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Performance of school age reading disabled students on the Phonological Awareness Subtests of the Comprehensive Test of Phonological Processing (CTOPP).

This study was inspired by our observations over many years that reading disabled students, when evaluated for a phonological processing disorder, do much better with sound blending tasks than with tests of sound manipulation. Sound blending scores are often average or close to it. When strong sound blending scores are combined with weaker phoneme awareness measures to form the recommended composite score, they obscure a possible phonological awareness deficit. The resulting insignificant finding creates problems on two levels. Conceptually, the near average composite score seems to contradict well-established research regarding the importance of phonology in reading disabilities. Practically, use of the composite score makes it difficult to identify a needy child for special education services because no processing disorder is found.

A substantial body of research, much of it dating from the last quarter of the last century, finds phonological awareness to be a core deficit in specific reading disability or dyslexia (Christo, Davis & Brock, 2009; Fletcher, Lyon, Fuchs & Barnes, 2007; Lieberman & Shankweiler, 1989; Shaywitz, 1996; Velutino, Fletcher, Snowling & Scanlon, 2004). To the surprise of many, weaknesses in phonology proved to be more predictive of future reading failure than general intelligence especially for pre-literate and beginning readers (Share, Jorm, McClean & Mathews, 1984; Shaywitz, 1996, 2004; Torgesen et al., 1999). Results of this established research have been incorporated into the definition of dyslexia developed for the International Dyslexia Association:

Dyslexia is a specific learning disability.... characterized by difficulties with accurate and/or fluent word recognition. These difficulties typically result from a deficit in the phonological component of language (Lyon, Shaywitz & Shaywitz, 2003, p.1).

It is therefore incumbent upon the practitioner to include measures of phonological awareness in the evaluation of a struggling reader. This should help in demystifying the reading problem, deciding on appropriate interventions, and documenting progress or the lack thereof (Christo, Davis, & Brock, 2009).

The early studies that established the phonology-reading link used a variety of experimental, non-standardized procedures for assessment, intervention and prediction of future performance (Bradley & Bryant, 1983; Rosner & Simon, 1971; Yopp, 1988). Subsequent research has led to a more nuanced approach, both in defining the construct (Cassady, Smith, & Putnam, 2008; Sodoro, Allinder, & Rankin-Erickson, 2002) and in operationalizing it with nationally standardized measures (Berninger, 2007; Elliott, 2007; Kaufman & Kaufman, 2004; Martin & Brownell, 2005; Wagner, Torgesen & Rashotte, 1999; Woodcock, McGraw, & Mather, 2001).

The current research literature distinguishes between phonological processing, phonological awareness, and phonemic awareness. Phonological processing is an over-arching construct that can, depending on the scholar's definition, refer to the "automatic ... use of sounds to understand spoken words" (Walsh, 2009, p. 214), or "the use of phonological information, especially the sound structure of one's oral language, in processing written language" (Wagner, Torgesen & Rashotte, 1999, p. 2). Phonological awareness, under the umbrella of phonological processing, has been defined as conscious awareness of the sound structure of spoken words (Stahl & Murray, 1994; Wagner, Torgesen, & Rashotte, 1999; Walsh, 2009). Phonemic awareness, a sub-category of phonological awareness, refers to the ability to isolate and manipulate the smallest distinguishable sound unit that conveys meaning: the phoneme (Torgesen et al., 1999).

The data presented in this investigation will focus on phonological and phonemic awareness. The multiplicity of methods used to assess phonological awareness can be ordered as to level of task difficulty. This work has been summarized by Cassady, Smith, and Putnam (2008) in their fine-grained analysis of the development of phonological awareness skills. Their work also examines the role of linguistic complexity and phoneme position. Linguistic complexity refers to the size of the sound unit to be worked with, from words, syllables, onset and rhymes (b/ike, l/ike) to phonemes (b/i/k). Task difficulty refers to the operation the child is required to do: Say rhyming words, tap out syllables, find the word that is different, match a beginning sound to a picture of a word, combine two or more sounds to make words, and delete or substitute sounds in words. Position refers to the placement of a sound within a word; beginning, middle, or end.

There is general agreement as to a developmental progression for task difficulty, position, and linguistic complexity, although some controversy regarding the causal role of elements of this hierarchy continues (Goswami, 2002). Reviewing task difficulty, Adams (1990) constructed a five level phonemic awareness hierarchy as follows: 1) Knowledge of nursery rhymes, 2) Oddity tasks (choosing the word with the beginning, middle or ending sound that doesn't belong), 3) Blending/syllable splitting, 4) Phoneme segmentation, and, 5) Phoneme manipulation. Syllable splitting refers to the task of isolating the initial phoneme of a word. With respect to blending phonemes, Adams, (1990) concluded that, "... they have been shown to be significantly easier than segmentation and deletion tasks" (p. 76).

Concerned that Adams' (1990) hierarchy confounded task difficulty and linguistic complexity, Cassady, Smith, and Putnam (2008), after isolating these variables in an assessment tool named Standardized Assessment of Phonological Awareness (SAPA), concluded that "[their] results support the order of development offered by Adams" (p. 529). Even though researchers differ in details of their models, a table of comparisons presented by Cassady et al. (2008, p. 517) shows a consensus that deleting or substituting phonemes are at the top of the task difficulty hierarchy, while sound blending is placed at an earlier developmental level. (See also Pufpaff (2009), Shatschneider et al., 1999; Stanovich, Cunningham & Cramer, 1984; Wagner, Torgesen & Rashotte, 1994; Yopp, 1988). Cassady et al. (2008) also reported two other findings from their administration of the SAPA in the fall, winter and spring to a sample of 203 kindergarten children over the course of the 2002-2003 and 2003-2004 academic years. First was that "blending generally precedes segmenting tasks when holding linguistic complexity constant" (Cassady et al., 2008, p. 526). And second, segmenting tasks in turn precede phoneme deletion and manipulation in the developmental sequence.

A related finding from the Cassady et al. (2008) study was that "... when tested midway through their kindergarten year the students showed a marked increase in performance gains in the blending and segmenting tasks.... we interpret this sudden change to be evidence of explicit phonological training, which was the primary curriculum goal during that period of instruction" (pp. 525-526). Cassady's (2008) research documents that the beginning reading curriculum has changed significantly since the early studies demonstrated the importance of phonology to reading. Much of the work on phonological awareness in the last century was done with kindergarten students who were very beginning readers given little systematic instruction in sound awareness (Bradley & Bryant, 1983; Liberman & Shankweiler, 1985; Perfetti, Beck, Bell, & Hughes, 1987).

In time, the early reading curriculum was influenced by the ongoing research. While sound blending has previously been an intrinsic part of code oriented reading programs (children learn to "say it fast" as in SRA DISTAR (Engelmann & Bruner, 1983), it is now explicitly taught in kindergarten and first grade through state-adopted basic reading texts. (For example, see Houghton-Mifflin Reading: A Legacy of Literacy, 2003.) The more complex tasks of phoneme deletion and substitution, although included with sound blending in some curriculum standards, (e.g. California Common Core Content Standards 2010), are not directly required in decoding new words, and are probably not as intensively practiced in the same way as is blending sounds to make words. Because sound blending is less complex, appears earlier developmentally, and is now also more routinely taught, most children in the early elementary grades may become proficient at this task.

The importance of assessing phonology in reading disability evaluations is now recognized, and numerous well-standardized measures of phonological awareness are available. Sound blending, as an easily administered phonological awareness task, plays a significant role in these diagnostic processing tests.

Nationally standardized phonology measures now available include the Comprehensive Test of Phonological Processing (CTOPP, Wagner, Torgesen, & Rashotte, 1999); Process Assessment of the Learner (Pal II, Berninger, 2007); the Test of Auditory Processing Skills, 3rd Edition (TAPS -3, Martin & Brownell, 2005); and diagnostic subtests of global cognitive and their co-normed achievement tests including the Woodcock-Johnson III Cognitive and Achievement Batteries (W-J-III, Woodcock, McGrew, & Mather, 2001); the Differential Ability Scales, Second Edition (DAS-II, Elliott, 2007); and the Kaufman Test of Educational Achievement, Second Edition (KTEA-II, Kaufman & Kaufman, 2004). The DAS-II and KTEA-II phonological awareness scales consist of a number of tasks including sound blending, which generally follow the progression outlined by Adams (1990). Both these instruments yield one overall score, normed to age 12 or 6th grade. The KTEA-II sound blending items are given only at the kindergarten level, however. On the other hand the Sound Blending subtest of the TAPS3 is normed to age 18, while the Sound Blending test included in the Woodcock-Johnson III Tests of Cognitive Abilities Standard Battery yields standard scores through age 80 + !. (Ceiling effects are clearly evident.) Both the TAPS-3 and Woodcock-Johnson include sound blending as part of a composite score; the TAPS-3 provides a Phonologic Index and the Woodcock-Johnson an Auditory Processing Factor.

The Comprehensive Test of Phonological Processing (CTOPP, Wagner, Torgesen & Rashotte, 1999), the subject of the current study, has been widely used as a component of reading evaluations (Christo, Davis & Brock, 2009; Haight, 2006; Hurford, 2003). The CTOPP provides assessment in Phonological Awareness, Phonological Memory and Rapid Naming from ages 5 through 24. There are separate forms for ages 5 and 6, and 7 to 24. The Phonological Awareness Composite for ages 5 and 6 consists of three subtests, Blending Words, Elision, and Sound Matching, while only Elision and Blending Words are included in the 7-24 year form. Blending Words items vary in length and complexity from two to 10 phonemes; Elision begins by asking the student to delete initial phonemes, then progresses to deletion of final and medial consonants and to phonemes embedded in a consonant cluster. A supplementary test of Blending Nonwords is also available. All subtests are given equal weight in computing the Phonological Awareness Composite; thus sound blending results contribute 33% of the variation to the ages 5 and 6 composite, and 50% of the variation to the 7-24 year phonological awareness score.

The CTOPP test manual contains two predictive criterion validity studies which bear directly on the purpose of this paper (Wagner, Toregesen & Rashotte, 1999, pp. 90-97). The data show substantially lower correlations with reading skill criterion variables for the Sound Blending than the Elision subtest, especially for the 7-to-24 year-old version. Of note are results reported of a concurrent and predictive validity study with subjects drawn from a clinic for learning-disabled students (median age 9). At the time these students were given the CTOPP, and also six months later, the Word Attack and Word Identification subtests of the Woodcock Reading Mastery Test-R, the Gray Oral Reading Test-3, and the Wide Range Achievement Test-3 were given. The manual presents partial correlations (controlling for age and corrected for reliability) between all of the reading achievement measures and the CTOPP subtest scores for both testing times. The average concurrent correlation between six reading measures and the CTOPP Elision subtest score is r=.52, while the Blending Words subtest average correlation with these reading measures is r=.19. Average correlations between the Elision and Sound Blending Words subtests (given at time one) and the same criterion variables are somewhat higher six months later, at r=.62 and r=.38 respectively. Thus we see that the utility of Blending Words in explaining variation in reading achievement appears to be significantly less than the more complex Elision subtest.

The value of sound blending in differentiating among skilled and struggling readers is in question because of the relative simplicity of the task as shown in the established developmental hierarchies discussed above. Furthermore, current reading curricula provide intense training in sound blending, thus practice effects may impact student scores. The CTOPP manual criterion validity data (Wagner, Torgesen & Rashotte, 1999) indicate that skill in sound blending in elementary age reading disabled students is minimally related to success in reading. For all of these reasons, inclusion of sound blending test data as part of a reading disability evaluation becomes problematic. Use of an unweighted measure of sound blending in a composite score, may provide an inaccurate evaluation of the phonological status of reading disabled students. This in turn could lead to a significant under estimation of the phonologic core deficit that, at this point in time, is assumed to underlie dyslexia/reading disability.

To shed light on the questions surrounding sound blending as a useful phonological processing measure our study examines the relationships among subtest scores within the Phonological Awareness, Phonological Memory, and Rapid Naming Composites of the CTOPP. Our sample includes only school age students who meet stringent criteria for a reading disability.



Participants were selected from two clinical data sets. One data set was the population of students identified as having a specific learning disability with goals in reading in a large suburban school district. The second data set consisted of students who had been referred to a university-based assessment clinic. Participants were selected according to the following criteria:

1. Standard scores on a measure of real word reading or nonsense word reading below a score of 85, using either the Woodcock-Johnson Test of Achievement III, or the Wechsler Individual Achievement Test; and

2. Standard score on a measure of verbal ability above a score of 85, using either the Woodcock-Johnson Test of Cognitive Abilities III, the Wechsler Intelligence Scale for Children IV, or the Kaufman Assessment Battery for Children II; and

3. Scores available for all six core subtests of the Comprehensive Test of Phonological Processing.

To secure participants for the study an excel database of all clients at the university-based clinic was created. Filters were used to select students who met above criteria for both data sets. Visual inspection of student files was used to select participants who met the above criteria from the school district special education records. All participants meeting the above stated criteria were then placed into a new excel database for analysis. SPSS 18 was used to perform data analysis. Paired sample t-test and Pearson Correlation coefficients were determined for the selected variables. From a data set of 350 potential participants accumulated from both data sets, 48 met the above criteria and were used in this study.

The demographic characteristics as well as means for the verbal ability and real and pseudoword reading measures are listed in Table D.

It is important to note that the means for verbal ability, real word reading and pseudoword reading are derived from scores on different tests. The three tests used to measure verbal ability (Woodcock-Johnson Test of Cognitive Abilities III, the Wechsler Intelligence Scale for Children IV, or the Kaufman Assessment Battery for Children II) are commonly used for this purpose. The two tests used to measure word reading ability (Woodcock-Johnson Test of Achievement III, or the Wechsler Individual Achievement Test) are also commonly used for this purpose. The use of different tests to establish criteria for participation was deemed acceptable for this study as the purpose was to identify a population with average level verbal ability in general and with poor performance on word reading. Since these tests are routinely used in schools to measure these variables they were considered appropriate for establishing criteria. In addition, these scores were not used as part of the analysis and only for identifying participants.


The range, means and standard deviations for the CTOPP subtests used in this analysis are presented in Table E.

There was considerable variation among scores for the subtests of the CTOPP. In addition, visual inspection of scores suggested that there was considerable intra-individual variation among subtest scores as well.


Correlations (Pearson Correlation Coefficient) between the two subtests in each of the Composites of the TOPP were derived and are presented in Table F. The Phonological Awareness Composite is comprised of Elision and Blending Words. The Phonological Memory Composite is comprised of Nonword Repetition and Memory for Digits. The Rapid Naming Composite is comprised of Rapid Letter Naming and Rapid Digit Naming. These Composites were arrived at during CTOPP development through factor analysis (Wagner, Torgesen & Rashotte, 1999).

Both the Phonological Memory and Rapid Naming Composites showed significant correlations between their two respective subtests. The correlation coefficient for the two tests of the Phonological Memory composite (Nonword Repetition and Memory for Digits) was significant at the .01 level (r=.43), but is still considered a moderately low correlation (Sattler, 2008). The correlation coefficient for the two tests of the Rapid Naming Composite (Rapid Letter Naming and Rapid Digit Naming) was significant at the .01 level (with a strong correlation of r=.83), considered a high correlation by Sattler (2008). In contrast the correlation coefficient for the two tests of the Phonological Awareness Composite (Elision and Sound Blending) was not significant (r=.21).

Paired Samples t-test

To further investigate the difference in performance for this population on the tests making up the separate composites, paired sample t-tests were performed on the pairs of tests making up each of the


There was no significant difference between the scores for the two tests of the Phonological Memory Composite, Memory for Digits (M=8.71 SD=2.8) and Nonword Repetition (M=9.2, SD=2.6): t=-1.12, p=.27. There was no significant difference between the scores for the two tests of the Rapid Naming Composite, Rapid Letter Naming (M=7.76, SD=2.6) and Rapid Digit Naming (M=7.71, SD=2.62): t=-.194, p=.847. There was a significant difference between the two tests of the Phonological Awareness Composite, Elision (M=7.5, SD=1.9) and Blending Words (M=9.27, SD=1.98): t=-5.04, p=.000.


We initiated this study as clinicians trying to make sense of why we often found our students with basic word reading problems having differing scores on the Elision and Blending Words tasks. As we know, normed tests are standardized primarily on normal populations with much smaller numbers of students with learning disabilities or processing issues included in the standardization sample. Over the years we had waited for an analysis such as the one presented here to confirm or disconfirm our clinical impressions. Since we found no such study we decided to pool our clinical resources and analyze our data. These findings indicate to us that children with word reading difficulties, as we have defined them above, do perform differently and more poorly on the Elision subtest than the Blending Words subtest of the Phonological Awareness Composite of the CTOPP. Further, the mean scores of these two subtests are statistically significantly different from each other. This leads us to conclude that the composite score should not be considered the best measure of "phonological awareness" for students exhibiting reading disabilities as defined in this article and that the two subtests should be considered separately in trying to understand, classify, and treat students with word reading disorders.

We would also like to note that these results are supportive of the hierarchical models proposed by Adams (1990) and Cassidy et al., (2008) with the Elision task, a task of phoneme manipulation, being more likely to capture the weakness of our students than Blending Words. This then also supports the aforementioned studies (Cassady et al., 2008; Pufpaff, 2009; Shatschneider et al., 1999; Stanovich, Cunningham and Cramer, 1984; Wagner, Torgesen and Rashotte, 1994; Yopp, 1988) finding that tasks which require the deletion or substitution of phonemes are more difficult than the blending of phonemes.

Our data regarding Rapid Naming may be helpful in clarifying the conceptual status of these measures. Rapid Naming tests have been a matter of much study and controversy. Should Rapid Naming be subsumed under the rubric of phonological processing (Torgesen, Wagner & Rashotte, 1999), be conceptualized as a separate cognitive process (Wolf & Bowers, 1999), or viewed as a marker for processing speed? (For a literature review, see Christo & Davis, 2008.) The pattern of correlations, with very high correlations between the two Rapid Naming subtests and no or negative correlations with all other CTOPP subtests does lend empirical evidence to the hypothesis that Rapid Naming is a cognitive function distinct from phonological processing in children who are poor readers. (See Table F above.)

The lack of correlation between the CTOPP Blending Words subtest and the memory subtests, Memory for Digits and Nonword Repetition (-.001 and -.034 respectively) is also of interest. Some researchers (and no doubt practitioners) have suggested that sound blending items, especially nonword sound blending, discriminate between individuals because of a heavy load on short term memory (Wagner et al., 1993). The hardest Blending Words item on the CTOPP contains 10 phonemes which in theory have to be recalled sequentially. Our data do not support a relationship between short term memory and sound blending. In the experience of one of the authors, students who pass long sound blending items usually pull the correct word from long term memory after hearing no more than three to five sounds. Retrieval fluency and vocabulary development, rather than short term memory may be involved in success with very long sound blending items.


Our sample is small. To further understand the implications of these data, we recommend replication with a second, larger sample of poor readers using the same assessment tools to define selection criteria. The consistency of these data at different ages and reading levels needs to be examined. As we have suggested, sound blending may be more predictive of reading skill with young, beginning readers. We have used only one measure of sound blending. It would be instructive to repeat this study with sound blending tests other than from the CTOPP.


The utility of including a sound blending measure in phonological processing assessment of school age reading delayed children may be in question. The Phonemic Awareness Clinical Cluster of the Woodcock-Johnson III is of interest, because, as in the CTOPP, the subtest Sound Blending is given equal weight as its partners, Incomplete Words and Sound Awareness in an overall cluster score. (1) While examining the Woodcock-Johnson III it may be well to look more closely at the role of the Sound Blending subtest within the Auditory Processing Broad Ability cluster in a reading disabled sample. The Woodcock-Johnson III Technical Manual (McGrew & Woodcock, 2001) reports a modest correlation of. 23 between Sound Blending and Auditory Attention for 6-to-8 year olds in the standardization sample. A closer examination of the cognitive correlates of sound blending skill may be warranted. These would include short term memory, vocabulary development, long term retrieval, and processing speed among other variables.

Finally, as indicated above, the relationship between various measures of phonological awareness with reading achievement needs to be systematically examined for each grade/age level through high school.


We have speculated about a number of possible reasons for our CTOPP findings, including when the test was standardized, the changes in reading curriculum young students are currently receiving, and the level of difficulty of the two tasks students are asked to perform. We have been informed that the CTOPP is being revised and may well be out by next summer. We hope that the information presented in this article is considered in order to address the sound blending problem in the new edition.


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(1) The phonemic awareness cluster consists of the subtests Sound Blending and Incomplete Words if only the Cognitive Battery is given, but includes the Sound Awareness subtest of the Achievement Battery as well if this test is also given.

Dorothy Marshall, PhD, and Catherine Christo, PhD

California State University, Sacramento

John Davis, PhD

California State University, East Bay

Correspondence concerning this article should be sent to: Catherine Christo, PhD, c/o California State University, Sacramento, College of Education, 6000 J Street, Sacramento, CA 95819-6079. Email:

Dr. Catherine Christo is a professor in the School Psychology program at California State University, Sacramento. She has experience as a practicing school psychologist and as a Licensed Educational Psychologist specializing in the assessment of learning disabilities. Dr. Christo's primary areas of interest are reading disabilities, assessment, response to intervention models, learning disabilities and the use of data for program evaluation and progress monitoring. She has published and provided training in the areas of assessment and reading disabilities. Dr. Christo has also served on various state wide work groups to provide guidance on assessment, learning disabilities and response to intervention.

Dorothy Marshall, PhD was a school psychologist for the San Juan Unified School District from 1973 to 2000 and currently provides part time service. Her professional interests are in evaluating criteria for special education eligibility for learning disabled students, and in the assessment of, and interventions for, reading disabilities. Dr. Marshall developed an intervention program for beginning readers using music and visual stimuli to learn basic word families. She coordinates a volunteer reading intervention program now in its 19th year. She presently serves as part time faculty in the School Psychology program at California State University, Sacramento.

John M. Davis is currently Chair of the Educational Psychology Department at CSU East Bay. His primary interests are in learning disorders/disabilities. He also has a small private practice where he performs assessments and consultation in these areas.
TABLE D. Ranges and Means for Demographic Variables, Verbal
Ability and Word Reading Scores for Participants (n=48)

Variable                         Range     Mean

Age                              6-15      9.42
Grade                            1-9       3.82
Verbal Ability Stan Score        86-107    95.44
Real Word Read Stan Score        48-101    78.31
PseudoWord Read Stan Score       62-96     79.69

TABLE E. Ranges, Means and Standard Deviations for CTOPP Subtests

Subtest                    Range     Mean     Stand. Dev.

Blending Words             5-14      9.27         1.97
Elision                    3-13      7.50         1.90
Memory for Digits          3-15      8.70         2.85
Nonword Repetition         5-17      9.22         2.59
Rapid Digit Naming         1-15      7.71         2.62
Rapid Letter Naming        2-13      7.76         2.58

TABLE F. Correlations Among Subtests of CTOPP

                  Blending       Elision        Memory for
                  Words                         Digits

Blending                         .21 (+)       -.001

Elision                                         .221

Memory for


Rapid Digit

                  Nonword        Rapid Digit    Rapid Letter
                  Repetition     Naming         Naming

Blending          -.034          .016           -.055

Elision           .379           -.111          .013

Memory for        .428 * (+)     -.079          -.056

Nonword                          -.142          -.045

Rapid Digit                                     .826 * (+)

* significant at .01 level

(+) correlations of primary interest
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Author:Marshall, Dorothy; Christo, Catherine; Davis, John
Publication:Contemporary School Psychology
Article Type:Report
Date:Jan 1, 2013
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