Predictive Validity Of Multiple Measures As A Placement Method For Developmental Mathematics Courses At Chesapeake College

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Author/Creator ORCID

Date

2010

Department

Mathematics and Science Education Program

Program

Doctor of Education

Citation of Original Publication

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This item is made available by Morgan State University for personal, educational, and research purposes in accordance with Title 17 of the U.S. Copyright Law. Other uses may require permission from the copyright owner.

Abstract

This study develops a multiple measure placement method (MMPM) that is comprised of predictor variables such as ACCUPLACER math (ACCM), ACCUPLACER reading (ACCR), arithmetic diagnostic test (ADT), high school grade point average (HSGPA), high school mathematics performance (HSMP), and duration since last mathematics course taken in high school (DLMC) selected on the basis of research reported in the body of literature. Data is collected from 79 participants of MAT 031(elementary algebra) and 43 participants of MAT 023 (arithmetic) courses. Multiple regression analysis showed that MMPM is a significant predictor of success in the comprehensive final examination for both MAT 031 and MAT 023. Among the six predictor variables, stepwise/forward regression analysis selected HSMP and ACCM as the best predictor variables for the comprehensive final examination of MAT 031 while ACCR and HSMP were the best predictor variables for the comprehensive final examination of MAT 023. The possible reasons for the selection of only two independent variables for the best predictor model are discussed along with recommendations for practice and future research.