Predicting the Success of Black, Chicano, Oriental and White College Students

Goldman, Roy D.; Hewitt, Barbara Newlin

doi:10.1111/j.1745-3984.1976.tb00002.x

Cited by 66 publications

(16 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, a few researchers were interested in differential prediction (Abelson, 1952; Brown & Scott, 1967; Gulliksen & Wilks, 1950; Humphreys, 1952) and differential validity (Saunders, 1956; Stanley & Porter, 1967) prior to Cleary's classic study. After Cleary, the study of differential prediction grew in the late 1960s and 1970s (Bartlett & O’Leary, 1969; Bowers, 1970; Goldman & Hewitt, 1975, 1976; Goldman & Richards, 1974; Kallingal, 1971; Lefkowitz, 1972; Pfeifer & Sedlacek, 1971; Temp, 1971; Thomas & Stanley, 1969) and continues to receive serious attention (Norris, Oppler, Kuang, Day, & Adams, 2006; Sireci & Talento‐Miller, 2006; Young, 1990, 1991a, 1991b, 1994; Zwick, 2002; Zwick & Schlemer, 2004).…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing Differential Prediction of College Grades by Race/Ethnicity with a Multilevel Model

Culpepper

Davenport

2009

J Educational Measurement

View full text Add to dashboard Cite

Previous research notes the importance of understanding racial/ethnic differential prediction of college grades across multiple institutions. Institutional variation in selection indices is especially important given some states’ laws governing public institutions’ admissions decisions. This paper employed multilevel moderated multiple regression to study the variation of selection indices across 30 institutions and the accuracy of selection indices in predicting college grades for students of different racial/ethnic backgrounds. Several benefits of multilevel models for cross‐institutional differential prediction studies were described and include: controlling for institutional differences in range restriction, providing reliability estimates of least squares estimates, and adjusting criterion scores for differences in coursework difficulty. The findings from this study provide evidence of institutional variation in selection indices, which challenges current laws aimed at standardizing them. Specifically, there was evidence that the predictor slope coefficients varied across institutions, in addition to the estimates that measured intercept differences for African and Asian American students. Across universities, the results mirrored previous findings: high school grade point average (GPA) differentially predicted grades for African Americans, SAT verbal scores differentially predict grades for Asian Americans, and SAT math scores were better predictors of Asian Americans’ grades.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Assessing Differential Prediction of College Grades by Race/Ethnicity with a Multilevel Model

Culpepper

Davenport

2009

J Educational Measurement

View full text Add to dashboard Cite

show abstract

“…Wilson ( (Breland, 1977Wilson, 1978. Very few studies have compared more than two ethnic groups (Goldman & Hewitt, 1976;Scott, 1976). Some of the studies listed in Table 1 have made no comparisons, but they are important because they represent a sampling of blacks or Chicanos that is important for purposes of population validation (Borgen, 1972;Dalton, 1974;Funches, 1967;Hills, 1964;Hills & Stanley;McKelpin, 1965;Munday, 1965).…”

Section: "mentioning

confidence: 99%

Population Validity and College Entrance Measures

Breland

1978

ETS Research Bulletin Series

View full text Add to dashboard Cite

This report reviews and summarizes the data of published reports and papers pertaining to the validity of measures commonly used at college entrance. These measures consist of various types of quantitative indices used to describe the high school record and various types of academic tests. The data were categorized by sex and ethnic classifications where possible and comparisons were made. Most of the observations made in previous reviews of this kind were upheld. Both the high school record and standardized academic tests appear to be generally useful at college entrance. Both tend to predict college performance, but they are most appropriately used in combination. For Anglo populations, the high school record usually yields slightly higher predictive correlations. For black populations (except black females), however, the data suggest no superiority of the high school record as a predictor of college performance. The amount of data available for Chicano samples was not sufficient for any generalizations about predictive correlations, but the magnitude of those correlations available were on the average lower than those for Anglo populations. For recent years, correlations for black samples tended to be slightly lower than those for Anglo samples. A primary objective in the review was to consider whether inferences made from the high school record and test scores about different populations tended to be correct inferences. Where inferences tended to be systematically incorrect, there was an interest in the direction of the error. Since the high school record and test scores are used in making inferences about probable college performance, the systematic inferential errors of interest consisted of the degree to which college performance of populations were over or underpredicted when the data used in making the inference were not limited to data for that population. Data from a number of studies show that the college performance of black populations, male and female, have been consistently overpredicted by the traditional academic predictors (the high school record and standardized test scores) when predictions are based on data from white or predominantly white samples. The high school record would appear, from the studies reviewed, to be the principal source of this overprediction. Standardized test scores also have tended to overpredict college performance of black populations, but a combination of the high school record and test scores appears to minimize over prediction. In contrast, published data show women to be consistently under predicted by the traditional predictors when predictions are based on data from male or predominantly male samples. This review indicates a number of topics where further research appears to be needed. These topics include the study of: long‐range criteria, objective criteria, prediction within major‐field, the high school record for different populations, college grades for different populations, neglected populations, factorial consistency of measures across populatio...

show abstract

“…However, using dummy variables to categorize college majors improved the prediction of college grades in studies by Goldman and Hewitt (1976) and Pennock-Roman (1990). In these studies, the effects of ethnicity or gender in prediction were reduced but not completely eliminated.…”

Section: Introductionmentioning

confidence: 99%

College Major and Gender Differences in the Prediction of College Grades

Pennock-Román¹

1994

ETS Research Report Series

View full text Add to dashboard Cite

Recent studies have found substantial reductions in gender differences in the prediction of academic achievement in college when variations in grading standards among courses were taken into account. The purpose of this project was to examine gender differences in the prediction of freshman grades after controlling for differential course grading based on college majors. This method involved deriving a variable that measured grading leniency using residual scores from the within‐gender regressions of freshman grades on high school grades and scores on the SAT for the non‐Latino white group. The procedure worked quite well and generalized to other groups not involved in the derivation of the grading‐leniency scale. Nevertheless, there were modest, sometimes statistically significant, gender differences in prediction that remained after this control variable was introduced into the regressions. The largest and smallest differences for females between actual grades and grades predicted from the males' regressions tended to be found in the African American and Asian American groups, respectively. The results imply that the use of information on college majors is a reasonable, practical procedure for controlling for grading leniency.

show abstract

Predicting the Success of Black, Chicano, Oriental and White College Students

Cited by 66 publications

References 13 publications

Assessing Differential Prediction of College Grades by Race/Ethnicity with a Multilevel Model

Assessing Differential Prediction of College Grades by Race/Ethnicity with a Multilevel Model

Population Validity and College Entrance Measures

College Major and Gender Differences in the Prediction of College Grades

Contact Info

Product

Resources

About