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Rios, Joseph A.; Ihlenfeldt, Samuel D.; Dosedel, Michael; Riegelman, Amy – Educational Measurement: Issues and Practice, 2020
This systematic review investigated the topics studied and reporting practices of published meta-analyses in educational measurement. Our findings indicated that meta-analysis is not a highly utilized methodological tool in educational measurement; on average, less than one meta-analysis has been published per year over the past 30 years (28…
Descriptors: Meta Analysis, Educational Assessment, Test Format, Testing Accommodations
Katherine E. Castellano; Daniel F. McCaffrey; Joseph A. Martineau – Educational Measurement: Issues and Practice, 2025
Growth-to-standard models evaluate student growth against the growth needed to reach a future standard or target of interest, such as proficiency. A common growth-to-standard model involves comparing the popular Student Growth Percentile (SGP) to Adequate Growth Percentiles (AGPs). AGPs follow from an involved process based on fitting a series of…
Descriptors: Student Evaluation, Growth Models, Student Educational Objectives, Educational Indicators
Steedle, Jeffrey T.; Hong, Maxwell; Cheng, Ying – Educational Measurement: Issues and Practice, 2019
Self-report inventories are commonly administered to measure social-emotional learning competencies related to college and career readiness. Inattentive responding can negatively impact the validity of interpreting individual results and the accuracy of construct validity evidence. This study applied nine methods of detecting insufficient effort…
Descriptors: Construct Validity, Social Development, Emotional Development, College Readiness
Kostal, Jack W.; Sackett, Paul R.; Kuncel, Nathan R.; Walmsley, Philip T.; Stemig, Melissa S. – Educational Measurement: Issues and Practice, 2017
Previous research has established that SAT scores and high school grade point average (HSGPA) differ in their predictive power and in the size of mean differences across racial/ethnic groups. However, the SAT is scaled nationally across all test takers while HSGPA is scaled locally within a school. In this study, the researchers propose that this…
Descriptors: College Entrance Examinations, Scaling, Grade Point Average, Differences
Zhang, Charlene; Kuncel, Nathan R. – Educational Measurement: Issues and Practice, 2020
Measures of biographical data, or biodata, provide indicators of one's life history and past experiences. Biodata information is often available in various forms during processes of academic admissions to higher education. Such information can be used, in combination with other factors, to predict students' future academic and extra-curricular…
Descriptors: Meta Analysis, Biographical Inventories, Scores, Predictor Variables
Mattern, Krista; Sanchez, Edgar; Ndum, Edwin – Educational Measurement: Issues and Practice, 2017
In the context of college admissions, the current study examined whether differential prediction of first-year grade point average (FYGPA) by gender could be explained by an omitted variable problem--namely, academic discipline, or the amount of effort a student puts into schoolwork and the degree to which a student sees him/herself as hardworking…
Descriptors: Females, Academic Achievement, Predictive Validity, Grade Point Average
Higdem, Jana L.; Kostal, Jack W.; Kuncel, Nathan R.; Sackett, Paul R.; Shen, Winny; Beatty, Adam S.; Kiger, Thomas B. – Educational Measurement: Issues and Practice, 2016
Recent research has shown that admissions tests retain the vast majority of their predictive power after controlling for socioeconomic status (SES), and that SES provides only a slight increment over SAT and high school grades (high school grade point average [HSGPA]) in predicting academic performance. To address the possibility that these…
Descriptors: Socioeconomic Status, Gender Differences, Racial Differences, Grade Point Average

Gardner, Eric F. – Educational Measurement: Issues and Practice, 1983
In response to Ebel (TM 508 146) Gardner argues that neither intrinsic rational validity associated with ability tests nor a validity coefficient relating a test to performance as the sole information about validity is sufficient. All relevant data about a test and its functioning are essential in describing the validity of the test. (Author/LC)
Descriptors: Occupational Tests, Performance Tests, Predictive Validity, Standardized Tests