Multiple Measures Assessment: Improving Community College Student Placement in California

This paper discusses the result of a statewide research effort in California to improve the accuracy of student placement in math and English in the California Community College system. We apply decision tree methods to high school and college transcript data to identify key measures of high school...

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Published inAERA Online Paper Repository
Main Authors Bahr, Peter Riley, Fagioli, Loris, Hayward, Craig, Hetts, John, Lamoree, Daniel, Newell, Mallory Angeli, Nguyen, Alyssa, Sorey, Ken, Willett, Terrence
Format Report
LanguageEnglish
Published AERA Online Paper Repository 29.04.2017
Subjects
Academic Achievement
College English
College Mathematics
Community Colleges
Developmental Studies Programs
High Schools
Predictor Variables
Prior Learning
Student Evaluation
Student Placement
Two Year College Students
California
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Summary:This paper discusses the result of a statewide research effort in California to improve the accuracy of student placement in math and English in the California Community College system. We apply decision tree methods to high school and college transcript data to identify key measures of high school achievement that predict success in ten levels of community college math courses (four developmental and six college level) and five levels of community college English courses (four developmental and one college level). We use our results to develop placement rule sets that allow community colleges to directly apply our results to their placement processes.