Predictive Analytics Machinery for STEM Student Success Studies
Statistical predictive models play an important role in learning analytics. In this work, we seek to harness the power of predictive modeling methodology for the development of an analytics framework in STEM student success efficacy studies. We develop novel predictive analytics tools to provide sta...
Main Authors: | Lingjun He, Richard A. Levine, Andrew J. Bohonak, Juanjuan Fan, Jeanne Stronach |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2018-04-01
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Series: | Applied Artificial Intelligence |
Online Access: | http://dx.doi.org/10.1080/08839514.2018.1483121 |
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