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ERIC Number: EJ1153997
Record Type: Journal
Publication Date: 2017-Oct
Pages: 17
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-2211-1662
Predicting Student Success: A Naïve Bayesian Application to Community College Data
Ornelas, Fermin; Ordonez, Carlos
Technology, Knowledge and Learning, v22 n3 p299-315 Oct 2017
This research focuses on developing and implementing a continuous Naïve Bayesian classifier for GEAR courses at Rio Salado Community College. Previous implementation efforts of a discrete version did not predict as well, 70%, and had deployment issues. This predictive model has higher prediction, over 90%, accuracy for both at-risk and successful students while easing interpretation and implementation. Predictive results across eleven courses and cumulative gain charts show potential improvements to be made in students' academic success by focusing on high level risk students. Researchers at other colleges might find this empirical application relevant for implementation of early alert systems.
Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Publication Type: Journal Articles; Reports - Research
Education Level: Two Year Colleges
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Arizona