0.001, η2p = 0.40. From 4 to 5 letters, the increase in response times was also larger for the DYS group than for the CA group, but, as revealed by the effect size, this difference was not as large as from 3 to 4 letters, F (1, 42) = 5.874, p < 0.05, η2p = 0.12. The increase in response times from 5 to 6 letters was somewhat larger for the DYS group than for the CA group, but this difference did not reach significance, F (1, 42) = 3.051, p = 0.088. The larger effect of Length on the response times of the DYS group than on those of the CA group can also be seen in Figure 1. The Length by Reading Group interaction in the comparison of the DYS and the CA group demonstrated that, in absolute terms, the increase in response time due to (pseudo)word length was larger in the dyslexic children than in their chronological age controls. However, as the DYS group already responded more slowly than the CA group at the shortest (pseudo)word length, 3 letters, the Length 39
Chapter 3 by Reading Group interaction might merely reflect a proportional increase in response time with each extra letter. In other words, it is possible that every extra letter might require a similar percentage of additional reading time in both groups. A straightforward method to check whether a significant interaction reflects a proportional effect is to subject the scores in the various conditions to a logarithmic transformation (Levine, 1993; Salthouse & Hedden, 2002; van der Sluis, de Jong, & van der Leij, 2004; Zar, 1999), and subsequently perform a MANOVA on the transformed scores. If the interaction effect is not significant in the analysis on the transformed scores, then the interaction effect observed on the original scores reflects a proportional difference. However, if the interaction effect remains, then it is safe to conclude that the reading groups are differently affected by the experimental manipulation, such as length. Thus, we performed additional analyses on the logarithm of the response times, to check whether any of the interactions in the analyses on the response times reflected proportional differences. Whenever the analysis on the logarithm of the response times yielded different results than the analysis on the response times, it is reported in the text.
Response time (ms)
1600 DYS words
1400
DYS pseudowords CA words
1200
CA pseudowords 1000
RA words RA pseudowords
800 600 3
4
5
6
Length
Figure 1.
Response times (in milliseconds) for words and pseudowords consisting of
3, 4, 5, and 6 letters in lowercase by the Dyslexics (DYS), Chronological Age controls (CA), and Reading Age controls (RA).
40
Use of lexical knowledge in naming
In the analysis on the logarithm of the response times comparing the DYS group with the CA group, the only significant difference was that between 3 and 4 letters, F (1, 42) = 21.481, p < 0.001, η2p = 0.34. This indicated that the only disproportional difference between the DYS group and the CA group was a larger decrease in reading speed from 3 to 4 letters for the DYS group. For each subsequent additional (single) letter, the decrease in reading speed was proportionally similar for the DYS group and the CA group. In the analysis comparing the DYS group with the CA group, the three-way interaction of Lexicality, Length, and Reading group was significant, F (3, 126) = 3.232, p < 0.05, η2p = 0.07. In the analysis on the logarithm of the response times, this interaction was not significant, F < 1, which indicates that the interaction reflected a proportional difference; the larger effect of length on pseudowords than on words was proportionally similar in the DYS group and the CA group. The previous analyses showed that the effect of length was larger on pseudowords than on words. The analysis comparing the DYS group and the CA group further showed that the larger effect of length on pseudowords than on words was proportionally similar in these two groups. For the CA group, these results imply that length affected pseudoword-reading speed. However, it remains unclear for this group whether length affected word-reading speed as well. Therefore, we conducted a separate analysis on the words read by the CA group. This analysis showed that length also affected word-reading speed in the CA group, F (3, 63) = 11.632, p = 0.001, η2p = 0.36. In another analysis, we compared the DYS group with the RA group to reveal possible differences between these two groups. The effect of Reading Group approached significance, F (1, 41) = 3.034, p = 0.089, η2p = 0.07. A tendency was observed that the RA group read somewhat faster (see Figure 1). The interaction of Lexicality and Reading Group was not significant, F (1, 41) = 1.474, p > 0.20. The difference in response times for words and pseudowords was comparable for the DYS group and the RA group. The length effect was somewhat stronger for the DYS group than for the RA group, but this difference only approached significance, F (3, 123) = 2.188, p = 0.093, η2p = 0.05. The three-way interaction of Length, Lexicality and Reading group was not significant, F < 1.
41
Chapter 3 Alternated case Accuracy. To compare accuracy in lowercase to accuracy in alternated case, a difference score was calculated. We opted for analyses on the difference scores for two reasons. The first reason was that we were mainly interested in a possible differential effect of case alternation on the three reading groups, that is, in the interaction effects of case alternation with reading group, length, and lexicality. The second reason was a more practical one, namely to minimize redundancy and enhance clarity in the presentation of the results. The difference scores were calculated for each condition by subtracting the percentage of errors in lowercase from the percentage of errors in alternated case. Thus, a positive difference reflects that more errors were made in alternated case than in lowercase. A negative difference reflects that fewer errors were made in alternated case than in lowercase. The mean increases in error percentages due to presentation in alternated case for naming words and pseudowords of different lengths in lowercase for the three reading groups are displayed in Table 4. Overall, changes in accuracy due to case alternation were small. In alternated case, a decrease in error percentages with increasing length for the DYS group was observed. In contrast, the RA group seemed to make more errors with increasing length. The change in error percentages in the CA group was minimal. Consequently, the CA group was not included in the Table 4 Alternated-case naming: Mean increase in error percentages due to presentation in alternated case for words and pseudowords of 3, 4, 5, and 6 letters for the Dyslexic group (DYS), Chronological Age control group (CA), and Reading Age control group (RA) Length Reading
3
4
5
6
0.45 (2.13)
0.00 (5.35)
0.91 (4.26)
- 2.27 (10.66)
- 0.91
(6.84)
0.91 (12.69)
- 0.45 (3.75)
1.36 (10.82)
- 1.82
(5.89)
- 1.36 (11.25)
- 5.91 (17.09)
- 4.55 (18.44)
Group CA
Words
DYS
Words
Pseudowords
RA
(6.10)
Pseudowords
0.91
(8.11)
0.00 (12.72)
Words
1.43
(4.78)
0.48 (12.44)
2.86
- 2.86 (10.07)
0.00 (10.49)
2.86 (16.48)
Pseudowords Note.
0.91
(7.84)
1.82
4.29
(7.95)
(9.26)
9.52 (17.17)
Between parentheses are the standard deviations. Positive values reflect that more
errors were made in alternated case than in lowercase. Negative values indicate that fewer errors were made in alternated case than in lowercase.
42
Use of lexical knowledge in naming analysis on the change in error percentages due to case alternation. Because of difficulties in recording response times, half of the data for one child in the Reading Age control group was missing. This child was excluded from the analyses. A MANOVA for repeated measures with Lexicality (words or pseudowords) and Length (3, 4, 5, or 6 letters) as within subjects factors and Reading Group (DYS or RA) as a between subjects factor was performed on the difference score for accuracy. Note that this analysis was run on difference scores (i.e., alternated case – lowercase), so if a given effect is not significant, this reflects that the results in alternated case were comparable to those in lowercase, which have been reported in the previous section. A significant effect of Reading Group was found, F (1, 41) = 6.128, p < 0.05, η2p = 0.13. The DYS group made fewer errors in alternated case than in lowercase, whereas the RA group made more errors in alternated case than in lowercase. The interaction of Length and Reading group was significant, F (3, 123) = 4.931, p < 0.005, η2p = 0.11. This interaction is shown in Figure 2. The DYS group made fewer errors in alternated case than in lowercase
Increase in error percentage
8 6 4 DYS CA RA
2 0 3
4
5
6
-2 -4 -6 Length
Figure 2.
Mean increase in error percentage due to presentation in alternated case for
items consisting of 3, 4, 5, and 6 letters for the Dyslexics (DYS), Chronological Age controls (CA), and Reading Age controls (RA).
43
Chapter 3 with increasing length, whereas the opposite was found for the RA group: the RA group made more errors in alternated case than in lowercase with increasing length. None of the other effects reached significance, indicating that case alternation did not interact with any other variable(s). Response times. The analyses were based on response times for valid and correct trials only. The data cleaning procedure was the same as for the lowercase condition. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials were excluded from the analyses (0.11 %, 6.59 %, and 3.92 % for DYS, respectively, 0.28 %, 3.24 %, and 2.95 % for CA, respectively, and 0.06 %, 9.46 %, and 3.69 % for RA, respectively). For each child in each condition, a mean response time and a standard deviation were calculated. Response times that deviated more than 2.5 standard deviations from the child’s condition mean were considered outliers and excluded from the analyses (0.51 % for DYS, 0.74 % for CA, and 0.77 % for RA). In all, the outliers, incorrect and invalid trials amounted to 11.14 % of the data for DYS, 7.22 % of the data for CA, and to 13.99 % for RA (for a total of 10.73 % of the alternated-case data). To compare response times in alternated case to those in lowercase, a difference score was computed for each condition by subtracting the response time in lowercase from the response time in alternated case. Thus, a positive difference in response times reflects that reading in alternated case was slower than in lowercase. A negative difference in response times would reflect that reading in alternated case was faster than in lowercase, but this did not occur. In Table 5, the mean increases in response times due to presentation in alternated case compared to presentation in lowercase for words and pseudowords are displayed for the Dyslexic reader group (DYS), the Chronological Age control group (CA), and the Reading Age control group (RA). As in the analysis in lowercase, we checked whether differences in response times between lowercase and alternated case were not merely proportional differences, by performing additional analyses on the logarithm of the difference in response times. Whenever this analysis yielded different results than the analyses on the response times, it is reported in the text. Thus, unless explicitly mentioned otherwise, the reported differences were not proportional differences. Identical to the analyses of the results in lowercase, we conducted three analyses on the differences in response times due to case alternation. The first analysis concerned an overall analysis including all three reading groups. In the two subsequent analyses, we compared the DYS group with the CA group and the RA group, respectively. 44
Use of lexical knowledge in naming Table 5 Alternated-case naming: Mean increase in response time due to presentation in alternated case compared to presentation in lowercase for words and pseudowords of 3, 4, 5, and 6 letters for the Dyslexic group (DYS), Chronological Age control group (CA), and Reading Age control group (RA) Length Reading
3
4
5
6
Group CA DYS RA Note.
Words
31
(67)
92
(99)
102
(196)
104
(176)
Pseudowords
48
(107)
95
(120)
130
(143)
273
(247)
Words
141
(189)
178
(374)
251
(309)
690
(565)
Pseudowords
149
(311)
361
(375)
407
(400)
671
(660)
Words
153
(342)
124
(228)
302
(304)
423
(513)
Pseudowords
128
(175)
198
(190)
336
(418)
494
(418)
Between parentheses are the standard deviations.
For the overall analysis, a MANOVA for repeated measures with Lexicality (words or pseudowords) and Length (3, 4, 5, or 6 letters) as within subjects factors and Reading Group (DYS, CA, or RA) as a between subjects factor was performed. A significant effect of Reading Group was found, F (2, 62) = 6.525, p < 0.005, η2p = 0.17. The effect of Lexicality approached significance, F (1, 62) = 3.360, p = 0.072, η2p = 0.05, showing that case alternation affected pseudowords somewhat more than words. In the analysis on the logarithm of the difference in response times in lowercase and alternated case, the effect of Lexicality was not significant, F < 1, indicating that this difference was a proportional difference. As hypothesized, the effect of Length was significant, F (3, 186) = 42.133, p < 0.001, η2p = 0.41. Longer items were more affected by case alternation than shorter ones. Repeated contrasts showed that the difference in response times for alternated-case items increased with each additional letter (Increase in response times from 3 to 4 letters: F (1, 62) = 9.912, p < 0.005, η2p = 0.14; Increase in response times from 4 to 5 letters: F (1, 62) = 21.096, p < 0.001, η2p = 0.25; Increase in response times from 5 to 6 letters: F (1, 62) = 31.987, p < 0.001, η2p = 0.34). Contrary to what we expected, the Lexicality by Reading Group interaction was not significant, F < 1. The interaction of Length and Lexicality was not significant either, F (3, 186) = 1.466, p > 0.20, showing that the decelerating effect of case alternation increased with increasing length, and that this effect was as large on words as on pseudowords. However, the interaction of Length and Reading 45
Chapter 3 Group was significant, F (6, 186) = 5.425, p < 0.001, η2p = 0.15, as was the threeway interaction of Length, Lexicality and Reading Group, F (6, 186) = 2.234, p < 0.05, η2p = 0.07. These significant interactions are inspected more closely in the analyses comparing the DYS group with the CA group and the RA group, respectively. In the next analysis, we compared the DYS group with the CA group. We focus on the interactions with Reading Group that were found in the overall analysis. The main effect of Reading Group showed that the DYS group was more hampered by case alternation than the CA group, F (1, 42) = 12.116, p < 0.001, η2p = 0.22. The interaction of Length and Reading Group was significant, F (3, 126) = 11.569, p < 0.001, η2p = 0.22, indicating that the increase in response times due to case alternation was stronger with increasing length for the DYS group than for the CA group. Repeated contrasts showed that the difference between these groups was entirely due to a much larger increase in response time from 5 to 6 letters in the DYS group than in the CA group, F (1, 42) = 13.747, p < 0.001, η2p = 0.25. The increases in response time due to case alternation from 3 to 4 letters and from 4 to 5 letters were comparable for the DYS group and the CA group. In the analysis comparing the DYS group with the CA group, the three-way interaction of Length, Lexicality and Reading Group was also significant, F (3, 126) = 5.166, p < 0.005, η2p = 0.11. This interaction is shown in Figure 3. The decelerating effect of case alternation increased with length. This effect was larger on pseudowords than on words, but for the DYS group, the difference between words and pseudowords was smaller than for the CA group, exactly as we hypothesized. In the analysis on the logarithm of the response times, the three-way interaction of Length, Lexicality, and Reading Group was also significant, F (3, 126) = 7.966, p < 0.001, η2p = 0.16. This indicates that this difference between the DYS group and the CA group was not merely a proportional difference. For a closer inspection of this three-way interaction, two analyses were performed on the difference in response times due to case alternation, separately for words and pseudowords, including the DYS group and the CA group (i.e., without the RA group). Although the interaction of Length and Reading Group was significant for pseudowords, F (3, 126) = 3.789, p < 0.05, η2p = 0.08, the analysis on the logarithm of the response times showed that this concerned only a proportional difference, F < 1.
46
Use of lexical knowledge in naming
Pseudow ords
Words
Increase in RT (ms)
700 600 500
DYS
400
CA
300
RA
200 100 0 3
4
5 Length
Figure 3.
6
3
4
5
6
Length
Mean increase in response times (in milliseconds) due to case alternation
for words and pseudowords consisting of 3, 4, 5, and 6 letters for the Dyslexics (DYS), Chronological Age controls (CA), and Reading Age controls (RA).
Thus, for pseudowords, the increase in response times due to case alternation was proportionally similar for the DYS group and the CA group with increasing length. In contrast, for words, the interaction of Length and Reading group was significant both in the analysis on the difference of the response times, F (3, 126) = 15.281, p < 0.001, η2p = 0.27, and in the analysis on the difference of the logarithm of the response times, F (3, 126) = 9.450, p < 0.001, η2p = 0.18. Repeated contrasts showed that the difference in increase in response time was entirely due to a larger increase in response time from 5 to 6 letters in the DYS group than in the CA group, F (1, 42) = 21.478, p < 0.001, η2p = 0.34. From 3 to 4 letters and from 4 to 5 letters, the increases in response times were comparable for the DYS group and the CA group, both Fs < 1. Thus, for words up to 5 letters, the DYS group and the CA group were hampered to the same extent by case alternation, but for words consisting of 6 letters the DYS group was relatively more hampered by case alternation compared to the CA group (see Figure 3). In a final analysis, we compared the DYS group with the RA group. The main effect of Reading Group was not significant, F (1, 41) = 1.082, p > 0.20, indicating that the overall reading speeds for the DYS group and the RA group were hampered to the same extent by case alternation. The interaction of Length and Reading Group approached significance, F (3, 123) = 2.548, p = 0.059, η2p = 0.06. Repeated contrasts showed an inconsistent pattern: From 3 to 4 letters, the increase in response times due to case alternation did not differ significantly between the 47
Chapter 3 DYS group and the RA group, F (1, 41) = 2.945, p = 0.094, η2p = 0.07. From 4 to 5 letters, the increase in response times due to case alternation was smaller for the DYS group than for the RA group, F (1, 41) = 4.243, p < 0.05, η2p = 0.09. From 5 to 6 letters, however, the increase in response times due to case alternation was larger for the DYS group than for the RA group, F (1, 41) = 4.705, p < 0.05, η2p = 0.10. The three-way interaction of Length, Lexicality and Reading Group was not significant, F (3, 123) = 1.089, p > 0.20. Discussion The goal of the present study was to investigate the extent to which dyslexic children rely on lexical knowledge during reading, compared to normal readers of the same age and younger children with the same reading level as the dyslexics. Two methods were employed to investigate this. The first method was to examine the effect of length on the reading speed and accuracy of naming words and pseudowords. The second method was to investigate the extent to which lexical feedback is available that might compensate for the visual disruption caused by case alternation. As expected, it took more time to read aloud long words and pseudowords than short ones. This is in line with previous research involving children (e.g., Spinelli, et al., 2005; Ziegler, et al., 2003). Also consistent with previous studies (e.g., Spinelli, et al., 2005; Ziegler et al., 2003; Zoccolotti, et al., 2005), length influenced dyslexics’ reading speed more than normal readers’ reading speed. This suggests that dyslexics rely more on a sublexical reading procedure than normal readers do (Coltheart, et al., 2001; Weekes, 1997; Ziegler, et al., 2003). Zooming in on the length effect showed that the difference between the dyslexics and their chronological age controls decreased with length. As indicated by the contrasts, most of the difference could be attributed to a larger increase in response times for the dyslexics than for the chronological age controls from 3 to 4 letters (see Figure 1). From 4 to 5 letters, the dyslexics still showed a larger increase in response times than the chronological age controls, although this difference was smaller than from 3 to 4 letters. From 5 to 6 letters, the reading speeds of these groups increased to the same extent. These results fit well with an account positing that, in the course of (normal) reading development, an increasing number of letters can be read in parallel. This implies that normal reading children may process short words more in parallel (i.e., with a relatively large contribution from a lexical reading procedure), and that a sublexical reading procedure is progressively more involved with increasing word length. Hence, the difference between normal reading 48
Use of lexical knowledge in naming children and dyslexic children levels off with increasing word length. This is also in accordance with the results of Spinelli et al. (2005), who reported no effect of word length for words up to 5 letters in normal reading children (in Grades 6-8), and linear increases in response times for words consisting of 5-8 letters. Their findings suggested parallel processing for words up to 5 letters and (partial) sequential processing for longer words in normal reading children. In adults, no length effect was observed for words consisting of 3-8 letters, indicating parallel processing across the board. Another consideration is that the increase in response time from 3 to 4 letters might be ascribed (partly) to the higher incidence of consonant clusters (e.g., ‘st..’ and ‘..rm’) in (pseudo)words consisting of more than 3 letters. The introduction of consonant clusters may have impeded reading for dyslexics more than for chronological age controls, despite the matching of 3-letter (pseudo)words to those consisting of 4, 5, and 6 letters in word frequency and bigram frequency. It might be argued that preparing the articulation of (pseudo)words containing a consonant cluster is more difficult and consequently takes more time than preparing the articulation of (pseudo)words without consonant clusters. However, as the same pattern was observed in a lexical decision task performed by the same children on the same words and pseudowords, in which children did not pronounce them (Martens & de Jong, 2006b), this result pattern is unlikely to be due to an articulatory effect. In line with previous research, words were read faster than pseudowords. However, in contrast to the results in the study by Ziegler et al. (2003), length affected words less than pseudowords. This applied both to the normal readers and to the dyslexics. The smaller effect of length on words than on pseudowords suggests the use of at least some lexical knowledge, in normal and dyslexic readers alike. It cannot be ruled out that part of the advantage of words over pseudowords is due to a practice effect in pronouncing the words (prior to the naming task). However, in the lexical decision task mentioned earlier (Martens & de Jong, 2006b), the effect of length was also smaller on words than on pseudowords in all three groups. Since the children did not pronounce the items in the lexical decision task, a possible articulatory advantage for words in the naming task seems unlikely to be able to account fully for the difference in naming speed of words and pseudowords. Consistent with other studies (e.g., de Jong, 2003; Wimmer, 1993; Ziegler, et al., 2003), the difference in reading speed between words and pseudowords was larger for dyslexics than for normal readers. Difficulty in reading pseudowords has
49
Chapter 3 typically been interpreted as a marker of a phonological deficit (see Rack, Snowling, & Olson, 1992). The use of lexical knowledge was further investigated by measuring the extent to which the readers benefited from lexical feedback, in a reading situation where visually disrupted words and pseudowords had to be read aloud. The visual disruption was implemented by presenting words and pseudowords in alternating case. Dyslexics’ reading speed was more impeded by case alternation than that of chronological age controls. However, case alternation hampered the reading speed of the dyslexics as much as that of the reading age controls. As we hypothesized, case alternation decreased children’s reading speed more with each additional letter. This result provides support for the notion that case alternation induces a more serial reading strategy, as suggested by Mayall et al. (2001). Every additional letter took extra time to process compared to reading in standard lowercase format. This implies that letter combinations that can usually be processed in parallel were broken up by case alternation, forcing the readers to adopt a (more) sequential reading strategy. We had expected a smaller effect of case alternation on words than on pseudowords in normal reading 10-year-olds (i.e., the chronological age controls), compared to the dyslexics. Overall, however, case alternation affected reading speed for words as much as that for pseudowords, in all three groups of children. This is different from what has been reported for adults, whose reading speed for words is less affected by case alternation than that for pseudowords (e.g., Besner & Johnston, 1989; Mayall & Humphreys, 1996; Mayall et al., 1997). Our results therefore suggest that case alternation does not affect (pseudo)word recognition in children of this age in the same way as in adults. It suggests that children lack the lexical feedback that results in a smaller effect of case alternation on the reading speed of words than on the reading speed of pseudowords in adults. However, considering the interaction of lexicality with length and reading group modifies the picture somewhat. With increasing pseudoword length, the effect of case alternation was comparable for dyslexics and their chronological age controls (see the right panel of Figure 3). In contrast, with increasing word length, the effect of case alternation was found to be stronger in dyslexics than in chronological age controls (see the left panel of Figure 3). However, dyslexics only appeared to differ from their chronological age controls on words consisting of six letters. For words up to five letters, case alternation affected reading speed to the same extent in dyslexics and chronological age controls (as evidenced by the contrasts, and also clearly visible in 50
Use of lexical knowledge in naming the left panel of Figure 3). In sum, based on the overall similar effect of case alternation on words and pseudowords, it seems warranted to conclude that in general no lexical feedback was available in these dyslexic and normal reading children. However, the disproportional increase in response time for alternated-case words consisting of 6 letters in dyslexics may suggest less lexical feedback for 6letter words in dyslexics than in their chronological age controls. The abrupt increase in response time from 5- to 6-letter words in alternated case does seem puzzling (see left panel of Figure 3). A more gradual increase in response time with increasing length would have better met our expectations. Dyslexics’ increase in response times for words consisting of six letters in alternated case was not accompanied by a change in accuracy. Furthermore, Figure 3 shows a similar increase in response time due to case alternation for words and pseudowords consisting of six letters in the dyslexics. Therefore, a speed-accuracy trade-off was not involved. One possible explanation for the larger increase in reading speed for alternated-case words consisting of six letters in the dyslexics might be a higher occurrence of digraphs. Since all (pseudo)words consisted of one syllable, increasing length necessarily involves a more complex consonant-vowel structure, including vowel digraphs (e.g., aa, ie) and consonant digraphs (e.g., ch). Figure 1 shows that, in lowercase, the increasingly complex consonant-vowel structure in itself was not accompanied by a disproportionately larger increase in response times for (pseudo)words consisting of six letters in the dyslexics. However, the visual disruption of these digraphs by case alternation may have complicated reading for the dyslexics more than for the chronological age controls. In that case, the difference for 6-letter words between dyslexics and chronological age controls should not be explained in terms of a difference in lexical feedback, but rather in terms of flexibility of a parsing process or flexibility in the identification of visually disrupted graphemes. However, a counter-argument in this line of reasoning could be that the occurrence of digraphs in 6-letter words was identical to that in 6-letter pseudowords. And in pseudowords, there was no (disproportional) difference between the dyslexics and the chronological age controls. Therefore, the higher occurrence of digraphs in (pseudo)words consisting of six letters than in shorter (pseudo)words is unlikely to have caused the larger increase in reading speed in alternated-case 6-letter words in dyslexics than in chronological age controls. Another explanation for the larger increase in reading speed for alternatedcase words consisting of six letters in the dyslexics might be a possible decrease in orthographic neighbourhood size. We did not control for orthographic 51
Chapter 3 neighbourhood size, as it was hard enough to select an adequate number of words of different lengths that were sufficiently high frequent for children of 8 and 10 years old. Although the words of different lengths were matched in mean word frequency and mean bigram frequency, a difference in orthographic neighbourhood size cannot be ruled out. Orthographic neighbourhood size is generally negatively correlated with word length (e.g., Frauenfelder, Baayen, Hellwig & Schreuder, 1993). The possibly lower orthographic neighbourhood size for six-letter (pseudo)words than for shorter ones might cause a decrease in reading speed. However, two aspects of the result pattern seem to argue against this explanation. The first is that readers may be assumed to rely on orthographic neighbourhood size at least as much in lowercase as in alternated case (or even more in lowercase, assuming more parallel processing and presumably easier availability of orthographic neighbourhood information). Accordingly, a similar (disproportional) decrease in reading speed from 5 to 6 letters for the dyslexics would not only be expected in alternated case, but should also be apparent in lowercase, which was not found (see Figure 1). The second argument against the explanation in terms of a difference in orthographic neighbourhood size is that the larger increase in reading speed for alternated-case words consisting of six letters in the dyslexics would imply a stronger reliance on orthographic neighbourhood size by dyslexic readers than by normal readers. This is at odds with the general finding that the influence of orthographic neighbourhood size increases with reading ability (e.g., Share, 1995). Thus, dyslexics would rather be expected to rely less on orthographic neighbourhood size than normal readers, and consequently to be less bothered by a possible difference in orthographic neighbourhood size. In sum, the disproportional increase in response time for alternated-case words consisting of 6 letters in dyslexics may suggest less lexical feedback for 6letter words in dyslexics than in their chronological age controls. However, given the overall similar effect of case alternation on words and pseudowords, we did not find evidence for the availability of lexical feedback in children. The latter result is at odds with the findings of Mayall (2002). She reported that case alternation affected word and pseudoword reading accuracy to the same extent in 6- and 8-year-old (normal reading) children, whereas in 9-year-old children word reading was less affected than pseudoword reading, as in adults. Mayall explained this in terms of the amount of lexical knowledge available to children of different reading levels. In contrast, we did not find a stronger effect of case alternation on pseudoword reading accuracy than on word reading accuracy in the normal reading 10-year-olds. In addition, our results on reading speed did not show 52
Use of lexical knowledge in naming a stronger effect of case alternation on pseudowords than on words either. Possibly, these conflicting results can be explained in terms of the depth of the orthography. English has a deep orthography, in which the correspondences between graphemes and phonemes are highly irregular. To enable accurate reading, readers of deep orthographies generally rely on relatively large reading units. In contrast, Dutch has a shallow orthography with highly regular grapheme-to-phoneme correspondences. In shallow orthographies, readers can rely on relatively small reading units (Goswami, Ziegler, Dalton, & Schneider, 2003; Wimmer & Goswami, 1994; Ziegler, Perry, Jacobs, & Braun, 2001). It is possible that in readers of a shallow orthography, the difference in the effect of case alternation on words and pseudowords is smaller than in readers of a deep orthography, due to the reliance on relatively small reading units. To date, however, most studies on case alternation have involved English readers, and to our knowledge no study has yet compared the effects of case alternation across orthographies. In short, two methods were employed in the present study to investigate the use of lexical knowledge in dyslexic and normal reading children: word length and case alternation. With regard to the first method, the stronger length effect on pseudowords than on words in the dyslexics indicated that they used lexical knowledge. However, the larger length effects in the dyslexics than in their normal reading age peers suggested that the dyslexics did rely more on a sublexical reading strategy and accordingly used less lexical knowledge than the normal readers. The results on the second method, case alternation, were somewhat equivocal. As predicted, case alternation was shown to induce a more serial reading strategy, indicated by an increase in the decelerating effect for longer (pseudo)words. However, the ‘standard’ stronger effect of case alternation on pseudowords than on words that has typically been reported in English adult readers (e.g., Besner & Johnston, 1989; Mayall & Humphreys, 1996) did not appear in children. Thus, whereas lexical status mediates the effect of case alternation in English adult readers (evidencing the availability of lexical feedback), Dutch children did not appear to have lexical knowledge available in words presented in such a visually disrupted format. It is unclear whether the absence of a lexical feedback effect in the present study can be attributed to the depth of the orthography, as explained in the previous paragraph, or whether it was due to the reading level of the participants (children). Whatever the possible cause, due to the lack of a differential effect of case alternation on words and pseudowords, this second method did not provide information regarding a difference in the availability of lexical knowledge in dyslexic and normal reading children. 53
Chapter 3 An additional finding of the current study concerns the reading accuracy of the dyslexics and the normal readers. Surprisingly, dyslexics read items in alternated case more accurately than items in lowercase. In contrast, the opposite pattern was found for the reading age control group, who read items in alternated case less accurately than items presented in lowercase (see Figure 3). For both of these groups, this pertained to the longer items only (consisting of 5 and 6 letters), and not for the shorter items (consisting of 3 and 4 letters). The accuracy of the chronological age controls did not appear to be affected by case alternation at all. A possible explanation for the improved accuracy in dyslexics when reading in alternated case is that case alternation might enhance attention to each constituent letter, thus reducing a ‘guessing’ reading strategy. Some evidence for an increase in attention when reading in alternated case is provided by a PET study (Mayall, et al., 2001), in which reading in alternated case elicited extra activation in an area that has been associated with visual attention, suggesting an increase in attentional processing. The results of the present study can be explained only in part by the two reading models mentioned in the introduction, the Dual Route Cascaded (DRC) model by Coltheart, et al., (2001) and the connectionist network (ACV98) proposed by Ans, et al., (1998). We will now outline how these two models can account for some results of the current study. As already indicated, both models can explain the effects of length in general, and the stronger effect of length on pseudowords than on words. Thus, the next step is to see how either model can account for the effects of case alternation. At present, the ACV98 model does not incorporate multiletter visual word features, which case alternation is assumed to disrupt. However, we can infer what the model would predict for the effect of case alternation, if we assume that case alternation renders parallel processing more difficult, by breaking up letter combinations that can usually be processed as a unit. In the ACV98 model, case alternation can be assumed to reduce the size of the visual attentional window, making it more difficult to apply the global procedure that captures all letters in a word at once. Thus, given the reduced size of the visual attentional window, the reader is likely to be forced to use the analytic procedure, thereby processing words in a serial way. The ACV98 model will predict that reading words in alternated case will take longer than reading them in lowercase, because lowercase words can be read by the faster (parallel) global procedure, whereas alternated-case words have to be read by the (serial) analytic procedure. Given that the analytic procedure is not used until the global procedure has failed, alternated-case words will necessarily take longer to read than lowercase words. 54
Use of lexical knowledge in naming For pseudowords, the ACV98 model will also predict that reading in alternated case takes longer than reading in lowercase. Whereas both lowercase and alternated-case pseudowords will be processed by the analytic procedure, there will be a difference in the size, and consequently in the number of, the processing units. For (unfamiliar) pseudowords, the processing unit captured by the visual attentional window is typically a syllable. As all pseudowords in our study consisted of one syllable, this would imply that, at this point of processing, the visual attentional window would still capture the whole pseudoword. However, when an unfamiliar syllable is encountered, in this case a one-syllable pseudoword, processing is typically fine-grained to the next largest familiar spelling pattern: the level of onsets and rhymes. Thus, the lowercase pseudowords in our study, each one of them consisting of familiar onsets and rhymes, will be processed at the level of onsets and rhymes. For alternated-case pseudowords, however, the visual attentional window will probably have to be fine-grained to the level of letters, because the constituent letters are presented in alternating lowercase and uppercase. The assumption is that case alternation disrupts familiar spelling patterns, hampering the recognition of letter clusters such as onsets and rhymes, and inducing the processing of single letters. Thus, alternated-case pseudowords will be processed at the level of single letters. As alternated-case pseudowords have to be ‘encoded’ in a larger number of processing units (i.e., single letters) than lowercase ones, and as these units are processed sequentially in the analytic procedure, alternated-case pseudowords will take longer to read than lowercase ones. For the DRC model (Coltheart et al., 2001), predicting the effect of case alternation on words and pseudowords seems to be more difficult. There are two features in the model’s architecture that complicate making predictions. The first problem is constituted by the incorporation of ‘case alternation’ in the model. Although the DRC model includes a level of ‘Visual Feature Units’, these features were based on a 16-feature font applying only to uppercase letters (Rumelhart & Siple, 1974). Since the model is based on uppercase letters only, it seems difficult to imagine how the model could account for case alternation effects, in which the difference between lowercase and uppercase letters is crucial. The ‘Visual Feature Units’ map onto the 26 ‘Letter Units’, each for one of the 26 letters in the Roman alphabet. It is unclear whether these letter units represent both lowercase and uppercase versions of each letter, or whether the model applies to uppercase letters only. Given the present architecture of the model, it is obscure how the ‘case status’ of letters could influence word recognition. For the sake of the argument, we assume that the DRC model would include both lowercase and uppercase versions of each 55
Chapter 3 letter. The second problem that complicates making (correct) predictions about case alternation is that the DRC model does not include any intermediate level between the letter level and the word level, such as letter clusters or multiletter units. From the letter units onwards, words can be processed by the nonlexical route, in which the graphemes are converted to phonemes in a serial way, or by the lexical route, in which all letters are processed in parallel, and the word’s pronunciation is accessed directly in the orthographic lexicon, without previous print-to-sound decoding. Previous research on case alternation (Besner & McCann, 1987; Mayall, Humphreys, & Olson, 1997) has suggested, however, that its origins lie in the disruption of multiletter features. The lack of an intermediate level between the letter level and the word level implies that the DRC model would predict that case alternation does not affect word recognition. This prediction is refuted by empirical results, in which case alternation has repeatedly been found to disrupt word recognition (Besner & Johnston, 1989; Besner & McCann, 1987; Mayall & Humphreys, 1996). Thus, at present, the ACV98 model seems better able than the DRC model to account for some results in the present study, such as the differential effect of case alternation on words and pseudowords. Summarizing, we found that both normal reading children and dyslexics read shorter (pseudo)words faster than longer ones, suggesting that the dyslexics and both groups of normal readers alike relied, at least partly, on a sublexical reading procedure. The stronger effect of length in dyslexics showed that these children relied relatively more on a sublexical reading procedure than normal readers of the same age. All three groups read words faster than pseudowords. In addition, the effect of length was smaller on words than on pseudowords. These findings indicate the use of at least some lexical knowledge in both dyslexics and normal reading children. Dyslexics were relatively more hampered by case alternation than normal readers of the same age. Overall, words and pseudowords were affected by case alternation to the same extent. This suggests that in children of this age, no lexical feedback is generally available to compensate for the visual disruption caused by case alternation. However, for words of six letters, the results did suggest that more lexical feedback might have been available to the normal reading 10-year-olds than to the dyslexics. The results were related to two current computational models of reading.
56
Visual word features and the acquisition of orthographic knowledge
Chapter 4 The effect of visual word features on the acquisition of orthographic knowledge4
Research with adults has shown that the distortion of visual word features, and in particular of the multiletter features within words, hampers word recognition. In this study, ‘CaSe MiXiNg’ was employed to examine the effect of disrupting visual word features on the acquisition of orthographic knowledge in children. During the training, 18 beginning and 27 advanced readers (in Grades 2, 4, and 5) repeatedly read a set of pseudowords in either lowercase or mixed case. During this training, case mixing appeared to impair reading speed in both reader groups. At posttest, 1 day after the training, case format was either the same as or different from that during the training. Lowercase pseudowords were recognized faster after a lowercase training than after a mixed-case training. In a second study, case was found not to affect the rapid naming of single letters. The combined results suggest that case mixing disrupted the multiletter features in pseudowords and that the disruption of these features can affect the acquisition of orthographic knowledge.
4
Martens, V. E. G. & de Jong, P. F. (2006a). The effect of visual word features on the acquisition of orthographic knowledge. Journal of Experimental Child Psychology, 93 (4), 337-356. 57
Chapter 4 Introduction Learning to read accurately and quickly is generally believed to require the acquisition of orthographic knowledge, establishing associations between (parts of) written words and (parts of) spoken words (e.g., Ehri, 1992; Share, 1995; Stanovich, 1993). A large body of research has shown that phonological skills are of major importance for the acquisition of orthographic knowledge (for reviews see Goswami & Bryant, 1990; Share, 1995; Vellutino, Fletcher, Snowling, & Scanlon, 2004; Wagner & Torgesen, 1987). However, there are several reasons to believe that other factors may also affect orthographic learning. For example, in Share’s (1995) selfteaching model of reading acquisition, the acquisition of orthographic knowledge of a novel word is viewed as a two-step process. In the first step, the word is phonologically recoded. The success of this step is heavily affected by phonological abilities. If the first step is successful (i.e., if the word is identified correctly), this provides an opportunity to acquire orthographic knowledge. Thus, the second step of this model concerns the establishment of orthographic knowledge, and the success of this second step, as argued by Share (1995), might be dependent on visual/orthographic processing abilities (Share, 1999). Accordingly, on top of phonological processing abilities, differences in visual/orthographic processing might determine, as a secondary source of variance, the acquisition of orthographic knowledge (e.g., Cunningham, Perry, Stanovich, & Share, 2002). A more empirical reason is provided by evidence from research on dyslexia. If phonological skills were the only factor to influence orthographic learning, then the presence of good phonological skills would guarantee the acquisition of orthographic knowledge. However, a number of cases of developmental dyslexics with good phonological skills have been reported (e.g., Castles & Coltheart, 1996; Hanley & Gard, 1995; Romani, Ward, & Olson, 1999). A further reason for the possible importance of visual/orthographic factors for the acquisition of orthographic knowledge stems from research on the rapid automatized naming of symbols (RAN) (Denckla & Rudel, 1974). In general, the relationship of reading ability with RAN has been found to be partly independent of its relation with other phonological skills such as phonological awareness and working memory (e.g., de Jong & van der Leij, 1999; Wolf & Bowers, 1999). Although the interpretation of what RAN reflects is still disputed, several researchers have emphasized its nonphonological properties and have hypothesized that RAN is of particular importance for the acquisition orthographic knowledge as exemplified in sight word reading and fluency (Manis, Seidenberg, & Doi, 1999; Wolf & Bowers, 1999). In line with a nonphonological interpretation, Bowers (2001) suggested that RAN 58
Visual word features and the acquisition of orthographic knowledge reflects the speed of processing of visual letter strings. This interpretation would imply that quick processing of low-level visual features is important for the acquisition of orthographic knowledge. The focus of the current study is on the relation between visual processing and the acquisition of orthographic knowledge. Some evidence for the importance of visual processing in learning to read is provided by research on dyslexia. A common observation, at least among dyslexics learning to read in a more transparent orthography, is that they tend to adopt a serial reading strategy. This observation is supported by eye movement studies (e.g., de Luca, Borrelli, Judica, Spinelli, & Zoccolotti, 2002; de Luca, di Pace, Judica, Spinelli, & Zoccolotti,1999; Hutzler & Wimmer, 2004), in which dyslexics were found to display more eye movements during reading than were normal readers. This serial letter-by-letter reading strategy suggests that dyslexics are less proficient in using multiletter units during reading. Multiletter units are units larger than single letters and smaller than whole words. Of course, the deficient use of multiletter units by dyslexic readers could be due to their impairments in phonological processing. However, it might also be caused by a problem in the visual processing of multielements (e.g., Marendaz, Valdois, & Walch, 1996). In support of this view, Pammer, Lavis, Hansen, and Cornelissen (2004) found that dyslexics were less sensitive to the position of symbols in a briefly presented string of nonalphabetic but letter-like symbols than were normal readers. This difference could not be explained by dyslexics’ impairment in phonological processing, because the symbols were very difficult to name and were presented only briefly (100 ms). Instead, Pammer and colleagues (2004) proposed that “some aspect of pre-orthographic processing may represent a hitherto unrecognized visual component in children’s reading difficulties” (p. 607). This component might, as noted, hamper the processing of multiletter units (see also a recent study by Hawelka & Wimmer, 2005). Further evidence for the importance of low-level visual processing is provided by research on the effects of case mixing on word recognition. Case mixing is the alternate use of lowercase and uppercase letters (eXaMpLe), and has repeatedly been shown to slow down word recognition in naming (Besner & Johnston, 1989; Besner & McCann, 1987; Mayall & Humphreys, 1996) and lexical decision (Besner & McCann, 1987; Mayall & Humphreys, 1996). The effect of case mixing has been attributed to the disruption of low-level visual word features (Besner & McCann, 1987), and in particular to the disruption of multiletter features, which pertain to the visual features of units that are larger than single letters and smaller than whole words (Mayall, Humphreys, & Olson, 1997). Accordingly, the 59
Chapter 4 primary effect of case mixing is to break up multiletter units (Mayall, et al., 1997). In a PET study, Mayall, Humphreys, Mechelli, Olson, and Price (2001) found that mixed-case words (as compared to normal-case words) elicited extra activation in an area that has been associated with visual attention, suggesting an increase in attentional processing. Mayall and colleagues (2001) stated that breaking up the multiletter units might be responsible for an increase in attentional demands. One explanation for this increase could be that a larger number of visual units had to be processed in parallel, which would require more attention capacity. Another explanation given by Mayall and colleagues (2001) for the larger attentional involvement in mixed-case reading was that the disruption of multiletter units induced serial letter-by-letter processing. The latter explanation could also account for the slowing down of reading in mixed-case words (see also Bowey, 1996; Pring, 1981; Whiteley & Walker, 1997; see also Besner & Johnston, 1989). Although there is evidence for a relation between individual differences in visual processing and reading ability, and for the involvement of visual processes in reading, few studies have been concerned with the effect of visual word features on the acquisition of orthographic knowledge. In the current study, we examined the effect of the distortion of visual word features, and in particular of the disruption of multiletter features, on orthographic learning in children. There is some evidence that in adults, the distortion of visual features of words can impede their later reading. In a study by Masson (1986), university students read words with each constituent letter presented in mirror image while the order of the letters remained the same. In addition, within each word, some of the letters were presented in uppercase, and others were presented in lowercase. Thus, the visual pattern formed by adjacent letters (i.e., the multiletter features) was changed. After this training phase, the trained and untrained words were presented again. As in the training, all words were presented with reversed letters. The untrained words consisted of either letters that had been encountered during the training, or consisted of letters that had not been seen in mirror image before. The results showed that untrained words consisting of trained letters were read faster than untrained words consisting of untrained letters, suggesting that the acquisition of the skill of reading transformed words transferred only to words consisting of letters that were encountered before in mirror image. More interesting for the current study was the finding that trained words given in the original mixed-case pattern were read faster than trained words presented in the complementary mixed-case pattern (i.e., previously lowercase letters were now presented in uppercase and vice versa). Masson (1986) concluded that visual patterns formed by adjacent letters are 60
Visual word features and the acquisition of orthographic knowledge important in word recognition. Put differently, this result strongly suggests that visual multiletter features affect the acquisition of orthographic knowledge. More evidence that visual features of words play a role in their later identification is provided by a study of Jacoby and Hayman (1987). They reported several studies in which students were required, during a study phase, to read sets of words that were presented in various visual formats. In the subsequent perceptual identification test, these words were presented again, but this time very briefly (~35 ms). During the study phase of Jacoby and Hayman’s first study, the words were presented in either uppercase or lowercase. At test, words were presented either in the same case or in the opposite case as in the study condition. The results of the test showed that lowercase words were more easily identified when they had been studied in lowercase than when they had been studied in uppercase. For uppercase test words, the presentation format during the study phase did not have an effect. In two subsequent studies, more severe methods of distortion of visual word features were employed. For example, in their third study, Jacoby and Hayman (1987) included a condition in which the letters of words were presented sequentially from left to right. Sequential presentation tends to break up multiletter units. In the perceptual identification test, all words were presented in lowercase. Jacoby and Hayman again found that visual distortion during study hampered word identification at test. This result suggests that the acquisition of orthographic knowledge is at least partly dependent on the visual multiletter features of a word. In the current study involving children, we did not use sequential presentation of letters to disrupt low-level visual word features, because this might require too much working memory capacity. Instead, to disrupt the visual word features, we employed CaSe MiXiNg. As an additional feature of the current study, it should be acknowledged that the overall majority of the studies on case mixing have involved adults. The one exception is a study by Mayall (2002) with 6- to 9year-olds. In that study, case mixing affected accuracy of word and nonword reading. To date, however, a study on the effect of case mixing on children’s reading speed and their acquisition of orthographic knowledge is lacking. The current study consisted of a training phase followed by a posttest. During the training, beginning and advanced readers repeatedly read a set of onesyllable pseudowords. The advantage of pseudowords is that readers will not have lexical orthographic knowledge of such words. Thus, the repeated presentation of pseudowords enabled the monitoring of the acquisition of lexical orthographic knowledge. During the training phase, the pseudowords were read in either lowercase or mixed case. In addition, the number of presentations of a pseudoword 61
Chapter 4 was varied. In one condition pseudowords were read four times, whereas in the other condition they were read eight times. Our main hypothesis was that pseudowords were read more slowly in the mixed-case condition than in the normal, lowercase condition. In addition, we expected the regular effect of frequency. Reading speed was expected to increase as a function of frequency. We also hypothesized that beginning readers might need more presentations to improve their reading speed than would more advanced readers (e.g., Ehri & Saltmarsh, 1995; Reitsma, 1983a; Share, 1999). At posttest, 1 day after the training, the presentation of the pseudowords was either the same as or different from the presentation format (lowercase or mixed case) during the training. We hypothesized that if more lexical orthographic knowledge was acquired after a lowercase training than after a mixed-case training, lowercase words in the posttest would be read faster if they had been trained in lowercase than if they had been trained in mixed case. We did not have a specific prediction about the effects of the training conditions on the reading of mixed-case pseudowords at posttest. However, from the results of Jacoby and Hayman (1987), we could expect that a training in mixed case does not hold an advantage to a training in lowercase, if the pseudowords are presented in mixed case in the posttest. In addition to the trained pseudowords, a set of untrained lowercase and mixed-case pseudowords was included in the posttest. Thus, we could examine the extent to which children acclimated to reading in mixed case. A straight comparison between the reading speed of trained items in the posttest and reading speed of the same items on the very first reading trial would not take into account the possible habituation to reading in mixed case as a result of the training. By comparing trained pseudowords to (new and) untrained ones in the posttest, we take into account the children’s experience with reading in mixed case. If untrained lowercase and mixedcase pseudowords are read equally fast in the posttest, it would indicate that children have become familiar with reading in mixed case, and case mixing no longer slows down the reading process. If that is the case, the differences in reading speed in the posttest can be explained in terms of the orthographic knowledge that has been acquired for these items. To provide more insight into the origins of the effect of case mixing, we conducted a second study. The aim of this second study was to investigate whether case mixing affects word recognition at the letter level or at a multiletter level. For that purpose, we administered three versions of the RAN letter task: a lowercase version, an uppercase version, and a mixed-case version. As the RAN task involves the naming of individual letters (i.e., letters in isolation), multiletter features are not 62
Visual word features and the acquisition of orthographic knowledge assumed to play a role in this task. Consequently, if children perform better on a lowercase RAN task than on a mixed-case one, this suggests that case mixing affects individual letter processing in children. Alternatively, if performances on lowercase and mixed-case RAN tasks are comparable, this suggests that case mixing does not affect individual letter processing, but probably influences word recognition by disrupting multiletter features. However, if the mixed-case RAN task would appear to be more difficult than the lowercase version, this might also be due to slower naming of uppercase letters than lowercase ones. Therefore, we also included an uppercase version of the RAN task, to test whether naming letters in uppercase is more difficult than naming them in lowercase. Study 1 Method Participants A group of younger beginning readers and a group of older more advanced readers participated. The beginning reader group consisted of 18 children in Grade 2 (9 boys and 9 girls). The advanced reader group consisted of 27 children in Grades 4 and 5 (18 boys and 9 girls). The children came from three different schools in the Netherlands. Permission for all children was obtained from the parents and the schools. All participants were normally achieving children. To ensure this, we assessed their reading ability, vocabulary, and nonverbal reasoning ability. Word reading ability was measured with the One Minute Reading Test (Een Minuut Test) (Brus & Voeten, 1979). This test is regularly used in Dutch education to evaluate early reading achievement. The test required the children to read aloud as many words as possible within one minute, from a word list of 116 words of increasing difficulty. The score consisted of the number of words read correctly within one minute. The passive vocabulary test was part of a standard intelligence test battery, the Revised Amsterdam Child Intelligence Test (Revisie Amsterdamse Kinder Intelligentie Test [RAKIT]) (Bleichrodt, Drenth, Zaal, & Resing, 1987). The test consisted of 60 items. On each item, a word was given, and the child was asked to choose the matching picture among four alternatives. After four consecutive incorrect answers, the test was stopped. The Raven Standard Progressive Matrices was used to measure nonverbal reasoning (Raven, Court, & Raven, 1986). Each item consisted of three rows of three geometric patterns. On each row, the patterns changed from left to right according to some common logic. The third picture on the 63
Chapter 4 third row was missing, and the child was asked to complete this row by choosing the correct alternative. All children scored within the normal range of the 30th to 80th percentiles on these three tests. Training Materials. A total of sixty one-syllable pseudowords were constructed, with each one consisting of four letters. Half of the pseudowords had a CVCC structure, and half had a CCVC structure. The pseudowords were made of bigrams that were taken from a list by Bakker (1990). Each pseudoword was constructed by putting together an initial bigram and a final bigram. A large variety of bigrams was used. The pseudowords did not include any multiletter graphemes (e.g., ‘ch’, ‘ng’, ‘ou’, ‘ui’), so case mixing never distorted the recognition of graphemes. All pseudowords were easily pronounceable. Presentation frequency during training could be either four times or eight times. In addition, the presentation format was varied; pseudowords were presented in either lowercase or mixed case (i.e., alternating lowercase and uppercase). Half of the mixed-case pseudowords started with a lowercase letter (e.g., jUnT); and half started with an uppercase letter (e.g., KnAf). To avoid confusion between capital I and lowercase l in the mixed-case pseudowords, i was presented only as a lowercase letter and L was presented only as an uppercase letter. Crossing presentation frequency (four or eight times) with presentation format (lowercase or mixed case) yielded four training conditions. Each of these four training conditions contained 12 pseudowords. For each of these four training conditions, half of the pseudowords were presented in lowercase and half in mixed case in the posttest. Thus, of the 12 pseudowords that had been trained four times in lowercase, 6 were presented in lowercase and 6 in mixed case in the posttest. Similarly, of the 12 pseudowords that had been trained four times in mixed case, 6 were presented in lowercase and 6 in mixed case in the posttest, etc. The posttest also included 12 previously untrained pseudowords, half of which were presented in lowercase. Thus, during the training, 48 out of 60 pseudowords were presented repeatedly. During the posttest, all 60 pseudowords were presented once. Pseudowords were assigned at random to the ten training/posttest conditions. Two different random assignments were used. Each child was randomly given one of these assignments. Procedure. In the training, 48 of the 60 pseudowords were presented repeatedly. The training was evenly spread over 2 consecutive days. Pseudowords in lowercase and pseudowords in mixed case were presented in separate blocks. On 64
Visual word features and the acquisition of orthographic knowledge both days, children read one lowercase block and one mixed-case block. The order of the blocks (lowercase or mixed case) was balanced across children. On the second training day, the order of the (case) blocks was reversed for each child. In each of these blocks, 12 pseudowords were presented twice and 12 pseudowords were presented four times. Thus, each block consisted of 72 trials (12 × 2 + 12 × 4 = 72). On each day, children read 72 lowercase trials and 72 mixed-case trials, amounting to 144 trials. Each lowercase and mixed-case block was subdivided into four different smaller blocks of 18 pseudowords, within which presentation order of the pseudowords was randomized. The 12 pseudowords that would be trained eight times occurred once in each of these four smaller blocks; and the 12 pseudowords that would be trained four times occurred once in two of four of these smaller blocks. This way, a given item was not presented again until several other pseudowords had been presented. Pseudowords were presented individually in the middle of a 14-in. screen of an Apple Macintosh LC 475 computer. The pseudowords were presented in 48-point Amsterdam font, in black letters on a white background. All trials started with a short beep to focus the child’s attention. The stimulus appeared 750 ms after the beep and disappeared from the screen as soon as the voice key was triggered. The voice key registered responses, measuring the time from target onset to response onset. After each response, the test assistant marked its accuracy by pressing the appropriate key on the keyboard (correct, incorrect, or invalid if the voice key had not been set off properly or had been triggered by another sound). The child was not given feedback on the correctness of his or her response. The test assistant made the next word appear on the screen using the keyboard. One second later, a beep announced the next trial. Children were told that they would read words that did not really exist on the computer, and they were required to read these words aloud as fast as possible, without making errors. They were told in advance whether the words consisted of lowercase or mixed-case letters. Children were explicitly encouraged to refrain from speaking until they knew the entire word so as to make sure any sounding out of the word occurred silently. Furthermore, they were urged to avoid saying “uh”, because this would set off the voice key, immediately making the word disappear from the screen. The experiment began with five practice trials in the appropriate case. The practice trials familiarized the children with the task, and gave the test assistant the opportunity to check the sensitivity level of the voice key. Between the two blocks, 65
Chapter 4 there was a short break, during which children were given cartoon-like puzzles for about five minutes. Posttest The posttest consisted of the 48 trained pseudowords and a set of 12 untrained pseudowords. Thus, in the posttest, 60 pseudowords were read. Half of these pseudowords were presented in lowercase; half were presented in mixed case. Every pseudoword was read once. Pseudowords in lowercase and pseudowords in mixed case were presented in separate blocks. Children who had started with the lowercase block in the second training session started with the mixed-case block in the posttest, and vice versa. Procedure The study consisted of a screening, a training, and a posttest. First, in the screening, the passive vocabulary test and nonverbal reasoning test were administered to each group (e.g., all children in Grade 2 of a given school at the same time), taking 45 minutes each. Word reading ability was measured individually, taking about 3 minutes for each child. The screening of the three schools was spread over 3 weeks. The training began 3 weeks after the end of the screening. Children were tested individually in a separate room where testing could take place relatively quietly. Each child was trained on 2 consecutive days. On each of the 2 training days, testing took about 30 minutes. One day after the last training day, the posttest was administered, which took about 10 minutes. The tests were administered by six trained assistants. Results The results are presented in two different sections. First, we present error scores and reading speed during training. Second, we present error scores and reading speed on the posttest. As the patterns of results were highly similar for the advanced readers in Grades 4 and 5, they were combined into one group of advanced readers for the analyses. Training Errors. Over trials, error percentages varied between 3.8 and 14.9 % for the beginning readers and between 0.0 and 6.3 % for the advanced readers. We excluded the advanced readers from the analyses, because of the very low error percentages. 66
Visual word features and the acquisition of orthographic knowledge Furthermore, one of the assumptions of multivariate analysis of variance (MANOVA) is that the variance is greater than 0.0. Separate analyses were done for pseudowords that were read four times and pseudowords that were read eight times for two reasons. Firstly, due to the presentation format, twice as much time elapsed between trials for pseudowords that were read only four times compared to pseudowords that were read eight times. As mentioned earlier, pseudowords that were presented eight times during the training occurred once in every block of 18 trials. Pseudowords that were presented four times occurred only once in two blocks. Thus, more trials in mixed case were read in between for a specific word that was trained four times than for a specific word that was trained eight times. Consequently, the amount of reading experience with mixed-case stimuli in general after the same number of trials (of those specific words) was twice as large for pseudowords that were read four times than for pseudowords that were read eight times. The error percentages for beginning readers were subjected to a MANOVA for repeated measures with case (lower or mixed) and trial (1 – 8) as withinparticipants factors. The analysis revealed that case had no significant effect on errors, F (1, 17) = 1.47. For pseudowords that were read eight times, there was no significant change in error percentages as they were presented more often, F (7, 119) = 1.64. There was no significant interaction between case and trial, F < 1. For error percentages on pseudowords that were read four times, the results were virtually identical. A MANOVA for repeated measures with case (lower or mixed) and trial (1 – 4) as within-participants factors again showed that case had no effect on error percentages, F < 1. Error percentages did not change significantly as the pseudowords were presented more often, F < 1. The interaction between case and trial approached significance, F (3, 51) = 2.69, p = 0.056, η2p = 0.14. This effect could not be interpreted, because there was no systematic change in the difference between error percentages for lowercase and mixed-case pseudowords over trials. Reading speed. The analyses were based on response times for valid and correct trials only. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials were excluded from the analyses (1.02 %, 7.85 %, and 2.93 % for the beginning readers, respectively, and 0.49 %, 1.85 %, and 1.95 % for the advanced readers, respectively). For each child in each condition, a mean and a standard deviation were computed. Response times that deviated more than 2.5 standard deviations from the child’s mean were considered to be outliers and were excluded from the analyses. In all, the outliers, incorrect trials, and invalid
67
Chapter 4 trials amounted to 16.92 % of the training data for the beginning readers and to 8.95 % for the advanced readers (for a total of 12.14 % of the training data). For each child in each condition, mean response times were computed. The means for each child were based on at least half of the pseudowords in each condition. Three beginning readers and two advanced readers did not meet this criterion in all of the conditions. To keep all children in the analyses, the missing means (0.74 % of the training data) were estimated with the expectation maximization (EM) algorithm (Little & Rubin, 1987) separately for beginning and advanced readers. The variance in response times appeared to differ substantially between the groups. The variance among the beginning readers was approximately 25 times larger than the variance among the advanced readers. One of the assumptions in multivariate analysis of variance (MANOVA) is equal population variances for the groups (Stevens, 2002; p. 257). To make these variances equal, we converted the response times in milliseconds to mean numbers of pseudowords that were read per second (cf. Ratcliff, 1993). In the left panel of Figure 1, reading speed is displayed for lowercase and mixed-case pseudowords that were read eight times by each group. Reading speed scores were subjected to a MANOVA for repeated measures with training format (lowercase or mixed case) and trial (1 – 8) as within-participants factors and reading level (beginning or advanced) as a between-participants factor. Advanced readers were significantly faster than beginning readers, F (1, 43) = 107.67, p < 0.001, η2p = 0.72. The effect of training format was also significant, F (1, 43) = 24.94, p < 0.001, η2p = 0.37. Lowercase pseudowords were read faster than mixed-case pseudowords. Reading speed increased as pseudowords were read more often, F (7, 301) = 23.84, p < 0.001, η2p = 0.36. In addition, there was a significant training format by trial interaction, F (7, 301) = 4.49, p < 0.001, η2p = 0.10. The effect of case mixing on reading speed decreased as the pseudowords were read more often. No other interaction effects were significant. For lowercase and mixed-case pseudowords that were read four times, the results were similar to those for pseudowords that were read eight times. Mean reading speeds of the pseudowords that were read four times are presented in the right panel of Figure 1. Advanced readers were significantly faster than beginning readers, F (1, 43) = 96.92, p < 0.001, η2p = 0.69. Training format had a significant effect on reading speed, F (1, 43) = 17.91, p < 0.001, η2p = 0.29, with lowercase pseudowords being read faster than mixed-case ones. Reading speed increased as pseudowords were read more often, F (3, 129) = 21.26, p < 0.001, η2p = 0.33. In 68
Visual word features and the acquisition of orthographic knowledge 1.8 Advanced readers lower case
Pseudowords read per second
1.6
1.4
Advanced readers mixed case
1.2
Beginning readers lower case
1
Beginning readers mixed case
0.8
0.6 1
2
3
4
5
Trial
Figure 1.
6
7
8
1
2
3
4
Trial
Reading speed (in mean number of pseudowords read correctly per
second) for pseudowords that were read in lowercase and mixed case by beginning and advanced readers. The left panel displays pseudowords that were read eight times, and the right panel displays pseudowords that were read four times.
addition, there was a significant interaction between training format and trial, F (3, 129) = 4.51, p < 0.005, η2p = 0.10, indicating that the effect of case mixing on reading speed decreased as pseudowords were presented more often. Posttest Errors. The posttest consisted of pseudowords that had been trained four or eight times. In addition, a set of pseudowords that had not been trained was presented. Both trained and untrained pseudowords were presented in either lowercase or mixed case. In Table 1, the mean error percentages on the posttest are displayed for pseudowords that had been trained zero, four, or eight times in lowercase or mixed case and were presented in lowercase or mixed case in the posttest.
69
Chapter 4 Table 1 Mean error percentages for pseudowords that were read 0, 4, or 8 times in lower or mixed case during training and were tested in lower or mixed case, for beginning and advanced readers Nontrained
Trained
0 Reading
Posttest
level
Format
Beginning
Lowercase Mixed case
Advanced
Lowercase Mixed case
Note.
4 Lowercase
8 Mixed
Lowercase
case
Mixed case
9.26
6.48
7.41
5.56
5.56
(10.26)
(14.16)
(15.36)
(11.43)
(8.08)
11.11
7.41
5.56
2.78
3.70
(11.43)
(13.06)
(8.08)
(6.39)
(7.13)
1.85
1.23
0.62
0.00
0.00
(7.06)
(4.49)
(3.21)
(0.00)
(0.00)
1.23
1.23
0.62
0.62
0.00
(4.49)
(4.49)
(3.21)
(3.21)
(0.00)
Standard deviations are in parentheses.
As the advanced readers had very low error percentages in all conditions (ranging from 0.0 to 1.85 %), we analysed errors only for the beginning readers. In a first analysis, we examined the effect of training format on reading accuracy in the posttest. In this analysis, we included only the pseudowords that had been trained. A MANOVA for repeated measures with training format (lowercase or mixed case), posttest format (lowercase or mixed case), and training frequency (four or eight times) as within-participants factors showed no significant effects on error percentages. In a second analysis, we included both trained and untrained pseudowords. We included only the data from the lowercase training in this analysis, because in the literature, case mixing effects are always measured on items that have been read in lowercase beforehand. A MANOVA for repeated measures with posttest format (lowercase or mixed case) and training frequency (zero, four, or eigth) as withinparticipants factors did not show any significant effects on errors. Reading speed. The data cleaning procedure for the posttest was the same as for the training. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials were excluded from the analyses (0.56 %, 6.48 %, and 4.17 % for the beginning readers, respectively, and 0.43 %, 0.74 %, and 1.85 % for the advanced readers, respectively). For each child for each condition, a mean 70
Visual word features and the acquisition of orthographic knowledge and a standard deviation were computed. Response times that deviated more than 2.5 standard deviations from the child’s mean were considered outliers and excluded from the analyses. In all, the outliers, incorrect trials, and invalid trials amounted to 10.83 % of the posttest data for the beginning readers, and to 2.78 % for the advanced readers (for a total of 6 % of the posttest data). For each child in each condition, mean response times were computed. The means for each child were based on at least half of the pseudowords in each condition. In Table 2, the mean numbers of pseudowords that were read correctly per second are given for each condition. Table 2 Mean number of pseudowords read per second in lowercase and mixed-case posttest after having been trained zero, four, or eight times in lowercase or mixed case for beginning and advanced readers Nontrained
Trained
0 Reading
Posttest
level
Format
Beginning
Lowercase Mixed case
Advanced
Lowercase Mixed case
Note.
4 Lowercase
8 Mixed
Lowercase
case
Mixed case
0.801
0.889
0.888
1.001
0.904
(0.284)
(0.246)
(0.258)
(0.292)
(0.241)
0.821
0.784
0.876
0.952
0.894
(0.218)
(0.237)
(0.312)
(0.278)
(0.257)
1.515
1.625
1.574
1.646
1.591
(0.240)
(0.255)
(0.228)
(0.193)
(0.211)
1.504
1.545
1.571
1.597
1.589
(0.204)
(0.225)
(0.214)
(0.249)
(0.223)
Standard deviations are in parentheses.
One of the main research questions was whether training format affects the acquisition of orthographic knowledge. First, we analysed reading speed for the pseudowords that had been trained. A MANOVA for repeated measures with training format (lowercase or mixed case), posttest format (lowercase or mixed case), and training frequency (four or eight times) as within-participants factors and reading level (beginning or advanced) as a between-participants factor was performed. Advanced readers read significantly faster than beginning readers, F (1, 43) = 116.77, p < 0.001, η2p = 0.73. A significant effect for training frequency was found, F (1, 43) = 21.27, p < 0.001, η2p = 0.33. Pseudowords that had been read 71
Chapter 4
Pseudowords read per second
eight times were recognized faster than pseudowords that had only been read four times during training. Training format approached significance, F (1, 43) = 2.89, p = 0.096, η2p = 0.06. Pseudowords that had been trained in lowercase were recognized somewhat faster than pseudowords that had been trained in mixed case. Posttest format approached significance, F (1, 43) = 3.96, p = 0.053, η2p = 0.08 with pseudowords presented in lowercase being read faster than pseudowords presented in mixed case. More importantly, however, the interaction between training format and posttest format was significant, F (1, 43) = 5.75, p < 0.05, η2p = 0.12. After a lowercase training, lowercase pseudowords were read faster than mixed-case pseudowords. After a mixed-case training, however, lowercase pseudowords were read as fast as mixed-case pseudowords. This interaction is shown in Figure 2. Contrasts revealed that reading in lowercase was faster after a lowercase training than after a mixed-case training, F (1, 43) = 7.09, p < 0.05, η2p = 0.14. However, reading in mixed case was not faster after a mixed-case training than after a lowercase training, F < 1. There was also a training format by training frequency interaction, F (1, 43) = 8.53, p < 0.01, η2p = 0.17. The increase in reading speed from four to eight readings was larger in lowercase than in mixed case. In addition, a significant training frequency by reading level interaction was found, F (1, 43) = 4.95, p < 0.05, η2p = 0.10. The reading speed of beginning readers increased more as a result from
1.30 1.28 1.26 lower case posttest mixed case posttest
1.24 1.22 1.20 lower case
mixed case
Training Format
Figure 2.
Reading speed for pseudowords that had been trained in lowercase or
mixed case and presented in lowercase or mixed case in the posttest.
72
Visual word features and the acquisition of orthographic knowledge four additional exposures than did the reading speed of advanced readers. The latter two interactions were refined by a three-way interaction among training format, training frequency and reading level, F (1, 43) = 4.54, p < 0.05, η2p = 0.10. Contrasts revealed that the reading speed of beginning readers increased more as a result from four additional exposures than did the reading speed of advanced readers in lowercase, F (1, 43) = 24.79, p < 0.001, η2p = 0.37. However, in mixed case, the increases in reading speed after four additional exposures were similar for beginning and advanced readers, F (1, 43) = 1.22. To examine the extent to which children had gotten accustomed to case mixing, a set of untrained pseudowords was included in the posttest. In a subsequent analysis, we compared the reading speed for pseudowords that had been trained zero, four, and eight times. In this analysis the untrained pseudowords were included. We included only the response times for pseudowords that had been trained in lowercase, because case-mixing effects are generally measured only on words that have been read in lowercase beforehand. A MANOVA for repeated measures with posttest format (lowercase or mixed case) and training frequency (zero, four, or eight times) as within-participants factors and reading level (beginning or advanced) as a between-participants factor was performed. As in the previous analysis, advanced readers read significantly faster than beginning readers, F (1, 43) = 116.96, p < 0.001, η2p = 0.73. A main effect of posttest format was found, F (1, 43) = 5.65, p < 0.05, η2p = 0.12. Pseudowords presented in lowercase were recognized faster than pseudowords presented in mixed case. Again, training frequency also had a significant effect on reading speed, F (2, 86) = 35.01, p < 0.001, η2p = 0.45. Repeated contrasts revealed that pseudowords that had been read eight times were recognized faster than pseudowords that had been read four times, F (1, 43) = 24.79, p < 0.001, η2p = 0.37, which were, in turn, recognized faster than untrained pseudowords, F (1, 43) = 11.65, p < 0.001, η2p = 0.21. The training frequency by reading level interaction, F (2,86) = 4.69, p < 0.05, η2p = 0.10, indicated that reading frequency affected beginning readers different than advanced readers. Contrasts revealed that the difference in reading speed between pseudowords that had been trained zero and four times tended to be larger for the advanced readers than for the beginning readers, F (1, 43) = 2.90, p = 0.096, η2p = 0.06, whereas the difference in reading speed between pseudowords that had been trained four and eight times was larger for the beginning readers than for the advanced readers, F (1, 43) = 8.40, p < 0.01, η2p = 0.16. The interaction between posttest format and training frequency approached significance, F (2, 86) = 3.05, p = 0.053, η2p = 0.07. This interaction is shown in Figure 3. Subsequently, we specified 73
Chapter 4 two contrasts: between pseudowords that were trained four and eight times; and between trained (four and eight times) and untrained (zero times) pseudowords. The first contrast showed that case mixing affected pseudowords that had been trained (four or eight times) to the same extent, F (1, 43) = 1.06. The second contrast showed that case mixing did not affect untrained items, whereas case mixing did affect trained items, F (1, 43) = 5.65, p < 0.05, η2p = 0.12.
Pseudowords read per second
1.35 1.3 1.25 lower case posttest
1.2
mixed case posttest
1.15 1.1 1.05 0
4
8
Training Frequency
Figure 3.
Reading speed in the posttest after lower case training (in mean number of
pseudowords read per second) as a function of training frequency.
Discussion The two main findings of Study 1 were as follows. First, during the training, case mixing slowed down (pseudo)word recognition in children. This replicated the effect of case mixing typically found in adults (Besner & Johnston, 1989; Besner & McCann, 1987; Mayall & Humphreys, 1996). Second, during the lowercase posttest, pseudowords that had been trained in lowercase were read faster than pseudowords that had been trained in mixed case. Before discussing these results and some additional findings, we first report the results on Study 2, in which the locus of the effect of case mixing was investigated. 74
Visual word features and the acquisition of orthographic knowledge Study 2 In the second study, we examined whether case mixing affects the naming of single letters. To assess single letter naming, we administered several RAN tasks involving the reading aloud of letter names as fast and as accurately as possible. We included three different versions of the RAN task: a lowercase version, an uppercase version, and a mixed-case version. Thus, we could examine whether naming letters in uppercase, in general, is more difficult than naming them in lowercase. More specifically and of particular interest to the current article, we could test whether case mixing affects single letter reading. Method Participants As in Study 1, a group of younger beginning readers and a group of older more advanced readers participated in the current study. The beginning reader group consisted of 130 children in Grade 2 (78 boys and 52 girls). The advanced reader group consisted of 140 children in Grade 4 (67 boys and 73 girls). The children came from six different schools in The Netherlands. Permission for all children was obtained from the parents and the schools. As in Study 1, children’s passive vocabulary and word reading ability were assessed. The same tests were used as in Study 1. To prevent severe difficulties on either the passive vocabulary test or the word reading ability test from clouding the results on the RAN tasks, children with a standard score of more than 2 standard deviations below the population mean on either one of these tests were excluded from the analyses. Materials Three versions of the RAN tasks were administered: a lowercase version, an uppercase version, and a mixed-case version. In each of these three tasks, 5 letters (o, a, d, s, and p) were each presented ten times in random order. The letters were presented in five rows of 10 letters. Procedure Children were asked to read aloud the letter names of the letters as fast and as accurately as possible. First, children practiced with a separate row of 10 letters, until they read this practice row without errors. Time was measured using a
75
Chapter 4 stopwatch. Each child read one version of the RAN task. The different versions of the RAN tasks were randomly assigned to the children. Results and Discussion The mean numbers of letters that were read per second on the three RAN tasks are displayed in Table 3. To test whether case affects the reading of isolated letters, an analysis of variance (ANOVA) was performed with reading level (beginning or advanced) and version of the RAN task (lowercase, uppercase, or mixed case) as between-participants variables and mean number of letters read per second as the dependent variable. This analysis showed that advanced readers named the letters significantly faster than did beginning readers, F (1, 264) = 247.23, p < 0.001. More importantly, case did not affect RAN, F (2, 264) = 1.46, p > 0.20. Posthoc tests showed there were no differences between the lowercase RAN task and the uppercase RAN task (p > 0.20), between lowercase and mixed case (p > 0.20), or between uppercase and mixed case (p > 0.20). Table 3 Mean number of letters read per second on the RAN tasks by the beginning and the advanced readers RAN version Lowercase
Uppercase
Mixed case
Beginning readers
1.40 (0.36)
1.53 (0.33)
1.45 (0.40)
Advanced readers
2.10 (0.37)
2.13 (0.33)
2.21 (0.35)
Note.
Between parentheses are the standard deviations.
To check whether the same results would be obtained for the most typical average readers, a second ANOVA was performed. In this analysis, only those children who scored within 1 standard deviation of the population mean on both word reading ability and passive vocabulary were included. This analysis yielded the same results. Thus, case did not to affect isolated letter naming for either typical average readers or a larger sample of children covering a wider range of reading ability.
76
Visual word features and the acquisition of orthographic knowledge General Discussion The main aim of Study 1 was to investigate whether the disruption of visual word features within a pseudoword would impede the acquisition of orthographic knowledge. The visual word features were disrupted by presenting pseudowords in mixed case. At the outset of the training, children read lowercase pseudowords faster than mixed-case ones. This result is in accordance with studies on adult word recognition in mixed-case naming tasks (Besner & Johnston, 1989; Besner & McCann, 1987; Mayall & Humphreys, 1996). During the training, as expected, reading speed for both lowercase and mixed-case pseudowords increased. The disruptive effect of case mixing decreased as the pseudowords were read more often. Assuming that an increase in reading speed reflects the acquisition of orthographic knowledge, this indicates that orthographic knowledge was acquired in both the lowercase and the mixed-case training. More important, as hypothesized, reading in lowercase at posttest was faster after a lowercase training than after a mixed-case training. This suggests that, indeed, less orthographic knowledge was acquired during a mixed-case training than during a lowercase training. This effect in the posttest cannot have been due to a switch in visual presentation in general (i.e., from lowercase to mixed case). If it were, then reading in mixed case in the posttest should have been faster after a mixed-case training than after a lowercase training. However, reading in mixed case was as fast after a mixed-case training as after a lowercase training. Further support for the notion that disrupting visual word features within a (pseudo)word impedes the acquisition of orthographic knowledge is provided by the results on the untrained pseudowords in the posttest. These untrained pseudowords were presented in lowercase or in mixed case. They were included in the posttest to examine the extent to which children had gotten accustomed to case mixing. Whereas after a lowercase training case mixing slowed down reading trained pseudowords (see left part of Figure 2, and Figure 3), case mixing did not slow down reading untrained pseudowords (Figure 3). Thus, case mixing no longer affected reading speed. Therefore, the differences in reading speed in the posttest for trained lowercase and mixed-case pseudowords should be explained in terms of the orthographic knowledge that had been acquired for these pseudowords. During training, orthographic knowledge was acquired for the pseudowords that were repeatedly read. For the untrained pseudowords, no orthographic knowledge had been acquired. As case mixing did not affect reading speed of untrained pseudowords in the posttest, we conclude that children had learned to read in mixed case. This is also supported by the decreasing effect of case mixing during the 77
Chapter 4 training. Consequently, the case-mixing effect on trained items in the posttest can be ascribed to the difference in orthographic knowledge that had been acquired from the lowercase and mixed-case training. Our results are in line with the findings of Jacoby and Hayman (1987), who found that distortion of visual multiletter features (by presentation in uppercase) hampered subsequent identification of those words in a lowercase test. In contrast, uppercase words in the test were not more likely to be identified if they had been studied in uppercase than if they had been studied in lowercase. Jacoby and Hayman concluded that distortion of visual word features disrupts visual cues that are present in normal lowercase words, which can normally be used for transfer in (pseudo)word recognition. On the basis of the kinds of visual disruption they employed (i.e., uppercase, degraded type face, or sequential presentation), however, it remained unclear whether word recognition was disrupted by the distortion of individual letter visual features or multiletter visual features. In effect, all three kinds of visual disruption they employed affected (lowercase) multiletter features. Our results on the RAN tasks in Study 2 may clarify this matter. The results on the RAN tasks provide evidence that distortion of visual word features affects word recognition by disrupting visual multiletter features. The RAN tasks in mixed case were read as fast as the RAN tasks in lowercase. Thus, in single letter reading case mixing did not influence reading speed, whereas in pseudoword reading, case mixing did influence reading speed. Consequently, the influence of case mixing does not seem to be due to the disruption of individual letter identification. Instead, the disrupting effect of case mixing in word recognition seems to be due to the distortion of multiletter features. It was also shown in Study 2 that letters in uppercase were read as fast as letters in lowercase. This suggests that recognizing uppercase letters in itself is not more difficult than recognizing letters in lowercase. Therefore, the effect of case mixing cannot be traced back to a greater difficulty of recognizing letters in uppercase than in lowercase. It may be worth noting, however, that the children were asked to read aloud the letter names of the letters in the RAN tasks. One might argue that reading aloud letter sounds would be more closely related to word reading. In another study, however, 22 beginning and 22 advanced readers were asked to read aloud the letter sounds in lowercase, uppercase, and mixed-case versions of the RAN tasks (Martens & de Jong, unpublished manuscript). These data suggested that case did not affect the rapid naming of letter sounds either; thus, they support the notion that case mixing does not affect isolated letter naming. Therefore, our findings on the RAN tasks add to a more general understanding of the origins of the case-mixing effect, 78
Visual word features and the acquisition of orthographic knowledge and is in line with a study by Mayall and colleagues (1997), who suggested that the effect of case mixing might be due to a disruption of multiletter features. Jacoby and Hayman (1987) commented briefly on their finding that, in an uppercase test, words studied in uppercase held no advantage to words studied in lowercase (paralleling our findings with lowercase and mixed case). They suggested that lowercase provides more distinctive word shapes than does uppercase. Yet, this explanation seems implausible in the current study, because mixed case can hardly be conceived to provide less distinctive word shapes than lowercase. However, an alternative explanation is that two opposite effects cancel each other out. On the one hand, if we assume that more orthographic knowledge is acquired after a lowercase training than after a mixed-case training (as is suggested by the results), then reading in mixed case in the posttest should also be faster after a lowercase training than after a mixed-case training. On the other hand, if a training in mixed case results in knowledge of word-specific multiletter features in mixed case, then reading in mixed case in the posttest would be faster after a mixed-case training than after a lowercase training. Thus, the advantage of a lowercase training over a mixed-case training might be cancelled out by word-specific visual information acquired in mixed case. Besides the main finding, that the processing speed of visual word features affects the acquisition of orthographic knowledge, the current study yielded some additional findings worth mentioning. Whereas, to date, all but one of the studies with case mixing involved adults, the current study examined the effects of case mixing in children. Case mixing appeared to hamper the reading speed of both beginning and advanced readers. Interestingly, beginning readers were slowed by case mixing to the same extent as were advanced readers. This suggests that both the beginning and advanced readers in our sample relied on multiletter features during word recognition. Advanced readers were found to learn more quickly from the first four readings in lowercase than were beginning readers, whereas beginning readers benefited more from four additional readings than did advanced readers. These results suggest that advanced readers build up orthographic knowledge relatively quickly, whereas beginning readers learn more slowly and continue to learn over more trials. These results are in line with earlier research (e.g., Ehri & Saltmarsh, 1995; Reitsma, 1983a; Share, 1999). In mixed case, however, the increases in reading speed as a result from four additional readings were similar for beginning and advanced readers. Possibly, advanced readers learned faster in lowercase due to their reading experience (in lowercase). However, when visual word features were 79
Chapter 4 disrupted, advanced readers could not rely on the familiar (lowercase) multiletter features. Thus, in mixed case, reading experience was the same for beginning and advanced readers. This suggests, although somewhat speculatively, that at least part of the difference in the speed with which beginning and advanced readers acquire orthographic knowledge stems from the ability to rely on multiletter features. In contrast to Mayall (2002), we found no effect of case mixing on accuracy. This may be ascribed to the difference in orthographic depth of English and Dutch. Dutch has a shallow orthography in which there often is a one-to-one correspondence between graphemes and phonemes. This consistency in print-tosound correspondence results in high accuracy, even in beginning readers. English, in contrast, has a deep orthography in which the relationship between graphemes and phonemes is much more inconsistent. Consequently, readers of an inconsistent orthography must learn to rely on larger units in word recognition, whereas readers of a consistent orthography can rely on smaller processing units (Goswami, 1997; Goswami, Ziegler, Dalton, & Schneider, 2003; Ziegler, Perry, Jacobs, & Braun, 2001). Research has shown that children learning to read in English take longer to reach accuracy levels comparable to those of readers of shallow orthographies such as German, Spanish, and Dutch (e.g., Wimmer & Goswami, 1994). This may explain why Mayall found a negative effect of case mixing on accuracy in English readers, whereas we found no such effect in Dutch readers. To summarize, the current study yielded three primary results. First, we found that children, like adults, are susceptible to case mixing. At the start of the training, pseudowords presented in lowercase were read faster than pseudowords presented in mixed case. Second, the results on the RAN tasks suggest that the origins of the effect of case mixing lie in the disruption of multiletter features and not in a disruption of individual letter identification. Third and most important, visual multiletter features were found to play a role in the acquisition of orthographic knowledge.
80
Repeated reading
Chapter 5 Effects of repeated reading in dyslexic and normal reading children5
Two studies are reported in which the effect of repeated reading on the acquisition of orthographic knowledge was examined. Acquisition of orthographic knowledge was assessed by comparing the effect of word length on reading speed before and after a training. In both studies, children read the same words and pseudowords of 4-6 letters 15 times. In Study 1, dyslexic children repeatedly read the (pseudo)words in either alternated case or in lowercase. In Study 2, beginning and advanced normal readers repeatedly read the (pseudo)words in lowercase. In all three groups, reading speed improved without a concomitant change in the effect of length on reading speed. These results suggest that no development from a predominant sublexical reading procedure to a progressively larger role for a lexical reading procedure took place, thereby giving no evidence of the acquisition of orthographic knowledge.
5
Martens, V. E. G., & de Jong, P. F. (2006d). Effects of repeated reading in dyslexic and normal reading children. Manuscript submitted for publication. 81
Chapter 5 Introduction Learning to read entails the establishment of firm associations between written and spoken forms of words. The first stages of learning to read are characterized by recoding the constituent letters of a word into phonemes, and subsequently blending these together to build a word’s pronunciation (e.g., Ehri, 1992,1998; Share, 1995). With reading experience, the grapheme-to-phoneme conversion process speeds up and readers implicitly learn what letter and sound combinations co-occur frequently. Thus, implicit knowledge on statistical regularities in a given orthography is acquired. With the expansion of this knowledge, the laborious letter-by-letter recoding process gradually develops into a reading process that is based upon the recognition of letter patterns (i.e., letter combinations)(e.g., Bowey & Hansen, 1994; Ehri, 1998). Reading becomes increasingly ‘lexicalized’, with direct connections between the written and spoken forms of words (Ehri, 1992; Share, 1995; Stanovich, 1993). The establishment of connections between written and spoken forms of words is also called the acquisition of (word-specific) orthographic knowledge (Share, 1995). It is generally acknowledged that orthographic knowledge is acquired as a result of repeated reading, and that this is evidenced by an increase in reading speed (Ehri, 1992; Share, 1995). A number of studies have shown an increase in reading speed after repeated reading of the same words. Whereas normal readers generally require only few repetitions to speed up their reading, dyslexics need more extensive practice (Berends & Reitsma, 2005, 2006; Brunsdon, Hannan, Coltheart, & Nickels, 2002; Ehri & Saltmarsh, 1995; Hayes, Masterson, & Roberts, 2004; Judica, de Luca, Spinelli, & Zoccolotti, 2002; Reitsma, 1983b; Share, 2004). Nevertheless, reading speed has been shown to increase in dyslexics as a result of repeated reading, and, consequently, repeated reading is generally considered to constitute a powerful remediation method to improve reading in dyslexics (Chard, Vaughn, & Tyler, 2002). Although training studies that applied the method of repeated reading have found increases in reading speed, the interpretation of this acceleration is not straightforward. In general, the increase in reading speed is interpreted as a sign that orthographic knowledge has been acquired. However, at least part of this increase in reading speed may be ascribed to increased phonological familiarity and possibly to improved skill in articulating the trained words. For example, Reitsma (1983b) had children read a set of homophones either 4 or 8 times. After three days, the children read the trained spellings of the homophones, the untrained alternative spellings of the homophones, and a set of untrained control words. Both homophonic spellings 82
Repeated reading were read faster than the control words. This suggests that the repeated articulation of a word and its correspondingly growing phonological familiarity (i.e., its sound form becoming increasingly familiar) may contribute to the increase in reading speed typically observed after repeated reading. Therefore, the interpretation of an increase in reading speed is somewhat equivocal, and a complementary marker of (the acquisition of) orthographic knowledge is called for. One method to examine orthographic knowledge is to compare reading speed for words that are correctly spelled with homophonic words that have incorrect (or untrained) spellings. In the study by Reitsma (1983b) mentioned above, the trained spellings were read faster than the untrained spellings after as few as four trials. The difference in reading speed for trained and untrained spellings was replicated (Ehri & Saltmarsh, 1995; Share, 1999), although not consistently (Kyte & Johnson, 2006; Share, 2004). In the current study, we examined the effect of repeated reading on another marker of the use of orthographic knowledge: the word length effect. This effect implies that the longer a word is, the more time is required to read it. Word length has been interpreted as an indicator of the extent to which readers rely on lexical or sublexical reading procedures (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; Weekes, 1997). A sublexical reading procedure is characterized by the sequential recoding of graphemes into phonemes. As every letter (or grapheme) has to be processed separately, every additional letter of a word takes extra time. Thus, the longer a word, the more time is needed to read it. In contrast, when all letters are processed in parallel, long words take as much time to recognize as short ones. This has been interpreted as the reliance on a lexical reading procedure. In this case, the letters of a word are directly linked to its spoken form without previous graphemeto-phoneme recoding (Share, 1995; Stanovich, 1993). Given that reading becomes progressively based on the recognition of letter combinations instead of single letters, a decrease in the effect of word length can also be argued to be indicative of the acquisition of orthographic knowledge. In children with a normal reading development, the length effect has been reported to decrease with reading experience, suggesting an increasing involvement of a lexical reading procedure. Dyslexics, however, appear to experience difficulties in the transition from a (predominantly) sublexical reading procedure to a (predominantly) lexical reading procedure, evidenced by stronger and more persistent effects of word length (Spinelli, de Luca, di Filippo, Mancini, Martelli, & Zoccolotti, 2005; Ziegler, Perry, Ma-Wyatt, Ladner, & Schulte-Körne, 2003; Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005). This is well 83
Chapter 5 illustrated by a naming study reported by Zoccolotti, et al. (2005). Normal reading children in first, second, and third grade read aloud words consisting of 2-5 letters. These children were compared to a group of dyslexic children in third grade. Zoccolotti and colleagues observed that reading became progressively faster with age, and more importantly, that the word length effect decreased dramatically in normal reading children from first grade to third grade. In first grade, each additional letter took 173 ms; in third grade, this had decreased to 36 ms per letter. The reading speed of the dyslexic children in third grade, however, was comparable to the normal reading children in first grade, with a 170-ms increase in response time per letter. Zoccolotti et al. inferred that dyslexics continue to rely on the phonological recoding process characteristic of the sublexical reading procedure, and fail in the development of the lexical reading procedure. Interestingly, another study involving older children in sixth, seventh, and eighth grade showed that reading speed continues to improve in normally developing children without a concomitant change in the effect of length (Spinelli, et al. 2005). The children read words consisting of 3-8 letters. Reading speed was shown to be independent of length up to words of 5 letters, and to decrease linearly with length from 6 to 8 letters. The reading speed curves of the three grades ran parallel to each other, with a downward shift of about 30 ms a year. In a group of adults, reading speed was even faster and was not affected by length at all. These results suggest that reading speed continues to improve with reading experience, even when it has become (partially) independent of word length. This shows that there is a dissociation between the effect of length on reading speed and an overall improvement in reading speed. To date, most studies comparing reading speed and its sensitivity to word length in dyslexics and normal reading control groups of various ages have focused on one point in time (Martens & de Jong, 2006c; Spinelli, et al., 2005; Ziegler, et al., 2003; Zoccolotti et al., 2005). In the current study, we examined the acquisition of orthographic knowledge in dyslexic children by investigating whether the effect of length on reading speed would decrease after repeated reading. Mixed results have been obtained regarding a change in the effect of length on dyslexics’ reading speed after repeated word reading. In a study involving dyslexic children, no change in word length was observed (Judica et al., 2002), whereas in a case study involving one dyslexic adult, a decrease in the effect of word length was found (Hayes, et al., 2004). Both of these studies involved the repeated reading of existing words only. In the current study, both words and pseudowords were included. As pseudowords
84
Repeated reading have never been read before, reading frequency and phonological familiarity can be assumed to be the same for each participant. To study the ease with which orthographic knowledge is acquired, a second condition of repeated reading was created in which the acquisition of orthographic knowledge was rendered more difficult. This was accomplished by repeatedly presenting the (pseudo)words in alternated case instead of in normal lowercase (eXaMpLe). Repeated presentation in alternated case has been shown to hamper the acquisition of orthographic knowledge in normal reading children (Martens & de Jong, 2006a). Martens and de Jong suggested that this was due to the disruption of visual multiletter features by case alternation. Visual multiletter features are features larger than single letters but smaller than whole words, such as the relative shape and size of letters and the shape of the spaces between the letters. If visual multiletter features play a role in the acquisition of orthographic knowledge in dyslexic children as they do in normal reading children, then word length should affect reading speed less after a lowercase training than after an alternated-case training. However, considering the notoriously low rate at which dyslexics typically improve their reading speed, it is conceivable that dyslexics are unable to acquire orthographic knowledge in a relatively short training period in both conditions. In that case, a lowercase and an alternated-case training should result in similar increases in reading speed, and neither training is expected to result in a change in the effect of word length on reading speed. To examine whether a possible lack of a reduction in the length effect on reading speed was due to a deficient ability of the dyslexics to acquire orthographic knowledge, we conducted a second study. In this second study, normally developing readers in Grades 2 and 4/5 repeatedly read the words and pseudowords in lowercase. In both studies, words and pseudowords consisting of 4 to 6 letters were read 15 times. The (change in) reliance on orthographic knowledge was examined by comparing the reading speed and its sensitivity to word length before and after the training. Based on the rather quick acquisition of orthographic knowledge reported in normal reading children in several studies involving the detection of spelling changes in trained words such as homophones (Ehri & Saltmarsh, 1995; Reitsma, 1983b; Share, 1995, 1999, 2004), normal reading children were expected to show a decrease in the effect of word length on reading speed after the training.
85
Chapter 5 Study 1 The aim of this study was to examine the effect of repeated reading on the acquisition of orthographic knowledge in dyslexic children. Orthographic knowledge was assessed by comparing the effect of length on reading speed before and after the training. The ease with which orthographic knowledge was acquired was measured by comparing two groups of dyslexics who repeatedly read the (pseudo)words in either lowercase or alternated case. Method Participants Sixty dyslexic children took part in this study. They were selected from 25 primary schools in the western part of the Netherlands. All dyslexic children (33 boys and 27 girls) had a reading lag of at least 15 months (mean 22.8; range 15-40). Two children were in third grade, 31 children were in fourth grade, and 27 children were in fifth grade. The children were selected on the basis of their performance on a word reading ability test and a vocabulary test. Both tasks were administered a few weeks prior to the training. Word reading ability. Word reading ability was assessed with the One Minute Reading Test (Een Minuut Test) (Brus & Voeten, 1979), which was administered individually. This test consists of a list of 116 unrelated words, of increasing length and difficulty. The children were required to read aloud as many words as possible without making errors within one minute. The score was the number of words that were read correctly. All children in the DYS group scored below the 20th percentile (van den Bos, lutje Spelberg, Scheepsma, & de Vries, 1994). Vocabulary. To assess vocabulary, a standardized sub-test of the Revised Amsterdam Child Intelligence Test Battery (Revisie Amsterdamse Kinder Intelligentie Test) (Bleichrodt, Drenth, Zaal, & Resing, 1987) was used. During this test, the test assistant read 60 words of increasing difficulty aloud (one at a time), upon which the children had to choose the matching picture out of four alternatives. The score consisted of the number of correct answers. Children scoring more than two standard deviations below the population mean were excluded from the study. The 60 dyslexics were divided into two comparable groups of 30 children each. First, pairs of children were matched on mean age, gender, word reading ability, and vocabulary. Next, the children in each pair were randomly assigned to the lowercase training (‘DYS-low’) or the alternated-case training (‘DYS-alt’). 86
Repeated reading
Training Materials. The stimulus set consisted of 36 words and 36 pseudowords. The length of the items varied from four to six letters. The mean frequency of the words was 223.33 per million (SD = 200.33) (Staphorsius, Krom, & de Geus, 1988), and was matched across words of different lengths. Mean bigram frequency was 260.17 per 20,000 words (SD = 104.50) (Bakker, 1990), and was also matched across words of different lengths. Pseudowords were constructed by changing one or two adjacent letters at either the beginning or the end of the words. Letters that were replaced within a given word were interchanged with the letters of another word. As a consequence, the mean bigram frequency of the pseudowords was comparable to the mean bigram frequency of the words. In addition, the CV structures of the words and pseudowords were similar. To decrease the chance of obtaining results that were inherent to a particular stimulus set, we created two stimulus sets. To make sure that the items assigned to one stimulus set were comparable to the items assigned to the other set, the 36 words were divided into two similar sets of 18 words each. Each set consisted of 6 words of each length (4, 5, and 6 letters). The two sets were also matched in mean word frequency and mean bigram frequency. In addition, the CV structures of the words assigned to the different sets were as comparable as possible. Likewise, the 36 pseudowords were divided into two sets of 18 pseudowords. Both sets consisted of 6 pseudowords of each length. The two pseudoword sets were also comparable in mean bigram frequency and CV structure. Each of the two word sets was randomly assigned to half of the children. If a given word set was read during training, the pseudowords derived from the other word set were read during that same training. Procedure. During training, 18 words and 18 pseudowords were each presented 15 times. The words and pseudowords were presented in either lowercase format or in alternated-case format. The training was spread over four days. On the first training day, the words and pseudowords were presented three times in the appropriate training format (lowercase or alternated case), after having been presented once in lowercase (the pretest). On each of the following three training days, every item was read four times. Words and pseudowords were presented in two separate blocks every day. Within a block, every word (or pseudoword) was presented once, in random order. A block was presented four times running, with the items in a different random order each time. The order of the word block and the pseudoword block was counterbalanced across children. In addition, the order of the word and pseudoword blocks was alternated within children over training days; if a 87
Chapter 5 child started with the word block on the first day, it started with the pseudoword block on the second day, with the word block on the third day, etc. There was a short break between the words and pseudowords. Two portable computers were used to collect data at different schools at the same time: a Dell Latitude C610 and an Advance 1200. The experiment was programmed and run using E-prime software. To register the speed of the response times, a small microphone clipped onto the child’s collar was connected to the voice key within a serial response box (model 200A). Response times were measured from the moment a (pseudo)word appeared on the screen to voice onset. To record the accuracy of each response, a test assistant pressed the appropriate key on the response box (right, wrong, or invalid if the voice key had not been set off properly or had been triggered by another sound). No feedback was given to the children on the accuracy of their response. One by one, the items appeared in the middle of a 14” screen of a portable computer. The items were presented in 72-point Arial font, in black letters on a white background. All trials started with a fixation point (a plus), which was presented for 750 ms. Immediately following the fixation point, a word or pseudoword appeared on the screen, which disappeared as soon as the voice key was triggered. If the voice key had not been triggered 7 seconds after item onset, the item disappeared from the screen. The test assistant made the next trial begin using the response box. Children were instructed that they would read real words and nonsense words on the computer, and they were asked to read these words aloud as quickly as possible, without making errors. Children were asked not to start speaking until they knew the entire word, to make sure any sounding out of the word occurred silently. In addition, they were urged to avoid saying “uh”, as this would set off the voice key, immediately making the word disappear from the screen. Before each block, the test assistant announced whether they would read words or nonsense words. Each block started with 6 practice trials. The practice trials familiarized the children with the task, and gave the test assistant the opportunity to adjust the sensitivity level of the voice key, if necessary. Pretest and posttest Materials and procedure. In the pretest, the 18 words and 18 pseudowords that would be repeatedly read during the training were presented once in lowercase for both of the training conditions, to provide a baseline before the training. Words and pseudowords were presented in two separate blocks. Within these blocks, presentation order was randomized. The posttest consisted of the 18 trained words 88
Repeated reading and 18 trained pseudowords. Every (pseudo)word was read once. As in the pretest, the (pseudo)words were presented in lowercase to all of the children (i.e., both to the children that had been assigned to the lowercase training and to the children that had been assigned the alternated-case training). Again, words and pseudowords were presented in two separate blocks. Within these two blocks, words or pseudowords were presented in random order. Children who had started with the word block on the last training day, started with the pseudoword block in the posttest, and vice versa. General procedure The study comprised a screening, a pretest, a training, and a posttest. In the screening, a vocabulary test was administered per group, taking about 45 minutes. Subsequently, on the same day, word reading ability was assessed individually, taking approximately three minutes for each child. A few weeks later, the training started. Children were individually tested in a separate, quiet room in school. The training was evenly spread over four days, within two weeks time. The training was given either on Mondays and Wednesdays, or on Tuesdays and Thursdays. On the fifth day, Friday, the posttest was administered. Testing on each training day took 20-25 minutes. The posttest took about 10 minutes. Results The results will be presented in two sections. In the first section, accuracy and response times during the first and the last trial of the training will be reported. During the training, presentation format was either lowercase or alternated case. The second section is concerned with the pretest and the posttest. In this section, accuracy and response times before and after the training will be compared. Training Accuracy. Mean error percentages on the first and the last reading trials of the training are displayed in Table 1. As the error percentages on words were very low, they were not subjected to statistical analyses. To examine whether presentation in alternated case affected pseudoword reading accuracy on the first reading trial (i.e., the first reading trial in which presentation format was varied) and the last reading trial of the training (i.e., the last reading trial of the training in which presentation format was varied), a MANOVA was conducted with Time (first reading trial or last reading trial) and Length (4, 5, or 6 letters) as within subjects
89
Chapter 5 Table 1 Mean error percentages on the first and last reading trial of the training for words and pseudowords of 4, 5, and 6 letters for the dyslexic group assigned to the lowercase training (DYS-low) and the dyslexic group assigned to the alternated-case training (DYS-alt) Length Reading trial
Training
in Training
Condition
First trial
DYS-low
4 Words Pseudowords
DYS-alt
Words Pseudowords
Last trial
DYS-low DYS-alt
Note.
2.22
(5.76)
17.78 (16.34) 1.72
5 3.33
(8.07)
5.56 (10.11)
11.67 (13.94)
19.44 (21.48)
(5.17)
5.75 (10.23)
14.94 (15.65)
15.52 (19.89)
Words
1.11
(4.23)
3.33
(8.07)
Pseudowords
5.56 (10.11)
5.56
(9.11)
Words
1.15
2.87
(7.80)
Pseudowords
6.32 (12.13)
(4.30)
6
15.52 (22.24)
6.32
(9.36)
22.99 (18.59) 2.78
(7.69)
11.67 (15.26) 2.87
(6.41)
20.69 (21.20)
Between parentheses are the standard deviations.
factors and Training Condition (DYS-low or DYS-alt) as a between subjects factor. There was no overall effect of Training Condition on accuracy, F (1, 57) = 1.95, p > 0.15. The main effects of Time, F (1, 57) = 18.21, p < 0.001, η2p = 0.24, and Length, F (2, 114) = 7.34, p < 0.001, η2p = 0.11, were qualified by a Time by Length interaction, F (2, 114) = 3.78, p < 0.05, η2p = 0.06. The effect of length on pseudoword accuracy was larger on the last trial of the training than on the first trial. Repeated contrasts showed that this interaction was due to a stronger increase in accuracy on 4-letter pseudowords than on 5-letter pseudowords, F (1, 57) = 7.12, p < 0.01, η2p = 0.11, whereas 5- and 6-letter pseudowords increased to the same extent in accuracy, F < 1. The interaction of Time and Training Condition approached significance, F (1, 57) = 3.06, p = 0.085, η2p = 0.05. Accuracy tended to improve more in the DYS-low group than in the DYS-alt group. None of the other effects were significant. Response times. The analyses on the response times were based on correct and valid trials only. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials (in which the voice key had not been set off properly or had been triggered by another sound) were excluded from the analyses (on the first reading trial: 0.00 %, 10.00 %, and 8.33 % for DYS-low, respectively, and 0.19 %, 11.21 %, and 8.72% for DYS-alt, respectively; on the last reading trial: 0.37 %, 5.00 %, and 5.56 % for DYS-low, respectively, and 0.38 %, 90
Repeated reading 8.24 %, and 4.50 % for DYS-alt, respectively). For each child, a mean response time and a standard deviation were computed for words and pseudowords separately. Response times that deviated more than 3 standard deviations from the child’s word or pseudoword mean were considered outliers and excluded from the analyses (first reading trial: 1.11 % for DYS-low and 0.38 % for DYS-alt; last reading trial: 1.20 % for DYS-low and 1.05 % for DYS-alt). In all, the outliers, incorrect and invalid trials amounted to 19.44 % of the data for DYS-low, and to 20.50 % of the data for DYSalt on the first reading trial of the training (in total 19.96 %). On the last reading trial, the outliers, incorrect and invalid trials amounted to 12.13 % of the data for DYS-low, and to 14.18 % of the data for DYS-alt (in sum 13.14 %). In Table 2, the mean response times on the first and the last reading trials of the training are reported. To investigate whether case alternation affected reading speed on the first reading trial and the last reading trial of the training, a MANOVA was performed with Time (first reading trial or last reading trial), Lexicality (words or pseudowords), and Length (4, 5, or 6 letters) as within subjects factors and Training Condition (DYS-low or DYS-alt) as a between subjects factor. There was no main effect of Training Condition on the mean response times, F (1, 49) = 1.62, p > 0.20. Main effects of Time, F (1, 49) = 102.54, p < 0.001, η2p = 0.68, Lexicality, Table 2 Mean response times on the first and last reading trials of the training for words and pseudowords of 4, 5, and 6 letters for the dyslexic group assigned to the lowercase training (DYS-low) and the dyslexic group assigned to the alternated-case training (DYS-alt) Length Reading trial
Training
in Training
Condition
First trial
DYS-low
4 Words Pseudowords
DYS-alt
Words Pseudowords
Last trial
DYS-low
Words Pseudowords
DYS-alt
Note.
5
6
838 (257)
904 (371)
892 (377)
1548 (660)
1645 (658)
1908 (842)
939 (220)
1052 (362)
1280 (553)
1705 (631)
2059 (772)
2128 (702)
798 (234)
836 (272)
842 (287)
1172 (906)
1129 (542)
1256 (676)
Words
784 (310)
870 (356)
888 (365)
Pseudowords
982 (373)
1230 (660)
1290 (551)
Between parentheses are the standard deviations.
91
Chapter 5 F (1, 49) = 132.73, p < 0.001, η2p = 0.73, and Length, F (2, 98) = 35.76, p < 0.001, η2p = 0.42, were found, but these main effects were refined by several interactions. The main effect of Time was qualified by three two-way interactions. The interaction of Time and Training Condition showed that the difference in reading speed between DYS-low and DYS-alt had decreased from the first reading trial of the training (i.e., the first time that words and pseudowords were presented in alternated case for the DYS-alt group) to the last trial of the training, F (1, 49) = 5.97, p < 0.05, η2p = 0.11. A separate analysis on the first trial showed that reading was slower in the DYS-alt group than in the DYS-low group on the first reading trial of the training, F (1, 50) = 4.15, p < 0.05, η2p = 0.08. In contrast, on the last reading trial of the training, there was no difference between the groups, F < 1. Thus, case alternation slowed down reading on the first trial of the training, but did not affect reading speed (anymore) on the last trial of the training. The interaction of Time and Length indicated that the effect of Length on reading speed had decreased from the first reading trial to the last reading trial of the training, F (2, 98) = 5.78, p < 0.005, η2p = 0.11. However, as overall reading speed had increased at the end of the training, it is possible that this interaction might reflect a proportional decrease in the effect of length on response times. In other words, it is possible that every additional letter took a similar extra percentage of time on the last reading trial as on the first reading trial. A straightforward method to check whether a significant interaction reflects a proportional effect is to apply a logarithmic transformation to the response times (Levine, 1993; Salthouse & Hedden, 2002; van der Sluis, de Jong, & van der Leij, 2004; Zar, 1999), and then perform the MANOVA on the transformed response times. If the interaction effect is not significant in the analysis on the transformed scores, then the original interaction effect is proportional. However, if the interaction effect is still significant, this warrants the conclusion that the effect of length was different at the end of the training. Thus, additional analyses on the logarithm of the response times were performed, to examine whether any of the interactions in the analyses on the response times reflected proportional differences. In this analysis, the Time by Length interaction approached significance, showing that this interaction largely reflected a disproportional decrease, F (2, 98) = 2.49, p = 0.089, η2p = 0.05. The interaction of Time and Lexicality showed that reading speed for pseudowords had increased more than reading speed for words during the training, F (1, 49) = 66.80, p < 0.001, η2p = 0.58. The analysis on the logarithm of the response times yielded the same result.
92
Repeated reading The interactions of Length and Lexicality, F (2, 98) = 9.23, p < 0.001, η2p = 0.16, and Length and Training Condition, F (2, 98) = 3.62, p < 0.05, η2p = 0.07, were each qualified by the three-way interaction of Length, Lexicality, and Training Condition, F (2, 98) = 3.67, p < 0.05, η2p = 0.07. This three-way interaction showed that Length affected pseudoword reading speed more than word reading speed. The difference in the effect of Length on words and pseudowords was larger in the DYSlow group than in the DYS-alt group. In the analysis on the logarithm of the response times, this interaction approached significance, F (2, 98) = 2.80, p = 0.066, η2p = 0.05. This indicates that the interaction largely concerned a disproportional difference. None of the other effects was significant. Summarizing, case alternation slowed down reading at the beginning of the training, but not (anymore) at the end of the training. Pseudoword reading speed increased more than word reading speed. The effect of length on response times had decreased at the end of the training, but this was close to being a proportional difference. Pseudowords were more affected by length than words, and this difference was larger in the DYS-low group than in the DYS-alt group. Pretest and posttest Accuracy. The mean error percentages for words and pseudowords in the pretest and the posttest for both groups of dyslexics are presented in Table 3. As in the training, the error percentages for words were very low. Therefore, they were not included in the analysis. A MANOVA for repeated measures with Time (pretest or posttest) and Length (4, 5, or 6 letters) as within subjects factors and Training Condition (DYS-low or DYS-alt) as a between subjects factor was performed. Before and after the training, there was no difference in accuracy between the two dyslexic groups, F (1, 56) = 1.57, p > 0.20. The main effect of Time indicated that accuracy had increased from the first to the last reading trial in the training, F (1, 56) = 38.07, p < 0.001, η2p = 0.41. In addition, the main effect of Length was significant, F (2, 112) = 4.13, p < 0.05, η2p = 0.07. Repeated contrasts revealed that there was no difference in accuracy for pseudowords consisting of 4 and 5 letters, F < 1, but that pseudowords consisting of 5 letters were read more accurately than those of 6 letters, F (1, 56) = 5.73, p < 0.05, η2p = 0.09. None of the other effects were significant. The lack of a Time by Training Condition interaction indicated that the dyslexic group that had repeatedly read the items in alternated case had increased
93
Chapter 5 Table 3 Mean error percentages in the pretest and the posttest for words and pseudowords of 4, 5, and 6 letters for the dyslexic group assigned to the lowercase training (DYS-low) and the dyslexic group assigned to the alternated-case training (DYS-alt) Length Reading trial
Training
4
5
6
Condition Pretest
DYS-low
Words Pseudowords
DYS-alt
Words Pseudowords
Posttest
DYS-low DYS-alt
Note.
3.89
(9.47)
17.22 (18.82) 2.30
3.89
(8.40)
15.00 (18.74)
(5.84)
5.74 (10.23)
19.54 (18.93)
20.69 (20.24)
Words
1.15
(4.30)
4.02
(8.52)
Pseudowords
6.90
(9.47)
4.02
(8.52)
Words
1.72
(5.17)
2.87
(6.41)
Pseudowords
8.04 (13.08)
10.92 (18.51)
4.44
(9.72)
21.67 (19.15) 5.17
(7.84)
23.56 (21.60) 2.87
(6.41)
10.34 (15.04) 2.87
(7.80)
15.52 (18.33)
Between parentheses are the standard deviations.
their accuracy as much as the dyslexics that had repeatedly read them in lowercase, F < 1. Response times. The data cleaning procedure for the pretest and posttest was the same as for the training. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials were excluded from the analyses (in the pretest: 0.0 %, 11.02 %, and 9.63 % for DYS-low, respectively, 0.19 %, 12.84 %, and 7.57 % for DYS-alt, respectively; in the posttest: 0.19 %, 4.89 %, and 5.17 % for DYS-low, respectively, and 0.77 %, 6.99 %, and 5.65 % for DYS-alt, respectively). In addition, outliers were discarded (in the pretest: 0.64 % for DYSlow and 1.05 % for DYS-alt; in the posttest: 0.67 % for DYS-low, and 0.96 % for DYS-alt). In all, the outliers, incorrect and invalid trials amounted to 21.30 % of the data for DYS-low, and to 21.64 % of the data for DYS-alt in the pretest (in total 21.47 % of the data in the pretest). In the posttest, the outliers, incorrect and invalid trials added up to 10.92 % of the data for DYS-low, and to 14.37 % for DYS-alt (in sum 12.64 % of the data in the posttest). The mean response times on words and pseudowords consisting of 4, 5, and 6 letters in the pretest and the posttest for the dyslexic reader group assigned to the lowercase training (DYS-low) and the dyslexic reader group assigned to the alternated-case training (DYS-alt) are displayed in Table 4. A MANOVA for 94
Repeated reading repeated measures with Time (pretest or posttest), Lexicality (words or pseudowords) and Length (4, 5, or 6 letters) as within subjects factors and Training Condition (DYS-low or DYS-alt) as a between subjects factor was performed. There was no significant effect of Training Condition, F < 1, showing that there was no difference in overall reading speed between the two dyslexic groups either before or after the training. The main effects of Time, F (1, 49) = 60.54, p < 0.001, η2p = 0.55, Lexicality, F (1, 49) = 90.97, p < 0.001, η2p = 0.65, and Length, F (2, 98) = 25.95, p < 0.001, η2p = 0.35, were each qualified by interactions. Table 4 Mean response times in the pretest and the posttest for words and pseudowords of 4, 5, and 6 letters for the dyslexic group assigned to the lowercase training (DYS-low) and the dyslexic group assigned to the alternated-case training (DYS-alt) Length Reading trial
Training
4
5
6
Condition Pretest
DYS-low DYS-alt
Posttest
DYS-low
Words
1005
(429)
1223
(643)
1221
Pseudowords
1860
(912)
2041
(887)
2315 (1188)
Words
1001
(528)
1079
(690)
1114
Pseudowords
1898
(985)
2112 (1179)
Words Pseudowords
DYS-alt
Words Pseudowords
Note.
(608) (697)
2232 (1128)
880
(321)
1061
(553)
975
(309)
1172
(487)
1404
(704)
1407
(590)
819
(454)
935
(521)
913
(446)
1114
(493)
1283
(667)
1463
(819)
Between parentheses are the standard deviations.
The interaction of Time and Lexicality indicated that reading speed had increased more for pseudowords than for words after the training, F (1, 49) = 38.06, p < 0.001, η2p = 0.44. Overall, average reading speed for words increased with 211 ms (from 1113 ms in the pretest to 901 ms in the posttest). Average reading speed for pseudowords increased with 813 ms (from 2072 ms in the pretest to 1259 ms in the posttest). The interaction was also significant in the logarithm of the response times, indicating it was not a proportional difference. This difference is shown in Figure 1. The interaction of Time and Length was not significant, F (2, 98) = 2.30, p > 0.10. Finally, the Length by Lexicality interaction showed that length affected reading speed more for pseudowords than for words, F (2, 98) = 7.02, p < 0.001, 95
Chapter 5
Words
Pseudowords
2300
Response time (ms)
2100 1900 1700 1500 1300 1100 900 700 4
5
6
4
5
6
Length pretest DYS-low pretest DYS-alt
Figure 1.
posttest DYS-low posttest DYS-alt
Response times (in milliseconds) for words and pseudowords consisting of
4, 5, and 6 letters in the pretest and the posttest for the dyslexics assigned to the lowercase training (DYS-low) and the alternated-case training (DYS-alt). The error bars represent 95 % confidence intervals.
η2p = 0.13. None of the other interactions was significant. The lack of interactions with Training Condition indicated that repeated reading in alternated case led to the same result pattern after the training as repeated reading in lowercase. This is also shown in Figure 1. Discussion In this study, dyslexic children repeatedly read a set of words and pseudowords consisting of 4 to 6 letters in either lowercase or in alternated case. At the beginning of the training, case alternation was shown to decrease reading speed. At the end of the training, when the (pseudo)words had been read repeatedly, the difference in reading speed in alternated case and lowercase had disappeared. These 96
Repeated reading results replicate previous findings with normal reading children (Martens & de Jong, 2006a). However, whereas normal reading children in the study by Martens and de Jong had increased their reading speed more after repeated reading in lowercase than after repeated reading in alternated case, the present study showed that for dyslexics, repeated reading in alternated case resulted in a similar increase in reading speed and accuracy as repeated reading in lowercase. At the end of the training, the effect of length on dyslexics’ reading speed had remained unchanged. This suggests that after 15 repeated reading trials (or 16 when including the pretest), the dyslexics relied as much on sublexical recoding as before, and the contribution of a lexical reading strategy had not increased. Before discussing the findings of Study 1 more extensively, we will report our findings on Study 2. Study 2 Study 1 showed that dyslexics read faster and more accurately after the training. However, the effect of length on reading speed had remained unchanged after reading the same words and pseudowords 15 times. In order to assess whether the unchanged effect of length on dyslexics’ reading speed reflects a deficient ability to acquire orthographic knowledge, we conducted a second study. In this study, we examined how normally developing readers in Grade 2 and Grade 4/5 responded to the same training in lowercase. For these two groups of normal readers, we also assessed the acquisition of orthographic knowledge by comparing changes in reading speed and the effect of length on reading speed before and after the training. Method Participants Thirty-six children took part in this study. The children were selected from two primary schools in the western part of the Netherlands. The Beginning Reader group (BEG) consisted of 18 normal readers (9 boys and 9 girls) in Grade 2. The Advanced Reader group (ADV) comprised 18 normal readers (6 boys and 12 girls) in Grades 4 and 5. Children were selected on the basis of their performance on the same Reading ability test and Vocabulary test described in Study 1. All children scored within one standard deviation of the population mean on the Reading ability test (van den Bos, et al., 1994). Children scoring more than two standard deviations below the population mean of the Vocabulary test were excluded from the study. Permission for all children was obtained from the parents and the schools. 97
Chapter 5
Training and posttest The same materials and procedure were used as in Study 1. All children repeatedly read the words and pseudowords in lowercase. Results Pretest and Posttest Accuracy. The mean error percentages for words and pseudowords in the pretest and the posttest for the Beginning Reader group (BEG) and the Advanced Reader group (ADV) are displayed in Table 5. As the overall error percentages were low, no formal analyses were performed. Overall, more errors were made on pseudowords than on words. Error percentages appeared to have decreased in the posttest. Table 5 Mean error percentages in the pretest and the posttest for words and pseudowords of 4, 5, and 6 letters for the Beginning reader group (BEG) and the Advanced reader group (ADV) Length Reading
Reading
trial
Group
Pretest
BEG
Words Pseudowords
6.48 (11.63)
ADV
Words
0.93
(3.93)
0.00
(0.00)
0.93
Pseudowords
7.41 (10.26)
0.93
(3.93)
9.26 (11.74)
BEG
Words
0.93
0.93
(3.93)
0.93
Pseudowords
0.00
(0.00)
5.56
(9.90)
5.56 (11.43)
ADV
Words
0.00
(0.00)
0.00
(0.00)
0.00
(0.00)
Pseudowords
2.78
(6.39)
0.00
(0.00)
2.78
(6.39)
Posttest
Note.
4 0.00
5
(0.00)
3.70
6
(7.13)
5.56 (11.43)
15.74 (15.63)
15.74 (13.37)
(3.93)
(3.93) (3.93)
Between parentheses are the standard deviations.
Response times. The data cleaning procedure was the same as for Study 1. Response times below 325 ms, response times on incorrect trials, and response times on invalid trials (in which the voice key had not been set off properly or had been triggered by another sound) were excluded from the analyses (in the pretest: 0.00 %, 7.87 %, and 6.48 % for BEG, respectively, 0.15 %, 3.24 %, and 8.64 % for ADV, respectively; in the posttest: 0.00 %, 2.32 %, and 5.56 % for BEG, respectively, 0.00 %, 0.93 %, and 3.86 % for ADV, respectively). For each child, a mean response time and a standard deviation were calculated for words and pseudowords 98
Repeated reading separately. Response times that deviated more than 3 standard deviations from the child’s word or pseudoword mean were considered outliers and excluded from the analyses (in the pretest: 1.70 % for BEG and 0.77 % for ADV; in the posttest: 1.39 % for BEG and 1.08 % for ADV). In all, the outliers, incorrect and invalid trials amounted to 16.05 % of the data for BEG, and to 12.81 % of the data for ADV in the pretest (in total 14.43 % of the data on the pretest). In the posttest, the outliers, incorrect and invalid trials amounted to 9.26 % of the data for BEG, and to 5.86 % of the data for ADV (for a total of 7.56 % of the data on the posttest). In Table 6, the mean response times on words and pseudowords consisting of 4, 5, and 6 letters in the pretest and the posttest for the BEG group and the ADV group are presented. A MANOVA for repeated measures with Time (pretest or posttest), Lexicality (words or pseudowords) and Length (4, 5, or 6 letters) as within subjects factors and Reading Group (BEG or ADV) as a between subjects factor was performed. The main effect of Reading Group showed that the ADV group read faster than the BEG group, F (1, 34) = 37.07, p < 0.001, η2p = 0.52. The main effects of Time, F (1, 34) = 35.34, p < 0.001, η2p = 0.51, Lexicality, F (1, 34) = 64.27, p < 0.001, η2p = 0.65, and Length, F (2, 68) = 11.89, p < 0.001, η2p = 0.26, were each qualified by an interaction with Reading Group. The interaction of Time and Reading Group showed that the reading speed of the BEG group had increased more after the training than the reading speed of the Table 6 Mean response times in the pretest and the posttest for words and pseudowords of 4, 5, and 6 letters for the Beginning reader group (BEG) and the Advanced reader group (ADV) Length Reading
Reading
4
trial
Group
Pretest
BEG
Words
ADV
Words
Note.
6
843
(192)
961
(336)
973
(337)
1462
(609)
1643
(678)
1715
(740)
567
(98)
589
(100)
574
(90)
Pseudowords
865
(301)
888
(339)
893
(391)
BEG
Words
704
(98)
745
(130)
757
(173)
Pseudowords
799
(170)
857
(235)
907
(248)
ADV
Words
529
(54)
534
(60)
532
(62)
Pseudowords
599
(81)
580
(76)
590
(74)
Pseudowords
Posttest
5
Between parentheses are the standard deviations.
99
Chapter 5 ADV group, F (1, 34) = 7.90, p < 0.01, η2p = 0.19. The interaction of Lexicality and Reading Group indicated that the difference between words and pseudowords was larger for the BEG group than for the ADV group, F (1, 34) = 9.05, p < 0.005, η2p = 0.21. In the analysis on the logarithm of the response times, this interaction approached significance, F (1, 34) = 3.19, p = 0.083, η2p = 0.09. The Length by Reading Group interaction showed that the BEG group was more affected by length than was the ADV group, F (2, 68) = 9.34, p < 0.001, η2p = 0.22. Inspection of the response times in Table 6 raised the question whether the ADV group was affected by length at all. An analysis including this group only showed that their reading speed was in fact not influenced by length, F < 1. Unexpectedly, the lack of an interaction of Length and Lexicality indicated that this applied not only to words, but also to pseudowords, F < 1. Turning back to the overall analysis, the interaction of Time and Length approached significance, F (2, 68) = 2.91, p = 0.061, η2p = 0.08. This suggests that the effect of Length on reading speed had tended to decrease in number of milliseconds after the training. The analysis on the logarithm of the response times revealed that this trend reflected a proportional decrease in the effect of length on reading speed, F (2, 68) = 2.27, p > 0.10. The Time by Lexicality interaction showed that reading speed had increased more for pseudowords than for words, F (1, 34) = 36.97, p < 0.001, η2p = 0.52. This is shown in Figure 2. In addition, a significant three-way interaction with Reading Group was found, F (1, 34) = 5.59, p < 0.05, η2p = 0.14. The BEG group had gained more reading speed than the ADV group after the training, and this difference was larger for pseudowords than for words. In the BEG group, word reading speed had increased with 191 ms (from 926 ms in the pretest to 735 ms in the posttest) and pseudoword reading speed had increased with 753 ms (from 1607 ms to 854 ms). In the ADV group, a 45-ms increase in word reading speed was observed (from 577 ms to 532 ms) and a 292-ms increase for the pseudowords (from 882 ms to 590 ms). The analysis on the logarithm of the response times showed that the larger difference in the increase in reading speed for pseudowords than for words in the BEG group than in the ADV group reflected a proportional difference between the groups, F (1, 34) = 1.17, p > 0.20. None of the other interactions was significant.
100
Repeated reading
Words
Pseudowords
1800
Response time (ms)
1600 1400 1200 1000 800 600 400 4
5
6
4
5
6
Length
Figure 2.
pretest BEG
posttest BEG
pretest ADV
posttest ADV
Response times (in milliseconds) for words and pseudowords consisting of
4, 5, and 6 letters in the pretest and the posttest for the beginning readers (BEG) and the advanced readers (ADV). The error bars represent 95 % confidence intervals.
Although the Time by Lexicality interaction and the lack of a three-way interaction with Reading Group (in the analysis on the logarithm of the response times) indicated that reading speed had increased more for pseudowords than for words in both the BEG group and the ADV group, these results are not conclusive as to whether reading speed for words had increased to a significant extent in both groups as well. Therefore, a separate analysis on the words was performed for each of the groups. These analyses showed that words, too, were read faster after the training in both the BEG group, F (1, 17) = 7.89, p < 0.05, η2p = 0.32, and in the ADV group, F (1, 17) = 5.81, p < 0.05, η2p = 0.26. Analyses on the logarithm of the response times yielded the same results.
101
Chapter 5 Discussion The second study was conducted to investigate how normally developing readers would respond to the training of repeated reading that had been administered to dyslexics in Study 1. Beginning and advanced readers repeatedly read the same set of words and pseudowords in lowercase. As in Study 1, we compared reading speed and its sensitivity to word length before and after the training, to examine the acquisition of orthographic knowledge. Similar to what was found in Study 1, reading speed increased after training, but the effect of length remained unchanged. General discussion The aim of the present study was to investigate the acquisition of orthographic knowledge by dyslexic and normal reading children after repeated reading. The acquisition of orthographic knowledge was assessed by comparing the effect of length on reading speed before and after a short training, involving the repeated reading of a set of words and pseudowords 15 times. A change in the effect of length on reading speed would suggest a development from a predominant sublexical reading procedure to a progressively larger role for a lexical reading procedure, thereby indicating the acquisition of orthographic knowledge. In the first study, two groups of dyslexic children read a set of words and pseudowords consisting of 4 to 6 letters in either lowercase or in alternated case. The alternatedcase training was included to examine the ease with which orthographic knowledge was acquired. To investigate how normally developing readers would respond to the training and whether they would show a decrease in the effect of length on reading speed, a second study was conducted, in which normally developing beginning and advanced readers in Grades 2 and 4/5 repeatedly read the words and pseudowords in lowercase. Overall, reading had improved in the dyslexics after the training, both in terms of accuracy and reading speed. Error rates dropped for both words and pseudowords, with a larger improvement for pseudowords (from 19.73 % in the pretest to 5.96 % in the posttest) than for words (from 4.21 % in the pretest to 2.59 % in the posttest). These high levels of accuracy in dyslexics are in line with previous research in transparent orthographies (e.g., de Jong & van der Leij, 2003; Wimmer, 1993; Zoccolotti, de Luca, di Pace, Judica, Orlandi, & Spinelli, 1999). More of interest to the current paper was the improvement in reading speed. Of particular interest was the comparison of the length effect on reading speed before and after the training. Before the training, length was found to affect reading speed in dyslexics and in the normally developing younger readers in Grade 2: The 102
Repeated reading longer a word, the more time was required to read it. Unexpectedly, however, length did not affect reading speed in the normal readers in Grade 4/5. The lack of a length effect before the training made a reduction in the effect of length impossible in this group. We will return to the lack of a length effect in the normal reading children in Grade 4/5 later. After the training, reading speed had increased in all groups, but the effect of length had remained unchanged. Although the effect of length on response times tended to decrease somewhat in number of milliseconds (i.e., in absolute terms), this was shown to reflect a proportional difference. In relative terms, the influence of length on reading speed remained unchanged. This suggests that, although reading became faster, there was no change in the reliance on a serial sublexical reading procedure for the dyslexics and younger normally developing readers in Grade 2. They had not developed a stronger reliance on a lexical reading procedure for the trained (pseudo)words after reading them 15 times. These findings illustrate that the general improvement in reading speed was not due to the acquisition of wordspecific orthographic knowledge (which would have been evidenced by a reduction in the length effect), but should be attributed to practice in articulating the words and pseudowords and to the increase in the familiarity of their phonological form. This is supported by the larger improvement in reading speed for pseudowords than for words. Reading speed for pseudowords could simply improve more than reading speed for words, because the pseudowords sounded unfamiliar before the training and had not been articulated yet. In contrast, the words did sound familiar and they had been articulated before a number of times. A remarkable finding was that (both word- and pseudoword-) reading speed was subject to improvement even in the normal readers in Grade 4/5 who appeared to rely predominantly on a lexical reading procedure (as suggested by the lack of a length effect). This provides further support for the contention that at least part of the gain in reading speed in all groups can be attributed to an articulatory practice effect. The lack of a reduction in the effect of length on reading speed after repeated reading in both dyslexic children and normally developing readers is an important finding. Although it has been reported before in dyslexics (Judica, et al 2002), it had not been found consistently (Hayes, et al., 2004), and it had not yet been investigated in normal readers. The present study showed that not only dyslexics, but also younger normal readers continue to be affected by length to the same extent after reading the same words and pseudowords 15 times (or 16 times, including the pretest). The lack of a reduction in the length effect suggests that for this limited set of 18 words and 18 pseudowords, no word-specific orthographic 103
Chapter 5 knowledge was acquired after repeated reading. Apparently, the training was too short to promote a shift from a predominantly sublexical reading procedure to a more important role for a lexical reading procedure. This finding is not in line with previous studies that suggested that orthographic knowledge is acquired in only a few reading trials (Ehri & Saltmarsh, 1995; Reitsma, 1983b; Share, 1995, 1999). In these studies, however, orthographic knowledge was not assessed by a reduction in the effect of word length on reading speed, but by a difference in reading speed for words with trained versus untrained spellings. After a few exposures to a specific spelling of a word, this word was read faster than its homophonic alternative. This difference in reading speed was taken as evidence for the acquisition of word-specific orthographic representations. However, this result was not replicated consistently (Kyte & Johnson, 2006; Share, 2004). Although the detection of spelling differences may suggest word-specific orthographic knowledge, it does not imply that the reading procedure used to recognize a word has changed. Put differently, word recognition may become faster after repeated reading, without a shift from a predominantly sublexical to a predominantly lexical reading procedure (cf. Spinelli et al., 2005). Thus, although knowledge of specific word spellings may be present, this does not necessarily imply that direct connections between the written and spoken forms of those words have already been established. Theoretically, the lack of a reduction of the length effect on reading speed after repeated reading is at odds with the hypothesis that the acquisition of orthographic knowledge is item based and word-specific (Share, 1995). If it were item based, then reading the same words 15 times would not only be expected to result in an overall increase in reading speed, but also in a reduction of the effect of length on the reading speed of those words. This implies that the acquisition of orthographic knowledge is not primarily item based, but is probably dependent on a gradual development of the entire reading system (cf. Plaut, McClelland, Seidenberg, & Patterson, 1996). Alternatively, however, the possibility that (a decrease in) the effect of word length on reading speed is not an adequate indicator of (the acquisition of) orthographic knowledge should also be considered. Possibly, the repeated reading did result in the acquisition of orthographic knowledge in the present study, but this might not have manifested itself in a reduction in the effect of word length on reading speed. For example, Whitney and Cornelissen (2005) suggested that the decrease in the length effect observed in children (until adult competence is reached) is not necessarily due to a shift from serial to parallel processing, but might also 104
Repeated reading simply reflect an increase in efficiency. On the basis of the results of the present study, this possibility cannot be excluded. In addition to repeated reading in lowercase, a second condition was included in Study 1 in which the acquisition of orthographic knowledge was rendered more difficult. In this condition, the words and pseudowords were repeatedly presented in alternated case instead of in normal lowercase. On the first reading trial of the training, in which the (pseudo)words were presented in alternated case for the first time, case alternation was shown to slow down reading speed and to induce a more serial reading procedure. The effect of length on reading speed was larger in alternated case than in lowercase. On the last training trial, this difference in general reading speed between the groups had disappeared. These results are in line with the study of Martens and de Jong (2006c) in which alternated-case presentation was also found to induce a more serial reading procedure in a naming task. In addition, the disappearance of the effect of case alternation after repeated reading replicates the findings of Martens and de Jong (2006a) with normal reading children. After the training in Study 1, overall reading speed had increased as much in the alternated-case group as in the lowercase group. The lack of a difference in overall reading speed after the two different training conditions suggests that dyslexics were not affected by the distortion of the multiletter features in their acquisition of orthographic knowledge, or, put more carefully, in their improvement in reading speed, in contrast to what has been reported for normal reading children (Martens & de Jong, 2006a). Whereas the acquisition of orthographic knowledge in normal reading children has been shown to be at least partly dependent on visual multiletter features, the present study suggests that dyslexic children do not rely on these multiletter features present in larger letter patterns. This is in accordance with our expectation, considering the slow, laborious, letter-by-letter reading process that is often observed in dyslexics. Another finding concerns the length effect on the reading speed of the normally developing children in Study 2. The normal readers in Grades 4/5 read faster and were less affected by length than the normal readers in Grade 2, as expected on the basis of reading level. Unexpectedly, however, length did not affect the reading speed of the normal readers in Grade 4/5 at all, not even for pseudowords. This suggests that they relied on a lexical reading procedure not only for words, but also for pseudowords. The latter finding contrasts with previous research comparing the effect of length on words and pseudowords, both in children (Martens & de Jong, 2006c; Ziegler et al., 2003) and in adults (e.g., Juphard, 105
Chapter 5 Carbonnel, & Valdois, 2004; Weekes, 1997). An explanation in terms of excellent reading ability in the selected sample of advanced readers seems unlikely, given their average scores (compared to age peers) on the reading ability test. It should be considered that the detection of a length effect might be difficult for at least two reasons. Length was manipulated by taking (pseudo)words that varied from 4 to 6 letters. However, as about half of the (pseudo)words contained digraphs (e.g., ch, ee, aa), the difference in the number of phonemes was smaller than the difference in the number of letters. On average, the (pseudo)words of 4, 5, and 6 letters consisted of 3.83, 4.5, and 5 phonemes, respectively. Increasing the range of word lengths would have enhanced the power of the length manipulation. A second reason for difficulty in detecting a length effect in the normal Grade 4/5-readers in the present study lies in the high variances in reading speed in children. In normal reading adults, the effect of length on reading speed has been reported to be small (Juphard et al, 2004; Weekes, 1997). For example, Weekes (1997) reported no length effect in high frequency words, a 11.3-ms decrease in reading speed per letter in low frequency words, and a 19.6-ms decrease per letter in pseudowords. However, in adults, the variance in reading speed is smaller than in children. The larger variance in the children in the present study may have precluded the effect of word length from reaching significance. Increasing the number of (pseudo)words of each length would probably result in smaller variances in reading speed, and consequently increase the power of the statistical analyses. Summarizing, the combined results of Study 1 and Study 2 suggest that a training involving the repeated reading of the same words and pseudowords increased reading speed in both dyslexic and normal (beginning and advanced) readers. However, the effect of length on reading speed had remained unchanged after the training. For the readers who mainly relied on a sublexical reading procedure at the outset of the study, the training appeared to be too short to develop a shift from a predominant reliance on a sublexical reading procedure to a more important contribution of a lexical reading procedure.
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Epilogue
Chapter 6 Epilogue
In the first two studies reported in the present thesis, the use of orthographic knowledge in dyslexic children and children without reading difficulties of either the same age or the same reading level as the dyslexics was investigated. Two different methods were used to assess the use of orthographic knowledge: word length and case alternation. As these two studies suggested that dyslexics used less orthographic knowledge than their age peers without reading difficulties, additional studies were conducted to examine the ability to acquire orthographic knowledge in children with and without reading difficulties. First, the main findings of each of the studies will be reviewed, and subsequently several issues addressed in this thesis will be discussed in more detail. Review of main findings In the study described in Chapter 2, the relative contributions of sublexical and lexical reading procedures were examined in 10-year-old dyslexic children, normal reading age peers, and normal reading younger children with the same reading level as the dyslexics. The children made lexical decisions on words and pseudowords consisting of 3 to 6 letters. A lexical decision task does not require an articulation of the words and pseudowords, but a simple response as to whether the visually presented letter string constitutes an existing word or not. Due to its focus on visual orthographic characteristics, the demand on phonological processing was assumed to be reduced compared to a task requiring the preparation of a (pseudo)word’s pronunciation and the subsequent generation of its articulation. By diminishing the need for sublexical recoding, the reliance on a lexical reading procedure was expected to be promoted. Performance was highly accurate in all three groups of children. As for reading speed, length affected pseudoword-reading more than word-reading in all three groups, suggesting a larger contribution of a lexical reading procedure in word-reading than in pseudoword-reading in dyslexic and normal reading children alike. In addition to differences in the contribution of a sublexical reading procedure within each of the three reading groups, there were also differences in the reliance 107
Chapter 6 on a sublexical reading procedure between the groups in general. Length affected dyslexics more than their normal reading age peers, suggesting that dyslexics relied more heavily on a sublexical reading procedure. However, length affected the dyslexics to the same extent as the reading age control group. Therefore, dyslexics’ stronger reliance on a sublexical reading procedure compared to their normal reading age peers appeared to be due to the limited size of their orthographic lexicon, related to their reading level. The normal reading age peers were not affected by length at all when making lexical decisions on words. The results suggest that children perform a lexical decision task differently than adults. Whereas adults generally base their lexical decision solely on a lexical reading procedure (e.g., de Groot, Borgwaldt, Bos, & van den Eijnden, 2002; Juphard, Carbonnel, & Valdois, 2004), children first appear to identify the (pseudo)word relying heavily on a sublexical reading procedure if necessary and subsequently make their lexical decision. In Chapter 3, the use of lexical knowledge in reading aloud was investigated, using two methods. As in Chapter 2, the contribution of a lexical reading procedure was assessed by comparing the effect of length on word- and pseudoword-reading across the groups. The same three groups of children were asked to read aloud the words and pseudowords consisting of 3 to 6 letters. In addition, the use of lexical knowledge was examined by evaluating the extent to which lexical feedback was used when (pseudo)words presented in a visually disrupted format (i.e., in aLtErNaTeD cAsE) had to be read aloud. Supposing that dyslexics have less lexical knowledge available than their normal reading age peers, case alternation was expected to affect words and pseudowords to the same extent in dyslexics, but to affect word-reading less than pseudoword-reading in the normal reading age peers. Similar to the results on the lexical decision task, performance was highly accurate in all groups. The effect of length was larger on pseudoword-reading than on word-reading in each of the three groups. This suggests that both normal readers and dyslexics used at least some lexical knowledge in reading aloud. In contrast to the lexical decision task, the normal reading age peers were affected by length both in word-reading and pseudoword-reading, suggesting that this task indeed involved more phonological processing. As in the lexical decision task, dyslexics were more affected by length than their normal reading age peers, but were affected as much as the normal reading younger children. With regard to the second method to assess lexical knowledge, case alternation slowed down the dyslexics more than their normal reading age peers, but had a comparable influence on dyslexics and the 108
Epilogue normal reading younger children. Contrary to our expectation, case alternation affected words and pseudowords to the same extent, overall, in all three groups of children. The combined results suggest that dyslexic and normal reading children alike use lexical knowledge when reading in lowercase, but that this lexical knowledge generally does not aid in overcoming the visual disruption caused by case alternation, as it has been hypothesized to do in adults (Mayall & Humphreys, 1996). In Chapter 4, the acquisition of orthographic knowledge was investigated. Previous research on adults has shown that visual word features affect word recognition (e.g, Besner & McCann, 1987; Mayall & Humphreys, 1996), and that a disruption of these features can impede the acquisition of orthographic knowledge (Jacoby & Hayman, 1987; Masson, 1986). We examined whether a disruption of visual word features affected the acquisition of orthographic knowledge in normal reading children. Normally developing children in Grade 2 and Grade 4/5 repeatedly read a set of pseudowords in lowercase or alternated case. The pseudowords were presented 4 or 8 times during training. In the posttest, the pseudowords were presented in the same case format as they had been trained in or in the other case format (i.e., lowercase or alternated case). The posttest included a set of pseudowords that had not been read during training. As in adults, case alternation slowed down reading in children. In the course of the training, the effect of case alternation gradually decreased. In the subsequent posttest, case alternation did not affect reading speed of pseudowords that had not been read during training, indicating that the children had got acccustomed to reading in alternated case in general. Importantly, pseudowords that had been trained in lowercase were read faster than pseudowords that had been trained in alternated case in the lowercase posttest. This suggests that more orthographic knowledge had been acquired after a lowercase training than after an alternated-case training. To examine whether the decelerating effect of case alternation can be attributed to a visual disruption at the level of single letters or at the level of multiletter features, a second study was performed. Children in second and fourth Grade read single letters in a Rapid Automatized Naming (RAN) task in lowercase, alternated case, and uppercase. Case alternation did not affect single letter reading, implying that the deceleration caused by case alternation originates in the disruption of visual multiletter features. The combined results of the two studies reported in Chapter 4 suggest that visual multiletter features contribute to the acquisition of orthographic knowledge in normal reading children. 109
Chapter 6 In Chapter 5, two studies were reported in which we examined the effects of repeated reading on the acquisition of orthographic knowledge in dyslexic and normal reading children. During the training, a set of words and pseudowords consisting of 4 to 6 letters was read 15 times. The acquisition of orthographic knowledge was assessed by comparing the effect of length on reading speed before and after the training. A reduction in the effect of length on reading speed would suggest a development from a predominant reliance on a sublexical reading procedure to a progressively larger contribution of a lexical reading procedure. In the first study, two groups of dyslexics repeatedly read the (pseudo)words in either lowercase or in alternated case. The alternated-case training was included to create a reading condition in which the acquisition of orthographic knowledge was rendered more difficult. The studies reported in Chapter 4 showed that visual word features play a role in the acquisition of orthographic knowledge in normal reading children. In this study we addressed the question whether this also applies to dyslexic children. As it was possible that the dyslexics would not show a reduction in the effect of length on reading speed after the training, we conducted a second study to examine whether this should be attributed to a deficient ability of the dyslexics to acquire orthographic knowledge. In this second study, normally developing children in Grades 2 and 4/5 repeatedly read the words and pseudowords in lowercase. As in the first study, reading speed and its sensitivity to length were compared before and after the training. In the first study, case alternation slowed down reading in the dyslexics at the beginning of the training. At the end of the training, the effect of case alternation had disappeared, replicating the results for normal reading children reported in Chapter 4. However, reading speed had improved as much in the dyslexics who had repeatedly read the (pseudo)words in alternated case as in those who had read them in lowercase. This suggests that multiletter features do not play a role in the improvement in reading speed in dyslexics as they do in normal reading children (as reported in Chapter 4). In both studies, overall reading speed had improved after the training, but the effect of length on reading speed had remained the same. The lack of a reduction in the length effect suggested that the contribution of a lexical reading procedure had not increased after the training. Put differently, no word-specific orthographic knowledge had been acquired after reading the same (pseudo)words for as many as 15 times. Importantly, this applied not only to the dyslexics, but also to the normal readers. This result contrasts with other studies that suggested that orthographic knowledge is acquired after only a few reading trials (Ehri & Saltmarsh, 1995; 110
Epilogue Reitsma, 1983b; Share, 1995, 1999; van den Bosch, van Bon, & Schreuder, 1995). An unexpected finding of the second study was that length did not affect either word- or pseudoword-reading speed at all in the normal reading 4th- and 5th-graders. Possibly, a stronger manipulation of length might have resulted in the detection of a length effect in this group. Limitations Before discussing the combined findings and implications of the studies, a few limitations of the experimental studies should be considered. The limitations mainly concern the stimulus materials and methods that were used in the various studies. In two studies, the condition means were based on a fairly small number of words. Whereas the mean response times of the trials during the training reported in Chapter 4 were each based on 12 pseudowords, the mean response times for each of the conditions in the subsequent posttest were based on only 6 pseudowords. Using small word sets may affect the extent to which the obtained results can be generalized to other words. It is therefore recommended to base the condition means on a larger numbers of words to increase the generalizability of the results. This also applies to the training study reported in Chapter 5. Obviously, the amount of time that children can be taken out of the classroom to partipate in a study is limited. This imposed restrictions on the number of trials that could be presented to the children in each session. In addition, the amount of time that children can be expected to pay close attention and sustain concentration is limited. Especially in dyslexic children – who are generally not too fond of reading – reading tasks can be demanding. Considering time limits, the number of conditions (words/pseudowords of three different lengths), and required training frequency (15 times), we opted for 6 words in each condition. In future research, however, we would aim to increase the number of words in each condition to enhance the generalizability of the results. A second limitation concerns the manipulation of length as it was employed in the present thesis. Although the range of 3 to 6 letters was adequate to detect length effects in all groups of children in the studies reported in Chapter 2 and 3, the slightly more restricted range of 4 to 6 letters in the studies reported in Chapter 5 did not turn out to be powerful enough to detect a length effect in the normal reading children in Grades 4/5. We speculated that one of the factors playing a role in the lack of a length effect in this group may have been the relatively small differences in length in number of phonemes. In future research, extending the range to, for example, 2 to 6 letters, or including (pseudo)words consisting of up to three 111
Chapter 6 syllables, might yield a more robust measure. Furthermore, an inclusion of multisyllabic words in the stimulus set would provide a more accurate reflection of the words that children typically encounter on a daily basis, thereby enhancing the generalizability of the results. Reading models In some computational models of reading, word length is postulated to have an effect on reading speed. In other models, word length in itself is not assumed to affect reading speed. Empirical results on the effect of word length on reading therefore provide a test of the adequacy of different reading models. The studies reported in the present thesis consistently showed that length affected children’s reading speed, with a larger effect on pseudowords than on words both in lexical decision and reading aloud (except for the children without reading difficulties in Grade 4/5 in Chapter 5). Dyslexics were invariably more affected by word length than age peers without reading difficulties, but were affected to the same extent as younger children at a similar reading level. These results are in line with previous research (e.g., Spinelli, de Luca, di Filippo, Mancini, Martelli, & Zoccolotti, 2005; van der Leij, & van Daal, 1999; Ziegler, Perry, Ma-Wyatt, Ladner, & Schulte-Körne, 2003; Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005). Current computational models of reading provide different accounts for these results. In the Dual Route Cascaded model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001), the larger length effect on pseudowords than on words in reading aloud is explained in terms of the relative contributions of the sublexical and lexical reading routes. In the sublexical route, letters are processed in a sequential way, requiring extra reading time for each additional letter. In contrast, the lexical route processes all letters in parallel, and, as a consequence, the number of letters does not affect reading time. The two routes work simultaneously, with the relative contribution of the lexical route depending on whether the target word is represented in the orthographic lexicon and/or on how many similar words are represented in the orthographic lexicon in general. As pseudowords are not in the orthographic lexicon, the contribution of the sublexical route is relatively larger than for words, resulting in a larger length effect on pseudoword-reading than on wordreading. Likewise, the overall stronger length effect in the dyslexics can be explained in terms of a relatively larger contribution of the sublexical route in general than in children without reading difficulties. The latter have larger 112
Epilogue orthographic lexicons, resulting in a stronger contribution of the lexical route in both word- and pseudoword-reading compared to the dyslexics. Whereas the DRC model can easily account for the length effects in reading aloud, the length effects observed in lexical decision are more difficult to explain. According to the model, lexical decision is exclusively based on the lexical route. Length is therefore predicted not to affect lexical decision speed. Although this is in accordance with the evidence on adult reading (de Groot, Borgwaldt, Bos, & van den Eijnden, 2002; Juphard, Carbonnel, & Valdois, 2004), the findings reported in Chapter 2 showed strong length effects on lexical decision speed in both dyslexic and normal reading children. Length affected words less than pseudowords in all groups. In the children without reading difficulties in Grade 4, length did not even affect lexical decisions on words at all. However, their lexical decisions on pseudowords were affected by length, indicating that they did first phonologically recode them before giving a ‘no’ response. Overall, these results suggest that children up to the age of 10 perform a lexical decision task in a different way than adults do. Adults seem to base their response on a familiarity check in the orthographic lexicon, without phonologically recoding either words or pseudowords. Children also seemed to start with a familiarity check in the orthographic lexicon. In contrast to adults, however, if a word was not represented in their orthographic lexicon, they proceeded by (silently) phonologically recoding it before making a lexical decision. In other words, if a word was not represented in their orthographic lexicon, they subsequently performed a familiarity check in their phonological lexicon. This seems a sensible strategy to enable accurate performance for readers whose orthographic lexicon is (considerably) smaller than their phonological lexicon. The results on children of varying reading levels combined with the findings for adults in other studies suggest that lexical decision becomes based on a lexical reading procedure to an increasing extent with the development of reading skill. The DRC model, which is based on skilled word recognition, requires an extension to enable an account of the length effects in lexical decision for readers who have not yet fully developed their orthographic lexicon, such as children and dyslexics. The connectionist network model by Ans, Carbonnel, and Valdois (1998) provides a slightly different account of the length effects. As the DRC model, this model (ACV98 for short) postulates two reading procedures: a global procedure that uses knowledge about whole words, and an analytic procedure that is based on smaller word parts. In the global procedure, all letters are processed in parallel, whereas the analytic procedure processes word parts sequentially. Different from 113
Chapter 6 the DRC model, however, these two procedures do not operate at the same time, but are activated successively; the analytic procedure is applied only if the global procedure fails to recognize a word. For reading aloud, the model makes similar predictions as the DRC model, in terms of differences in the relative reliance on the global and analytic reading procedures. In its predictions for lexical decision, the ACV98 model partly diverges from the DRC model. For adults, the predictions are similar to those of the DRC model: Lexical decision is assumed to be exclusively based on the global procedure, resulting in a lack of a length effect on lexical decision speed. For dyslexics, however, the model predicts a problem in the global procedure, resulting in a stronger reliance on the analytic procedure with following stronger length effects. Thus, whereas adults are assumed to base their lexical decision solely on the global procedure (as in the DRC model), readers who do not (yet) have the adequate printto-sound connections that underlie the global procedure perform the lexical decision task by relying heavily on the analytic procedure, resulting in length effects on their lexical decision speed. Although these predictions were specified for dyslexics, they may also be taken to apply to readers who have not yet fully developed their orthographic lexicon (e.g., children). To date, the DRC model and the ACV98 model are the only reading models that postulate a role for word length in reading. In both models, differences in the effect of length on reading speed are explained in terms of relative contributions of two reading procedures. This could be rephrased in terms of the contribution of phonological recoding and of lexical/orthographic knowledge. Nevertheless, it should be considered whether differences in the effect of word length necessarily reflect differences in the contribution of sublexical and lexical reading procedures, or, put differently, differences in the use of orthographic or lexical knowledge. For example, in the reading models developed by Seidenberg and colleagues (e.g., Harm & Seidenberg, 1999; Plaut, McClelland, Seidenberg, & Patterson, 1996; Seidenberg & McClelland, 1989), differences in reading speed for (pseudo)words of different lengths are argued to be a consequence of neighbourhood effects. This alternative account for the observed differences in reading speed for (pseudo)words of different lengths merits consideration. Orthographic neighbours are words that differ in only one letter position from the target word (Coltheart, Davelaar, Jonasson, & Besner, 1977). For example, some orthographic neighbours of the Dutch word bank are: mank, bink, balk, and bang (bank, lame, hunk, beam, and afraid, respectively). Orthographic neighbourhood size is generally negatively correlated with length (e.g., 114
Epilogue Frauenfelder, Baayen, Hellwig, & Schreuder, 1993; Weekes, 1997). Posthoc inspection of the (pseudo)word sets used in the present thesis indeed showed that orthographic neighbourhood size consistently decreased with word length (CELEX, Frauenfelder, et al., 1993). These differences may have affected the results differently in various tasks. In reading aloud, a larger orthographic neighbourhood size generally facilitates low frequent words and pseudowords, whereas it has no effect on high frequent words (e.g., Andrews, 1989; Peereman & Content, 1995). For the studies reported in this thesis, the difference in neighbourhood size may have enhanced the length effect in pseudoword naming, but – given the high word frequency – did probably not affect word naming, at least not in the children without reading difficulties in Grades 4 and 5. Therefore, we cannot exclude the possibility that the larger effect of length on pseudowords than on words in these children is partly due to the differences in neighbourhood size across pseudowords of different lengths. For the dyslexics and the younger children without reading difficulties, however, the orthographic form of the words may not have been as high frequent. This implies that the differences in neighbourhood size may have enhanced the length effect on both word- and pseudoword-naming. In these children, then, orthographic neighbourhood differences might be assumed to have affected both words and pseudowords, and may therefore have affected the result pattern as well. In lexical decision, a larger orthographic neighbourhood size generally facilitates low frequent words and has no effect on high frequent words, as in reading aloud. In contrast to its facilitating effect on reading aloud pseudowords, however, a larger orthographic neighbourhood size slows down responses to pseudowords in lexical decision (e.g., Andrews, 1989; Coltheart, et al., 1977; Sears, Hino, & Lupker, 1995). For the study reported in Chapter 2, this implies that the difference in neighbourhood size may have levelled off the length effect on lexical decisions on pseudowords. For lexical decisions on words, the difference in neighbourhood size for words of different lengths did probably not modify the results. Thus, had there been no difference in neighbourhood size across (pseudo)words of different lengths, the difference in the effect of length on words and pseudowords would have been even more pronounced. This implies that the difference in neighbourhood size does not affect the result pattern, and, consequently, does not change the interpretation of the results. However, given the observed length effects in lexical decision, the question can be raised whether the children (partly) performed the lexical decision task like a (silent) naming task, and subsequently made lexical decisions on the phonologically recoded (pseudo)words. If this is the case, then the differences in neighbourhood size may have affected the 115
Chapter 6 results in the lexical decision task in a similar way as in the naming task, as discussed in the previous paragraph. It should be noted that, in the selection of the words and pseudowords, taking into account orthographic neighbourhood size, word frequency and bigram frequency at the same time appeared to be impossible, given the limited number of words that are sufficiently high frequent for 8- to 10-year-old children. Lowering the minimal word frequency might have enabled matching a set of words of different lengths in terms of orthographic neighbourhood (or at least have decreased the differences), but this would certainly have affected the familiarity of the words, of both their phonological and their orthographic form. As a reduction in the difference between words and pseudowords (in terms of familiarity/frequency) would be undesirable, especially in children with limited reading experience, the selection of the present word sets seemed to be warranted. Furthermore, at present, information on neighbourhood size is solely based on adults’ vocabulary (e.g., Frauenfelder, et al., 1993). Information on neighbourhood size based on children’s vocabulary is not available. Although neighbourhood size for adults and children will certainly be correlated, children’s vocabulary is not yet as fully developed as in adults, resulting in (unknown) differences in neighbourhood sizes. It is worth mentioning that orthographic neighbourhood size was not controlled for in most other studies investigating the effect of word length (e.g., de Luca, Borrelli, Judica, Spinelli, & Zoccolotti, 2002; Hutzler & Wimmer, 2004; Juphard, Carbonnel, & Valdois, 2004; Spinelli, de Luca, di Filippo, Mancini, Martelli, & Zoccolotti, 2005; van der Leij & van Daal, 1999; Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005; Zoccolotti, de Luca, di Pace, Judica, Orlandi, & Spinelli, 1999). However, Ziegler, Perry, Ma-Wyatt, Ladner, and Schulte-Körne (2003) did control for the neighbourhood size of the orthographic rime (i.e., the number of body neighbours). Note that the number of body neighbours reflects only part of the orthographic neighbourhood, as this number is solely based on words that differ from the target word in the initial letter, and not on words that differ on other letter positions from the target word (such as middle or final letters). This cross-linguistic naming study involved dyslexic and normal reading English and German children. For the English children, a large number of body neighbours attenuated the length effects on reading speed. More importantly, they found that in the German children, length effects were as large on reading aloud (pseudo)words with a large number of body neighbours as on reading aloud (pseudo)words with a small number of body neighbours. This suggests that in shallow orthographies, such as German and Dutch, neighbourhood size (of the 116
Epilogue orthographic rime) does not modulate the effect of length on children’s reading speed. As orthographic neighourhood size may well differ across children at varying reading level and ability (Share, 1995), a posthoc analysis on the effect of orthographic neighbourhood size on word naming latencies in the studies reported in the present thesis was not possible at the subject level. However, to get at least an impression of the effect of orthographic neighbourhood size on reading speed, we did perform an analysis at the item level. In a posthoc regression analysis on the word naming latencies reported in Chapter 3, length was found to affect reading speed over and above the effect of orthographic neighbourhood size6 in all three groups. However, when orthographic neighbourhood size was entered into the analysis after length, it did not contribute to reading speed in the dyslexics and their age peers without reading difficulties. This suggests that length was the more important factor in reading speed. In the younger children, length and orthographic neighbourhood size both contributed to reading speed irrespective of the order in which they were entered into the analysis. These results suggest that the observed length effects on reading speed cannot be (fully) accounted for by the differences in orthographic neighbourhood size across (pseudo)words of different lengths. Furthermore, they suggest that the stronger length effects in the dyslexics than in their age peers without reading difficulties cannot be attributed to (differences in) the effect of orthographic neighbourhood size, thereby supporting the interpretation that dyslexics rely on a sublexical reading procedure to a larger extent than age peers without reading difficulties. To conclude, then, based on the results of the study by Ziegler and colleagues (2003) and on the additional analyses on our own data, it seems unlikely that the difference in neighbourhood size across (pseudo)words of different lengths in the studies reported in the present thesis affected the results to a large extent. The acquisition of orthographic knowledge Another issue in the present thesis was whether dyslexic children differ in their ability to acquire orthographic knowledge from children without reading
6
Note that orthographic neighbourhood size was based on adult’s vocabulary (CELEX; Frauenfelder et al., 1993), as this information is not yet available for children. Therefore, this analysis only provides a rough estimate of the effect of orthographic neighbourhood size on children’s reading. 117
Chapter 6 difficulties. Whereas it was shown in the studies reported in Chapter 4 that children without reading difficulties partly rely on visual word characteristics (or multiletter features) to improve their reading speed, the first study reported in Chapter 5 showed that for dyslexics these visual word features do not play a role in the increase in reading speed. It should be noted that the effect observed in the children without reading difficulties only concerned a small effect. Possibly, the change in visual multiletter features caused by case alternation demanded additional attention in these children (cf. Mayall, Humphreys, Mechelli, Olson, & Price, 2001). Dyslexic children might restrict their attention more to individual letters and consequently dedicate less attention to (a change in) multiletter features. In Chapter 4, the acquisition of orthographic knowledge was defined as an increase in reading speed. However, as argued in in Chapter 5, an increase in reading speed might be at least partly due to practice in articulating (pseudo)words after repeated reading (cf. Reitsma, 1983b). In addition, it has been suggested that an increase in reading speed may also, in part, be ascribed to familiarization to the experimental procedure of reading words on a computer screen (Thaler, Ebner, Wimmer, & Landerl, 2004). Therefore, an increase in reading speed in itself does not provide unequivocal evidence for the acquisition of orthographic knowledge, and an additional measure is needed. We argued that a decrease in the effect of length on reading speed would reflect a development from a predominantly sublexical reading procedure to a progressively larger contribution of a lexical reading procedure, thereby marking the acquisition of orthographic knowledge. At least in the normal readers, a decrease in the length effect on reading speed was expected, based on findings of previous studies that suggested the acquisition of orthographic knowledge after only a few reading trials (Ehri & Saltmarsh, 1995; Reitsma, 1989; Share, 1995, 1999). For the dyslexics, a smaller decrease in the length effect on reading speed, if any, was expected than in normally developing readers. This would indicate that dyslexics acquire orthographic knowledge at a lower rate than normal readers. Although overall reading speed increased substantially in both dyslexic and normal readers, however, neither dyslexics nor normal readers showed a decrease in the length effect after repeated reading. An unchanged effect of length on reading speed was anticipated in dyslexics, but it was not foreseen in the normal readers. The unchanged effect of length on reading speed suggests that no orthographic knowledge was acquired after reading the same (pseudo)words 15 times, not even in normally developing readers. This result does not tally with the previously reported finding that orthographic knowledge is acquired after only a few reading trials (Ehri 118
Epilogue & Saltmarsh, 1995; Reitsma, 1989; Share, 1995, 1999). Furthermore, it does not support the hypothesis that the acquisition of orthographic knowledge is wordspecific (Share, 1995). If it were, then the length effect on reading speed for trained (pseudo)words would surely decrease within 15 exposures. The unchanged effect of word length in both normal and dyslexic readers can have either of the following two theoretical implications. The first is that the acquisition of orthographic knowledge is not word-specific (as hypothesized by Share, 1995), but rather hinges on the gradual change of the reading system as a whole. This might involve a network with gradually changing relations between nodes as a result of (extensive) reading experience, as described in connectionist reading models (e.g., Plaut, McClelland, Seidenberg, & Patterson, 1996). What should also be considered is that the effect of word length in general has been observed to take years to change, continuing into adulthood (Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005; Spinelli, de Luca, di Filippo, Mancini, Martelli, & Zoccolotti, 2005). Zoccolotti et al. observed that the effect of word length decreased in children from first grade to third grade. This suggests that normally developing children acquire orthographic knowledge in these first three years of reading instruction. In another naming study (Spinelli et al., 2005), children in grades 6, 7, and 8 read words consisting of 3 to 8 letters. Length did not affect words up to 5 letters, but reading time did increase linearly with length for words consisting of 5 to 8 letters. This applied to the children in grades 6, 7, and 8 alike, with the reading speed curves moving down in a parallel fashion with about 30 ms a year. Thus, reading speed still increased every year, but the effect of word length remained the same in this more advanced stage of reading instruction. In contrast, a group of adults was not affected by word length at all. The combined results of these studies suggest a substantial acquisition of orthographic knowledge during the initial years of reading instruction, which then continues to develop at a slower pace in the subsequent years. Thus, although reading speed steadily increases with reading experience after the initial years of reading instruction, lexical orthographic knowledge is actually acquired much more slowly. The second possible theoretical implication of the unaltered effect of word length on reading speed is that (a decrease in) the effect of word length on reading speed is not an adequate marker of (the acquisition of) orthographic knowledge. Perhaps the effect of word length is not sensitive enough to detect changes in orthographic knowledge. Spelling changes in trained words such as homophones might then be more sensitive to detect the acquisition of orthographic knowledge. However, although the detection of spelling changes was reported in orthographic 119
Chapter 6 choice tasks and naming tasks (Ehri & Saltmarsh, 1995; Reitsma, 1983b; Share, 1999), it has not been replicated consistently in the latter task (Kyte & Johnson, 2006; Share, 2004). A more practical implication of the unchanged length effect after repeated reading might be that a considerable part of the improvement in reading speed actually seems to be due to practice in articulating the same words. The larger increase in response time for pseudowords than for words after reading them for the exact same number of times illustrates that the improvement in reading speed depends to a large extent on previous practice with that particular (pseudo)word. It might be interesting to compare repeated silent reading with repeated reading aloud, to examine how much can actually be attributed to practice in generating a word’s articulation. In addition, it should be considered that the assessment method might also make a difference; not only previous practice in articulating the word, but also generating its articulation at the time of testing can affect its response time. Comparing verbal and non-verbal responses to (pseudo)words after repeatedly reading them either silently or aloud might unravel the contribution of previous practice of a word’s articulation and of generating its articulation at the time of testing to reading speed. Specific deficits in dyslexia In the present thesis, orthographic knowledge was compared in dyslexic children and children without reading difficulties. Dyslexics were consistently more affected by length than age peers without reading difficulties, but length affected them to the same extent as younger children at the same reading level. This was not only found in tasks in which (pseudo)words had to be read aloud, but also in a lexical decision task, a task specifically appealing to the availability of lexical orthographic knowledge. Dyslexics still had to revert to a sublexical recoding strategy to give a correct response in a reading situation not requiring the articulation of the (pseudo)words, but a simple response as to whether they recognized the letter string as an existing word or not. The dyslexics (and the normal reading younger children) appeared to phonologically recode the words and pseudowords (silently) before making a lexical decision. This suggests that their orthographic lexicon is much smaller than in dyslexics’ age peers without reading difficulties. In other words, dyslexics used less lexical orthographic knowledge. Although the reliance on a lexical reading procedure did not come up to scratch with regard to the (chronological) age norm, the lack of a difference with younger normal 120
Epilogue readers with a comparable reading level suggested that this primarily reflects a lag in their development. Put differently, the limited size of their orthographic lexicon and the concomitant stronger reliance on a sublexical reading strategy seems to be tied to a slower development of the word recognition process, and does not necessarily imply a deficiency in the word recognition process itself. Although the disproportionally larger length effects in dyslexics suggests a difference in orthographic knowledge between dyslexics and age peers without reading difficulties, this does not seem to be the only difference between these groups. The slow reading speed in dyslexics cannot be fully accounted for by a stronger reliance on a sublexical reading procedure. The fact is that dyslexics’ reading speed is not only slower for (even very short) words, but also in single letters (e.g., Denckla & Rudel, 1974; 1976; Felton, Naylor, & Wood, 1990; Stenneken, Markus, Hutzler, Braun, & Jacobs, 2005; van der Leij & van Daal, 1999). This suggests that dyslexics also experience difficulties in processing at the letter level. In addition, dyslexics do not come up to the mark in reading pseudowords accurately and quickly, even in orthographies with regular print-tosound correspondences (e.g., Landerl, 2001; van der Leij & van Daal, 1999; Wimmer, 1996). This might indicate that their phonological recoding mechanism is also less successful than that in normal reading age peers, and that, again, part of their slow reading speed may be attributed to problems in processing individual letters. Conclusion The aim of the present thesis was to investigate possible differences in the use and acquisition of orthographic knowledge by dyslexic and normal reading children. The studies consistently showed that dyslexics’ reading speed was more affected by word length than reading speed of age peers without reading difficulties. This suggests that dyslexics rely relatively more on a sublexical reading procedure (i.e., phonological recoding) than their age peers, even in a task specifically drawing on lexical knowledge. In other words, dyslexics use less lexical orthographic knowledge than age peers without reading problems. However, there were no differences between dyslexics and normally developing younger children who had the same reading level as the dyslexics. Therefore, our results suggest that dyslexics’ stronger reliance on a sublexical reading procedure is associated with their reading level, primarily reflecting a delay in their development rather than a deficit. The
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Chapter 6 combined findings suggested that dyslexics do use lexical orthographic knowledge, but less than age peers without reading difficulties. Regarding the acquisition of orthographic knowledge, normally developing readers appeared to rely on visual multiletter features to increase their reading speed. In contrast, these features did not play a role in the improvement of reading speed in dyslexic children. Repeated reading resulted in considerable improvements in reading speed both in dyslexic and in normal reading children. Surprisingly, however, neither normally developing readers nor dyslexics appeared to acquire lexical orthographic knowledge after reading the same (pseudo)words 15 times, at least not when defined as a decrease in the effect of length on reading speed. The present findings suggest that reading speed steadily improves with reading experience and the development of reading skill, but that the acquisition of lexical orthographic knowledge probably takes more extensive practice.
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132
Appendices
Appendices Appendix A Word frequencies and bigram frequencies of the words used in the studies reported in Chapters 2 and 3 3 letters vis oog arm les dus uur gek bal dun pot oom bus nek bak elk zin kat vee rug kop MWF MBF
WF 162.9 83.9 158.0 108.6 913.5 419.7 153.1 148.1 74.1 79.0 227.1 88.9 79.0 98.8 256.8 187.6 207.4 103.7 172.8 192.6 195.8
4 letters WF
BF 48.5 1035.5 36.5 66.0 209.0 85.5 51.5 170.5 440.5 171.5 707.5 117.5 225.0 81.5 64.5 312.5 2258.0 320.5 42.0 268.5 335.6
gras stok fles zoon zelf boos melk plan knop stof soms grot slot leeg warm kort plat trap vuur hulp
192.6 74.1 133.3 113.6 883.8 217.3 153.1 138.3 74.1 88.9 691.3 88.9 74.1 93.8 241.9 113.6 88.9 108.6 162.9 123.4 192.8
5 letters WF
BF 145.3 201.7 81.7 926.3 466.0 1010.0 439.7 305.7 60.7 185.7 240.3 92.0 69.0 1334.0 342.3 223.7 271.3 99.0 98.7 133.7 336.3
sterk helft prins meest lucht licht sport plant zwart krant groot zwaar vocht droog nacht kraan straf markt kunst storm
162.9 98.8 128.4 113.6 543.1 464.1 148.1 153.1 93.8 177.8 765.3 88.9 74.1 93.8 222.2 113.6 79.0 207.4 93.8 69.1 194.5
6 letters WF
BF 239.0 440.0 103.5 464.3 378.3 411.8 199.8 179.0 213.8 243.0 611.0 318.0 373.5 381.8 430.5 468.0 226.5 435.0 194.8 319.0
slecht kracht herfst rechts steeds plaats vriend vreemd twaalf staart school schrik schoon streng straat stroom straks strand liefst dienst
BF
162.9 74.1 128.4 113.6 824.6 429.6 133.3 118.5 103.7 74.1 814.7 88.9 79.0 93.8 241.9 103.7 103.7 103.7 93.8 74.1 198.0
138.4 183.6 399.2 117.2 396.4 190.8 226.2 169.2 130.6 262.8 371.2 239.2 360.2 351.2 348.6 360.6 231.4 317 232.2 256.8
331.5
264.1
Note. WF = word frequency per million (based on Staphorsius, Krom, & de Geus, 1988); BF = mean bigram frequency, reported per 20,000 words (Bakker, 1990); MWF = mean word frequency per length category; MBF = mean bigram frequency per length category
133
Appendices
Appendix A (continued) Bigram frequencies of the pseudowords used in the studies reported in Chapters 2 and 3 3 letters W BF vik oot arg ges duk bur zek nal bun pom oos uus vek bap elm din kag lee rut kos
MBF
vis oog arm les dus uur gek bal dun pot oom bus nek bak elk zin kat vee rug kop
38.5 761.5 136.5 52.5 116.0 53.0 400.5 158.0 349.0 117.5 673.0 150.0 91.0 62.5 38.5 1192.5 533.5 294.5 40.5 304.0
278.2
4 letters W BF grat ston ples zook kelf boof helk plap knos stos loms grop flot seeg varm zort slat tran wuur mulp
gras stok fles zoon zelf boos melk plan knop stof soms grot slot leeg warm kort plat trap vuur hulp
204.3 196.0 92.0 932.0 363.0 992.0 563.3 160.7 46.3 203.3 201.7 105.3 64.7 1248.0 218.3 120.0 265.3 244.0 85.0 48.7
317.7
stert melft krins neest hucht vicht sporm plart zwant prant groon zwaag locht droof kacht kraat strar larkt munst stork
5 letters W
BF
sterk helft prins meest lucht licht sport plant zwart krant groot zwaar vocht droog nacht kraan straf markt kunst storm
321.0 301.5 142.0 463.3 351.5 382.5 117.5 231.8 161.0 204.5 598.5 332.5 387.5 383.5 421.8 518.8 228.0 439.5 195.8 319.3
vrecht stacht lerfst dechts kreeds slaats vrieks steemd twaand plaart schoom schrit schook strend straan strool strang stralf riefst hienst
6 letters W
BF
slecht kracht herfst rechts steeds plaats vriend vreemd twaalf staart school schrik schoon streng straat stroom straks strand Liefst dienst
123.8 233.6 298.4 115.6 271.4 199.4 107.0 327.2 214.0 163.8 398.0 255.6 345.0 362.2 368.4 333.8 306.0 233.6 220.0 198.4
325.1
Note. W = word that pseudoword was derived from; BF = mean bigram frequency of a pseudoword, reported per 20,000 words (Bakker, 1990); MBF = mean bigram frequency per length category
134
253.8
Appendices Appendix B Pseudowords used in the study reported in Chapter 4
Condition Lowercase training (8 times), Lowercase posttest
Assignment 1 CVCC CCVC MeLf sNaM kOrM pLaF tErN bLiM
Assignment 2 CVCC CCVC NiRk sNuK DaPt SmOp fOmP KrUp
LM8:
Lowercase training (8 times), Mixed-case posttest
ZiRk jUnT FaSp
kLoR tRiF sMiG
WaNs kOrM MuLs
TwEk ZwEr vRoL
ML8:
Mixed-case training (8 times), Lowercase posttest
NiLt sArK MuLs
pLaR PrEn sKaF
GoSt DeLg tErN
kWaN tRiF tJoF
MM8: Mixed-case training (8 times), Mixed-case posttest
WaNs HiRf vUrS
SnUk vLuP tJoF
kOnS jUnT GuRf
TrOp PrEn SpUf
LL4:
Lowercase training (4 times), Lowercase posttest
dOnT DaPt nOfS
bLuK sTuL vRoL
MeLf sArK TaGs
dRaK fReL sMiG
LM4:
Lowercase training (4 times), Mixed-case posttest
kOnS VePs fOmP
vLiS fReL BrEg
NiLt zEfT nOfS
sNaM vLuP kNiM
ML4:
Mixed-case training (4 times), Lowercase posttest
GoSt BuLf SiLm
dRaK sNiG kNiM
dOnT ToLg ZuLg
kLoR pLaF KnAf
MM4: Mixed-case training (4 times), Mixed-case posttest
MiGt DeLg GuRf
TwEk SmOp KnAf
hEtS HiRf SiLm
vLiS SkEt sKaF
–L0:
Untrained, Lowercase posttest
NiRk ToLg TaGs
TrOp SkEt SpUf
MiGt BuLf VuRs
pLaR sTuL BrEg
–M0:
Untrained, Mixed-case posttest
LL8:
hEtS kWaN ZiRk bLuK zEfT ZwEr VePs sNiG ZuLg KrUp FaSp bLiM Note. CVCC = pseudoword consisting of one initial consonant, a vowel, and two final consonants; CCVC = pseudoword consisting of two initial consonants, a vowel, and one final consonant
135
Appendices Appendix C Word frequencies and bigram frequencies of the words and pseudowords used in the studies reported in Chapter 5 4 letters
5 letters
6 letters
WORDS Set 1
Set 2
punt echt blik kerk vast half MWF MBF stuk duur hart soms plan kort MWF MBF
WF 94 425 84 84 543 158 231
BF 331 105 93 330 332 389
straf prins soort krant lucht zwaar
WF 79 128 351 178 543 89 228
263 336 119 104 691 138 114 250
259 102 381 240 306 224
BF 227 104 371 243 378 318
twaalf streek straks school kracht rechts
WF 104 69 104 815 74 114 213
273 zelfs kaart buurt sterk dicht sport
523 74 153 163 286 148 225
252
196 293 218 239 388 200
BF 131 399 231 371 184 117 239
plaats straat stroom schuur slecht herfst
430 242 104 89 163 128 193
256
191 349 361 231 138 399 278
PSEUDOWORDS Set 1
Set 2
stur duut wart roms plap tort MBF
W stuk duur hart soms plan kort
BF 224 85 349 279 161 377 246
delfs kaans zuurt stert vicht slort
W zelfs kaart buurt sterk dicht sport
BF 158 214 220 321 383 249 257
kraats stroot schuuf plecht terfst straar
W plaats stroom schuur slecht herfst straat
BF 239 310 227 130 257 396 260
vunt punt 335 stral straf 229 zwaalf twaalf 137 icht echt 77 zwins prins 73 strees streek 407 blis blik 170 soork soort 289 strakt straks 249 lerk kerk 333 krats krant 236 schoom school 398 valf vast 233 bucht lucht 362 knacht kracht 160 hast half 488 praar zwaar 370 hechts rechts 249 MBF 273 260 267 Note. WF = Word frequency per million; BF = mean bigram frequency; MWF = mean word frequency per length category; MBF = mean bigram frequency per length category; W = word that pseudoword was derived from. A given child was allotted either set 1 or 2 for training. This way, the words and pseudowords that were trained for that child were not too much alike, as the pseudowords were not derived from the words that were trained.
136
Samenvatting
Samenvatting (Summary in Dutch) De ontwikkeling van leesvaardigheid begint met het leggen van associaties tussen individuele letters en klanken (Ehri, 1992; 1998; Share, 1995). Aanvankelijk lezen kinderen woorden door de afzonderlijke letters één voor één om te zetten in klanken en deze klanken vervolgens aan elkaar te plakken tot een woord. Dit is een langzaam proces dat bewuste aandacht vergt. Naarmate kinderen meer leeservaring opdoen, leren ze impliciet dat sommige letter- en klankcombinaties vaker voorkomen dan andere. Ze worden gevoelig voor statistische regelmatigheden in de geschreven taal (bv. Bowey & Hansen, 1994; Ehri, 1998). Langzamerhand hoeven ze woorden niet meer letter voor letter te ontcijferen, maar leren ze lettercombinaties herkennen. Deze impliciete kennis, die ertoe bijdraagt dat het lezen (gedeeltelijk) gebaseerd is op de herkenning van letterpatronen en niet alleen meer op individuele letters, wordt orthografische kennis genoemd (Share, 1995). Door deze orthografische kennis gaat het lezen sneller. Dyslectici hebben moeite met de herkenning van letterpatronen, en lijken te blijven steken in een leesstrategie waarbij ze de woorden letter voor letter ontcijferen (bv. Zoccolotti, de Luca, di Pace, Gasperini, Judica, & Spinelli, 2005). Zij lijken dus problemen te hebben in het gebruik en de verwerving van orthografische kennis. In dit proefschrift werd in vier empirische studies het gebruik en de verwerving van orthografische kennis onderzocht bij kinderen met en zonder leesproblemen. Er werden twee methoden gebruikt om het gebruik van orthografische kennis vast te stellen. De eerste methode betrof het bepalen van het effect van woordlengte op de snelheid en nauwkeurigheid waarmee kinderen met en zonder leesproblemen woorden en pseudowoorden lazen. Hierbij werd verondersteld dat indien er een sublexicale leesprocedure aangewend werd waarbij de letters van een woord één voor één worden verklankt, elke letter extra tijd kost. Een tragere leessnelheid met toenemende woordlengte suggereert dus dat er overwegend gebruik wordt gemaakt van een sublexicale leesprocedure. Indien er echter een lexicale leesprocedure wordt aangewend, worden alle letters in een woord tegelijkertijd verwerkt. In dat geval maakt het aantal letters niet uit voor de leessnelheid, en worden langere woorden even snel gelezen als kortere. De mate waarin de leessnelheid van kinderen beïnvloed wordt door het aantal letters waaruit een woord bestaat geeft aan in hoeverre de kinderen gebruik maken van een sublexicale en een lexicale leesprocedure; hoe groter het effect van lengte, des te groter is het aandeel van een sublexicale leesprocedure (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; Weekes, 1997). 137
Samenvatting De tweede methode om het gebruik van orthografische kennis te evalueren bestond uit een verstoring van de visuele kenmerken van een woord door het te presenteren in afwisselend hoofdletters en kleine letters (vOoRbEeLd). Dit wordt in het Engels aangeduid met ‘case alternation’. Eerder onderzoek bij volwassenen heeft uitgewezen dat ‘case alternation’ het lezen vertraagt, hetgeen waarschijnlijk toe te schrijven is aan een verstoring van ‘multiletter’ kenmerken (Besner & Johnston, 1989; Mayall, Humphreys, & Olson, 1997). Deze kenmerken omvatten visuele eigenschappen van lettercombinaties, zoals bijvoorbeeld de vorm van de ruimtes tussen de letters en de grootte van de letters ten opzichte van elkaar. Door deze kenmerken te verstoren worden lettercombinaties die normaal gesproken als eenheid kunnen worden verwerkt opgebroken, en zodoende wordt een meer seriële leesprocedure in de hand gewerkt. De mate waarin ‘case alternation’ het lezen bij volwassenen vertraagt hangt af van de frequentie van het woord. Hoe frequenter het is, des te minder wordt het vertraagd door ‘case alternation’ (Besner & McCann, 1987; Besner & Johnston, 1989; Mayall & Humphreys, 1996). Volgens Mayall en Humphreys (1996) komt dit doordat er meer lexicale feedback beschikbaar is naarmate een woord frequenter is. De representatie van een woord in het orthografische lexicon helpt bij de identificatie van het woord, ook als de visuele kenmerken ervan verstoord zijn door ‘case alternation’. In de studie die beschreven wordt in Hoofdstuk 2 werd onderzocht in hoeverre dyslectische kinderen van 10 jaar oud gebruik maakten van lexicale en sublexicale leesstrategieën in een lexicale decisie taak, in vergelijking met leeftijdsgenoten zonder leesproblemen en jongere kinderen met hetzelfde leesniveau. Bij deze taak moesten de kinderen zo snel en nauwkeurig mogelijk aangeven of een visueel gepresenteerde letterreeks een bestaand woord was of niet. Aangezien woorden en pseudowoorden niet hardop uitgesproken worden in een lexicale decisie taak, was de veronderstelling dat het beroep op fonologische verwerkingsprocessen (zoals verklanking) in deze taak minder groot was dan in een taak waarbij de woorden wel hardop gelezen worden. Daardoor zou het gebruik van een lexicale leesstrategie kunnen worden bevorderd. Om de mate waarin de kinderen gebruik maakten van lexicale en sublexicale leesstrategieën te onderzoeken, werd de lengte van de woorden gevarieerd van 3 tot en met 6 letters. Alle drie de groepen kinderen maakten weinig fouten in de lexicale decisie taak. Woordlengte beïnvloedde de leessnelheid van pseudowoorden meer dan die van woorden in elke groep, hetgeen een groter aandeel van een lexicale leesprocedure suggereert bij het lezen van woorden dan bij het lezen van pseudowoorden, zowel bij kinderen met als zonder leesproblemen. De 138
Samenvatting leeftijdsgenoten van de dyslectici werden zelfs helemaal niet beïnvloed door lengte bij lexicale decisie op woorden. De leessnelheid van de dyslectische kinderen werd meer door lengte beïnvloed dan die van de leeftijdsgenoten zonder leesproblemen, wat suggereert dat de dyslectici een groter beroep deden op een sublexicale leesprocedure. Lengte had echter evenveel invloed op de leessnelheid van de dyslectici als op die van de jongere kinderen met hetzelfde leesniveau. De resultaten suggereren dat kinderen een lexicale decisie taak op een andere manier uitvoeren dan volwassenen. De snelheid van lexicale decisie op woorden en pseudowoorden wordt bij volwassenen niet beïnvloed door lengte (bv. de Groot, Borgwaldt, Bos, & van den Eijnden, 2002; Juphard, Carbonnel, & Valdois, 2004). Dit geeft aan dat volwassenen alleen een beroep doen op een lexicale leesprocedure tijdens de lexicale decisie taak. Kinderen lijken daarentegen, als ze een letterreeks niet direct herkennen met een lexicale leesprocedure, het (pseudo)woord vervolgens te verklanken met een sublexicale leesprocedure alvorens te beslissen of de letterreeks een bestaand woord is of niet. Met andere woorden: als ze een woord niet in hun orthografisch lexicon vinden, dan gaan ze vervolgens na of het woord wel in hun fonologisch lexicon gerepresenteerd is. Dit is een verstandige strategie voor lezers wiens orthografisch lexicon (veel) kleiner is dan het fonologisch lexicon, om ervoor te zorgen dat er weinig fouten worden gemaakt. In Hoofdstuk 3 werden twee verschillende methoden gehanteerd om het gebruik van orthografische kennis vast te stellen. Net als in de lexicale decisietaak (hierboven beschreven) werd gekeken of lengte een grotere invloed had op de leessnelheid van dyslectische kinderen dan op die van kinderen zonder leesproblemen. In deze studie lazen (dezelfde) dyslectische kinderen, leeftijdsgenoten zonder leesproblemen, en jongere kinderen met hetzelfde leesniveau als de dyslectici de woorden en pseudowoorden hardop. Het gebruik van orthografische kennis werd ook onderzocht door te kijken in hoeverre de kinderen lexicale feedback gebruikten wanneer de visuele kenmerken van de (pseudo)woorden verstoord waren door ‘case alternation’. De verwachting was dat ‘case alternation’ woorden minder zou vertragen dan pseudowoorden bij kinderen met meer lexicale (orthografische) kennis (d.w.z. de leeftijdsgenoten zonder leesproblemen), terwijl het woorden en pseudowoorden evenveel zou vertragen bij dyslectici. Bij het hardop lezen beïnvloedde lengte de leessnelheid van pseudowoorden meer dan die van woorden, zowel bij kinderen met als zonder leesproblemen, net als in de lexicale decisie taak. De leessnelheid van de dyslectici werd ook in deze taak meer beïnvloed door lengte dan de leessnelheid van leeftijdsgenoten zonder 139
Samenvatting leesproblemen, maar werd evenveel door lengte beïnvloed als die van de jongere kinderen met hetzelfde leesniveau. Verder bleek dat ‘case alternation’ de dyslectici meer vertraagde dan hun leeftijdsgenoten, maar dat het effect hiervan vergelijkbaar was op de leessnelheid van de dyslectici en op die van de jongere kinderen. Tegen de verwachting in vertraagde ‘case alternation’ woorden evenveel als pseudowoorden in alle drie de groepen. De resultaten lieten zien dat zowel kinderen zonder leesproblemen als dyslectische kinderen lexicale orthografische kennis gebruiken wanneer ze lezen in ‘normale’ kleine letters, maar dat deze lexicale kennis niet helpt bij het beperken van een vertraging in de leessnelheid door een verstoring van de visuele kenmerken, zoals dat wel bij volwassenen het geval lijkt te zijn (Mayall & Humphreys, 1996). In Hoofdstuk 4 werd gekeken naar de verwerving van orthografische kennis door kinderen zonder leesproblemen. Onderzoek met volwassenen heeft uitgewezen dat een verstoring van visuele kenmerken de woordherkenning vertraagt (Besner & McCann, 1987; Mayall & Humphreys, 1996) en dat dit de verwerving van orthografische kennis kan belemmeren (Jacoby & Hayman, 1987; Masson, 1986). In deze studie werd bekeken in hoeverre de visuele kenmerken bijdragen aan de verwerving van orthografische kennis bij kinderen met een normale leesontwikkeling. Tijdens een korte training lazen kinderen in groep 4 en groep 6/7 herhaaldelijk een set pseudowoorden in ofwel kleine letters, ofwel in afwisselend hoofd- en kleine letters. In de natest werden dezelfde pseudowoorden nogmaals gelezen, waarbij ze ofwel op dezelfde manier gepresenteerd werden als tijdens de training, of juist niet. Bovendien werd in de natest een set pseudowoorden gelezen die niet tijdens de training was aangeboden. Net als bij volwassenen vertraagde ‘case alternation’ de leessnelheid van kinderen. Deze vertraging werd kleiner naarmate de pseudowoorden vaker werden gelezen tijdens de training. In de natest bleek dat ‘case alternation’ de pseudowoorden die niet tijdens de training waren gelezen zelfs helemaal niet vertraagde. Deze resultaten lieten zien dat de kinderen gewend waren geraakt aan het lezen in ‘alternated case’. Een belangrijker bevinding was dat pseudowoorden die in de natest in kleine letters werden aangeboden sneller gelezen werden indien ze herhaaldelijk in kleine letters gelezen waren tijdens de training dan wanneer ze herhaaldelijk in ‘alternated case’ gelezen waren. Dit suggereert dat er meer orthografische kennis verworven was tijdens een training waarbij de pseudowoorden in ‘normale’ kleine letters gelezen waren dan tijdens een training waarbij de pseudowoorden herhaaldelijk in ‘alternated case’ gelezen waren. De visuele
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Samenvatting kenmerken lijken dus van invloed te zijn bij de verwerving van orthografische kennis door kinderen met een normale leesontwikkeling, net als bij volwassenen. In een tweede studie werd gekeken of de vertraging door ‘case alternation’ toe te schrijven is aan de verstoring van de visuele kenmerken van individuele letters, of aan de verstoring van de visuele kenmerken van lettercombinaties. De kinderen kregen een taak waarbij ze individuele letters snel achter elkaar moesten benoemen. Ze lazen ofwel allemaal kleine letters, ofwel allemaal hoofdletters, ofwel afwisselend hoofdletters en kleine letters. ‘Case alternation’ bleek geen invloed te hebben op het lezen van individuele letters. Dit impliceerde dat de vertraging van ‘case alternation’ tijdens het lezen van woorden en pseudowoorden toe te schrijven is aan de verstoring van de visuele kenmerken van lettercombinaties, en niet aan een verstoring van de visuele kenmerken van individuele letters. Hoofdstuk 5 betrof een studie naar de verwerving van orthografische kennis door zowel dyslectische kinderen als door kinderen zonder leesproblemen. De aanname was dat herhaald lezen zou resulteren in de verwerving van orthografische kennis (bv. Share, 1995; Reitsma, 1983b), waarbij het aandeel van een lexicale leesprocedure ten opzichte van een sublexicale leesprocedure zou toenemen. Dit zou zich moeten manifesteren in een afname van het effect van woordlengte op de leessnelheid na het herhaaldelijk lezen van dezelfde woorden en pseudowoorden. In de eerste studie lazen twee groepen dyslectici woorden en pseudowoorden van 4 tot en met 6 letters. De ene groep las de (pseudo)woorden in kleine letters; de andere groep las dezelfde (pseudo)woorden in afwisselend hoofdletters en kleine letters (d.w.z. in ‘alternated case’). Hiermee werd gekeken of de visuele kenmerken ook bij dyslectici van belang zijn bij het verwerven van orthografische kennis, zoals het geval was bij kinderen zonder leesproblemen (in Hoofdstuk 4). De dyslectische kinderen werden vertraagd door ‘case alternation’ aan het begin van de training, maar deze vertraging was aan het eind van de training verdwenen, net als bij de kinderen met een normale leesontwikkeling beschreven in Hoofdstuk 4. In tegenstelling tot de kinderen zonder leesproblemen was de leessnelheid van de dyslectici echter evenveel toegenomen na herhaald lezen in ‘normale’ kleine letters als na herhaald lezen in ‘alternated case’. Dit suggereert dat de visuele kenmerken van lettercombinaties niet bijdragen aan de verwerving van orthografische kennis bij dyslectische kinderen, zoals dat bij kinderen zonder leesproblemen het geval leek te zijn. De leessnelheid van de dyslectici nam aanzienlijk toe na het herhaald lezen. Het effect van lengte op de leessnelheid bleef echter hetzelfde. Dit suggereert dat het aandeel van een lexicale leesprocedure niet groter werd naarmate dezelfde woorden 141
Samenvatting vaker werden gelezen, en dat er dus geen orthografische kennis verworven werd. Om na te gaan of de verwerving van orthografische kennis een specifiek probleem is voor dyslectische kinderen, werd een tweede studie uitgevoerd. In deze tweede studie werd gekeken wat het effect was van dezelfde training op de leessnelheid van kinderen zonder leesproblemen uit groep 4 en 6. Ook bij de kinderen zonder leesproblemen nam de leessnelheid toe na het herhaald lezen, maar het effect van lengte op de leessnelheid bleef ook bij hen onveranderd. De resultaten van deze twee studies suggereren dat er geen orthografische kennis verworven werd na het herhaald lezen van dezelfde woorden en pseudowoorden. Deze bevinding strookt niet met de aanname dat de verwerving van orthografische kennis woordspecifiek is (Share, 1995). De resultaten lijken veeleer te suggereren dat leessnelheid weliswaar gestaag toeneemt door het herhaaldelijk lezen van dezelfde (pseudo)woorden, maar dat de verwerving van orthografische kennis waarschijnlijk meer tijd kost. De toename in leessnelheid lijkt vooral een gevolg te zijn van het oefenen van de articulatie van hetzelfde (pseudo)woord. In Hoofdstuk 6 werden de belangrijkste resultaten samengevat. Verder werd onder meer besproken in hoeverre een aantal computationele leesmodellen de resultaten kunnen verklaren. Zowel het Duale Route model (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) als het connectionistische model van Ans, Carbonnel en Valdois (1998) verklaren de verschillen in lengte effecten op de leessnelheid in termen van de relatieve bijdrage van een sublexicale en lexicale leesprocedure. In de modellen die ontwikkeld zijn door Seidenberg en zijn collega’s (bv. Harm & Seidenberg, 1999; Plaut, McClelland, Seidenberg, & Patterson, 1996; Seidenberg & McClelland, 1989) worden verschillen in leessnelheid voor korte en lange(re) woorden niet verklaard door het aantal letters op zich, maar worden deze verschillen in leessnelheid toegeschreven aan het kleinere aantal buurwoorden dat langere woorden doorgaans hebben. Buurwoorden zijn woorden die slechts op één letterpositie verschillen van het doelwoord (Coltheart, Davelaar, Jonasson, & Besner, 1977). Er werd overwogen in hoeverre verschillen in het aantal buurwoorden tussen (pseudo)woorden van verschillende lengte de resultaten van de verschillende taken beïnvloed zouden kunnen hebben. De conclusie was dat het onwaarschijnlijk is dat deze verschillen de resultaten in hoge mate beïnvloed hebben, en dat de verschillen geen alternatieve verklaring kunnen bieden voor de sterkere woordlengte effecten op de leessnelheid van de dyslectische kinderen dan op die van kinderen zonder leesproblemen. Samenvattend kan gezegd worden dat dyslectische kinderen een groter beroep doen op een sublexicale leesprocedure dan leeftijdsgenoten zonder 142
Samenvatting leesproblemen, maar evenveel als jongere kinderen met hetzelfde leesniveau. De dyslectici leken wel orthografische kennis te gebruiken, maar minder dan leeftijdsgenoten zonder leesproblemen. Verder werd gevonden dat visuele kenmerken van lettercombinaties een bescheiden rol spelen bij de toename van de leessnelheid van kinderen zonder leesproblemen. Deze visuele kenmerken leken bij dyslectici echter niet van belang voor de toename van de leessnelheid. Tenslotte bleek dat het aandeel van een lexicale leesprocedure niet toenam na het herhaald lezen van dezelfde woorden, hetgeen suggereerde dat er geen orthografische kennis verworven werd. Dit gold zowel voor de dyslectici als voor kinderen zonder leesproblemen. Mede aan de hand van enkele andere studies werd besproken dat de verwerving van orthografische kennis vooral in de eerste jaren van het leesonderwijs snel toe lijkt te nemen, en dat daarna de leessnelheid weliswaar minder snel maar toch gestaag toe blijft nemen met oefening. De verwerving van orthografische kennis lijkt in de latere jaren van het leesonderwijs echter langzamer te verlopen.
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Dankwoord
Dankwoord (Acknowledgements) Zowel binnen als buiten de muren van de Universiteit van Amsterdam zijn er heel wat mensen die het schrijven van dit proefschrift mogelijk hebben gemaakt. Allereerst: Zonder deelnemers geen onderzoek… Daarom wil ik graag de betrokken docenten en kinderen van de volgende scholen bedanken: SBO De Catamaran en Openbare Basisschool Nicolaas Beets in Alkmaar, SBO Kingmaschool en De Zonnewijzer in Amersfoort, Het Palet en Roelof Venemaschool in Amstelveen, St. Jozefschool in Blokker, Da Costaschool in Bodegraven, ’t Palet in Bovenkarspel, SBO De Vijverhof in Breukelen, De Hoeksteen in Bussum, ’T Palet in Diemen, SBO ’t Palet in Grootebroek, Hilversumse Schoolvereniging, Dr. Ir. C. Lelyschool, Violenschool, en De Wegwijzer in Hilversum, Bockxmeerschool, De Hoeksteen, De Ichtusschool, Mariaschool, Openbare Montessorischool, en De Zonnewijzer in Hoorn, De Parcival in Kersenboogerd, Openbare Basisschool Kudelstaart in Kudelstaart, De Stap in Landsmeer, De Dolfijn, Eerste Leidse Schoolvereniging, Lorentzschool, Roomburg, De Schakel, De Singel, en De Viersprong in Leiden, Het Bolwerk, De Driemaster, Elckerlyc, De Hobbit, De Regenboog, en Willem de Zwijgerschool in Leiderdorp, Rembrandtschool in Lisse, De Binnendijk, Kohnstamm Basisschool, en Ligthart Basisschool in Monnickendam, Comeniusschool in Naarden, Bommelstein in Nieuw-Vennep, De Beekvliet in Velserbroek, De Triangel in Weesp, De Mei in Wormerveer, SBO De Boekanier in Ymuiden, Corbuloschool, Klaverweide, en Westwoud in Zoeterwoude, en tenslotte De Tandem in Zwaag. De kinderen van die scholen heb ik niet allemaal zelf getest. Mijn dank gaat uit naar Nienke Bollen, Renate van der Jagt, en Constantijn Bloemendaal voor hun hulp bij de dataverzameling en het werven van scholen tijdens hun afstudeerprojecten. Ook de studenten van het onderzoekspracticum hebben hier een steentje aan bijgedragen: Anja Benjamin, Jolanda Spierenburg, Jouri Horsthuis, Margot van Setten, Merel Koolenbrander, Renate van der Knaap, en Rianne Hofman. De studentassistenten die als testleider op pad gingen wil ik ook graag bedanken voor hun inzet: Annelies de Muijnck, Anouk van Tooren, Arigje den Hartog, Claire Coombes, Dorine van Meel, Elke Jacobs, Esther Hakvoort, Femke Dekema, Inge Braakenburg, Irene Maris, Josien Dessens, Kina Smit, Lotte Raat, Marieke Mangnus, Mariëtte Sanders, Marjan Schumacher, en Tamara Mes. Mijn co-promotor Peter de Jong en mijn promotor Aryan van der Leij wil ik hartelijk bedanken voor hun begeleiding. Peter, jouw kritische commentaar was stimulerend om ergens diep over na te denken. Altijd bleef je betrokken door regelmatig even binnen te vallen om te horen hoe het ging. Aryan wil ik graag bedanken voor zijn 145
Dankwoord meer algemene feedback en voor het gul ter beschikking stellen van gelden om studentassistentie in te huren voor de dataverzameling. De leden van de promotiecommissie wil ik bedanken voor de tijd die zij hebben besteed aan de beoordeling van dit proefschrift. Victor van Daal dank ik tevens voor zijn instructies hoe ik het computerprogramma WordTest kon aanpassen voor de studie in Hoofdstuk 2. Een goede sfeer op het werk en collega’s die met je meedenken maken een promotietraject een stuk leuker. Vooral Anna Steenbergen, Judith Bekebrede, Eva Marinus, Vera Messbauer, Patrick Snellings, en Femke Scheltinga hebben hiertoe bijgedragen. Mijn vrienden ben ik dankbaar voor hun betrokkenheid, de gezellige en diepgaande gesprekken, en alle welkome afleidingen van dagelijkse promotiebeslommeringen. Met name Jacq, Suzanne, en Nelleke nemen een speciale plaats in. Mijn ouders wil ik heel graag bedanken voor hun nooit aflatende steun, liefde en vertrouwen. Jullie hebben mij een geweldige start gegeven. Sander en Liesbeth, jullie betrokkenheid heeft ook bijgedragen aan het welslagen van dit proefschrift, en hoe ik in het leven sta. Bedankt dat je er zowel online als offline altijd voor me was, San. Dat jij, en ook Jacq, naast me staan als paranimfen weerspiegelt hoe jullie ook naast mij stonden tijdens mijn gehele promotietraject. Verder wil ik mijn schoonouders bedanken voor hun interesse en steun, zowel binnen als buiten het werk. Tenslotte is er Hugo. En Hugo is er. In alle mogelijke opzichten ben je er voor mij geweest tijdens het schrijven van dit proefschrift. Dank je wel voor alles.
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Curriculum Vitae
Curriculum Vitae Vanessa Martens was born in Oostburg, the Netherlands, on December 5th 1975. After completing secondary education at the Scholengemeenschap ‘t Zwin in Oostburg in 1994, she did a foundation course in English Language and Literature at the Radboud University Nijmegen. In 1995, she proceeded with Applied Linguistics at the same university. From 1997 to 2001, she studied Experimental Psychology, specializing in bilingualism for both studies. She was appointed as a student assistant in the department of Applied Linguistics from 1998 to 2001, performing a number of studies, mainly on (re)learning vocabulary in a foreign language. With her final project, in which she studied the reactivation of forgotten (French) words, she graduated in Applied Linguistics in 2001. At the same time, she graduated in Experimental Psychology, with a final project on interlingual homophone recognition by Dutch-English bilinguals. From 2002 to 2006, she carried out a PhD project in the department of Educational Sciences at the University of Amsterdam. This research focused on the use and acquisition of orthographic knowledge in children with and without reading difficulties. Currently, she is working as a cognitive psychologist in the department of Research & Development (Consumer Perception and Behaviour) at Unilever in Vlaardingen.
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