LDXspldxJ Learn DisabilJournal of Learning Disabilities0022-21941538-4780SAGE PublicationsSage CA: Los Angeles, CA10.1177/002221941143269010.1177_0022219411432690Cognitive Component of Componential Model of Reading Applied to Different OrthographiesJoshiR. Malatesha1TaoSha2AaronP. G.3QuirozBlanca41Texas A&M University, College Station, TX, USA2Beijing Normal University, Beijing, China3Indiana State University, Terre Haute, IN, USA4Southwest Educational Developmental Laboratory, Austin, TX, USAR. Malatesha Joshi, Texas A&M University, College of Education and Human Development, MS 4232, College Station, TX 77843-4232, USA Email: mjoshi@tamu.edu92012455480486© Hammill Institute on Disabilities 20122012Hammill Institute on DisabilitiesWhether the simple view of reading (SVR) as incorporated in the componential model of reading (CMR) is applicable to other orthographies than English was explored in this study. Spanish, with transparent orthography and Chinese, with opaque orthography were selected because of their diverse characteristics. The first part reports a study of students from grades 2 and 3, whose home language and medium of instruction was Spanish, and were administered tests of decoding, listening, and reading comprehension. A comparison group of 49 children from Grade 2, 54 children from Grade 3, and 55 children from Grade 4, whose home language and instruction was English, were also administered tests of decoding, listening, and reading comprehension. Multiple regression analysis showed that approximately 60% of the variance in reading comprehension of Spanish participants and 50% of the variance in reading comprehension of English participants were explained by decoding and listening comprehension. Furthermore, the performance of third grade Spanish participants resembled that of fourth grade English-speaking participants. In the second study, 102 Chinese students from Grade 2 and 106 students from Grade 4 were administered tasks of Chinese character recognition, reading fluency, listening, and reading comprehension. Multiple regression analyses showed character recognition and listening comprehension accounted for 25% and 42% of the variance in Chinese reading comprehension at Grades 2 and 4 respectively. These results indicate that the simple view of reading is applicable to writing systems other than that of English.Simple View of Reading (SVR)orthographic depthSpanish orthographyChinese orthographycover-dateSeptember/October 2012One of the pragmatic models that attempts to explain the reading process is the Simple view of reading (SVR) proposed by Gough and Tunmer (1986) and Hoover and Gough (1990), according to which the two most important elements of reading are decoding and comprehension. The relationship between decoding and comprehension is expressed as R = D × L, where R is reading comprehension, D is decoding, and L is linguistic comprehension. SVR is straightforward in format and has been found to be useful in identifying and remediating reading problems (Aaron, Joshi, & Williams, 1999; Aaron & Joshi, 2009; Aaron, Joshi, Boulware-Gooden, & Bentum, 2008; Catts, Adlof, & Weismer, 2006). With a view to broaden the scope of SVR, Aaron and colleagues (Aaron, Joshi, Boulware-Gooden, et al., 2008; Aaron, Joshi, & Quatroche, 2008; Joshi & Aaron, 2000) proposed the componential model of reading, according to which reading difficulties are caused by several factors in addition to decoding and comprehension and classified into three domains—cognitive, psychological, and ecological. Each domain has its own components: The cognitive domain represents the view that SVR has word recognition and comprehension components. The components of psychological domain are factors such as motivation and interest, teacher expectation, and gender differences. The components of the ecological domain include teacher knowledge, dialect differences, home environment, and English as a second language (ESL). Even though there have been support for the importance of different components such as gender differences, dialect differences, and reading comprehension, CMR is perhaps the first model to present all of these factors in an unified way.Even though one of the first studies supporting SVR was conducted on English–Spanish bilinguals (Hoover & Gough, 1990), most of the later studies validating SVR have been conducted with English-speaking children (Conners, 2009; Dreyer & Katz, 1992; Johnston & Kirby, 2006; Joshi & Aaron, 2000; Savage, 2006). However, a few studies carried out in other alphabetic orthographies have lent support to the SVR. Høien-Tengesdal and Høien (2012) report approximately 50% of the variance in reading comprehension is explained by decoding and listening comprehension among Norwegian sixth graders. Høien-Tengesdal (2010) also reported a similar result for sixth graders from Sweden. Applying SVR to French, Megherbi, Seigneuric, and Ehrlich (2006) found more than 50% of the variance in reading comprehension was explained by decoding and listening comprehension among French-speaking first and second graders. Thus, most of the studies have explained about 50% of the variance in reading comprehension by decoding and listening comprehension. The orthographies studied thus far are alphabetic languages. The purpose of the present study was to examine whether the cognitive component of CMR—decoding and comprehension—is also applicable to Spanish and Chinese. These two orthographies were selected because of the differences in their orthography. Spanish is an alphabetic language where the letter is the basic written unit, and its orthography is considered transparent because of the close relationship between phoneme and grapheme. Chinese orthography, on the other hand, is morphosyllabic, where a character, representing a morpheme, is the basic writing unit. Because of the lack of one-to-one correspondence between sound and the written unit, Chinese is considered an opaque orthography.MethodStudy 1ParticipantsA total of 38 children from Grade 2 and 42 children from Grade 3 from a large metropolitan area in the southwestern part of the United States were selected to participate in the study. The primary language of these children at home and the medium of classroom instruction from kindergarten until Grade 2 was Spanish. Beginning in the middle of Grade 3, instruction in English began with the introduction of letters and sounds. Thus, participants had 3 years of formal instruction in Spanish and had very rudimentary instruction in spoken English but no formal instruction in English. A comparison group whose home language and language of instruction was English was selected from the same city. The comparison group consisted of 49 children from Grade 2, 54 children from Grade 3, and 55 children from Grade 4. Because English was introduced about the middle of Grade 3 in the Spanish school, a comparison group of Spanish fourth graders was not selected for the present study as these participants in Grade 4 would be more bilingual compared to the English group. None of the participants had repeated a grade nor had any uncorrected vision or hearing problems.ProcedureThe Spanish-speaking children were administered the Decoding, Listening Comprehension, and Reading Comprehension subtests from Bateria III (Woodcock, Muñoz-Sandoval, McGrew, & Mather, 2005) and the English-speaking children were administered Woodcock–Johnson III Diagnostic Reading Battery (Woodcock, Mather, & Schrank, 1999). According to the test manual, both the tests can be used for participants from ages 2 to older than 90 years and have reliabilities of about .90. All the tests were administered individually according to the test manual in a quiet room in the school. The number of correct responses was recorded and converted to standard scores, which have a mean score of 100 and a standard deviation of 15. The means and standard deviations for the sample are shown in Table 1.Table 1.Means and Standard Deviations on Woodcock MeasuresDecodingListening Comp.Reading Comp.GradeLanguagenMSDMSDMSD2Spanish38112.929.4194.977.9997.685.12English4995.4512.37100.518.5298.827.343Spanish42109.199.3698.9310.2595.645.96English54102.0016.83107.6115.76102.6511.234English5598.9817.73112.4218.43104.5117.63The next step was to compute multiple regression analyses to find out the contributions of decoding and listening comprehension to reading comprehension. The results are shown in Tables 2, 3, and 4.Table 2.Multiple Regression Analysis: R2 Values and Beta Weights of Reading Components by Grade for Spanish GroupGrade23R2.57.60β Listening comp..39**.44** Decoding.24*.21*p < .05. **p < .01.Table 3.Multiple Regression Analysis: R2 Values and Beta Weights of Reading Components by Grade for English GroupGrade234R2.47.48.50β Listening comp..31*.36**.50** Decoding.20*.25*.23**p < .05. **p < .01.Table 4.Multiple Regression Analysis: Contributions of Listening Comprehension, Decoding, to Reading ComprehensionSpanishEnglishLC & DLC (%)D (%)LC & D (%)LC (%)D (%)Grade%n%%%n%%2573847493604248544505524525333534715373544114LC = listening comprehension; D = decoding.As Table 4 shows, approximately 60% of the variance in reading comprehension of Spanish speakers can be explained by decoding and listening comprehension and approximately 50% of the variance in reading comprehension of English speakers can be explained by decoding and listening comprehension. Table 4 also presents a breakdown of the contribution of individual components of decoding and listening comprehension to reading comprehension. In this study, the amount of variance contributed by decoding and listening comprehension for the English group seems to be about the same as reported by others (Tilstra, McMaster, van den Broek, Kendeou, & Rapp, 2009). Furthermore, most of the studies from other languages, such as French, Norwegian, and Swedish, have also reported that about 50% of the variance is explained by decoding and comprehension. What is noteworthy, however, is although decoding and listening comprehension can account for 50% of the variance in reading comprehension, IQ scores have been reported to account for about only 25% of the variance in reading comprehension. It can also be noticed that the contribution of decoding and listening comprehension to reading comprehension of Spanish third graders resembled that of English fourth graders. This result can be explained by the fact that as Spanish orthography is more transparent than that of English, Spanish-speaking children master decoding skills in Spanish sooner than it takes to master decoding skills in English. A similar observation was made by Seymour, Aro, and Erskine (2003). The findings also support the orthographic depth hypothesis, proffered by Frost, Katz, and Bentin (1987), according to which “lexical word recognition in shallow orthographies is mediated primarily by phonemic cues generated prelexically by grapheme-to-phoneme translation. In contrast, lexical access for word recognition in a deep orthography relies strongly on orthographic cues, whereas phonology is derived from internal lexicon” (p. 113).Study 2The purpose of Study 2 was to extend the findings of the first study to see whether the cognitive component of CMR is also applicable to Chinese orthography. Chinese orthography is far more opaque than English orthography. Although the letter is the basic unit of alphabetic writing systems such as Spanish and English, the written character is the basic unit of the Chinese writing system. Although some mapping principles underlie the relationship between orthography and phonology for many Chinese characters, which is called OPC rules (Ho, Ng, & Ng, 2003; Tzeng, Lin, Hung, & Lee, 1995), there is no direct correspondence between any component of character (stroke or radical) and its intrasyllabic unit. This is in sharp contrast to the grapheme–phoneme relationship (GPC rules) in both Spanish and English.ParticipantsA total of 102 students from Grade 2 and 106 students from Grade 4 from Zhejiang province, which is in the southeastern part of China, participated in this study. All students began to learn to speak general Mandarin (Putonghua) in kindergarten and were instructed in general Mandarin in school. The students were administered tasks of Chinese character recognition, character reading fluency, Chinese language comprehension, and Chinese reading comprehension tasks. As indicated by their teachers and school records, these children had no mental problems or learning disabilities.MeasuresReading comprehension was measured by sentence and paragraph reading comprehension tasks. In this test, four multiple-choice items were presented after each sentence or paragraph, and children were asked to choose one correct answer from the four options. The materials were taken from Reading Assessment for Primary School Students (Mo, 2004) and Guidelines for Reading in Primary School (National Committee for Primary School Chinese Arts Instruction, 2003). There were 43 items for the second graders, and a set of 13 items was added for the fourth graders to avoid any ceiling effects. The score was the number of correct responses. The Cronbach’s α coefficients for these tests for Grades 2 and 4 were .78 and .79, respectively.Language comprehension was examined by sentence and paragraph listening comprehension tasks. The stimuli were prerecorded and played back to the children, who were asked to listen to the stimuli and answer multiple-choice questions. Materials for the listening comprehension were taken from the same source as the reading comprehension tests. There were 45 items in the listening comprehension test. The Cronbach’s α coefficients for Grades 2 and 4 were .67 and .68, respectively.Character recognition was measured with a Pinyin writing task that has commonly been used in previous studies. For example, children were presented with a character (e.g., 烤) and were asked to write the Pinyin (e.g., /kăo/) in parentheses. An individual’s score was the total number correct. To score children’s responses, children’s textbooks were referred to. The scoring of an accurate response was required to be correct in both syllable and tone.Pinyin, literally “spell sound,” is a roman alphabetic system created to help learn Chinese characters in mainland China and has been in use since the 1950s. It is composed of 26 Roman letters, including 21 onsets (e.g., b, p, m, f), 35 rimes (e.g., a, o, e, ai, an, iao, uang), and four tone symbols: - (level), ’ (rising), ˇ (dipping), and ‘ (falling; Zhou, 1993). As a pedagogical tool, Pinyin has perfect one-to-one correspondence between spelling and sound, which makes it easy to learn and to use. Pinyin is usually taught at the beginning of the first semester of primary school and is used to assist character learning in later grades. Primary school children in mainland China are highly skilled in writing Pinyin for characters they have learned. The task of writing Pinyin for characters has been shown in previous studies to be highly reliable and valid as a measure of character reading and to work well as a substitute for pronouncing characters directly (Anderson, Li, Ku, Shu, & Wu, 2003; He, Wang, & Anderson, 2005; Meng, Zhou, & Shu, 2000; Shu, Anderson, & Wu, 2000). The advantages of the Pinyin writing task over the direct pronunciation task include not only allowing for valid and reliable group based assessment but also assisting in reducing the possible confound from individual differences in pronunciation (Anderson et al., 2003).Because there exist no direct GPC rules in Chinese orthography, and the OPC rules are far less reliable, real characters instead of pseudo-characters were used for Chinese character recognition tasks. Grade-appropriate character lists were drawn from the Chinese Literacy Test Battery and Assessment Scales for Primary School Students (Wang & Tao, 1996), as done in previous studies (e.g., Shu, McBride-Chang, Wu, & Liu, 2006). There were 153 and 167 characters in the lists for Grades 2 and 4, respectively. All these characters were from the List of Frequently Used Modern Chinese Characters released by the State Language Commission of China (1988). The Cronbach’s α coefficients for Grade 2 and 4 were .95 and .96, respectively.Character reading fluency was measured with timed reading of familiar characters. A total of 100 characters that appeared in the textbooks used in the first two grades and were of high frequency (among the first 700 on the frequency list of Chinese characters) were presented to students, and students were asked to read as accurately and quickly as possible. The score was the number of characters read correctly within 30 seconds. Means and standard deviations as well as the correlations for all the measures are presented in Table 5, and the results of the multiple regression analyses are presented in Tables 6 and 7.Table 5.Means and Standard Deviations of Chinese Character Recognition, Character Reading Fluency, Listening Comprehension, and Reading Comprehension and Correlation Matrix by GradeGrade 2 (n = 102)Grade 4 (n = 106)MSD1234MSD1. Character recognition84.7518.24—.33***.47***.57***96.3322.942. Character reading fluency45.617.24.47***—.03.1553.757.213. Listening comprehension27.634.70.35**.43***—.52***30.514.824. Reading comprehension28.875.36.47***.47***.33**—40.685.94Note: Correlations below the diagonal are for Grade 2, and those above the diagonal are for Grade 4.**p < .01. ***p < .001.Table 6.R2 and Beta Weights for Grades 2 and 4 With and Without Character Reading FluencyGrade 2 (n = 102)Grade 4 (n = 106)R2.31.25.42.42β character recognition.30.40.37.38β character reading fluency.29.03β listening comprehension.10.20.37.37Table 7.Percentage of Contribution of Different Components to Reading Comprehension by Grade With and Without Character Reading FluencyReading ComprehensionGraden%LC and recognition210231Fluency410642LC and recognition210225410642LC210211410631Recognition210222410632Fluency21022241063Note: LC = listening comprehension.Multiple regression analyses showed that character recognition, character reading fluency, and listening comprehension accounted for 31% of the variance in Chinese reading comprehension at Grade 2 and 42% at Grade 4. Moreover, character recognition accounted for a significant part of the variance in Chinese reading comprehension at both Grade 2 (22%) and Grade 4 (32%), whereas character reading fluency accounted for 22% of the variance in Chinese reading comprehension at Grade 2 but only 3% at Grade 4 (p > .05). With character reading fluency excluded from the regression model, character recognition and listening comprehension accounted for somewhat less variance (25%) in Chinese reading comprehension at Grade 2 while accounting for the same 42% of the variance at Grade 4. Chinese listening comprehension explained much more variance in reading comprehension at Grade 4 (31%) than at Grade 2 (11%). Since the mean percentages of correct responses of each measure were comparable for Grades 2 and 4 in reading comprehension (67% vs. 72%), listening comprehension (72% vs. 78), and character recognition (55% vs. 58%), the varied contributions of character recognition and listening comprehension to reading comprehension in Grades 2 and 4 did not result from the difficulty level of each measure.DiscussionStudy 2 supported the view that the cognitive component of the CMR model is applicable to learning to read in Chinese—a very opaque script compared to the alphabetic scripts as English and Spanish. Compared to the applicability of CMR in English and Spanish, some similar patterns could be observed. For example, much more variance of Chinese reading comprehension was explained by listening comprehension at Grade 4 than at Grade 2. It could be concluded that no matter how opaque the script is, language comprehension becomes more important for reading comprehension as children move up in grades. The role of decoding fluency was important for early grades but decreased with grades, suggesting fluency may be critical for beginners universally.On the other hand, there were differences in applying the CMR model to learning to read in Chinese. First, the variance of reading comprehension explained by decoding and listening comprehension was less in Chinese than in English and in Spanish. This might partly be the result of differences in tests used. Standardized instruments were used for English and Spanish groups, whereas standardized instruments were not available for the Chinese group. But there was a sizable difference (10%) in the variances explained by the model (see Table 4) even for English and Spanish groups who used standardized and very comparable instruments. For English, the percentages were around 50%, whereas for Spanish they were around 60%. In another study about Chinese-speaking children’s learning to read in English, more than 50% of the variance in English reading comprehension was explained by word decoding and language comprehension (Peng & Tao, 2009). Therefore, it is plausible that the uniqueness of the Chinese writing system may demand some critical componential skill in addition to decoding and listening comprehension. Ziegler and Goswami (2005) suggested that vocabulary should be more strongly related to reading development in less consistent orthographies. A larger vocabulary can help word recognition when the grapheme-to-phoneme correspondence rules do not work or are not available. Further study may explore the validity of revised CMR model and offer important evidence for understanding the universality and uniqueness of reading development in different writing systems.Second, in contrast to the role of word decoding decreasing significantly from Grade 2 to Grade 4 in English and Spanish as shown in Study 1, Chinese character recognition accounted for a significant amount of the variance in Chinese reading comprehension at both Grade 2 and Grade 4. It is noteworthy that for Spanish reading comprehension, word decoding accuracy accounted for much less variances even at Grade 3, whereas for English reading comprehension, the turning point was Grade 4 (see Table 4). The findings from the present study may suggest that the importance of decoding accuracy in reading comprehension may remain for a more prolonged time with a more opaque script like Chinese.ConclusionsEven though ecological, psychological, and cognitive factors such as socioeconomic status, teachers’ knowledge of content and pedagogy, gender, dialect, decoding, and linguistic comprehension may affect reading, the nature of orthography of a language also plays a role in fluent reading. In the present study, we explored two contrasting orthographies—Spanish, a transparent orthography, and Chinese, which is opaque. Even though a substantial amount of variance in reading comprehension was explained by decoding (character recognition in Chinese) and linguistic comprehension, decoding explained less variance in Spanish compared to English and Chinese. This may be the result of the transparency of Spanish orthography. However, linguistic comprehension explains more variance in reading comprehension in early grades. It is suggested that future studies include different kinds of orthographies such as Korean Hangul, Japanese, and Arabic and also include different tasks such as vocabulary and real-word reading.Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.FundingThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was supported by a grant from the Mexican American/Latino Research Center, Texas A&M University, and from the National Science Foundation of China (30970908).About the AuthorsR. Malatesha Joshi, PhD, is a professor of literacy education, English as a second language, and educational psychology at Texas A&M University, where he teaches courses and conducts research in the areas of assessment and intervention of reading problems in monolinguals and bilinguals. He is the editor of Reading and Writing: An Interdisciplinary Journal.Sha Tao, PhD, is a professor of developmental psychology in the National Key Laboratory of Cognitive Neuroscience and Learning at Beijing Normal University. She is interested in the cognitive aspects of bilingual and biliteracy development.P. G. Aaron, PhD, was the Coffman Distinguished Professor in the Department of Educational Psychology at Indiana State University. His areas of research interest are reading disability and inconsistent attention in children. His publications focus on differential diagnosis and treatment of these learning-related problems.Blanca Quiroz is a research associate at the Southwest Educational Development Laboratory in Austin, Texas.ReferencesAaronP. G.JoshiR. M.WilliamsK. (1999). Not all reading disabilities are alike. Journal of Learning Disabilities, 32, 120-137.AaronP. G.JoshiR. M. (2009). Why a component model of reading should drive instruction. Perspectives, 35(
By R. Malatesha Joshi; Sha Tao; P. G. Aaron and Blanca Quiroz
