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Shaw, Emily – College Board, 2010
Presented at the College Board National Forum in Washington, D.C., October 2010. This presentation examines the recent national validity evidence that supports the use of SAT Writing in college admissions and English placement. Additionally it includes information on the College Board's free online Admitted Class Evaluation Service (ACES) system,…
Descriptors: Test Validity, College Entrance Examinations, Writing Achievement, Writing Tests
Shaw, Emily J. – College Board, 2011
Presented at the 23rd Annual Historically Black Colleges & Universities (HBCU) Conference in Atlanta, GA, in September 2011. Admitted Class Evaluation Service (ACES) is the College Board's free online service that predicts how admitted students will perform at a college or university generally, and how successful students will be in specific…
Descriptors: College Admission, Student Placement, Test Validity, Graphs
Patelis, Thanos – College Board, 2012
This is a keynote presentation given at AERA on developing a validity agenda for growth models in a large scale (e.g., state) setting. The emphasis of this presentation was to indicate that growth models and the validity agenda designed to provide evidence in supporting the claims to be made need to be personalized to meet the local or…
Descriptors: Test Validity, Statistical Analysis, Conferences (Gatherings), Evidence
Reshetar, Rosemary; Kaliski, Pamela; Chajewski, Michael; Lionberger, Karen – College Board, 2012
This presentation summarizes a pilot study conducted after the May 2011 administration of the AP Environmental Science Exam. The study used analytical methods based on scaled anchoring as input to a Performance Level Descriptor validation process that solicited systematic input from subject matter experts.
Descriptors: Advanced Placement Programs, Science Tests, Achievement Tests, Classification
Godfrey, Kelly E.; Matos-Elefonte, Haifa – College Board, 2010
[Slides] presented at AERA in Denver, CO in April 2010. In today's education climate, an enormous amount of pressure has been placed on states, school districts, and programs to produce graduates who are prepared to successfully enter, persist through, and graduate from the nation's universities and colleges. However, much of this research has…
Descriptors: Educational Indicators, College Students, Predictor Variables, Academic Achievement
Kobrin, Jennifer L.; Patterson, Brian F. – College Board, 2010
There is substantial variability in the degree to which the SAT and high school grade point average (HSGPA) predict first-year college performance at different institutions. This paper demonstrates the usefulness of multilevel modeling as a tool to uncover institutional characteristics that are associated with this variability. In a model that…
Descriptors: Scores, Validity, Prediction, College Freshmen
Shaw, Emily J.; Mattern, Krista D. – College Board, 2010
[Slides] presented at AERA in Denver, CO in April 2010. This study examined the relationship between students' self-reported high school grade point average (HSGPA) from the SAT Questionnaire and their HSGPA provided by the colleges and universities they attend. The purpose of this research was to offer updated information on the relatedness of…
Descriptors: Accuracy, Grade Point Average, High School Students, Correlation
Kim, YoungKoung Rachel – College Board, 2009
Presented at the national conference for AERA (American Educational Research Association) in April 2009. The large variability of SAT taker population across states makes state-by-state comparisons of the SAT scores challenging. Using a mixture modeling approach, therefore, the current study presents a method of identifying subpopulations in terms…
Descriptors: Conference Papers, Scores, Comparative Analysis, College Entrance Examinations
Finkelstein, Doreen – College Board, 2009
Presented at the Annual Meeting of the American Educational Research Association (AERA) in April 2009. Compares results of different approaches to propensity-score matching with hierarchical data.
Descriptors: Comparative Analysis, Statistical Analysis, Computation, Probability