VSS Report - Executive Assessment Predictive Validity for Full-Time MBA

Oct 15, 2026

VSS Report analyzes whether Executive Assessment (EA) Total and section scores, derived from GMAT 10th edition (Gen 10), and UGPA predict graduate academic performance in three full-time U.S. programs (two MBA and one Master of Management). EA Total shows the strongest predictive value among admission criteria, and combining EA with UGPA improves predictive validity versus UGPA alone. The study reconstructs EA scores from Gen 10 item-level data to enable full-time inference, while noting caution due to test-design and behavioral differences.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages13

Reading Time33 min

AccessFree to download

Overview

Study purpose and predictive-validity approach

EA test structure and score computation

Verbal, Quantitative, and Integrated Reasoning

EA Total vs Gen 10 Total

Evidence base

VSS predictive validity and EMBA use

Need for full-time MBA evidence

Study design for full-time programs

Programs A, B, and C and sample sizes

Score reconstruction and correlation analysis

Results

Correlations with GGPA

VSS Report The Graduate Management Admission Council (GMAC) examined how well individual Executive Assessment (EA) scores and UGPA predict academic performance (i.e., graduate GPA) in two full-time MBA programs and one full-time Master of Management program, using EA scores derived from the GMAT 10th edition (Gen 10) . The findings are shown below. • The EA Total score, comprising the three section scores, had the highest predictive value among section scores and UGPA, suggesting that it is a better predictor of academic success in graduate business education programs than any individual section score or UGPA. • Combining UGPA with EA scores resulted in significantly higher predictive validity than using UGPA alone, suggesting that including EA scores can improve the accuracy of admission decisions. A decade ago, GMAC launched Executive Assessment (EA) to measure the most critical and relevant skills in executive MBA (EMBA) programs and other business programs for working professionals and people with extensive work experience. It aims to minimize the burden on test-takers by offering a shorter, more flexible, and controlled test-taking experience. EA was newly formulated using the existing test items from the GMAT 10th edition (Gen 10), along with newly defined test constructs and skill dimensions. The test has three sections: Verbal Reasoning (VR), Quantitative Reasoning (QR), and Integrated Reasoning (IR) . The EA VR items include all item types from the VR section of the Gen 10. The items in the EA QR section are derived from the Gen 10 QR section, except for the geometry items. The EA Integrative Reasoning (IR) section includes all item types from the previous Gen 10 IR section. It should be noted that, unlike the Gen 10 Total score, which was composed of the QR and VR sections, the EA Total score is computed from all three sections. Over the years, we have collected evidence of the predictive validity of EA scores from many EMBA programs through GMAC's free predictive validity study service (VSS) . The predictive validity study examines the relationship between various admission criteria (e.g., EA Total and section scores) and mid-program performance, as measured by the graduate grade point average (GGPA) . The results of the study are very useful for identifying the predictive validity of individual admission criteria and their relative importance in evaluating applicants. In recent years, many full-time MBA programs have begun using EA scores in their admissions decisions. Given the lack of formal EA validity studies for full-time MBA programs, there is a need for scientific evidence of predictive validity to support the use of EA scores in these programs, as their curricula may differ from those of EMBA programs. Obtaining evidence in those programs is challenging. By far, there are no full-time MBA programs with enough enrolled students who submitted EA scores. To address this, the psychometric team at GMAC devised an innovative way to “triangulate” the predictive validity evidence using previous admission data that included Gen 10 scores as part of the evaluation criteria. For the triangulated predictive validity evaluation, the question/item response data from Gen 10 were dismantled to the item level and reconstructed under the EA test specification, yielding estimated EA section and Total scores, which were subsequently analyzed for correlation with GGPA. Although the overall reconstruction of the EA scores was successful, the estimated EA scores were not expected to fully capture their predictive validity due to the limited availability of individual-level test data (which could reduce data variance/information) . Also, the EA data did not account for differences in individuals’ test-taking behavior that may later be observed in the real EA. For example, EA is a multi-stage adaptive testing approach that allows candidates to answer questions in any order and to review and change any answers within a m

FAQs

What admission criteria does the VSS Report evaluate for predicting graduate performance?

The report evaluates EA Total scores, EA section scores, and undergraduate GPA (UGPA) for predicting graduate grade point average (GGPA).

How does combining EA scores with UGPA affect predictive validity?

Combining UGPA with EA scores yields significantly higher predictive validity than using UGPA alone, indicating improved accuracy of admission decisions.

Why were EA scores reconstructed for full-time MBA programs?

The report notes a lack of formal full-time MBA validity studies with enough candidates who submitted EA scores, so a triangulated approach reconstructs estimated EA scores from Gen 10 item-level data.

Oct 15, 2026

Uploaded by Aria Callaghan