Discrepant SAT Critical Reading and Writing Scores: Implications for College Performance

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Discrepant SAT Critical Reading andWriting Scores: Implications for CollegePerformanceEmily J. Shaw a , Krista D. Mattern a & Brian F. Patterson aa The College BoardPublished online: 08 Sep 2011.

To cite this article: Emily J. Shaw , Krista D. Mattern & Brian F. Patterson (2011) Discrepant SATCritical Reading and Writing Scores: Implications for College Performance, Educational Assessment,16:3, 145-163, DOI: 10.1080/10627197.2011.604241

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Educational Assessment, 16:145–163, 2011

Copyright © Taylor & Francis Group, LLC

ISSN: 1062-7197 print/1532-6977 online

DOI: 10.1080/10627197.2011.604241

Discrepant SAT Critical Reading and WritingScores: Implications for College Performance

Emily J. Shaw, Krista D. Mattern, and Brian F. PattersonThe College Board

Despite the similarities that researchers note between the cognitive processes and knowledge

involved in reading and writing, there are students who are much stronger readers than writers

and those who are much stronger writers than readers. The addition of the writing section to the

SAT provides an opportunity to examine whether certain groups of students are more likely to

exhibit stronger performance in reading versus writing and the academic consequences of this

discrepant performance. Results of this study, based on hierarchical linear models of student

performance, showed that even after controlling for relevant student characteristics and prior

academic performance, an SAT critical reading–writing discrepancy had a small effect on 1st-

year grade point average as well as English course grades in college. Specifically, students who

had relatively higher writing scores as compared to their critical reading scores earned higher

grades in their 1st year of college as well as in their 1st-year English course(s).

The addition of the writing section to the SAT in March 2005 not only allowed admission

officers the opportunity to better understand students’ writing skills but also allowed students

to show another aspect of their knowledge, skills, and abilities—those related to writing—that

they will need and surely use in their 1st year of college. Although there were a number of

proponents of this change, including the president of the University of California system at

the time (Atkinson, 2002), numerous critics were skeptical of the new section, claiming that

it would only increase test-taking time while adding little value to the meaning of their scores

(Baron, 2005; Perelman, 2005). Many thought the new section might be redundant or capture

many of the similar cognitive dimensions that were already being examined on the critical

reading section. Although reading and writing do rely on many of the same cognitive skills, they

are essentially utilized in different ways within these two domains (Kucer, 1987, 2005; Langer

& Flihan, 2000; Rosenblatt, 1994; Shanahan & Lomax, 1986; Tierney & Shanahan, 1991).

Therefore, it is not surprising that some students have much higher writing than critical reading

Correspondence should be sent to Emily J. Shaw, Research & Development, The College Board, 45 Columbus

Avenue, New York, NY 10023. E-mail: [email protected]

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146 SHAW, MATTERN, PATTERSON

scores, and vice versa. Very few studies, however, have effectively analyzed the discrepant

reading and writing performance of high school students, despite Stotsky’s (1983) call for

such research more than two decades ago. The addition of the writing section to the SAT

provides a fitting opportunity to examine this performance discrepancy and to understand the

student characteristics and academic consequences associated with much stronger performance

in critical reading than writing, and vice versa.

A practical understanding of the consequences of discrepant performance in these two

domains is particularly useful for admission and enrollment professionals who examine student

test scores in conjunction with other student information on an application. Having access to

empirical research on the impact of discrepant critical reading and writing performance and its

relationship with 1st-year college performance would provide context and deeper understanding

when highly discrepant SAT critical reading and writing scores are present during holistic or

“whole folder” reviews of applicants (Rigol, 2003, p. 9).

This study examines whether certain groups of students are more likely to have higher

writing performance as compared to critical reading performance, and vice versa. In addition,

this study examines the relationship between discrepant SAT critical reading and writing

performance and college outcomes, including 1st-year grade point average (FYGPA) and 1st-

year English grade point average (FY English GPA). This predictive model includes relevant

variables such as academic performance (i.e., SAT total score, high school grade point average

[HSGPA]) and demographic variables (i.e., gender, best spoken language, and race/ethnicity) to

determine the independent impact of the discrepancy on 1st-year grades. Finally, the interaction

between the demographic variables and the critical reading and writing performance discrepancy

will be included in the model to determine whether discrepant performance has a different

relationship with college outcomes for certain subgroups of students.

REVIEW OF THE LITERATURE

It is largely accepted that reading and writing are highly related processes. Although there are

clear overlaps in many of the component skills and knowledge bases (Shanahan, 1984, 1987;

Stotsky, 1983), there are also differences between reading and writing that are sometimes not

as clear (Fitzgerald & Shanahan, 2000; Kucer, 1985; Langer, 1986a, 1986b; Shanahan, 1984,

1987; Stotsky, 1983; Tierney & Shanahan, 1991). Studies primarily examining elementary and

middle school students have found that when writing, students tend to be more concerned with

bottom-up issues such as syntax, mechanics, and lexical choices than when reading (Gleason,

1995; Kucer, 1985; Langer, 1986b). Students are also more likely to set goals and be more

cognizant of the strategies employed while writing versus reading. When reading, however,

students are more focused on the content and validation of their understanding of the meaning

behind the text.

The few studies that have examined discrepant reading and writing performance in depth

have looked at this issue among relatively small samples of elementary and middle school

students utilizing discrepant performance on local measures to primarily classify students

as good readers/good writers, good readers/poor writers, or poor readers/poor writers (e.g.,

Honeycutt, 2002; Jordan, 1986; Thacker, 1990, 1991). Jordan (1986), for example, looked at

the differences between good readers/good writers’ and good readers/poor writers’ composing

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DISCREPANT SAT CRITICAL READING AND WRITING 147

processes using think-aloud protocols and used a set of descriptive categories to code reading

and writing behaviors. This research showed that good readers/good writers (a) were able to

abstract content from a reading passage and write about what they read in their own words,

(b) were more aware of the structural features of sentences, and (c) spent much more time

planning prior to writing. Good readers/poor writers struggled with each of these aspects.

Similarly, based on 90 ninth-grade students divided equally into groups of good readers/good

writers, good readers/poor writers, and poor readers/poor writers, Thacker (1990, 1991) studied

students’ ability to understand and recognize varying degrees of text organization when reading.

He found that good readers/good writers and good readers/poor writers were both skilled at

distinguishing between well and poorly organized text. However, good readers/poor writers

seemed to lack an awareness of how cohesive ties can bring meaning to disorganized text

and would likely benefit from greater instructional focus on cohesive relationships and the

effective organization of their own written responses to material. Given that there are students

with highly discrepant reading and writing performance and that these students do tend to

approach the two related tasks in different ways than students with more consistent reading

and writing performance, it would seem useful to study the impact of discrepant reading and

writing performance at the postsecondary level.

Although discrepant SAT critical reading and writing performance has not yet been studied

in relation to postsecondary performance, other analyses related to discrepant SAT performance

patterns have been conducted. For example, a recent study by Mattern, Camara, and Kobrin

(2007) showed that there are sizeable groups of students considered to have discrepant critical

reading and writing scores on the SAT. Mattern et al. standardized students’ critical reading

and writing scores across the 2006 College Bound Seniors cohort1 to examine the difference

between these scores. Those students with critical reading and writing scores that differed by

1 or more standard units were considered to be discrepant. There were 49,356 students (3.6%

of the cohort of test takers) who scored 1 or more standard units higher on writing than critical

reading (referred to as better at writing), and there were 50,336 students (3.7% of the cohort

of test takers) who scored 1 or more standard units higher on critical reading than writing

(referred to as better at critical reading).

Mattern et al. (2007) also investigated whether there were any differences between the

performance groups with regard to gender and/or racial/ethnic composition. They found that

the better at writing group was comprised of almost twice as many female as male students.

Conversely, the better at critical reading group had almost twice as many male as female

students. With regard to race/ethnicity, the only differences noted were that the percentages of

White and American Indian/Alaskan Native students were higher in the better at critical reading

group, whereas the percentage of Asian, Asian American, and Pacific Islander students was

higher in the better at writing category. The difference in HSGPA among the better at critical

reading group, better at writing group, and students who scored similarly on both sections was

also investigated. Mattern et al. found that HSGPA was the highest for the better at writing

group and lowest for the better at critical reading group, with significant differences (p < .05)

among all three groups based on analysis of variance (ANOVA) results.

In addition to noting gender and racial/ethnic differences in discrepant critical reading and

writing performance on the SAT, in a different study, Shaw (2007) also found that students

1Comprised of students with an SAT or SAT Subject Test score that reported to graduate from high school in 2006.

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that were much stronger in SAT writing than SAT critical reading were significantly more

likely (p < .05) to have taken English as a Second Language coursework in high school than

students who were much stronger in SAT critical reading than SAT writing. Shaw speculated

that perhaps this much stronger writing than reading performance for students with English as

a Second Language experience was related to issues of biliteracy, noting that Holm and Dodd

(1996) found that students from nonalphabetic written language backgrounds tend to struggle

with new or unfamiliar words when attending universities where English is the medium of

instruction. There are likely many unfamiliar words to students on the SAT critical reading

section, whereas the writing multiple-choice section tends to be more rule based and related

to grammar and the SAT essay is student produced, free from most of the constraints placed

on a reader by the author of an existing text.

These demographic and academic (HSGPA) differences between the discrepant groups signal

that there may also be differences in how these students perform in college, or specifically how

the magnitude and direction of the critical reading and writing discrepancy might impact 1st-

year college performance, particularly in English coursework. Despite the importance and

value in integrating writing across the disciplines, many content areas require few or no

writing assignments, nor do they offer the corresponding writing instruction that would foster

success on the writing assignments (Lavelle, 2003). Writing scholars have remarked that

training in writing has all too often become the sole responsibility of the freshman English or

composition course (Lavelle, 2003; Moore, 2003). Understanding the connection between the

critical reading and writing discrepancy with English course performance would be particularly

interesting, as both reading and writing activities are both considered central to freshman

English coursework (El-Hindi, 1997; Flower et al., 1990). However, Bosley (2008) commented

that although there is a large body of literature that documents the value in teaching critical

reading and writing reciprocally in the classroom, most college composition courses do not

explicitly cover critical reading strategies or effectively integrate reading into the writing

lessons and assignments. Further complicating our understanding of undergraduate English

coursework and performance, Lavelle (2003) observed that 1st-year composition grades do

not always reflect the students’ writing skills (such as analysis, synthesis, transcription, and

revision) but includes contaminating factors like attendance, promptness, or public speaking

skills.

This model-based study allows for the systematic investigation of differences in 1st-year

college performance, in addition to descriptive information about discrepant reading and writing

performance by different subgroups. Unlike the few previous studies that have focused on

describing students with discrepant reading and writing performance, the current research

focuses on the academic consequences of discrepant reading and writing performance in

college. Moreover, studying discrepant reading and writing performance on the SAT allows

for the examination of this issue on a much larger, national scale than has been studied in the

past. Also different from previous studies on discrepant SAT reading and writing performance,

which developed categorical groups of discrepant performance for analysis (i.e., Mattern

et al., 2007; Shaw, 2007), this study uses a continuous discrepancy measure to avoid losing

any measurement precision associated with dichotomizing continuous variables (MacCallum,

Zhang, Preacher, & Rucker, 2002). More than 1.5 million students take the SAT each year

(College Board, 2010), and the test is used in admission decisions at the large majority of 4-

year colleges and universities, rendering the results of the current study to be both theoretically

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and practically useful to various stakeholders. In a similar vein, much of the research in this

area is based on small samples, thereby potentially limiting the generalizability of the results,

whereas the current study includes a sample of more than 140,000 attending a diverse set of

109 postsecondary institutions.

METHOD

Participants

The sample for this study is based on the students in the national SAT Validity Study sample

(for details, see Kobrin, Patterson, Shaw, Mattern, & Barbuti, 2008). For the national SAT

Validity Study, a wide range of 4-year institutions in the United States submitted 1st-year

college performance data to the College Board on the first-time, 1st-year students who entered

their institutions in the fall of 2006. The final sample in the current study included 140,919

students—all with valid SAT scores, self-reported high school GPAs, and FYGPAs provided

by their college/university, from 109 four-year institutions in the United States.

Measures

FYGPA. Each participating institution supplied FYGPA values for their 2006 first-time,

1st-year students. The range of FYGPA across institutions was 0.00 to 4.27.2

FY English GPA. Each participating institution supplied grades for all of the courses

taken by their 1st-year, first-time students during the 2006–2007 school year. All coursework

was coded for the subject area of the course. Those courses coded as English courses taken in

the 1st year of college3 were averaged for each student and considered to be the students’ FY

English GPA. Of the 140,919 students in the sample, 101,765 took at least one English course;

therefore, analyses based on FY English GPA are based on that subset of students.

SAT critical reading section. The SAT critical reading section, scored on a scale ranging

from 200 to 800, consists of 67 items in two 25-min sections and one 20-min section. The

SAT critical reading section measures a student’s ability to read and think carefully based on

sentence completions and items related to passages ranging in length from 100 to approximately

850 words and on topics from literary fiction to natural sciences. There are 19 sentence

completion items and 48 passage-based reading items, all of which fall into three general

content categories: extended reasoning (42–50 items), literal comprehension (4–6 items), and

vocabulary in context (12–16 items).

2Although a few institutions’ GPA scales ranged from 0.00 to 4.33, most had a maximum of 4.00.3Shaw and Patterson (2010) examined 1st-year college coursework in English across a national sample of 4-year

institutions and found that the vast majority of English courses are composition courses (72%).

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SAT writing section. The SAT writing section consists of one 25-min essay, one 25-min

multiple-choice section, and one 10-min multiple-choice section with a total of 60 items. The

SAT writing section measures a student’s ability to improve sentences, identify sentence errors,

improve paragraphs, and write an essay that will assess a student’s ability to think critically and

write effectively in response to a prompt adapted from an authentic text, under time constraints

similar to those encountered in essay tests in college courses. The essay score scale ranges

from 0 to 12 and is based on the ratings of two trained essay readers. The multiple-choice

writing section counts for approximately 70%, and the essay counts for approximately 30% of

the total raw score, which is used to calculate the 200 to 800 scale score for the section.

SAT Questionnaire. The SAT Questionnaire is a survey administered to all students

when they register for the SAT, either online or by mail. It consists of 42 questions about

the student’s background, high school experiences, and plans for college. Self-reported gender,

race/ethnicity, and best language spoken were obtained from the SAT Questionnaire.

Design and Procedure

This study focused on discrepant critical reading (CR) and writing (W) performance as indexed

by the difference in the two SAT section scores (CR-W Discrepancy D SAT CR–SAT W).

Unlike previous research, which created categorical groups based on a difference score (i.e.,

Mattern et al., 2007; Shaw, 2007), the continuous CR-W Discrepancy variable was used in

subsequent analyses to avoid any loss of information. The CR-W Discrepancy scores ranged

from �320 to 530 with a mean of 6.16 and a standard deviation of 60.58, indicating that, on

average, students’ SAT critical reading scores were 6 points higher than their writing scores. The

first set of analyses examined whether the magnitude of CR-W Discrepancy differed for specific

subgroups, and if so, in what direction. That is, the average CR-W Discrepancy score was

computed overall and by gender, race/ethnicity, and best language subgroups. Student’s t tests

were conducted to examine whether the average CR-W Discrepancy score was significantly

different from zero (p < .01), where a zero value indicates that, on average, students earn

the same SAT critical reading and writing score. This information is useful in highlighting

the commonalities and differences that characterize students exhibiting discrepant critical

reading and writing performance on the SAT and can be particularly helpful in the design

and development of specific educational interventions for their weaker area.

In addition, this study examined whether a student’s CR-W Discrepancy score is related

to subsequent college performance (i.e., FYGPA and FY English GPA), above and beyond

traditional measures of academic performance and student characteristics. Such analyses can

inform whether discrepant performance has a positive, negative, or insignificant effect on

college success. Also, whether the direction of the discrepancy (i.e., higher writing performance

vs. higher critical reading performance) mattered in relation to future college performance

was examined. Finally, the impact of discrepant reading and writing performance on college

performance for different student subgroups, such as English Language Learners, was analyzed.

To study these research questions, hierarchical linear modeling (HLM) techniques were

employed because of the inherent nested structure (i.e., students within colleges) of the data

(Raudenbush & Bryk, 2002). In the first step, a model with student-level demographic charac-

teristics (i.e., gender, race/ethnicity, best spoken language) and academic performance measures

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(i.e., HSGPA, SAT composite score) was estimated. Next, the CR-W Discrepancy variable was

added and the change in model fit was examined using the Akaike Information Criterion (AIC).

Finally, interactions among student subgroups and the CR-W Discrepancy were added to the

model, and again the change in AIC was computed to examine the change in model fit.

RESULTS

Descriptive Statistics

The sample size, mean, and standard deviation for each academic performance measure for the

total sample and by gender, racial/ethnic, and best spoken language subgroups are provided

in Table 1. In general, female participants earned higher grades in high school and college

and had slightly higher SAT writing scores as compared to male participants who had higher

SAT math and critical reading scores. With regard to racial/ethnic comparisons, White and

Asian students outperformed the other subgroups on all academic indicators. Students whose

best spoken language was English earned the highest grades in their 1st-year English courses;

however, students whose best spoken language was something other than English had the

highest FYGPA. It should be pointed out that not all students took a 1st-year English course, and

therefore the sample sizes for that measure are smaller than for the other academic indicators.

To determine whether certain students performed more discrepantly on the SAT critical

reading and writing sections than other students, the mean CR-W Discrepancy score overall

and by student subgroups is provided along with the corresponding t-test results in Table 2. As

mentioned previously, the average CR-W Discrepancy score was 6.16 (SD D 60.58), indicating

that, on average, students in this sample had critical reading scores that were six points higher

than their writing. This is similar to the national results, where the average critical reading

TABLE 1

Descriptive Statistics of Study Variables by Student Characteristics

HSGPA SAT CR SAT M SAT W FYGPA FY English GPA

Subgroup n M SD M SD M SD M SD M SD n M SD

Overall 140,919 3.61 0.50 560 95 579 96 553 94 2.97 0.71 101,765 3.12 0.84

Gender

Female 75,940 3.65 0.48 556 95 559 93 556 93 3.05 0.67 56,064 3.21 0.78

Male 64,979 3.55 0.52 564 95 602 95 550 94 2.89 0.74 45,701 3.01 0.89

Race/Ethnicity

American Indian 772 3.53 0.54 544 87 555 89 529 88 2.78 0.76 538 2.97 0.92

Asian 13,775 3.67 0.47 563 104 624 97 563 101 3.05 0.66 9,426 3.15 0.79

Black 9,944 3.40 0.55 508 88 505 87 499 87 2.64 0.73 8,187 2.80 0.94

Hispanic 10,338 3.59 0.51 525 93 538 94 520 90 2.74 0.77 7,123 2.83 0.97

Other 4,372 3.58 0.50 559 98 573 98 554 97 2.96 0.71 3,217 3.08 0.83

White 101,718 3.62 0.49 568 92 585 92 561 91 3.02 0.69 73,274 3.18 0.80

Best spoken language

Another 1,605 3.62 0.52 464 99 606 114 480 102 3.05 0.68 1,139 3.09 0.84

English and another 7,033 3.62 0.49 531 100 570 108 534 101 2.90 0.72 4,959 2.97 0.89

English only 132,281 3.61 0.50 562 94 579 95 555 93 2.98 0.70 95,667 3.12 0.83

Note. HSGPA D high school grade point average; CR D critical reading; M D math; W D writing; FYGPA D 1st-year grade

point average.

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TABLE 2

SAT CR-W Discrepancy by Student Characteristics

Subgroup n M SD t p

Overall 140,919 6.16 60.58 38.15 <.001

Gender

Female 75,940 �0.50 59.24 �2.33 .020

Male 64,979 13.94 61.19 58.07 <.001

Race/Ethnicity

American Indian 772 15.38 58.69 7.28 <.001

Asian 13,775 0.39 62.06 0.73 .465

Black 9,944 8.54 60.91 13.98 <.001

Hispanic 10,338 4.49 59.58 7.65 <.001

Other 4,372 4.29 60.85 4.66 <.001

White 101,718 6.89 60.39 36.36 <.001

Best spoken language

Another 1,605 �16.65 63.43 �10.51 <.001

English and another 7,033 �2.92 61.60 �3.97 <.001

English only 132,281 6.92 60.40 41.65 <.001

Note. CR D critical reading; W D writing.

score was six points higher than the average writing score for the 2006 College Bound Seniors

cohort (SAT CR D 503, SAT W D 497; College Board, 2006). These results suggest that most

students had similar scores on the two sections of the SAT; however, there was much variability

across students with CR-W Discrepancy scores ranging from �320 to 530. See Figure 1 for

the distribution of CR-W Discrepancy scores in the sample.

The mean CR-W Discrepancy score also varied across student subgroups. For example,

female students had similar critical reading and writing scores (M D �0.50, t D �2.33,

p D .020) whereas male students had critical reading scores that were roughly 14 points

higher (M D 13.94, t D 58.07, p < .001). In addition, ANOVA results revealed that CR-W

Discrepancy scores were significantly higher for male than female students (F D 1401.18,

p < .001). These results parallel the pattern of scores for the national population of SAT test

takers in 2006, where female participants had both an average critical reading and writing

score of 502 and male participants had an average critical reading score of 505 and writing

score of 491 (College Board, 2006). When the results were parsed by race/ethnicity, all CR-W

Discrepancy score averages were positive, but the magnitude varied across subgroups, with

American Indian students followed by Black students having the most discrepant performance.

All values were significantly different from zero (p < .01) except for the Asian students, who

had a mean CR-W Discrepancy score of 0.39 (t D 0.73, p D .465). ANOVA results revealed

significant differences among racial/ethnic groups in CR-W Discrepancy scores (F D 29.91,

p < .001). Of the 15 post hoc pairwise comparisons, six were not significant at p < .01.

Four of the nonsignificant comparisons included White students when compared to American

Indian, Black, Hispanic, and Other students. The American Indian—Black and Hispanic—

Other contrasts were also nonsignificant. Finally, the results by best language spoken revealed

that students who indicated that their best language was not English earned higher writing

scores than critical reading scores, whereas the opposite was true for students who indicated

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FIGURE 1 Distribution of students’ CR-W discrepancy scores.

that their best spoken language was English. Results revealed significant differences among

best language groups in CR-W Discrepancy scores (F D 146.46, p < .001) with all post hoc

pairwise comparisons significant at p < .01. The results are consistent with the findings from

Mattern et al. (2007).

HLM Results

FYGPA. In the first set of HLM analyses, the effect of CR-W Discrepancy scores on

FYGPA was examined, modeling student-level effects and controlling for random college-level

variation. The reference group was defined as White, male students whose best spoken language

was English. Prior to model estimation, HSGPA, SAT composite score, and CR-W Discrepancy

scores were grand mean centered—across all colleges and using sample means (HSGPA M D

3.61; SAT composite M D 1692)—in order for the intercept to be more meaningful (i.e., the

expected FYGPA for a student in the reference group with quantitative predictors equal to

the sample mean). In addition, the SAT composite score was divided by 600 and the CR-W

Discrepancy score was divided by 300 to make the scale of the predictors more comparable

and for significance test results to be more meaningful. The model estimates and corresponding

p values are provided in Table 3.

In the first step, a model was estimated that included gender, race/ethnicity, best language

spoken, HSGPA, and SAT total score as predictors of FYGPA. For Level 1, all of the parameter

estimates for the demographic variables were significant (p < .01) except for the indicator for

Asian students and for students whose best spoken language was English and another language.

HSGPA and SAT scores were both positively related to FYGPA, which is congruent with

previous research (Kobrin et al., 2008).

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TABLE 3

Hierarchical Linear Model Results for 1st-Year Grade Point Average

Model 1 Model 2 Model 3

Effect Est. p Est. p Est. p

Intercept 2.964 <.001 2.965 <.001 2.966 <.001

Gender

Female 0.151 <.001 0.148 <.001 0.148 <.001

Race/Ethnicity

American Indian �0.151 <.001 �0.149 <.001 �0.152 <.001

Asian �0.026 .018 �0.026 .015 �0.026 .016

Black �0.163 <.001 �0.162 <.001 �0.162 <.001

Hispanic �0.118 <.001 �0.116 <.001 �0.116 <.001

Other �0.049 <.001 �0.050 <.001 �0.050 <.001

Best language

Another 0.213 <.001 0.208 <.001 0.210 <.001

English and another 0.007 .576 0.005 .652 0.005 .691

HSGPAa 0.400 <.001 0.399 <.001 0.399 <.001

SAT CR C M C Wa;b 0.487 <.001 0.489 <.001 0.488 <.001

SAT CR � Wa;c �0.069 <.001 �0.107 <.001

SAT CR � Wa;c � Female 0.060 <.001

SAT CR � Wa;c� American Indian 0.090 .414

SAT CR � Wa;c� Asian 0.023 .415

SAT CR � Wa;c � Black 0.056 .073

SAT CR � Wa;c � Hispanic 0.006 .863

SAT CR � Wa;c� Other 0.018 .699

SAT CR � Wa;c� Another language 0.010 .894

SAT CR � Wa;c� English and another language �0.032 .394

Covariance Parameter Estimates With Approximate p Values

Group Parameter Est. p Est. p Est. p

College Intercept 0.016 <.001 0.016 <.001 0.016 <.001

College Gender 0.001 <.001 0.001 <.001 0.001 <.001

College Race/Ethnicity 0.003 <.001 0.003 <.001 0.003 <.001

College Best language 0.003 .001 0.003 .001 0.003 .001

College HSGPAa 0.010 <.001 0.010 <.001 0.010 <.001

College SAT CR C M C Wa;b 0.012 <.001 0.012 <.001 0.012 <.001

College SAT CR-Wa;c 0.002 .057 0.001 .083

Residual 0.348 <.001 0.348 <.001 0.348 <.001

Par. AIC Par. AIC Par. AIC

18 252,441 20 252,361 28 252,357

Note. N D 140,919, k D 109. Reference group: White male students whose best spoken language is English alone, with high school

grade point average (HSGPA) D 3.61 and SAT critical reading (CR) C SAT math (M) C SAT writing (W) D 1692. Models estimated

under full-information maximum likelihood with random college effects for all predictors. AIC D Akaike Information Criterion.aVariable was grand mean centered based on the sample included in the 1st-year grade point average analysis. bVariable was

divided by 600 to make the scale of predictors more comparable. cVariable was divided by 300 to make the scale of predictors more

comparable.

In the next step, the students’ CR-W Discrepancy score was added to the model. The

parameter estimate was �0.069 (p < .001), indicating that students with higher SAT writing

scores than critical reading scores earned higher grades in college, controlling for the students’

demographic characteristics and academic credentials (i.e., HSGPA, SAT total score). The

addition of the two parameters (i.e., the student-level effect for CR-W Discrepancy and its

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college-level variance) indicates an improvement in model fit as illustrated by the reduction in

AIC.

Finally, the interaction terms between a student’s discrepancy score and demographic vari-

ables were included in the model to examine whether the relationship between CR-W Discrep-

ancy score and FYGPA differed for various subgroups of students. Only the parameter estimate

for CR-W Discrepancy � Gender interaction was significant (0.060, p < .001) indicating that

discrepant performance had a smaller effect on FYGPA for female participants as compared to

male. In Table 4, the expected FYGPA for various combinations of CR-W Discrepancy scores

are provided to illustrate the effect of discrepant performance on FYGPA. For example, for

White male students whose best spoken language is English and who have a HSGPA of 3.61

and an SAT total score of 1500, students with a �100 CR-W Discrepancy have an expected

FYGPA of 2.84 as compared to 2.77 for students with a C100 CR-W Discrepancy. However,

for White female students whose best spoken language is English and who have a HSGPA

of 3.61 and an SAT total score of 1500, students with a �100 CR-W Discrepancy have an

expected FYGPA of 2.97 as compared to 2.94 for students with a C100 CR-W Discrepancy.

The difference in FYGPA was 0.03 for female students as compared to 0.07 for male students.

Refer to Table 4 for the expected FYGPA for other combinations of SAT scores, SAT CR-W

Discrepancy scores, and student subgroups.

FY English GPA. Given that students take a variety of courses during their college

experience, grades in English courses were also examined as a more focused investigation of

the consequences of discrepant performance on the SAT writing and critical reading sections.

Only students who took at least one English course during their 1st year of college were

included in the analyses, reducing the sample to 101,765 students. For students who took more

than one English course, the average English grade was used as the outcome of interest.

Parallel to the FYGPA analyses, gender, race/ethnicity, best language spoken, HSGPA, and

SAT composite scores were included in the first step as predictors of FY English GPA. For the

student-level effects, gender and all of the race/ethnicity indicators except for Asian students

were significant (refer to Table 5). Unlike the FYGPA results where stating a language other

than English was their best language was significant (p < .01), neither of the best language

effects were significantly different from zero for FY English GPA. The parameter estimates

for both HSGPA and SAT scores were positive, indicating that students with higher HSGPAs

and SAT scores earned higher grades in their 1st-year English course(s).

In the next step, the students’ CR-W Discrepancy score was added to the model. The

parameter estimate was �0.134 (p < .001) indicating that students with higher SAT writing

scores than critical reading scores earned higher grades in their 1st-year English course(s),

controlling for the students’ demographic characteristics and academic credentials. Perhaps not

surprising, the effect is more than twice as large as what was found for FYGPA, which is

likely a function of matching the content area of the criterion with that of the predictors. In

terms of model fit, the addition of the two CR-W Discrepancy parameters (i.e., the fixed- and

random-effects) indicates an improvement as illustrated by the reduction in AIC.

Finally, the interaction terms between a student’s discrepancy score and demographic vari-

ables were included in the model to examine whether the relationship between the CR-W

Discrepancy score and FY English GPA differed for various subgroups of students. Similar to

the FYGPA results, only the parameter estimate for the CR-W Discrepancy � Gender interaction

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TABLE 4

Expected 1st-Year Grade Point Average by SAT CR-W Discrepancy Score

White, Male, English-Only Students With HSGPA D 3.61

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 2.84 2.82 2.80 2.79 2.77

1600 2.92 2.90 2.88 2.87 2.85

1700 3.00 2.98 2.97 2.95 2.93

White, Female, English-Only Students With HSGPA D 3.61

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 2.97 2.96 2.96 2.95 2.94

1600 3.05 3.04 3.04 3.03 3.02

1700 3.13 3.13 3.12 3.11 3.10

White, Male, Another–Language-Only Students With HSGPA D 3.61

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 3.05 3.03 3.01 3.00 2.98

1600 3.13 3.11 3.09 3.08 3.06

1700 3.21 3.19 3.18 3.16 3.14

White, Female, Another–Language-Only Students With HSGPA D 3.61

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 3.18 3.17 3.17 3.16 3.15

1600 3.26 3.25 3.25 3.24 3.23

1700 3.34 3.33 3.33 3.32 3.32

Note. Based on the parameter estimates from Model 3. CR D critical reading; M D math; W D writing; HSGPA

D high school grade point average.

was significant (0.095, p < .001), indicating that discrepant performance had a smaller effect

on FY English GPA for female students as compared to male students. Analogous to Table 4

for FYGPA, Table 6 provides the expected FY English GPA for various combinations of CR-

W Discrepancy scores to illustrate the effect of discrepant performance on English course

performance. For example, for White male students whose best spoken language is English

and who have a HSGPA of 3.56 and a SAT total score of 1500, students with a �100 CR-W

Discrepancy score have an expected FYGPA of 2.98 as compared to 2.85 for students with

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TABLE 5

Hierarchical Linear Model Results for 1st-Year English Grade Point Average

Model 1 Model 2 Model 3

Effect Est. p Est. p Est. p

Intercept 3.040 <.001 3.045 <.001 3.046 <.001

Gender

Female 0.208 <.001 0.202 <.001 0.202 <.001

Race/Ethnicity

American Indian �0.127 <.001 �0.124 <.001 �0.125 <.001

Asian �0.029 .030 �0.031 .023 �0.030 .028

Black �0.143 <.001 �0.141 <.001 �0.141 <.001

Hispanic �0.114 <.001 �0.112 <.001 �0.112 <.001

Other �0.043 .009 �0.043 .009 �0.043 .008

Best language

Another 0.062 .018 0.056 .033 0.053 .053

English and another �0.033 .038 �0.035 .026 �0.035 .028

HSGPAa 0.345 <.001 0.343 <.001 0.343 <.001

SAT CR C M C Wa;b 0.421 <.001 0.425 <.001 0.424 <.001

SAT CR � Wa;c �0.134 <.001 �0.201 <.001

SAT CR � Wa;c � Female 0.095 <.001

SAT CR � Wa;c� American Indian 0.067 .681

SAT CR � Wa;c� Asian 0.102 .016

SAT CR � Wa;c � Black 0.022 .624

SAT CR � Wa;c � Hispanic 0.036 .454

SAT CR � Wa;c� Other 0.077 .236

SAT CR � Wa;c� Another language �0.094 .374

SAT CR � Wa;c� English and another language �0.021 .712

Covariance Parameter Estimates With Approximate p Values

Group Parameter Est. p Est. p Est. p

College Intercept 0.034 <.001 0.034 <.001 0.034 <.001

College Gender 0.002 <.001 0.002 <.001 0.002 <.001

College Race/Ethnicity 0.003 <.001 0.003 <.001 0.003 <.001

College Best language 0.003 .018 0.003 .020 0.003 .018

College HSGPAa 0.016 <.001 0.016 <.001 0.016 <.001

College SAT CR C M C Wa;b 0.041 <.001 0.041 <.001 0.041 <.001

College SAT CR-Wa;c 0.013 <.001 0.012 .001

Residual 0.540 <.001 0.539 <.001 0.539 <.001

Par. AIC Par. AIC Par. AIC

18 257,162 20 226,993 28 226,985

Note. N D 101,765, k D 109. Reference group: White male students whose best spoken language is English alone, with high school

grade point average (HSGPA) D 3.56 and SAT critical reading (CR) C SAT math (M) C SAT writing (W) D 1666. Models estimated

under full-information maximum likelihood with random college effects for all predictors. AIC D Akaike Information Criterion.aVariable was grand mean centered based on the sample included in the 1st-year grade point average analysis. bVariable was

divided by 600 to make the scale of predictors more comparable. cVariable was divided by 300 to make the scale of predictors more

comparable.

a C100 CR-W Discrepancy score. However for White female students whose best spoken

language is English and who have a HSGPA of 3.56 and a SAT total score of 1500, students

with a �100 CR-W Discrepancy score have an expected FYGPA of 3.16 as compared to 3.09

for students with a C100 CR-W Discrepancy score. As was the case for FYGPA, the difference

in expected FY English GPA (given the sample mean HSGPA, SAT composite of 1500, and

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TABLE 6

Expected 1st-Year English Grade Point Average by SAT CR-W Discrepancy Score

White, Male, English-Only Students With HSGPA D 3.56

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 2.98 2.95 2.92 2.88 2.85

1600 3.05 3.02 2.99 2.95 2.92

1700 3.12 3.09 3.06 3.02 2.99

White, Female, English-Only Students With HSGPA D 3.56

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 3.16 3.14 3.12 3.11 3.09

1600 3.23 3.21 3.19 3.18 3.16

1700 3.30 3.28 3.27 3.25 3.23

White, Male, Another-Language-Only Students With HSGPA D 3.56

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 3.06 3.01 2.96 2.91 2.87

1600 3.13 3.08 3.03 2.99 2.94

1700 3.20 3.15 3.10 3.06 3.01

White, Female, Another–Language-Only Students With HSGPA D 3.56

SAT CR-W

SAT CR C M C W �100 �50 0 50 100

1500 3.24 3.20 3.17 3.14 3.10

1600 3.31 3.27 3.24 3.21 3.17

1700 3.38 3.35 3.31 3.28 3.25

Note. Based on the parameter estimates from Model 3. CR D critical reading; M D math; W D writing; HSGPA

D high school grade point average.

a change of �100 to C100 CR-W Discrepancy) was smaller for female students (0.07) as

compared to male students (0.13).

DISCUSSION

The intent of this study was to determine whether there were distinct differences in 1st-

year college performance, by discrepant reading and writing performance, overall, and for

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different subgroups among a large, national sample of students, as well as to provide descriptive

information by subgroup. A primary contribution of this research is that it is the first study

to examine the academic consequences (e.g., FYGPA, grades in 1st-year English courses) of

discrepant reading and writing performance in higher education.

Results of the current study showed that, indeed, there were differences in the magnitude and

direction of the reading and writing discrepancy by demographic subgroups. For example, on

average, male students perform 14 points higher on critical reading than writing, whereas female

students, on average, perform quite similarly on both SAT sections. Also of note, American

Indian students perform, on average, 15 points higher on critical reading than writing, whereas

students, whose best spoken language is not English, perform almost 17 points higher on

writing than critical reading.

These performance differences by subgroup are interesting because they call into question

various explanations for systematic performance differences in two highly related domains. As

previously mentioned, though reading and writing are highly related, they entail the different use

of similar but not exactly the same knowledge, skills, and abilities. The discrepancy favoring

reading over writing for American Indian students may at least be partially explained by

cultural factors that have historically placed a greater emphasis on the oral tradition with a

lesser focus on writing skills (Ingalls, Hammond, Dupoux, & Baeza, 2006; Pearce & Gayle,

2009). Although there has been a substantial amount of research documenting stronger writing

performance for female students over male students (e.g., Engelhard, Gordon, Siddle Walker,

& Gabrielson, 1994; Halpern, 2004), there has been far less research as to why male students

might be stronger at reading than writing. The stronger writing than reading performance for

students who report their best language as other than English may be related to issues of

biliteracy or the transfer of literacy-processing skills from students’ first language to English

(Holm & Dodd, 1996). Shen (2009) remarked that for English Language Learners, reading and

writing are often taught as such separate skills and that the emphasis is typically on grammar

and mechanics, which could help to explain the performance difference favoring SAT writing

versus critical reading for this group of students.

When the academic consequences of discrepant critical reading and writing performance

were examined, including a measure of this discrepancy in a model of general 1st-year college

performance and controlling for relevant demographic and academic variables, there was an

improvement in the model fit. There was even greater improvement of model fit by the

discrepancy measure when the outcome of interest was 1st-year English GPA. The findings

from these analyses indicate that there appears to be a slight academic advantage in college to

being stronger at writing than reading. A cognitive explanation may be related to the strengths

and weaknesses found in earlier studies of discrepant reading and writing performance (e.g.,

Honeycutt, 2002; Jordan, 1986; Langer, 1986a, 1986b; Palmer, 1986; Thacker, 1990, 1991).

For example, Thacker (1990, 1991) found that good readers/poor writers, compared to good

readers/good writers, seemed to lack an awareness of how cohesive ties can bring meaning to

disorganized text. This weakness may be closely tied to performance in college coursework,

particularly in the 1st year. Another potential hypothesis to explore is whether students who are

stronger writers than readers are more likely to be conscientious, higher achieving students. Yet

another explanation may be that the outcome measures examined—FYGPA and FY English

GPA—are more closely related to writing skills and abilities than to reading skills and abilities

as measured by the SAT (Tierney & Leys, 1986). This would allude to a measurement effect

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of some sort, whereby writing is of greater import in the 1st year of college and therefore

very strong writing skills as measured by the SAT serve students extremely well. All of these

hypotheses require testing with further research.

In both the FYGPA and FY English GPA models, only the parameter estimates for the

CR-W Discrepancy � Gender interaction were significant (p < .01), indicating that discrepant

performance had a smaller effect on FYGPA and FY English GPA for female students as

compared to male students. More research is needed to better understand this finding. In a

study of the role of personality in college performance and individual course grades, Nguyen,

Allen, and Fraccastoro (2005) found that personality explains 7% of the variance in overall

college GPA and 16% of the variance in course grades and that gender often moderates the

personality–academic performance relationship. It is certainly possible that there are personality

characteristics that affect academic performance differently by gender, which may also be

related to discrepant reading and writing performance. Also, this finding may be linked to the

notion that the process of writing requires a great deal of cognitive planning and organization

(Thacker, 1990, 1991) and that grammar, in particular, is quite rule based. These metacognitive

strategies along with conscientiously following rules could be quite helpful in the 1st year of

college (R. L. Brennan, personal communication, September 12, 2008). Perhaps male students

who excel at writing, particularly over reading, are more conscientious and/or organized than

the average male student and are therefore slightly more successful in college or in a course.

An additional explanation may involve differences in the nature of the coursework taken by

male and female students in the 1st year of college, which could affect the relationship between

the CR-W Discrepancy and GPA by gender.

A few limitations of this research should be noted. First, reading and writing performance in

this study were defined only by scores on the critical reading and writing sections of the SAT,

respectively. Although the SAT critical reading and writing sections are neither complete nor

perfect measures of these domains, research has demonstrated a strong link between the skills

measured by the SAT introduced in March 2005 and high school and college curricula and

instructional practice in reading and writing (Milewski, Johnsen, Glazer, & Kubota, 2005). It

would be useful to study discrepant performance among other reading and writing measures in

the future. Similarly, the definition and operationalization of discrepant performance in reading

in writing is open to interpretation. Also, the students in this sample with outcome data from

colleges and universities were slightly higher performing students based on mean SAT scores

and HSGPA than the general SAT cohort. This was expected, however, because the sample

included only students attending 4-year colleges and universities, whereas the SAT cohort

includes all students who have taken the SAT in a particular year. However, based on the fact

that the sample SAT critical reading and writing gaps by subgroup mimicked those of the full

cohort, it is unlikely that there would vastly different results for a less able group of college

students.

There are a number of avenues for future research, as there is still much to learn about

students with discrepant reading and writing performance. For example, it would be interesting

to study the role of first and best language in discrepant reading and writing performance

and study whether there are certain languages or types of alphabets that make a student more

apt to perform much more strongly in writing than reading in English. Similarly, it could

be worthwhile to examine the role that English Language Learner’s curricula in the K–12

system may play in this discrepancy. Another area for future research is whether there may

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be some high schools that cultivate discrepant performance by focusing on different areas

of English Language Arts in the curriculum more than others. Perhaps this could also be

investigated with hierarchical linear modeling to determine if there are high school effects in

discrepant performance. It would also be interesting to determine whether there are cultural or

personality factors related to discrepant performance and/or the relationship between discrepant

performance and college performance.

It would also be useful to examine the relationship between having discrepant SAT critical

reading and writing scores and more distal academic outcomes, such as 2nd- or 3rd-year GPA,

or retention to the 2nd or 3rd year. This would help to disentangle the potential effect of having

so many writing intensive courses required in the 1st year of college. In addition, does being

weaker in one domain or the other relate to one’s choice of major, with students selecting

majors that fit their academic strengths and weakness? It would also be interesting to learn

whether graduation rates vary systematically as function of a student’s CR-W discrepancy

score.

Another area for future study is related to the definitions of discrepant performance. The

current study considers discrepant performance to be based on relative differences between

each student’s own reading and writing performance. Using this method, students exhibiting

discrepant reading and writing performance could be quite skilled at both but have wide gaps

in performance. A different approach to studying discrepant performance would be to create

discrepant categories relative to the student’s standing on the measure (in this study, the SAT),

so that students performing x points above the mean on critical reading and x points below the

mean on writing would be categorized as stronger readers than writers, for example.

Finally, it would be worthwhile to explore whether reading and writing self-efficacy inter-

ventions such as modeling, goal setting, and progress feedback in the weaker domain may

be useful in building up performance in the weaker area, particularly because the student has

excelled and developed a strong foundation in a highly related domain.

The results from this study on discrepant SAT critical reading and writing performance

clearly show that the critical reading and writing sections provide unique and relevant informa-

tion about students’ knowledge, skills, and abilities in two related domains. Not only was there a

sizeable number of students who displayed discrepant critical reading and writing performance,

but discrepant performance favoring SAT writing over reading is related to higher FYGPAs

and FY English GPAs, even after controlling for relevant demographic and academic student

characteristics. Future research on students with discrepant reading and writing performance

is particularly important because differing performance in cognitively similar domains may

present an opportunity to build and develop skills and expertise in the weaker area by efficiently

building on the ample foundation in the stronger area.

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Documents

Discrepant SAT Critical Reading and Writing Scores: Implications for College Performance