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ERIC Number: ED462116
Record Type: RIE
Publication Date: 2001-May
Pages: 22
Abstractor: N/A
Reference Count: N/A
ISBN: N/A
ISSN: N/A
Predicting Student Outcomes Using Discriminant Function Analysis.
Martinez, Daniel
This document discusses how community colleges often under-utilize collected student data. For example, community colleges use student pre-college assessment data to place students in specific courses. The paper suggests that student data can also be used to predict academic success (a grade of A, B, or C) in community college courses. Some of the limitations of using multiple regression for decisions on student placement are also discussed. The use of discriminant function analysis is presented as an alternative method to help make more informed decisions on placement as well as predict possible student success in specific courses. A detailed explanation of how discriminant function analysis can be designed and used by community college researchers is provided. The report also includes a literature review of relevant research on the topics of research designs and student academic success. (Contains 23 references and 6 sample tables that display how discriminant function analysis results may be presented and interpreted.) (MKF)
Publication Type: Reports - Research; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Note: Paper presented at the Annual Meeting of the Research and Planning Group (39th, Lake Arrowhead, CA, May 2-4, 2001).