The relation between reading ability and morphological skills ...

Reading and Writing: An Interdisciplinary Journal 12: 219–252, 2000. © 2000 Kluwer Academic Publishers. Printed in the Netherlands.

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The relation between reading ability and morphological skills: Evidence from derivational suffixes MARIA SINGSON1, DIANA MAHONY2 and VIRGINIA MANN1 1 University of California, Irvine; 2 Brigham Young University-Hawaii, USA

Abstract. The English orthography represents both phonemes and morphemes, implying that sensitivity to each of these units could play a role in the acquisition of decoding skills. This study offers some new evidence about sensitivity to morphemes and the decoding skills of American children in grades three to six. It focuses on knowledge of derivational suffixes, which is examined with sentence completion and sentence acceptability tasks that manipulate the suffixes in real words (e.g., electric, electricity) and nonsense derived forms (e.g., froodly, froodness). Both written and spoken materials are considered over the course of two experiments in which the children also received various reading tests, as well as tests of phonological awareness, vocabulary and intelligence. The results indicate that knowledge of derivational suffixes increases with grade level, along with decoding ability and phoneme awareness. Path analyses further reveal that, although there is a consistent correlation between performance on the derivational suffix materials and phoneme awareness and decoding ability, performance on the derivational suffix materials makes an independent and increasing contribution to decoding ability throughout the higher elementary grades. Keywords: Morphological awareness, Reading ability, Derivational suffixes, Phonological awareness

Introduction Whereas ‘shallow’ alphabets such as Spanish or Serbo-Croatian represent spoken words as a sequence of phonemes, the ‘deeper’ English alphabet represents a more abstract level combining the representation of phonemes with the representation of such morphological units as word roots and derivational and inflectional affixes. Because of this combined transcription, both morphological and phonological skills could be important to successful reading, even at the level of word decoding. In this research we have explored this possibility over the course of two experiments that examine children’s awareness of the syntactic properties of derivational suffixes. Our study complements a considerable body of research that has considered the relation between reading ability and phonological skills. The importance of phonological skills to reading ability has been well-researched and amply documented for English as well as for a variety of other alpha-

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betic orthographies. Children and adults who are poor readers of English have given various forms of evidence that they lack sufficient awareness of phonemes as units of their spoken language (for references, see Adams 1990; Bradley & Bryant 1985; Liberman 1982; Mann 1991; Perfetti 1985). Lacking an appreciation of how spoken words break down into sequences of phonemes, they fail to appreciate the fact that the letters of the alphabet can stand as a code for phonemes, and as a consequence, they are poor decoders of an alphabetic orthography. In this paper our concern is with the possibility that, since English spellings can also encode morpheme-sized units, certain morphological skills might be related to decoding ability. As a measure of morphological skill, we consider the ability to recognize derivational suffixes as morphological units that distinguish nouns, verbs, adjectives, and adverbs. A brief review of some English spelling patterns that transcribe derivational morphemes can illustrate why we might think that recognition of derivational morphemes could be important to the decoding of English. (A more detailed discussion is available in Mahony 1994). Let us first look at some derivationally related words involving suffixes that do not change the pronunciation of the base or root form. Consider the examples hot, hotness and hotly: The first of these three words is an adjective which is the base form, while the second and third are a noun and an adverb derived from the base by adding the appropriate derivational suffix. Note how the spelling of the base is preserved in the derived forms and how the same suffixes appear in other derivationally related words such as bland, blandness and blandly. The spelling patterns help mark the bases and suffixes and, therefore, could benefit a reader’s comprehension. Among other things, the ability to parse words into bases and suffixes may help readers access word meaning (see Taft & Forster 1975) and offers grammatical information that make eye movements more efficient (Rayner & Pollatsek 1989). For the decoder of these words, however, there is no particular benefit to knowing that the spellings preserve the morphemes. Because the suffixes -ness and -ly are “neutral” suffixes that have no effect on the pronunciation of the base to which they attach, the decoding of hotness and hotly requires nothing above and beyond a basic appreciation of how letters and letter sequences stand for phonological structure. For evidence about how morphemic transcription could be of importance to decoding, we need to consider another type of derivational suffix, namely, those ‘non-neutral suffixes’ that do cause phonological shifts. Consider the spellings of word pairs like reduce-reduction, atom-atomic or personalpersonality. In each of these pairs there is also a base and a derived form. They differ from the examples discussed in the previous paragraph in that each

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derivational suffix changes the pronunciation of the base. The suffixes -tion, -ic and -ity alter the base’s stress, the pronunciation of certain consonants, etc., yet the spelling of the base remains constant. Consequently, certain letters and letter combinations that represent one phoneme in the root must represent another phoneme in the derived form, destroying the possibility of a one-to-one relationship between graphemes and phonemes. A decoder might bypass this problem by using a visual strategy and simply memorizing the letter sequences that represent each word (see Seidenberg 1985, for example). Another possibility is to use a linguistic strategy that draws upon the decoder’s sensitivity to the morphological units and the rules that govern pronunciation of concatenated suffixes and bases (see Liberman, Liberman, Mattingly & Shankweiler 1980). It is this latter possibility in which we are interested: It forecasts that decoding skill may be associated with sensitivity to morphemes. Our presumption, then, is that since morpheme-sized units are preserved at the cost of phoneme-to-grapheme regularity in the spellings of words such as reduce and reduction, the ability to draw upon a tacit sensitivity to morphemes could be a fundamental part of decoding print into sound. If so, certain tasks that manipulate morphemes may distinguish between children who are good and poor decoders. The literature to date has offered some confirmation of this prediction (see, for example, Carlisle 1995; Carlisle & Nomanbhoy 1993; Fowler & Liberman 1995). Most of word formation is of two types: inflectional and derivational, both of which are transcribed by the orthography. Mastery of inflections is usually accomplished relatively early in life in a fixed manner (Berko 1958; Brown 1973, but see Wiig, Semel & Crouse 1973) and has been related to academic progress during the first and second grades (Brittain 1970; Carlisle 1995; Carlisle & Nomanbhoy 1993; Vogel 1977). A recent study of children’s spellings shows that even five- and six-year-olds use inflectional morphology to some extent (Treiman & Cassar 1996). Their spellings are more likely to preserve the ‘n’ in loaned than in bound, which implies that inflectional morphology is an early, albeit imperfect, source of information about how words should be spelled. Mastery of derivational morphology seems to involve a longer, more openended course (Derwing & Baker 1979; Nagy, Diakidoy & Anderson 1993; Tyler & Nagy 1989) which has the potential for making a richer comparison to the development of reading ability both in early grades and beyond. There are indications that the production of derived forms is related to the ability to read English in the first and second grades (Carlisle 1995; Carlisle & Nomanbhoy 1993), and middle elementary grades (Fowler & Liberman 1995), as well as in the junior high school and high school years (Leong 1989;

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Mahony 1994; Myerson 1976). The ability to resolve humor that manipulates morpheme-sized units is related to reading ability in the second grade (Mahony & Mann 1992). Yet there is evidence from the study of spellings that use of derivational morphology does not take off until around third grade (Henderson 1985), and that 12-year-olds do not appear to analyze the morphological components of derived words like closely (Sterling 1983). Even some adult spellers may fail to take advantage of complex derivational relations such as the one between courage and courageous (Fischer, Shankweiler & Liberman 1985). Thus there is certainly more to be learned about the role of derivational knowledge in the development of reading skill. In particular, its relation to decoding ability and its importance beyond the second grade need to be more thoroughly explored. There are reasons why we might expect that the relation between children’s sensitivity to derivational morphology and their decoding ability should show marked changes between grades 3 and 6. One is that the third grade is the time at which derivational morphology begins to play a demonstrable role in spelling (Henderson 1985). Another is that this is a time when vocabulary growth shows a strong contribution of derivational morphology. Anglin (1993), for example, has estimated that children acquire approximately 4 monomorphemic words per day, but over 20 bimorphemic and multimorphemic words per day between grades 3 and 5. It is quite reasonable to expect that sensitivity to derivational morphology would relate to performance on tests of written language comprehension, given Anglin’s observations about the relationship between vocabulary growth and derivational morphology. Our question, however, is whether the ability to pronounce a written word, is also related to knowledge of derivational morphology. Our study has used materials from Mahony (1994), whose research design had been inspired by Tyler and Nagy (1989). These studies had used a cloze task in which subjects choose the derivational form that completes a sentence, as in: “Please don’t be so – critical, critically, criticism, criticize.” In such items, the ability to make the correct choice could reflect tacit knowledge of which suffix denotes an adjective, as opposed to a noun, verb or adverb. However, it could also reflect being familiar with the meaning of critical, critically, etc. without necessarily having knowledge of morphemes and their syntactic categories. Recognizing this problem, both studies also included items that contained derivational forms of a nonsense word, as in: “She wants to – while she’s young: morate, morious, moration, morational.” In this case, a subject must know that morate and not morational fits in the blank because he or she tacitly knows that (1) a verb is required, and (2) that -ate is a verb suffix but -al, -ious and -ion are not. If performance on the nonsense derived


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forms correlates with reading ability, it is clearer evidence that derivational morphology is the source of the relationship. Mahony (1994) examined the relation between knowledge of derivational morphology and the reading ability of young adults. Her results indicate that in the high school and college years, reading comprehension is related to the ability to choose the correct answers in sentence completion materials like those described above. Her low-literacy subjects made the correct choice less often than the more skilled readers in a high school population, and, though ceiling effects were a problem, reading ability in college also tended to correlate with verbal SAT performance. The fact that the more skilled readers made the correct choice more often on the nonsense derived forms, as well as on the real words points to an explanation in terms of morphological abilities rather than vocabulary knowledge, per se. Mahony’s (1994) study did not consider decoding ability; it sought to establish a relation between derivational morphology and reading, in general. Her high school subjects were classified as skilled or less skilled readers on the basis of a variety of measures that confounded comprehension and decoding, and the use of SAT scores in the case of her university population is even more clearly biased towards a measure of comprehension. Another limitation to her study lies in the use of written materials that were read silently by the subjects. To answer correctly, subjects must have decoded the words of the test item before they could show that they knew how to use the derivational suffix. When subjects answered incorrectly, there was no way of knowing whether they decoded the written words, and then failed to make the correct choice because they lacked the requisite suffix category awareness, or whether they were unable to decode the words in the first place. The exclusive use of paper and pencil test is also an attribute of Tyler and Nagy (1989), who focused on the development of morphological knowledge and not on its relationship to reading ability. Our study of third to sixth graders involves two experiments that replicate and extend the results of Mahony (1994). Experiment 1 examines the use of derivational suffixes among children who have been given tests of decoding ability, and the vocabulary, block design and digit span from the WISC-R. The test of morphological skill uses real and nonsense derivational forms, and it further compares written materials that are silently read to those that are read aloud by the experimenter. This was intended to minimize the possibility that poor performance reflects a problem with reading the test materials. The IQ subtests are included as a probe to the relation between morphological skills and other cognitive factors. Gottardo, Stanovich and Siegel (1996), for example, report that in a study of phonological sensitivity, working memory and syntactic processing in 112

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third graders, phonological sensitivity is the strongest predictor of reading ability. Syntactic processing also contributes to children’s reading performance, but not when effects of working memory and phonological sensitivity are controlled. Experiment 1 of this paper considers vocabulary and verbal short term memory as factors that might be responsible for any relation between knowledge of derivational suffixes and decoding ability. Experiment 2 seeks further confirmation of a relationship between morphological awareness and decoding ability. Where Experiment 1 compared a written version of the test to one that was read aloud while the children looked at the text, Experiment 2 considers a purely oral version of the text in which, rather than ‘filling in the blank’, the subjects give grammaticality judgments of ‘right’ or ‘wrong’ to spoken sentences that manipulate derivational suffixes. Experiment 2 also considers the possibility that decoding-related differences in sensitivity to derivational morphology might be the by-product of differences in phonological awareness. Being aware of syllable- and phoneme-sized units is probably a prerequisite of being able to separate a derived form into its base and suffix, and since performance on phoneme- and syllable-segmentation tasks is related to reading ability, poor sensitivity to derived morphology may seem related to decoding ability for no other reason than its reliance on phonological awareness. Carlisle and Nomanbhoy (1993; but also see Carlisle 1995) considered this problem in their study of first graders, and included separate measures of phoneme awareness and morpheme awareness. Their results indicated that the two skills were related to each other and to reading ability, but that, once the contribution of phoneme awareness was considered, morpheme awareness made little additional contribution to the children’s variance in reading ability. Using various phoneme and morpheme production tasks, Fowler and Liberman (1995) also investigated the levels of phonological and morphological awareness in less-skilled readers, and whether a low level in each skill correlated with poor reading ability. Their conclusions pointed more to a phonologically-based deficit in poor readers, rather than a morphological one. They reasoned that morphological production tasks often draw upon a mixture of skills (ranging from orthographic knowledge to phonological sensitivity and receptive vocabulary) that are well-documented to be underdeveloped in poor readers. Thus, it is possible that the poor readers’ low performance on morphological tasks may simply be a consequence of their deficiency in these other skills. In another relevant study which administered separate phoneme- and morpheme-based tests to reading disabled children between 7.5 and 9.5 years of age, Shankweiler et al. (1995) conclude that phonological deficits and deficient production of morphologically-related


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forms stem from a common weakness with the phonological components of language and not from separable problems with phonology and morphology.

Experiment 1 Participants. The participants were 98 children from a predominantly middle-class public elementary school in Newport Beach, California. One class each from grades three through six was tested. Twenty-five of the students were in grade 3 (13 boys and 12 girls, mean age of 8;8), 27 were in grade 4 (12 boys and 15 girls, mean age of 11;9). Testing was completed between September and November of the school year. All children were native speakers of English and were without speech or hearing deficiencies. Parental permission to participate was obtained for all members of the four classes, and scores were calculated for all children who completed the testing. The school required that those children who had previously been identified as learning-disabled be excluded from the study so that they would not be given experience with any of the subtests of the WISC-R (Wechsler 1974) that the school psychologist would be using to evaluate them later in the school year. The Derivational Suffix Test (DST). The materials, as adopted from Mahony (1994), were a sentence completion task with changes made to decrease the phonemic decoding confound and to make the materials more appropriate for younger subjects. To minimize the demand on decoding we manipulated the type of presentation: The ‘Written’ presentation required the subjects to silently read the materials, and the ‘Oral plus Written’ presentation required the experimenter to read each item aloud while the subjects silently followed the text on their answer sheet. As in Mahony (1994), the confound of vocabulary knowledge was avoided by having real and nonsense words: The real word items contained real words as targets and foils, while the nonsense word items contained nonsense roots that ended in appropriate derivational suffixes. The orthogonal combination of presentation and type of item resulted in four subtests: (1) ‘Written’ presentation of real words, (2) ‘Written’ presentation of nonsense words, (3) ‘Oral plus Written’ presentation of real words, and (4) ‘Oral plus Written’ presentation of nonsense words. To make the materials appropriate for children, some of Mahony’s very low-frequency real word answers (e.g., systematicity, reductionist) were eliminated, and the number of syllables in the nonsense bases was also reduced (e.g., benedumptist → bantist). Because the syntactic context surrounding the blanks is essential to determining the correct answer choice, it was necessary

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during presentation of the ‘Oral plus Written’ presentation to repeat the test sentence four times (i.e., once for each answer choice). Therefore, all of the test sentences were shortened and simplified greatly to prevent the procedure from becoming overly long and cumbersome as well as to prevent placing an unnecessary burden on verbal short-term memory, given that this type of memory is a well-documented problem for poor readers (for reviews, see Mann 1991; Brady & Shankweiler 1991). Each subtest contained ten items and there was a practice item at the beginning of each form. Following Mahony (1994) each subtest contained one token of each noun suffix, -ion/ation, -ity, and ist, one of each verb -ate, -ize and -ify, and one of each adjective -ous/-ious, -al and -ive. For the tenth item, one additional noun-forming suffix, -ness, was added. Wherever possible, the blanks occurred at the end of the sentence, as that is the position where the answer choices can be emphasized and compared most easily. (Mahony (1994) indicated no significant effects of the position of the blank, hence blank position was not a variable). The order of presentation of items in each version was randomized. For a list of the test materials, see Appendix A. Reading tests. Reading ability was measured by administering the Word Identification and Word Attack subtests of the Woodcock Reading Mastery Tests, Form A (Woodcock 1973) to all subjects. In the Word Identification Test subjects are asked to read aloud individual words of increasing difficulty (is, come, . . . , picayune, beatitude). The Word Attack Test consists of 50 nonsense items of increasing complexity (ift, bim, . . . , bafmotbem, nolhod) which test the subjects’ phonetic decoding ability. The four classroom teachers whose students participated in the experiments also rated each child as a ‘good’, ‘average’, or ‘poor’ reader based on holistic impressions and classroom reading-group membership. IQ tests. The ‘Vocabulary’ and ‘Digit Span’ Verbal Subtests and the ‘Block Design’ Performance Subtest of the Wechsler Interlligence Scale for Children-Revised (Wechsler 1974) were administered to all children. In a comparative analysis, Silverstein (1970) identified ‘Vocabulary’ and ‘Block Design’ as one of the most effective combinations of two subtests, yielding correlations of 0.908 (WAIS) and 0.856 (WISC) with Full Scale IQs. The ‘Digit Span’ subtest was also included because it is a measure of shortterm verbal memory, a factor which is relevant to discussions of reading disability. We were concerned that measures of morphological skills, such as those measured by the DST, may be tapping into one and the same set of reading abilities that is correlated with short-term verbal memory (Gottardo et al. 1996).


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Procedure. All materials were presented in a fixed order, starting with administration of the Derivational Suffix Test to classroom-sized groups of children. Administration of the reading and intelligence tests was completed individually, following standard procedures. The instructions for the Derivational Suffix Test appear in Appendix A with the test materials. All subjects were presented with the written version before the oral version so that any effect of practice would serve to enhance performance on the ‘Oral plus Written’ form (i.e., the form which should be the easiest because it did not require decoding as well as analysis of the suffix). During the ‘Oral plus Written’ form, the instructor read the materials aloud, repeating the sentence before each answer choice. The subjects had a copy of the sentence on their own paper so that demands on verbal short-term memory would be attenuated. Results Table 1 summarizes the means and standard deviations for all the data as a function of children’s grade level. The results of the three subtests of the WISC-R and the two subtests of the Woodcock Reading Mastery Test are discussed first, followed by discussion of the Derivational Suffix Test. Intelligence tests. Two types of scores for the WISC-R appear in Table 1, the raw scores and the scaled scores. An ANOVA computed on the scaled scores revealed a significant main effect of grade [F(3,94) = 9.31; p < 0.001] and a main effect of subtest [F(2,94) = 22.702; p < 0.001], but no interaction. Post hoc Tukey HSD tests indicated that the scaled scores of the fourth graders tended to surpass those of the third graders, and that digit span tended to surpass vocabulary but that all other differences were not significant (p > 0.05). Word Identification and Word Attack Tests. The raw scores together with the scaled Reading Grade Scores for the Woodcock Word Identification and Word Attack Tests are presented in Table 1. They show an overall increase between the third and sixth grades that is an uneven function of grade level. On Word Identification the increase between the average raw scores of the third and fourth graders is 17 points; the differences between the fourth, fifth, and sixth graders are much smaller. Similarly, on Word Attack the increase between the average raw scores of the third- and fourth-graders is 10 points, while the scores of the fourth, fifth, and sixth graders are within one point of each other. Analyses of variance considering grade level (3–6) and raw scores on each of the two Woodcock subtests, indicated a main effect of grade level for both Word Identification [F(3,94) = 17.44; p < 0.000] and Word Attack tests [F(3,94) = 4.94; p < 0.005]. Post hoc Tukey tests indicated

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Table 1. Performance of subjects by grade in Experiment 1. Standard deviations are in parentheses Variables

Grade 3 (n = 25)

4 (n = 27)

5 (n = 24)

6 (n = 22)

Intelligence measures: WISC-R (Raw) Block 26.28 (11.95) 38.07 (10.43) 38.58 (8.51) 40.05 (11.08) Digit Span 11.12 (2.4) 14.63 (3.47) 13.46 (4.63) 14.5 (2.89) Vocabulary 24.08 (6.56) 30.63 (3.54) 29.29 (5.43) 32.0 (8.88) WISC-R (Scaled) Block 11.76 (3.78) 14.33 (3.05) 12.29 (2.87) 12.32 (3.56) Digit Span 10.64 (3.05) 13.11 (2.85) 11.46 (3.83) 11.95 (2.85) Vocabulary 9.76 (3.47) 11.56 8.88 (2.49) 8.68 (3.67) Reading measures: Woodcock Word ID 101.2 (15.7) 118.2 (15.0) 124.9 (12.2) 125.9 (11.4) Woodcock Word Attack 29.8 (14.1) 40.5 (10.3) 39.9 (8.6) 39.4 (12.1) Derivational Suffix Test: Written Real 5.88 (2.52) 8.04 (1.0) 8.46 (1.74) 9.0 (1.41) Written Nonsense 3.64 (1.78) 6.0 (2.02) 6.0 (2.54) 7.77 (1.72) Oral + Written Real 7.4 (2.08) 8.81 (1.04) 9.04 (0.96) 9.5 (0.6) Oral + Written Nonsense 5.0 (1.63) 6.96 (2.05) 6.21 (2.19) 7.6 (1.44)

that in both cases the third-grade scores were significantly lower than the fourth, fifth and sixth grade scores (p < 0.01) and that all other differences were nonsignificant (p > 0.05). Correlational analyses involving the WISC-R and Woodcock Tests. Correlations between the raw scores for the Woodcock subtests, the WISC-R subtests, sex, grade, and teacher classification are summarized in Table 2. Not surprisingly, there was a significant relationship between grade level and scores on Word Identification, and between grade level and scores on Word Attack. There was no relationship between scores on either of these tests and sex (p > 0.25). There were also significant correlations between scores on Word Identification and teacher classification, and between scores on Word Attack and teacher classification. Note further that, while all the relationships involving the two Woodcock tests, grade level and teacher classification were highly significant, the correlations between scores on the Woodcock tests and teacher classification were always larger than the correlations between scores on the

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Table 2. Summary of correlations with the Woodcock Reading Tests, the WISC-R, sex, grade level, and teacher classification

Word Attack Block Design Digit Span Vocabulary Grade Classification Sex

Woodcock Reading Tests Word ID Word Attack

WISC-R Block Digit

Vocabulary

0.82∗ 0.48∗ 0.54∗ 0.48∗ 0.55∗ 0.60∗ −0.06

0.35∗ 0.41∗ 0.40∗ 0.34∗ 0.36∗

0.36∗ 0.47∗ −0.07

0.37∗ 0.49∗ 0.32∗∗ 0.26∗∗ 0.49∗ −0.07

0.37∗ 0.27∗∗ 0.43∗ −0.07

∗ p < 0.001; ∗∗ p < 0.005

Woodcock tests and grade level. This suggests that decoding skill might be more closely associated with an evaluation of reading ability than with the number of years spent in the classroom. As expected, significant relationships were found between Vocabulary and Word Identification, and between Vocabulary and Word Attack. Relationships were found between Digit Span and Word Identification, and between Digit Span and Word Attack. There is ample evidence that deficiencies in verbal short-term memory are associated with reading disability (see Mann 1991; Brady & Shankweiler 1991), so it is reasonable to assume that differences in verbal short-term memory should relate to differences in reading ability among normal subjects as well. A less expected result is the significant correlations between Block Design and Word Identification, and between Block Design and Word Attack. It appears that reading ability in this population correlates significantly with all indicators of general intelligence that were measured. No significant (point biserial) correlations were found between the subjects’ sex and either Digit Span (p > 0.02) or Vocabulary (p > 0.3). However, a significant correlation was found between sex and Block Design, with males being more likely to have higher scores than females. These results support the well-known finding that males are generally more skilled at visual-spatial tasks, but is counterfactual to the well-known finding that females are generally superior at vocabulary tests (see Maccoby & Jacklin 1974, for a review). The Derivational Suffix Test. These results are the main concern of this study. The mean scores (number correct, max. = 10) on each of the four subtests are

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summarized in Table 1 as a function of grade level. Although performance increases with grade level, the increase between grades three and the other grades is relatively large, whereas those between grades four and five and between grades five and six are either relatively small or nonexistent. This trend was seen in the Woodcock tests and is consistent with there being a transition between the third and fourth grades in this population. Alternatively, the differences between the third and fourth graders as well as the older subjects could be a function of the greater IQ of the fourth graders. An ANOVA computed between grade level (3–6), presentation (‘Written’, ‘Oral plus Written’), and item type (real vs nonsense) indicated a main effect of grade [F(3,94) = 149.48; p < 0.001], a main effect of presentation [F(1,94) = 21.9; p < 0.001] and a main effect of item type [F(1,94) = 233.22; p < 0.001]. There was a significant interaction between grade and presentation [F(3,94) = 3.35; p < 0.002], and a significant interaction between grade and item type [F(3,94) = 2.69; p < 0.05]. Post Hoc Tukey HSD tests indicated that on both ‘Written’ and ‘Oral + Written’ forms of presentation there is a significant difference in scores between the real and nonsense word items for the third and fifth graders (p < 0.01) whereas the differences in the case of the fourth graders are significant only in the case of the written presentation (p < 0.05). The sixth graders show no significant differences between any of the manipulations of presentation and item type and all other differences are also nonsignificant (p > 0.05). Post-hoc Tukey tests further indicate that, on the average, the third graders performed at a lower level than all of the older children (p < 0.05 for fourth and fifth graders, p < 0.01 for sixth graders). They performed at a lower level than the sixth graders on all four subtests (p < 0.01). However, they performed at a lower level than the fifth graders on the ‘Written’ but not the ‘Oral + Written’ form of presentation (p < 0.01), and a lower level than the fourth graders on all subtests but the ‘Oral + Written presentation of real words’. All other grade-related differences were not significant (p > 0.1). In general, then, as grade level increased, two things happened: The children gained a level of morphological sensitivity that goes beyond vocabulary knowledge, and they became more able to read the test materials. Correlational analyses involving the derivational suffix test. Pearson correlations involving the Derivational Suffix Test, IQ and the three reading measures appear in Table 3. Inspection of that table indicates that correlations at the p < 0.001 and p < 0.005 levels of significance were found between scores on all four subtests and the various measures of reading ability: Both of the decoding measures, as well as teacher classification, related to the ability to choose the correct derivational form. Derivational Suffix performance also


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Table 3. Summary of correlations with the Derivational Suffix Test

Woodcock Word ID Word Attack WISC-R Block Design Digit Span Vocabulary Grade Classification Sex

Real words Written Oral + Written

Nonsense words Written Oral + Written

0.76∗ 0.64∗

0.58∗ 0.47∗

0.61∗ 0.48∗

0.47∗ 0.40∗

0.46∗ 0.45∗ 0.45∗ 0.48∗ 0.56∗ 0.11

0.40∗ 0.36∗ 0.45∗ 0.48∗ 0.47∗ 0.10

0.44∗ 0.41∗ 0.37∗ 0.54∗ 0.41∗ 0.00

0.24∗∗ 0.36∗ 0.38∗ 0.37∗ 0.42∗ 0.01

∗ p < 0.001; ∗∗ p < 0.005

correlated with measures of intelligence, although correlations with Word Identification are the highest. Performance also correlated with grade level, but no significant correlations were found between sex and any subtest of the Derivational Suffix Test (p > 0.05). Linear model. To examine whether morphological skills contribute to reading variance independently from contributions made by short term memory, we conducted a multiple regression analysis using the following variables: (1) To represent morphological awareness (MA), we used the z-scores of the averaged real and nonsense Oral plus Written DST. We chose only the ‘Oral + Written’ format of the DST because they placed less demands on both decoding ability and verbal short term memory than the ‘Written’ DSTs. (2) To represent short term verbal memory (STVM), we used the z-scores of the children’s performance on the Digit Span. These two predictors model the children’s decoding ability, which is represented by the age-restricted zscores from the combined raw scores on the Word Identification and Word Attack. Our regression of decoding ability, which entered MA after STVM, yielded a low r2 of 0.21 [F(2,95) = 12.91; p < 0.000]. While STVM achieved a beta of 0.33 (p < 0.001), the most note-worthy aspect of this analysis is the significant contribution made by MA to reading: Above and beyond STVM’s 16% contribution, MA contributes an additional 5% to total reading variance (p < 0.05).

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Item analysis. As there were different items in the different subtests, consistency among individual items should be considered. The mean percent correct responses for each item on each version and form of the test is reported in Appendix B. We incorporated the data for individual items into an ANOVA which indicated that scores for real word items were higher than scores for nonsense word items [F(1,14) = 10.7; p < 0.006] and that scores consistently increased with grade level [F(3.12) = 3.4; p < 0.05]. While there was a tendency for ‘Written’ presentation to be superior to ‘Oral + Written’, this failed to reach significance. There were also no significant interactions between grade, presentation and item type. There was no main effect of category (noun suffixes, for example, as opposed to adjective or verb suffixes). Discussion The children who participated in this experiment can be considered reasonably good representatives of the population of normal readers at their respective grades. Gender distribution is nearly even in all groups. The mean age of students at each grade is the norm for that level and there were no individuals whose age suggested that they had been either promoted ahead of their age-mates or held back a year. The average intelligence at each grade level is slightly above average for their ages based on their Block Design, Vocabulary, and Digit Span scores which, for all groups, were above the WISC-R raw score equivalents for test ages listed in the WISC-R test manual. Reading achievement for all groups is at or slightly above grade level as determined by Woodcock test results for both Word Identification and Word Attack. On the Derivational Suffix Test, the children’s performance also improves with grade level, such that, by sixth grade the children are correct on over 90% of the real word items and over 75% of the nonsense word items. There is slight advantage of the ‘Oral + Written’ over the purely ‘Written’ presentation and a much more consistent advantage of the real word versions over the nonsense ones. There is also evidence that, as grade level increases, the differences between the ‘Written’ and ‘Oral + Written’ items become less profound, and that children become more able to recognize the syntactic categories of the derivational suffixes in the nonsense materials. Our finding of age-related changes replicates the results of Tyler and Nagy (1989), who used similar real and nonsense word materials to study fourth-, sixth- and eighth-grade children. Like Tyler and Nagy, we find that scores improve equally across all types of suffix (i.e., noun, verb and adjective). However, where Tyler and Nagy emphasized age-related differences we place emphasis on decoding-related differences instead.


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The primary goal of Experiment 1 was to replicate Mahony’s (1994) indication that knowledge of the syntactic categories of suffixes relates to reading ability, and to extend it to younger children whose reading ability was measured in terms of their decoding skill. We have succeeded in meeting this goal. Performance on each of the four subtests of the Derivational Suffix Test is consistently correlated with two different reading measures: The two Woodcock tests, which were measures of decoding ability, and the classroom teachers’ evaluation which was a measure that confounded decoding and comprehension. Moreover, Experiment 1 directly answered the concern as to whether morphological awareness offers a genuine contribution to reading performance beyond what is already predicted by the more accepted ‘reading related’ abilities such as working memory and phonological awareness (as suggested by Gottardo et al. 1996). Results from our multiple regression suggest that morphological skill indeed upholds itself as an independent predictor of reading, even after the effects of verbal short term memory were controlled. At this point, two potential confounds remain to be addressed. First is the possibility that the relation between decoding ability and performance on the Derivational Suffix Test is only a byproduct of the written presentation of our test items. Second is the possibility that the relation is a byproduct of the association between phonological awareness and reading ability. To answer these questions, Experiment 2 employed a strictly oral version of the test and also administered independent measures of phonological awareness (Rosner & Simon 1971) and vocabulary.

Experiment 2 Participants. A total of 101 students from grades 3, 4, 5, and 6 were recruited from classrooms in a predominantly Caucasian and middle-class elementary school in Newport Beach, California. All participants were native speakers of English, and none were classified as learning-disabled. Twenty-five of the students were in grade 3 (14 girls and 11 boys, with mean age of 9 years; 1 month); twenty five were in grade 4 (13 girls and 12 boys, with mean age of 10;3); twenty six were in grade 5 (15 girls and 11 boys, with mean age of 11;1); and 25 were in grade 6 (15 girls and 10 boys, with mean age of 12;4). All testing was completed between late March and early June of the same academic year. Students participated with the written consent of their parents. Derivational Suffix Test (DST). To measure morphological awareness, we adopted the materials of Experiment 1. We left the ‘Written’ presentation

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of real and nonsense words unchanged. The only modification involved the ‘Oral + Written’ presentation. From the original ‘Oral + Written’ materials, we created a purely oral set of materials in which no text was provided for the children to follow while the experimenter read the sentences aloud. To maintain a low demand on children’s verbal short term memory, we transformed each item from the multiple choice ‘fill in the blank’ task into a grammaticality judgment format. Thus, instead of choosing one among four derived forms of the target word, which requires that all four choices be held in working memory, the children now simply judged whether or not each sentence they heard sounded ‘right’ or ‘wrong’. For example, “He wants to colonize the moon!” would be a ‘right’ sentence, as opposed to the ‘wrong’ sentence, “He wants to colonist the moon!” We used the same sentence framework and the same ten target real words and ten target nonsense words as in the ‘Oral + Written’ materials of Experiment 1. This time, however, the children had to make 40 grammatically judgments about sentences with real words and 40 about sentences containing nonsense derived forms, since we now had four variants of each test sentence (one of which contained the derived form that was syntactically appropriate with the sentence, and the other three presented the derivationally related foil words from Experiment 1). Printed on the children’s answer sheets were ‘Yes’ and ‘No’ columns of responses. The children were instructed to circle ‘Yes’ if they judged the sentence to be right, and to circle ‘No’ if the sentence sounded wrong. The order of presentation was randomized but blocked according to real and nonsense materials. In order to retain the ease of comparability between the written and oral versions of our tasks and to control for response bias, we scored the oral materials using a signal detection procedure. Since there was only one ‘Yes’ answer for every four variations of a target word, the total raw score indicated the number of correct ‘Yes’ responses (i.e., hits) less one-third of the incorrect ‘Yes’ responses (or false alarms). Although this scoring can yield scores ranging from a minimum of −10 to a maximum of 10, we equaled all negative scores to zero thus restricting our range within numbers zero to 10. Measures of phonological awareness. Our measures of phonological awareness were based on the 40-item Auditory Analysis Test (AAT), created by Rosner and Simon (1971). On this test, the experimenter pronounces a word and asks the child to repeat it while omitting certain sounds (e.g., “Can you say sour without /s/?”; “Can you say reproduce with /pro/?”). The testing continues until the child fails to correctly repeat four words consecutively. Given that there might be ceiling effects among the older children, we also designed an additional test of phonological awareness, the AAT-Nonce, to


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complement the AAT. This test uses nonsense words instead of real word stimuli. On this test, the child was asked to repeat pseudo-words without certain sounds (e.g., “Can you say shrup with /sh/?”). See Appendix C for a complete list of test items. All 40 nonsense words were matched both in length and sound extracted, item per item, with the original AAT stimuli. As with the Rosner test, this task was also terminated after the child failed to delete the correct phonemes in four consecutive nonsense words. Measure of vocabulary. We used the Peabody Picture Vocabulary TestRevised (PPVT-R) to measure each subject’s receptive vocabulary skills (Dunn & Dunn 1981). On this test, the experimenter pronounces a target word and shows four pictures simultaneously to the subject. The child must then choose the picture that corresponds best with the target word. The test is terminated once the subject made six errors within eight consecutive trials. Reading measure. To assess the children’s reading skills, we again used the Word Identification and Word Attack subportions of the Woodcock Reading Mastery Tests (Woodcock 1973). Procedure. All tests were administered in two days: The Woodcock subtests, the PPVT-R and phonological awareness measures were administered to individual children during the first day of testing. The Derivational Suffix Test was administered to separate groups of third, fourth, fifth, and sixth graders on a subsequent day. The real version of the DST was always administered first, followed by the nonsense version; written formats of both tests were given prior to their oral counterparts. Results Table 4 displays the means and standard deviations of the children’s performance on all of the tasks we administered. Reading tests. On the Woodcock tests, the children performed with increasing accuracy as grade level increased. No two grade levels scored equally; however, on the Word Identification task, a one-way Anova (factored by grade level) and Tukey’s HSD whose criterion was set at p < 0.05 for all analyses identified a significant difference only between the earlier grade levels (3 and 4) and the latter ones (5 and 6, p < 0.05) [F(3,97) = 21.81; p < 0.0000]. The differences between the reading scores of children in grades 3 and 4, as well as those in grades 5 and 6, were not sufficiently large to reach significance. The one-way ANOVA and test for Least Significance Difference (LSD) of the children’s performance on the Word Attack yielded

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Table 4. Performance of subjects by grade in Experiment 2 Variables

Grade 3 (n = 25)

4 (n = 25)

5 (n = 26)

6 (n = 25)

Reading measures: Word Identification (150) 103.5 (14.3) 110.6 (10.9) 122.5 (14.0) 129.2 (9.6) Word Attack (50) 33.1 (10.7) 36.0 (8.8) 40.0 (10.5) 43.4 (5.3) Phonological awareness: AAT(40) 26.4 (9.4) 27.4 (7.1) 34.4 (3.9) 34.2 (4.4) AAT Nonce (40) 24.0 (8.5) 25.0 (6.9) 32.7 (4.9) 32.8 (5.5) Derivational Suffix Test (DST): Written Real (10) 6.1 (3.0) 7.1 (2.6) 9.2 (1.3) 9.4 (1.4) Written Nonsense (10) 3.2 (2.7) 4.6 (2.5) 7.3 (3.1) 8.6 (2.2) Oral Real (10) 6.3 (1.5) 6.9 (2.4) 8.6 (1.2) 7.2 (1.5) Oral Nonsense (10) 3.2 (2.5) 4.2 (3.0) 6.6 (1.6) 6.4 (2.1) Vocabulary measure: PPVT-R (raw) (175) 99.6 (9.9) 110.4 (12.4) 120.9 (11.3) 125.2 (12.1) (age-normalized) 99.1 (11.6) 102.2 (15.4) 106.9 (12.2) 103.6 (12.7) Note: Italicized numbers represent the number of correct items possible

similar results as above [F(3,97) = 6.08; p < 0.0008] except the difference in scores of grades 4 and 5 was not significant. Vocabulary. On the PPVT-R, the children’s performance improved with increasing age and training in school. A one-way ANOVA and Tukey’s HSD revealed significant differences across all grade levels [F(3,97) = 25.14; p < 0.0000] except between grades 5 and 6. We also converted the raw vocabulary scores into their age-normalized values according to charts provided in the PPVT-R manual (Dunn & Dunn 1981). Statistical comparisons of these age-normalized scores confirmed no significant differences between performances of children from different grade levels. Such results indicate that, when age is controlled, the four groups of students in this experiment appear to be well-matched in vocabulary, with no grade level being particularly more ‘advanced’ or inferior to the others. Phonological awareness tests. Scores on the phonological awareness measures also increased as grade level increased, with children performing slightly worse on the nonsense version (AAT-Nonce) than on Rosner and Simon’s (1971) original materials (AAT). Similar to the results of the Woodcock subtests, results of separate analyses of variance and Tukey’s HSD


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on both the original [FAAT(3,97) = 10.73; p < 0.0000] and nonsense version [FAAT−Nonce (3,97) = 13.31; p < 0.0000] point to significant differences only between the lower grade levels (3 and 4) and higher ones (5–6) (p < 0.05). Derivational Suffix Test. As in the case of the Woodcock tests and the Rosner tests, the younger children in grades 3 and 4 did not perform as well as the older ones in grades 5 and 6. It is also apparent that, as in Experiment 1, there was an overall lower performance on tasks with nonsense derived items than on tasks with real words. Performance on the oral and written formats also differed, although variance analyses show that this difference was an artifact of performance by the sixth graders. As can be seen from Table 4, performance on both the oral and written presentations assumes similar trends across grade levels, with the range of scores shifted lower for nonsense words. Tukey’s test for HSD revealed a significant difference between the lower (3, 4) and upper grades (5, 6) on the written tasks (p < 0.05). On the oral task, however, Tukey’s HSD identified significant differences only between performances of grade 5 and the younger grade levels, 3 and 4 (p < 0.05), as a result of the 6th graders performing less well than 5th graders. Thus, except for the performance of the 5th graders, the patterns of results on the oral and written tasks would be similar (as in Experiment 1). Results from a repeated measures ANOVA factored by grade level, item type (real vs. nonsense), and presentation (written vs. oral) indicated significant main effects of each factor: Grade level [F(3,97) = 23.89; p < 0.0001], item type [F(1,97) = 75.32; p < 0.001], and presentation [F(1,97) = 12.59; p < 0.0006]. The following interactions were also significant: Item type by grade [F(3,97) = 4.29; p < 0.007], presentation by grade [F(3,97) = 5.94; p < 0.001]. No two-way interaction between item type and presentation was found. There was also no three-way interaction present among grade level, item type and presentation. On a series of item analyses, we investigated whether certain types of suffixes were more difficult to process than others (e.g., noun vs. verb vs. adjective). Our results (as in Experiment 1) indicated no significant differences in children’s treatment of stimuli with different suffix types on the written tasks. However, on the oral task involving real words, children found adjectival suffixes (on target words glorious, identical, and active) easier than noun or verb suffixes [F(2,95) = 26.12; p < 0.0001]. This pattern reverses when the oral task involves nonsense words: Children found nonsense items with adjectival suffixes more difficult than items with noun or verb suffixes [F(2,97) = 11.00; p < 0.0001]. The descriptive statistics aside, let us now confront the major issues, namely (1) does performance on our strictly oral measure of children’s

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Table 5. Correlations of all variables in Experiment 2 Variables Reading measures 1. Word Identification 2. Word Attack Phonological awareness 3. AAT 4. AAT Nonce Derivational Suffix Test 5. Written Real 6. Written Nonsense 7. Oral Real 8. Oral Nonsense Vocabulary 9. PPVT-R

1 2

3

4

5

6

7

8

9

0.84c 0.44c 0.51c 0.76c 0.65c 0.35c 0.32c 0.51c 0.35c 0.46c 0.67c 0.57c 0.40c 0.30b 0.41c 0.73c 0.39c 0.46c 0.18a 0.33c 0.37c 0.48c 0.49c 0.21a 25b 0.32c 0.66c 0.36c 0.27b 0.30b 0.30c 0.36c 0.37c 0.21a 0.32c 0.33c

a p < 0.05; b p 0.01; c p < 0.001

knowledge of derivational morphology also relate to reading ability, and (2) does knowledge of derivational morphology contribute to decoding skill above and beyond the contribution of phonological awareness? Correlations. Table 5 below catalogs the correlations among standardized (i.e., z-) scores of all variables. In the standardization process, we computed the z-scores of each variable for grades 3 through 6 separately. For example, only the third grade sample means and variances were used in standardizing their scores on all variables; a separate standardization of the fourth grade scores used the fourth graders’ own means and variances in z-score computations, etc. All correlations and subsequent analyses presented in this paper used the same set of age-restricted standardized scores of all variables in replacement of raw data. As can be seen in Table 5, all measures were significantly correlated. Several interesting points can be made from these results. First of all, the AAT Nonce correlated better with Word Identification (r = 0.51; p < 0.0001) and Word Attack (r = 0.46; p < 0.0001) than Rosner and Simon’s AAT (1971). This suggests that decoding real words has perhaps become an easy task by the third grade, and nonsense word processing is a better measure of the phoneme awareness skills employed in reading. Secondly, performance on the PPVT-R correlated more strongly with performance on the Word Identification task (r = 0.51; p < 0.0001) than on


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the Word Attack (r = 0.41; p < 0.0001). This pattern of correlations seems only logical, since Word Identification is a task that calls for processing of real, meaningful words, whereas the Word Attack uses nonsense words. A more curious result is the PPVT-R’s equal correlations with performance on the phoneme measures and the morpheme tests. In particular, its moderate correlation with the nonsense version of the Rosner (AAT Nonce), (r = 0.32; p < 0.001), is equivalent to its correlation with the oral DST (r = 0.32; p < 0.001). One might have expected vocabulary to relate more to real word test materials, and less to words that do not have meaning. Lastly, the subtests of the Derivational Suffix Test, in general, were significantly correlated with reading. As in Experiment 1, performance on the written presentations of real and nonsense words were well correlated with Word Identification (rreal = 0.76; p < 0.0001; rnonsense = 0.65; p < 0.0001) and Word Attack (rreal = 0.67; p < 0.0001; rnonsense = 0.57; p < 0.0001). The orally presented subtests that are unique to this experiment were also significantly correlated with the reading measures: The oral real items had a correlation of r = 0.35; p < 0.001 with Word Identification, and (r = 0.40; p < 0.0001) with Word Attack; the oral nonsense items also correlated with Word Identification (r = 0.32; p < 0.001), and with Word Attack (r = 0.30; p < 0.01). Linear models. The correlations aside, we are yet to answer whether knowledge of derivational suffixes plays an independent role in decoding ability above and beyond the contributions of phonological skills and vocabulary knowledge. To this end, we conducted a series of multiple regressions with the following variables: (1) To represent Vocabulary skills, we simply used the children’s age-restricted PPVT-R scores. (2) To represent phonological awareness (PA), we averaged the AAT and AAT-Nonce raw scores, and transformed the combined scores into age-restricted standardized scores (as described earlier). (3) In representing derivational suffix knowledge, we wanted to capture only those skills which are not conflated by demands on reading capabilities; thus, we averaged only the scores from the oral presentations, real and nonsense forms, of the DST. This average was then transformed into age-restricted z-scores (DS). Decoding ability, the dependent variable in our regression models, is represented by the age-restricted z-scores from the combined raw scores on the Word Identification and Word Attack, as in the linear models of Experiment 1. Table 6 lists the results from three sets of hierarchical regressions, highlighting the amount of independent contribution of individual variables to reading variance. In the first analysis (Order 1), a simple linear regression of reading by PA showed that PA accounted for 25% of reading variance.

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Table 6. Hierarchical regressions of morphological awareness, phonological awareness and vocabulary Variables Order 1 PA DS Vocabulary Order 2 DS Vocabulary PA Order 3 Vocabulary PA DS

r2 increase

F-value

F-significance

0.25 0.09 0.06

F(1,99) = 33.09 F(1,99) = 12.80 F(2,98) = 10.16

p < 0.0000 p < 0.001 p < 0.01

0.20 0.11 0.09

F(1,99) = 24.21 F(1,99) = 15.18 F(1,98) = 13.97

p < 0.0000 p < 0.001 p < 0.001

0.24 0.12 0.04

F(1,99) = 31.57 F(1,99) = 18.28 F(1,98) = 6.31

p < 0.000 p < 0.001 p < 0.05

When entered after vocabulary and DS measures (Order 2), PA continued to significantly account for 9% of the total reading variance [F(1,98) = 13.07; p < 0.001]. Vocabulary accounted for 24% of the reading variance in a simple linear regression (Order 3); beyond the influence of PA and DS (Order 1), it contributed an additional 6% to total reading variance [F(1,98) = 10.16; p < 0.01]. When DS was entered into a simple linear regression predicting decoding ability (Order 2), it obtained an r2 of 0.20. Beyond the effect of PA (Order 1), DS contributed significantly to reading [0.09 increase in r2 , F(1,99) = 12.80; p < 0.001]. Order 3 offers a direct answer to our search for a separate contribution of knowledge of derivational suffixes (as measured by a purely oral grammaticality judgment task) to decoding: When entered after vocabulary and PA, DS (our measure of morphological skill) remained a significant contributor to reading, accounting for 4% of the total reading variance. Thus, at least for this particular sample, the contribution of the Oral DST (though slim) cannot be ignored. To further investigate the degree of influence of one variable on another, we looked at a path analysis within a causal framework that assumes the following : (1) Of the three variables, vocabulary skills are the most global measure; (2) these skills, in turn, couch the development of the more readingrelated phonological awareness and morphological awareness. This analysis affords us another (and perhaps more illustrative) view of not only the independent contribution made by each variable, but also of the interrelationship among our predictors. As Figure 1 indicates, each variable poses an independent and significant weight upon reading performance: βVOCABULARY = 0.28, βPA = 0.32, and βDS


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Figure 1. Path analysis of the results of Experiment 2, showing the contributions of vocabulary, phonological awareness and morphological awareness as measured by the oral subtests of the Derivational Suffix Test.

= 0.22. These independent weights are often coupled with indirect influences from other variables. For example, the interaction between vocabulary and PA [βV−AP = 0.37; it p < −0.0002] purports an indirect weight of (0.37) × (0.32) = 0.12 on reading in addition to the independent contributions of vocabulary and PA. Similarly, vocabulary’s correlation with DS [βV−DS = 0.41; p < 0.0000] results in an additional effect of 0.09 (or 0.41 × 0.22) on reading. Over all, our path analysis highlights the degree of overlap between phonological awareness and morphological awareness. Apart from their own independent contributions to decoding, PA and DS are correlated, and therefore, share significant indirect effects. Via its correlation with DS [βPA−DS = 0.33; p < 0.0006], PA gains an additional weight of 0.07 (or 0.33 × 0.22). Via DS’s correlation with PA, it places an additional weight of 0.11 on decoding ability. What is clearest in the above analyses is that morphological awareness (as measured by performance on the oral DST) does, indeed, offer a separate contribution to reading performance above and beyond what is furnished by vocabulary and phonological skills. Our results indicate that performance on this test of morphological awareness is as good a predictor of reading ability as performance on either phonological or vocabulary tasks. Lastly, we performed a series of hierarchical regressions on separate grade levels in order to examine the trend of suffix awareness development as age increased. From Figure 2, two trends are apparent: (1) Phonological awareness gradually loses its contribution to reading variance as grade level increases. In fact, when entered in a hierarchical regression after the effect of

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Figure 2. The relative contribution of phonological and morphological awareness to decoding ability as a function of age. The values reflect the correlation between the (normalized) Rosner tasks and decoding ability and the residual correlation that is due to the contribution of the oral real and nonsense subtests of the Derivational Suffix Text (normalized) after the contribution of the Rosner tasks has been removed from the equation.

DS were controlled, PA’s contribution to total reading variance failed to reach significance beyond the third grade level. (2) The contribution of morphological awareness (as measured by the Oral DST) to reading, on the other hand, slowly increases beginning in the fourth grade level. Above and beyond the effects of PA, performance on the DST offers a significant contribution to reading in grade levels 5 [F(1,24) = 4.49; p < 0.05] and 6 [F(1,23) = 5.85; p < 0.05]. Discussion In reaching closure on this study, let us consider a two-part question: First, we ask if there is a correlation between performance on our test of derivational morphology and children’s ability to learn to decode English. If such a correlation exists, then does knowledge of derivational morphology make an independent contribution to reading ability, above and beyond the contributions of phonological awareness and vocabulary? The answer to the first half of the question is resoundingly positive. In two different experiments we have shown an association between our Derivational Suffix Text materials and decoding ability in grades three through six. In each experiment we find that children’s performance on the derivational suffix test increased at the same point in time that their decoding ability significantly changed, although the location of that point differed between the two samples. In each experiment there are significant correlations between performance


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on the Derivational Suffix Test and reading ability. Thus we have replicated Mahony’s (1994) findings about a relation between reading and knowledge of derivational suffixes. We have further extended those results to young children whose reading is measured solely in terms of decoding skill and whose knowledge of derivational suffixes is measured with an oral language test as well as with pen and pencil. As for the possibility that morphological skill makes an independent contribution to reading ability (i.e., the second part of our question), our Introduction had reviewed previous research suggesting that the contributions of morphological ability are highly overlapping with those of phonological skills (Carlisle et al. 1993; Shankweiler et al. 1995), and converge on a common ability. Carlisle and Nomanbhoy’s (1993) study of first graders, and Shankweiler et al.’s (1995) study of learning disabled third graders both report a large overlap between phonological and morphological skills. Carlisle and Nomanbhoy focused on the early stages of reading acquisition. They administered separate tests of phoneme and morpheme awareness, and the morpheme awareness test measured children’s production of derivational and inflectional suffixes. Their results indicated that morpheme awareness was correlated with their measure of phoneme awareness but accounted for only an additional 4% of the variance in reading ability above and beyond the 37% of variance accounted for by phoneme awareness. Shankweiler et al.’s (1995) study was an extensive examination of the cognitive profiles of 7.5 to 9.5 year old children with learning disabilities, who were compared as a function of the type of learning disability and to normally reading controls of the same age. Among other things, the extensive test battery included the Rosner test as a measure of phoneme awareness and a morpheme awareness test that was analogous to the production of derivational and inflectional morphemes developed by Carlisle and her colleagues. Performance on both the phoneme and morpheme awareness tests was deficient among reading-disabled children but not among math-disabled or attention deficit children. Performance on both tests was also highly correlated with decoding ability. As for the separability of the two, a comparison of phonologically shifted (five/fifth) and unshifted (four/fourth) items in the morphological test revealed that the shifted items resulted in greater differences between the performance of reading-disabled children and the other groups. It was further the case that when the effects of age and IQ were controlled, children’s production of derivational and inflectional morphemes accounted for only 5% of the variance above and beyond that accounted for by phoneme awareness, whereas phoneme awareness accounted for 11% of the variance above and beyond morpheme awareness. The authors interpret

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these two pieces of evidence as implying that the poor readers’ problems with phoneme and morpheme awareness have a common source of difficulty in the phonological component of language. Given that a contrast between phonologically-shifted and phonologicallyneutral items was an important part of Shankweiler et al.’s (1995) interpretation of their results, we might ask if there is any contrast between these two types of suffixes in our own data. Our study was not designed to directly contrast phonologically-shifted vs. phonologically neutral suffixes, but there were eight items of each type within our noun materials. Looking at these, it appears that those suffixes that appeared on the nonsense items (see Table B.II in the appendix) gave a consistent effect of phonological shift: Items for which the correct item involved a suffix that shift pronunciation were more difficult than those that did not. However, the results from the real word items are more complicated and there is not a consistent effect of phonological shift. We suspect that this may be due to differences in the frequency of our items, and perhaps in the relative frequency of the individual derivations. Further decisions about whether there is an interaction between the effect of reading ability and that of phonological shift will have to await further research designed for that purpose. The strongest point of comparison between our research and that conducted in the past is the regression analyses conducted in Experiment 2. For the population as a whole, the results of our analysis are virtually identical to those in Carlisle and Nomanbhoy (1993) and in Shankweiler et al. (1995). Although our measure exclusively focused on derivational morphology and on recognition and not production, we once again find that morpheme awareness is significantly correlated with phoneme awareness. Our analysis controlled for the effects of vocabulary knowledge whereas Shankweiler et al. (1995) controlled for age and IQ, yet our results are quite comparable. When we control for performance on the phonological awareness and for performance on the PPVT-R, performance on the ’Oral’ parts of the Derivational Suffix Test accounts for about 4% of the variance whereas when performance on the ‘Oral’ parts of the Derivational Suffix Test and the PPVT-R are controlled, phonological awareness accounts for about 9% of the variance. (When PPVT-R is controlled, the two tests together account for around 16% of the variance in reading ability, whereas when PPVT-R is uncontrolled, they account for around 34%). These aspects of our data lead us to agree with Shankweiler et al. that poor readers’ difficulty with morphology is at least in part the expression of a phonological limitation. Morphological ability does correlate with phonological awareness, and in and of itself, seems to account for about half the amount of variance accounted for by phonological awareness.


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However, at the same time that we agree that there is a strong phonological component to our morphological measure, we would caution against ascribing no importance to morphological skills. However small its magnitude, morphological awareness makes a separate and valuable contribution to reading ability in the present study as in those that preceded it. The analysis in Experiment 2 constitutes an extremely stringent test of the hypothesis in question. Our test of morphological knowledge (the purely Oral DST) focuses primarily on the syntactic function of suffixes. It is administered orally to remove any immediate contribution of decoding ability. Measures of phonemic awareness and vocabulary knowledge, both of which overlap substantially with morphological knowledge, are entered into the regression equation first. With these controls in place, we still find that the oral DST predicts significant unique variance in children’s reading performance. An important feature of our data, which included third through sixth graders where Carlisle and Nomanbhoy (1993) had studied first graders and Shankweiler et al. (1995) had studied third graders, is its indication that the relative contribution of phoneme vs morpheme awareness is age dependent. Like others before us, we see that the contribution of phonological awareness is quite strong in the third grade. What is notable is that, in our population, the contribution of phonological awareness gradually fades away, leaving in its wake a steady role of morpheme skill that persists as the reader progresses through the upper elementary grades. In fact, in this particular sample of fifth and sixth graders, the oral tests of morphological skill are significantly associated with reading ability (p < 0.05) where performance on the Rosner-based tests of phonological awareness are not. This increasing importance of morphological awareness between grades three and six calls to mind two of the observations about children’s morphological abilities that we had previously mentioned in the Introduction. One is Anglin’s (1993) observation that children’s sensitivity to the derivational morphology of spoken language should show marked changes between grades three and six. Another is Henderson’s (1985) observation that children do not really begin to represent derivational morphology in their spellings until they are in the third grade. Our data provide yet another indication that the later elementary grades is an important time for the development of derivational morphology in both written and oral language. It further emphasizes that with greater knowledge about the derivational morphology of spoken language comes an increasing ability to decode the English orthography.

246


Acknowledgments This research was part of a larger project described in Mahony (1993). We would like to thank M. L. Kean and W. Watt for their comments on earlier drafts and insightful discussions throughout the project. The continued assistance of the Newport-Mesa Unified School District and the Mariners Elementary School is gratefully acknowledged. Appendix A: Derivational suffix test Written form, real word version Instructions: Please look at the top of the first page. On this section of the test, you will see sentences that have a blank space. Above and below the blank are written four possible words that could be used to fill the blank. Only one of the words makes a good sentence. Look at the example. A. She hoped to make a good impressive. B. She hoped to make a good impressionable. C. She hoped to make a good impression. D. She hoped to make a good impressively. Word C makes a good sentence. She hoped to make a good impression. So the letter C is circled. For each set, please circle the letter of the word that makes a good sentence. Stop after you finish the ten sentences and look up. Do not turn to the next section of the test until I tell you to do so. Are there any question? A. impressive B. impressionable .

Example: She hoped to make a good C. impression D. impressively

A. operation B. operational 1. A famous doctor performed the

A. fertilize B. fertilization 6. Farmers

C. operative D. operationalize

their fields. C. fertility D. fertilizer A. industrialization B. industry

A. gratuity B. grateful his desires.

2. He likes to

7. She works hard. She’s very

C. gratify D. demonstrate

. C. industrious D. industrialize A. identical B. identify

A. demonstration B. demonstrative .

3. Watch carefully. I will

8. Those two dogs are almost

C. demonstrable D. demonstrate

. C. identification D. identity A. activist B. active

A. personify B. personalize .

4. Age improved her

9. He’s always going to meetings. He’s an

.

C. personality D. personal

C. activate D. activize A. bright B. brighten

A. productivity B. productive .

5. He’s too old to be C. production D. produce

10. He was blinded by the

. C. brightly D. brightness

247


Written Form, Nonsense Word Version Instructions: Please turn the page. Now you are ready for Section 2. Section 2 is very similar to Section 1, but there is one difference. In Section Two the four answer choices are not real words. They are nonsense words. Nevertheless, one of these nonsense words makes a good sentence. The other three do not. Read each sentence and decide which word is the best one to fill in the blank. circle the letter of that word the same way you did in Section 1. Do you have any questions about what you are supposed to do? Begin. A. froodly B. froodful

A. lorialize B. lorial

1. I could feel the

. C. frooden D. froodness A. tribacious B. tribicism idea. 2. What a completely C. tribacize D. tribation A. sufilive B. sufilify . 3. I admire her C. sufilation D. sufilize A. curfamic B. curfamity the money? 4. Where do they C. curfamate D. curfamation A. scriptial B. scriptize . 5. Please C. scriptist D. scriptious

6. The meeting was very

.

C. lorialism D. lorify A. dantment B. dantive 7. I just heard a story. C. danticism D. dantify A. cicarist B. cicarize 8. Dr. Smith is a famous . C. cicarify D. cicarial A. romify B. romity 9. Can you both sides? C. romious D. romative A. brinable B. brinicity 10. He has too much . C. brinify D. brinicious

Oral + Written Form, Real Word Version Instruction: Please turn the page. Here are ten more sentences like the ones you just finished. This time I will read them aloud to you. Follow along on your paper. After you hear the four choices, circle the letter of the word that makes a good sentence. A. popular B. population 1.The census is a count of the C. populate D. popularize A. electrify B. electrical . 2. The garage has no C. electric D. electricity A. regulation B. regulate the water? 3. Does the city C. regularity D. regular A. colonist B. colonization the moon! 4. He wants to C. colonial D. colonize A. gloriousness B. glorify . 5. The sunrise was so C. glorification D. glorious

A. dead B. deadly .

in her feet. C. deadness D. deaden A. activation B. activity . 7. She is not very C. active D. activate A. critical B. critically 8. Please don’t be so . C. criticism D. criticize A. conversational B. conversationalist 9. I like to talk with her. She’s a good . C. converse D. conversation A. diversionary B. diversity 10. They need to . C. diversion D. diversify 6. She ignored the feeling of

248


Oral + Written form, Nonsense Word Version Instructions: Please turn the page. Here are ten more sentences like the ones you just finished. This time I will read them aloud to you. Follow along on your paper. After you hear the four choices, circle the letter of the word that makes a good sentence. Are there any questions? Let’s begin. A. spectitious B. spectition

A. tramicize B. tramify

1. Everyone resents Laura’s

.

C. specitionalize D. spectitive A. bantize B. bantious . 2. Have you ever met a C. bantify D. bantist A. ponic B. ponicize it on both sides. 3. You must C. ponicity D. ponicism A. fenious B. fenalize as possible. 4. Please be as C. fenament D. fenify A. lempment B. lemptivity . 5. The old model is too C. lemptify D. lemptive

6. They were stopped by the

. C. tramic D. tramity

A. morious B. moration 7. She want to

while she’s young. C. morate D. morational A. drighten B. drightness

8. He wasn’t bothered by the

. C. drightly D. drightsome A. rendalize B. rendify 9. That car is too . C. rendment D. rendal A. laptable B. laptification 10. He needs to his paycheck. C. laptify D. laptian

Appendix B: Item analysis: Mean percent correct for grades 3–6 on nominal, verb, and adjectival suffixes (Scores on the Oral + Written are in italics).

Noun suffixes -ion -ity -ist -ness All: -ion -ity -ist -ness All:

I. Real Word Version Grade 3 Grade 4

Grade 5

Grade 6

80 40 44 60 56 48 92 24 80 61

100 100 54 96 87.5 100 100 58 96 88.5

95 91 77 86 87.3 100 100 73 100 93.3

96 81 56 93 81.5 100 96 52 93 85.3

All

77.8

81.7

249


Verb suffixes -ate -ize -ify All: -ate -ize -ify All: Adjective suffixes -ous -al -ive All: -ous -al -ive All:

I. Real Word Version Grade 3 Grade 4

Grade 5

Grade 6

72 68 40 60 80 84 64 76

93 93 78 88 89 93 74 85.3

100 96 67 87.7 88 88 79 85

95 100 86 93.7 91 100 86 92.3

48 96 70 71.3 96 89 100 95

71 92 75 79.3 100 96 100 98.7

91 91 82 88 100 100 100 100

72 68 60 66.7 96 72 88 85.3

II. Nonsense Word Version Grade 3 Grade 4 Grade 5 Noun suffixes -ion -ity -ist -ness All: -ion -ity 36 -ist -ness All: Verb suffixes -ate -ize -ify All: -ate -ize -ify All:

40 16 48 68 43 52 44 84 60 58

59 33 81 70 60.8 67 42 89 93 73.3

83 33 71 92 69.8 54 64 79 83 64.5

52 24 20 32 52 40 64 52

67 56 67 63.4 67 70 78 71.7

54 58 67 59.7 67 67 67 67

Grade 6

50 82 91 82 76.3 73 91 100 82 73 82 64 86.4 82 82 95 86.4

All

82

84.5

75.8

94.6

All

61.9

69.2

59.7

68.8

250

M. SINGSON, D. MAHONY AND V. MANN II. Nonsense Word Version Grade 3 Grade 4 Grade 5 Adjective suffixes -ous -al -ive All: -ous -al -ive All:

21 64 16 33.7 24 56 60 46.7

63 67 44 58 33 81 63 59

50 50 50 50 17 63 79 53

Grade 6

77 82 91 83.4 18 86 82 62

All

55.5

94.6

Appendix C: AAT nonce test items Practice pseudowords: A. dow(loy) B. phoot(cush) Test pseudowords: 1. virth(cay) 2. ker(bot) 3. sel(t) 4. (g)an 5. (s)leck 6. ro(ne) 7. (v)our 8. (d)ray 9. stea(n) 10. (l)und

11. (s)nile 12. clea(se) 13. (p)ate 14. (c)lup 15. pi(me) 16. (sp)old 17. (t)reak 18. so(de) 19. (v)ill 20. (b)raim

21. (sh)rup 22. p(l)aw 23. br(e)ate 24. (sc)rain 25. s(n)oll 26. mis(ki)po 27. per(na)ny 28. le(s)k 29. st(r)ape 30. narto(no)mel

31. pe(cro)duce 32. s(n)eck 33. de(lo)pany 34. s(l)in 35. ho(ca)tion 36. dant(in)ant 37. s(l)ong 38. sar(ken)ter 39. c(l)upper 40. eff(er)ing

References Adams, M.J. (1990). Beginning to read: thinking and learning about print. Cambridge, MA: M.I.T. Press. Anglin, J.M. (1993). Vocabulary development: a morphological analysis, Monographs of the Society for Research in Child Development 58: 1–166. Berko, J. (1958). The child’s learning of English morophology, Word 14: 150–177. Bradley, L. & Bryant, P. (1985). Rhyme and reasons in reading and spelling. Ann Arbor, MI: University of Michigan Press.


251

Brady, S.A. & Shankweiler, D.P. (eds.) (1991). Phonological processes in literacy. Hillsdale, NJ: Erlbaum. Brittain, M.M. (1970). Inflectional performance and early reading achievement, Reading Research Quarterly 6: 34–48. Brown, R. (1973). A first language: the early stages. Cambridge, MA: Harvard University Press. Carlisle, J.F. (1995). Morphological awareness and early reading achievement. In: L. Feldman’s (ed.), Morphological aspects of language processing (pp. 189–209). Hillsdale, NJ: Erlbaum. Carlisle, J.F. & Nomanbhoy, D.M. (1993). Phonological and morphological awareness in first graders, Applied Psycholinguistics 14: 177–195. Derwing, B.L. & Baker, W.J. (1979). Recent research on the acquisition of English morphology. In: P. Fletcher & M. Garman (eds.), Language acquisition: Studies in first language development (pp. 209–222). Cambridge: Cambridge University Press. Dunn, L. & Dunn, L. (1981). Peabody picture vocabulary test: revised. Circle Pines, MN: American Guidance Service. Fischer, F.W., Shankweiler, D. & Liberman, I.Y. (1985). Spelling proficiency and sensitivity to word structure, Journal of Memory and Language 24: 423–441. Fowler, A. & Liberman, I. (1995). The role of phonology and orthography in morphological awareness. In: L. Feldman’s (ed.), Morphological aspects of language processing (pp. 157–188). Hillsdale, NJ: Erlbaum. Gottardo, A., Stanovich, K. & Siegel, L. (1996). The relationships between phonological sensitivity, syntactic processing, and verbal working memory in the reading performance of third-grade children, Journal of Experimental Child Psychology 63: 563–582. Henderson, E. (1985). Teaching spelling. Boston: Houghton Mifflin. Leong, C.K. (1989). Productive knowledge of derivational rules in poor readers, Annals of Dyslexia 39: 94–115. Liberman, I.Y. (1982). A language-oriented view of reading and its disabilities. In: H. Mykelburst (ed.), Progress in learning disabilities, Vol. 5 (pp. 81–101). New York: Grune and Stratton. Liberman, I.Y., Liberman, A.M., Mattingly, I.G. & Shankweiler, D. (1980). Orthography and the beginning reader. In: J. Kavanaugh & R. Venezsky (eds.), Orthography, Reading and Dyslexia (pp. 137–154). Baltimore: University Park Press. Maccoby, E.E. & Jacklin, C.N. (1974). The psychology of sex differences. Stanford, CA: Stanford University Press. Mahony, D.L. (1993). The role of sensitivity to word structure in the development of reading skill. Unpublished doctoral dissertation, Department of Cognitive Sciences, University of California, Irvine. Mahony, D.L. (1994). Using sensitivity to word structure to explain variance in high school and college level reading ability, Reading and Writing: An Interdisciplinary Journal 6: 19–44. Mahony, D.L. & Mann, V.A. (1992). Using children’s humor to clarify the relationship between linguistic awareness and early reading ability, Cognition 45: 163–186. Mann, V.A. (1991). Language problems: a key to early reading problems. In: B. Wong (ed.), Learning about learning disabilities (pp. 129–160). New York: Academic Press. Myerson, R. (1976). A study of children’s knowledge of certain word formation rules and the relationship of this knowledge to various forms of reading achievement. Doctoral dissertation, Harvard University, 1976. University Micro-films International, 76–30, 205.

252


Nagy, W., Diakidoy, I. & Anderson, R.C. (1993). The acquisition of morphology: learning the contribution of suffixes to the meanings of derivatives, Journal of Reading Behavior 25: 15–170. Perfetti, C.A. (1985). Reading skill. Hillsdale, NJ: Erlbaum. Rayner, K. & Pollatsek, A. (1989). The psychology of reading. Englewood cliffs, NJ: Prentice Hall. Rosner, J. & Simon, D.P. (1971). The auditory analysis test: an initial report, Journal of Learning Disability 4: 384–392. Seidenberg, M.S. (1985). The time course of phonological activation in two writing systems, Cognition 19: 1–30. Shankweiler, D., Crain, S., Katz, L., Fowler, A.E., Liberman, A.E., Brady, S.A., Thornton, R., Lundquist, E., Dreyer, L., Fletcher, J.M., Stuebing, K.K., Shaywitz, S.E. & Shaywitz, B.A. (1995). Cognitive profiles of reading-disabled children: Comparisons of language skills in phonology, morphology and syntax, Psychological Science 6: 149–156. Silverstein, A.B. (1970). Reappraisal of the validity of WAIS, WISC, and WPPSI short forms, Journal of Consulting and Clinical Psychology 34: 12–14. Sterling, C.M. (1983). Spelling errors in context, British Journal of Psychology 74: 353–364. Taft, M. & Forster, K. (1975). Lexical storage and retrieval of prefixed words, Journal of Verbal Learning and Verbal Behavior 14: 638–647. Treiman, R. & Cassar, M. (1996). Effects of morphology on children’s spelling of final consonant clusters, Journal of Experimental Child Psychology 63: 141–170. Tyler, A. & Nagy, W. (1989). The acquisition of English derivational morphology, Journal of Memory and Language 28: 649–667. Vogel, S.A. (1977). Morphological ability in normal and dyslexic children, Journal of Learning Disabilities 10: 41–49. Wechsler, D. (1974). Wechsler intelligence scale for children-revised manual. New York: Harcourt Brace Jovanovich. Wiig, E.H., Semel, E.M. & Crouse, M.A. (1973). The use of English morphology by high-risk and learning disabled children, Journal of Learning Disabilities 6: 457–465. Woodcock, R.W. (1973). Woodcock reading mastery tests. Circle Pines, MN: American Guidance Service. Address for correspondence: Professor Virginia Mann, School of Sciences, University of California, Irvine, CA 92697, USA Phone: (949) 824-6680; Fax: (949) 824-3548; E-mail: [email protected]

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