Interaction Between SES and College Performance Zwick,

Interaction between SES and College Performance

Zwick, R. & Himelfarb, I. (2011). The effect of high school socioeconomic status on the predictive validity of SAT scores and high school grade-point average. Journal of Educational Measurement, 48(2), 101-121.

African-American (AA) and Latino students underperform other racial groups during their first year of college if SAT scores are used in the prediction formula. The reasons for this are unknown, although socioeconomic status (SES) is suspected.

The current study was undertaken to evaluate whether an SES index could improve the predictive performance of a formula incorporating high school grade-point averages (HSGPAs) and SAT scores.

Objectives

Evaluate the value of including a SES correction factor in the formula used for predicting first-year college grade-point average (FGPA) performance, for the purpose of correcting for errors introduced by the suspected racially-insensitive HSGPAs. The predictive value of the SAT score in relation to SES will also be evaluated. The overall goal is to develop a formula that more accurately predicts FGPA scores.

Review of Literature

Crouse and Trusheim in 1988 presented an argument for eliminating the SAT as a predictor of FGPA, because a number of studies had repeatedly shown that high school GPAs (HSGPAs) were the best predictor of FGPA and that the added value of using the SAT was so tiny as to be irrelevant. Another downside of using SAT scores to predict FGPA is that race and ethnicity affects its accuracy. This finding has been repeated a number of times and AA and Latino students tend to do worse than the SAT would predict; however, when HSGPA alone is used then the magnitude of overprediction increases. In other words, including SAT scores in the prediction formula minimizes overestimating FGPA performance for these racial groups.

A number of different factors have been proposed as explanations for underperforming AA and Latino students, including racial hostility on campus, less financial resources, and poor attitudes. Another explanation offered by Zwick and Himelfarb (2011) is that any error associated with the prediction formula would disproportionately impact scores closer to the tails of a normal distribution. For example, if AA and Latino students do worse on the SAT and HSGPA on average, then any error built into the prediction formula would impact them more. Alternatively, the inclusion of HSGPA scores in the prediction formula could be contributing the lion's share of overestimation for FGPA performance, since minority schools could be overestimating academic performance for their students.

Procedures

The data from 34 U.S. universities and colleges, with at least five feeder high schools, were retrieved from a number of sources, including the College Board, universities and colleges, and high schools. The College Board, the organization funding this study, matched student records to the data and then de-identified the information. The number of public high school students that were eventually included was 70,712 from 5,702 schools. Regression analysis was performed to identify the key variables that could accurately predict FGPA performance.

Findings

Three regression models were tested: (1) self-reported HSGPA only, (2) model 1 plus SAT scores, and (3) models 1 and 2 plus high school SES. The contributions to FGPA in model 3 were as follows: 0.31 for HSGPA, 0.14 for SAT (writing), 0.11 for SES, and 0.6 for SAT creative writing and math. SES as a predictor tended to overestimate and underestimate FGPA performance for students from low-SES and high-SES schools, respectively, except for AA students who were overestimated in both cases. The inclusion of SAT scores in model 2 and an SES index in model 3 rendered the prediction of FGPA performance more accurate, regardless of racial identity; however, prediction error for AA students from high-SES schools actually worsened. The authors of this study also compared the predictive value of self-reported HSGPAs obtained from SAT applications vs. transcripts and discovered that the latter rendered all three prediction models more accurate; however the overall prediction pattern was unchanged.

Summary

Combining HSGPAs, SAT scores, and an SES index produces the most accurate prediction formula for FGPA performance. If HSGPAs are obtained from official transcripts, then accuracy increased for all groups. The only exceptions are AA students from high-SES schools, who tend to underperform regardless of the prediction model used.

Conclusions

The accuracy of predicting first year academic performance at the college level can be improved substantially by combining official HSGPAs with SAT scores and an SES index.

Recommendations

Model 3 should be used by college admissions officers to select the students most likely to succeed in college. In addition, these finding may help researchers and educators become more focused on developing interventions that could minimize academic underperformance associated with poverty and racial disparities.

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