Designing a Transferable Predictive Model for Online Learning Using a Bayesian Updating Approach

Volume: 14, Issue: 4, Pages: 474 - 485
Published: Aug 1, 2021
Abstract
Predictive modeling in online education is a popular topic in learning analytics research and practice. This study proposes a novel predictive modeling method to improve model transferability over time within the same course and across different courses. The research gaps addressed are limited evidence showing whether a predictive model built on historical data retrospectively can be directly applied to a future offering of the same course or to...
Paper Details
Title
Designing a Transferable Predictive Model for Online Learning Using a Bayesian Updating Approach
Published Date
Aug 1, 2021
Volume
14
Issue
4
Pages
474 - 485
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