Students matter the most in learning analytics: The effects of internal and instructional conditions in predicting academic success

Volume: 172, Pages: 104251 - 104251
Published: Oct 1, 2021
Abstract
Predictive modelling of academic success and retention has been a key research theme in Learning Analytics. While the initial work on predictive modelling was focused on the development of general predictive models, portable across different learning settings, later studies demonstrated the drawbacks of not considering the specificities of course design and disciplinary context. This study builds on the methods and findings of related earlier...
Paper Details
Title
Students matter the most in learning analytics: The effects of internal and instructional conditions in predicting academic success
Published Date
Oct 1, 2021
Volume
172
Pages
104251 - 104251
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