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Gough Hoover Peterson 1996 Some Observations on a Simple View of Reading

CHAPTER ONE

Some Observations on a Simple View of Reading

Philip B. Gough, University of Texas at Austin

Wesley A. Hoover, Southwest Educational Development Laboratory

Cynthia L. Peterson, Southwest Texas State University

Only a fool would deny that reading is complex. Reading clearly involves many subprocesses, and those subprocesses must be skillfully coordinated.

There is first of all the control of eye movements. Reading begins with the fixation of the printed page. A quarter of a second later, a saccade to a new location takes place, and then the sequence is repeated, interrupted only by return sweeps and an occasional regression. Within each fixation, the reader must decide how long to maintain it and where to fixate next; because eye movements are ballistic, she must also program the eyes' musculature to carry out these decisions.

Then there is word recognition. On fixating a printed word, the reader must translate that meaningless set of letters into a recognizable object, locating or activating precisely the right word in a mental lexicon containing tens of thousands of items; she accomplishes this feat in less than one fifth of a second. At the same time, the reader is developing information about the form of the next word, and the location of the word after that.

Mere recognition of the word is not enough; the reader must also decide what the word means. Many words are ambiguous, and the reader must choose among those meanings; the reader must disambiguate the word.

Having selected the appropriate meaning for each word, the reader must then fit them together. She must determine the syntactic function of each word, and then determine the relations among them; she must decide which noun or noun phrase is the subject of each verb, which noun each adjective modifies, and where each prepositional phrase is to be attached. In short, she must parse the sentence.

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Once these relations are established, the reader must use this information to determine the meaning of the sentence. Often this will require inference: The reader will need to draw upon her knowledge of the world to construct a representation of the sentence's meaning.

Given a representation of the sentence's meaning, it must be related to meanings of previous sentences; it must be fitted into the reader's mental structure of the discourse.

Finally, the reader must decide what to do with this information. If she decides that it is true and valuable, she must incorporate it into her body of knowledge; she must learn. Screenshot

All of these things must be accomplished by the reader. But we note that many of them must be done by the auder, the person who is listening to language, not reading it. Beyond the point of word recognition, listening and reading appear to require essentially the same processes.

To be sure, the common processes are not exactly the same. Disambiguation is occasionally different, for the ambiguities of the spoken word and those of the printed word are not identical. Many spoken words (e.g., /sel/) are ambiguous; they must be disambiguated. But often their printed counterparts (e.g., sail and sale) are not ambiguous, at least not in the same way. In contrast, many printed words (e.g., bow) are polyphonic; they correspond to two different phonological forms (e.g., /bo/, /bau/) and those forms may or may not require disambiguation.

The process of parsing is also slightly different, for the two modalities convey information about syntax in different ways. Speech offers intonation and stress; print offers punctuation and capitalization.

The availability of the materials for integration differs as well. In print, the previous sentences remain on the page, and the reader can return to them at will. But speech is ephemeral, and the external evidence of previous sentences is lost; the auder must rely on memory.

But these differences pale in comparison to the similarities of processing in the two modalities. Virtually the same lexicon is used to read and aud. The vast majority of ambiguities are ambiguous in both modalities. In both modalities, the words are laid out linearly (printed words in space, spoken words in time), and word order plays a central role in parsing. Virtually the same grammar is employed in parsing both written and spoken sentences. The same background knowledge is brought to bear on printed and spoken words.

What this suggests, then, is that reading can be divided into two parts; that which is unique to reading, namely decoding, and that which is shared with auding, namely comprehension. The division is natural; we are cutting nature at its joint.

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THE DISSOCIATION OF DECODING AND COMPREHENSION

Many students of reading would resist this division. They argue that reading is interactive, that decoding and comprehension are tightly interwoven.

The two are certainly correlated, and this correlation makes it difficult to separate the two. Skilled reading clearly requires skill in both decoding and comprehension. The most common sort of reading disability, which we call garden variety, involves deficits in both decoding and comprehension. In the general population, then, readers tend to be skilled in either both or neither. The result is a strong positive correlation between the two parts, and consequently, when researchers try to study differences in comprehension while matching on decoding, they are haunted by the problem of regression to the mean.

But decoding and comprehension can be separated, or at least dissociated. This is, we think, an important point, for neuropsychologists have offered such dissociation as evidence that the two skills are lodged in distinct mechanisms. In the case of decoding and comprehension, we think the dissociation is clear. To take one example, the typical 5-year-old Italian can understand Italian but not decode it; we, in contrast, can decode it (to a certain extent), but comprehend it very poorly.

Our favorite example is drawn from the life of John Milton. In his dotage, Milton wished to reread the Greek and Latin classics, but he was going blind. So he taught his daughters to decode Greek and Latin. They read the classics aloud while he listened to them. Between them, there was reading comprehension.

The dissociation of decoding and comprehension is also found in the dyslexic and the hyperlexic. The dyslexic can comprehend but not decode; the hyperlexic can decode but not comprehend. Between the two, there is double dissociation.

Decoding and comprehension, then, are the two halves of reading. But the two halves are not added together. Reading does not equal the sum of decoding and comprehension, for neither decoding in the absence of comprehension, nor comprehension in the absence of decoding, leads to any amount of reading. A child who cannot decode cannot read; a child who cannot comprehend cannot read either. Literacy-reading ability-can be found only in the presence of both decoding and comprehension. Both skills are necessary; neither is sufficient.

These observations led us to adopt a multiplicative hypothesis. If reading (r), decoding (d). and comprehension (c) are considered as skills that range from zero to one, then reading must be the product of decoding and comprehension. Put algebraically, r = d x c. Reading takes place only when both d and c are greater than zero.

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There is, then, only one way to read: by decoding and comprehending what you have decoded. There is only one kind of reading ability. But as we have seen, three kinds of reading disability can be distinguished; a deficiency in decoding (the dyslexic), a deficiency in comprehension (the hyperlexic), and a deficiency in both processes (the garden variety).

THE COMBINATION OF DECODING AND COMPREHENSION

We hold, then, that reading ability consists of two distinct parts. Two major efforts to factor analyze the reading process have come to a conclusion that differs from ours.

Zwick (1987) analyzed the reading data collected in the 1983-1984 National Assessment of Educational Progress (NAEP). NAEP set up groups of seemingly dissimilar kinds of items, including items measuring general reading comprehension, items testing inference of word meanings from context, items having to do with everyday reading skills, and essay items. Both a full-information factor analysis and a test of unidimensionality developed by Rosenbaum ( 1985) supported the same conclusion: Despite their dissimilarities, the reading items used could be regarded as measures of a single dimension.

Rost (1989) gave 38 different reading tests, a spelling test, and a speed-of-information processing test to 220 German second graders, and intercorrelated them. His study yielded 780 correlation coefficients. A factor analysis of this matrix revealed only one broad general reading comprehension component, accounting for 61 % of the total variance.

Carroll (1988) observed that multidimensionality is unlikely because as students progress, "different reading skills develop more or less in parallel" (p. 763). This argument seems to us to beg the question "Is reading unidimensional or multidimensional?" We think that a more convincing explanation of why Zwick and Rost failed to find two dimensions is because the tasks used in these studies all required decoding. As we see it, to separate the decoding and comprehension factors, we need tasks that measure each without involving the other.

What neither of these studies included were measures of listening comprehension, that is, measures of the comprehension component uncontaminated by decoding.

In 1990, we (Hoover & Gough) conducted a study that did obtain uncontaminated measures of each component skill. The Southwest Educational Development Laboratory (SEDL) measured separately the decoding, listening comprehension, and reading skills of 254 bilingual children in Texas each year for the first four grades. Decoding was assessed by asking the child to name pseudowords.

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Listening was measured by reading a story to the child, and then asking questions about the story. Reading comprehension was assessed in the same way, save that the child read the story.

It would surprise no one that we found both decoding ability and listening ability to correlate with reading comprehension. But we wanted to show that the multiplicative model accounted for the data better than the additive one. The problem we faced was that the two models make the same predictions almost everywhere: The best reader will be the child good at decoding and listening, the worst will be the child weak at both, and the intermediate reader will be the child intermediate at both skills. Where the two models differ is where the two skills are dissociated.

There was enough dissociation (i.e., enough children who were strong in one skill, but weak in the other) in the SEDL data to show that the product of decoding and listening comprehension correlated more highly with reading comprehension than did their sum. Those correlations were astonishingly high;

.84 in the first grade, .85 in the second, and .91 in both the third and the fourth. Despite the fact that SEDL's measures of the three variables were not perfectly reliable, these correlations could not be closer to 1. These results offer an accurate description of reading ability: Reading is best described as the product of decoding and comprehension.

THE RELATIONSHIP OF THE COMPONENTS TO READING

The simple view describes the joint relationship of decoding and comprehension to reading; it also helps us describe the separate relationships between the two components and reading.

In the typical kindergartner, comprehension is well developed; the typical 5-year-old can speak and understand her native language better than the typical foreign college student with four semesters in that language. The phonology and syntax of the language has been all but mastered, the child's vocabulary numbers in the thousands, and a great deal of knowledge about the world has been acquired. There is variability, to be sure, but we think that it is reasonable to assume that comprehension at school entry is normally distributed around a very substantial mean. The typical text that confronts the child at this age is very simple, with a difficulty level well beneath that mean. If the text were read to the child, it would be understood by almost every normal child. So, among beginning normal readers tested with typical materials, c approaches 1. In the multiplicative view, if c = 1, then r = d. Thus, we would expect to see that among beginning readers, the correlation between c and r would be negligible, whereas the correlation between d and r would be very high.

At the other end of the curriculum, the situation is just the reverse. The majority of college students can decode the vast majority of words they encounter; d approaches 1. But if d = 1, then r = c.

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So, although the correlation between c and r will be modest at best in the general population, among college students, we would expect it to be very high. Thus, the simple view leads us to expect that the correlation between decoding and reading will decrease across the grades, while the correlation between listening and reading will increase over the same time span.

Of course, in both cases above we presume that the materials used to assess c parallel those used to assess r. Although the language of print may indeed differ from that of speech (e.g., some syntactic devices used in the former rarely appear in the latter), this is not a necessary consequence of the medium, for anything that can be captured in language can be transmitted through either a written or oral form. Therefore, we must distinguish the message from the medium.

We looked for the trends predicted above in the relationships of reading to comprehension and decoding through a meta-analysis of existing research. We searched the published literature to identify investigations of normal reading in monolingual English speakers (first through sixth grade, and college level) where appropriate measures of the three variables were taken. By appropriate, we mean that (a) comprehension was measured free of decoding (i.e., using auding), and (b) auding and reading were measured in the same way. We found 10 such studies, reporting measures from 17 different samples.

Table 1.1 presents the correlations from these studies. The table displays the coefficients and tests of significance as well as the sample size; the data are grouped by grade level. In some cases, inverted scales were employed (e.g., latency was measured instead of accuracy), and for these scales, we reversed the signs of the coefficients so that a positive correlation indicates a direct relationship between two skills.

The simple vote-counting method applied to these data indicated that both relationships were positive: The 17 reported correlations between decoding and reading were all positive (15 of them significantly so), and 16 of the reported correlations between comprehension and reading were significantly positive as well (the sole exception being insignificant).

To obtain more precise estimates of these relationships, we conducted a series of statistical analyses using a standard meta-analysis package. Pooling the 17 correlations of decoding and reading yielded a highly significant (aggregate) correlation of .55; pooling the correlations of comprehension and reading yielded a value of .56. Within both analyses, the test for homogeneity was highly significant, indicating substantial differences among the 17 pooled coefficients.

Given the substantial differences between coefficients, an analysis of variance was conducted to test the hypothesis that grade level at the time of the test was an important determinant of such

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differences. For this purpose, the studies were divided into four groups, combining studies of subjects in grades 1-2 (Group 1), grades 3-4 (Group 2), grades 5-6 (Group 3), and college (Group 4), respectively. For the correlations between decoding and reading, a significant between-group effect was found, indicating that the correlations differed depending on the grade level of the sample. Descriotively, the average weighted correlations obtained between decoding and reading were .61, .53, .48, and .39 for Groups 1, 2, 3, and 4, respectively. Each c< Screenshot und to be significantly positive, with the computed effect sizes declining in magnitude from Group 1 to Group 4 (d = 1.51, 1.24, 1.09, .81).

Note. Entries are ordered by time of testing from youngest to oldest samples.

a Time of testing is represented in grade-level units using a grade-month coding with the integer portion representing the grade level and the decimal portion representing the month (.1 represents the month of September and .9 represents May). b 1 = first and second grade; 2 = third and fourth grade; 3 = fifth and sixth grade; and 4 = college. For Group 4, precise time of testing for individual subjects was not reported; the entry is an estimate based on the information provided. c DR = Decoding and Reading. d CR = Comprehension (auding) and Reading.

*p < 0.5 two-tailed

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For the correlations between comprehension and reading, a highly significant between-group effect was found, again indicating the significant impact of grade

level on the correlations. Descriptively, the average weighted correlations between comprehension and reading were .41, .50, .72, and .68 for Groups 1, 2, 3, and 4, respectively. Each coefficient was positive (significantly so), and the effect sizes for Groups 1 through 4 were .90, 1.13, 2.06, and 1.80. Note that in the three studies contained in Group 4, two found substantial correlational differences whereas the third, which was based on the largest sample size, reported almost identical coefficients. We note that the reliability of the comprehension measure employed in this last study was fairly low (.63), which might account for the correlational pattern found.

Overall, the results generally supported the pattern expected under the simple view. First, we found large positive, pooled correlations of reading with both decoding and comprehension. Second, the correlational trend between decoding and reading was consistent with the predicted decline with grade level, and the correlational trend between comprehension and reading was generally consistent with the predicted increase with grade level.

DECODING AND COMPREHENSION

We have observed that decoding and comprehension are positively correlated. The skilled decoder is also apt to be a skilled comprehender, and the child poor at either is likely to be poor at the other. But the simple view says that the relationship between decoding and comprehension must depend on reading level.

The skilled reader must be good at both decoding and comprehension; there can be little variation in either skill. Because the poor reader is generally poor at both, there is a positive correlation between decoding and comprehension in the total population.

But the poor reader can be poor in any of three ways; poor at decoding, poor at comprehension, or poor at both. What this entails is that, among poor readers, decoding skill and comprehension skill must be negatively correlated.

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If you are a poor reader but good at decoding, then you must be poor at comprehension; if you are a poor reader but good at comprehension, then you must be poor at decoding. In other words, if r =

.1, and if d is high, then c must be low, and vice versa. Hoover and Gough (1990) found that among the reading disabled, the correlation did indeed turn negative.

Multiple Literacies

Since ancient Rome, the term literacy (Latin literatus) has been ambiguous. It has always meant at least two things. In one sense, literacy (literacy1) meant the ability to read and write; the other (literacy2) meant cultured or educated. In recent years, it has been stretched even further, to the point where it may not even include the ability to read and write (see Kintgen, 1988). We read of computer literacy, Jewish literacy, musical literacy, and even visual literacy.

But a new and different ambiguity is being put forward. This is the claim that reading skill (literacyl) is not one thing but many. For example, McLean and Goldstein (1988, p. 371) claimed that, "To predict with any accuracy which reading materials an individual will be able to comprehend, we must know that person's prior knowledge and cultural experiences" (p. 371). They claimed that, "In reality, reading achievement is not unidimensional" (p. 371). Instead, "People tend to exhibit different performances in different contexts, since interest, motivation, intention, and the like all play a role" (pp. 371-372).

The issue at stake is clearly empirical: To what extent do performances across "contexts" correlate? The evidence seems to indicate that these correlations are only moderate.

How are we to accommodate these data in terms of the simple view? We would agree with McLean and Goldstein that the reader's prior knowledge must influence his reading comprehension. But in the simple view, reading comprehension (literacy1) is not one thing, but two. The question then becomes, where does background knowledge have its effect? Does background knowledge influence decoding, or comprehension, or both?

Background Knowledge, Decoding, and Comprehension

In her dissertation, Peterson (1993) endeavored to measure the interrelationships among background knowledge, reading, decoding, and comprehension. First, she assessed 135 naval reservists' knowledge of two unrelated subject matters, baseball and the personal computer (with the scope of background knowledge in each narrowed to knowledge of terminology and procedures). Next, she asked the reservists to read a passage from George Will's recent book on baseball, and then to respond to literal

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and inferential questions about the passage. The reservists also listened to another passage from the same book, and again answered questions. Finally, each reservist read aloud a list of 100 content words drawn randomly from the reading passage. The reservists completed a parallel series of tasks for passages drawn from the personal computer magazine, Byte. They read part of an article and answered questions about it, listened to part of another article and again answered questions, and then read aloud a list of 100 words taken from those articles.

Peterson thus obtained eight measures from each subject, measures of their background knowledge, reading, listening, and decoding skill in each of two domains.

Her results are presented in Fig. 1.1.

Peterson's data indicated that reading ability was only moderately correlated across the two domains: The correlation was somewhere between .35 (the observed correlation) and .53 (the correlation corrected for attenuation). But the moderation arose from the comprehension component: Baseball-listening comprehension and computer-listening comprehension correlated .40-.62. In striking contrast were her results with decoding: Baseball and computer decoding were correlated .88. Comprehension may not have been highly correlated across contexts, but decoding certainly was.

Peterson's data also made clear that background knowledge contributed primarily to comprehension, and not to decoding. Background knowledge correlated .60-.72 with listening comprehension in baseball, and .56-.82 with listening comprehension in computers. But it correlated much more modestly with decoding (.10 in baseball, .39 in computers) in the two subject matters.

These results suggest two answers to the question of whether there is a single, general literacy1, or a collection of specific literacies. One component of reading is completely general; that is decoding. The other component of reading is more specific: Comprehension varies from subject matter to subject matter, and that variation is likely due to variation in background knowledge.

We conclude that the simple view of reading offers clear answers to two important questions. Reading is not unidimensional; it has two dimensions, decoding and comprehension. Reading (literacy1) is both general and specific; decoding is general, and comprehension is specific.

TWO IMPLICATIONS

The simple view seems to us a sensible way of looking at reading; it seems like common sense. But we recognize that it is very much at odds with the current sense in education.

According to that sense, reading is whole; it cannot be broken down into subskills. Thus, we should not attempt to assess such subskills, nor should we attempt to teach them separately (International Reading Association, 1989).

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If the simple view is correct, the IRA' s position on assessment is wrong. If reading consists of two components, two skills, then it is surely important to separately assess those two skills. For example, if we encounter a disabled reader, then it is important to determine whether the disability results from a weakness in decoding, a weakness in comprehension, or (as is most likely) weaknesses in both, for the two disabilities call for very different types of remediation.

If the simple view is correct, then the IRA' s stance on instruction may also be wrong. If reading consists of two isolable subcomponents, then we should at least consider the possibility that we might teach them in different ways. That reading consists of two skills does not imply that either one should be taught by drill. As we see it, both decoding and comprehension are primarily developed through reading, rather than through direct instruction. But we believe that decoding seldom begins without some form of instruction (Gough & Billinger, 1980), and we hope that comprehension might benefit from it as well. The idea that the two skills are distinct suggests that they might best be taught in two different ways (a point convincingly developed by Stanovich, 1994). If reading has two parts, then we should determine whether optimal instruction should as well.

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REFERENCES

Carroll, J.B. (1988). The NAEP Reading Proficiency Scale is not a fiction: A reply to McLean and Goldstein. Phi Delta Kappan, 69, 761-764.

Cunningham, A. E., Stanovich, K. E., & Wilson, M. R. (1990). Cognitive variation in adult college students differing in reading ability. In T. H. Carr & B. A. Levy (Eds.), Reading and its development: Component skills approaches (pp. 129-159). San Diego: Academic Press.

Curtis, M. E. (1980). Development of components of reading skill. Journal of Educational Psychology, 72, 656-669.

Dreyer, L. G., & Katz, L. (1991, December). An examination of "The simple view of reading. "Paper presented at the meeting of the National Reading Conference, Palm Springs, CA.

Gough, P. B., & Billinger, M. L. (1980). Learning to read: An unnatural act. Bulletin of the Orton Society, 30, 179-196.

Hoover, W. A., & Gough, P. B. (1990). The simple view of reading. Reading and Writing, 2, 127-160. International Reading Association. (1989). Professional statements approved by the IRA Board of

Directors. Journal of Reading, 32, 297.

Jackson, M. D., & McClelland,]. L. (1979). Processing determinants of reading speed. Journal of Experimental Psychology: General, 108, 151-181.

Juel, C., Griffith, P. L., & Gough, P. B. (1986). Acquisition of literacy: A longitudinal study of children in the first and second grade. Journal of Educational Psychology, 78, 243-255.

Kintgen, E. R. (1988). Literacy literacy. Visible Language, 22, 149-168.

Peterson, C. L. (1993). Background knowledge and the decomposition of literacy in skilled adult readers. Unpublished doctoral dissertation, University of Texas, Austin.

Rosenbaum, P. R. (1985). Comparing distributions of item responses for two groups. British Journal of Mathematical and Statistical Psychology, 38, 206-215.

Rost, D. H. (1989). Reading comprehension: Skill or skills? Journal of Research in Reading, 12, 87-113.

Singer, M. H., & Crouse, J. (1981). The relationship of context-use skills to reading: A case for an alternative experimental logic. Child Development, 52, 1326-1329.

Stanovich, K. E. (1994). Constructivism in reading education. Journal of Special Education, 28, 259-274.

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Stanovich, K. E., Cunningham, A. E., & Feeman, D. J. (1984). Intelligence, cognitive skills, and early reading progress. Reading Research Quarterly, 19, 278-303.

Stanovich, K. E., Nathan, R. G., & Vala-Rossi, M. (1986). Developmental changes in the cognitive correlates of reading ability and the developmental lag hypothesis. Reading Research Quarterly, 21, 267-283.

Tunmer, W. E. (1989). The role of language-related factors in reading disability. In D. Shankweiler & I. Y. Liberman (Eds.), Phonology and reading disability (pp. 91-131). Ann Arbor, MI: The University of Michigan Press.

Zwick, R. (1987). Assessing the dimensionality of NAEP reading data. Journal of Educational Measurement, 24, 293-308.

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DMU Timestamp: November 04, 2020 17:29





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