Predictive analytics for learning and usage of the plant sciences E-library

This study examines learning and usage of the Plant Sciences E-Library (PASSEL, passel.unl.edu), a large international, open-source multidisciplinary learning object repository (7793 users from 14 countries). The analyses employ predictive analytics to isolate usage variables which predict learning from the instructional material. Specifically, the study focuses on student engagement as measured by total time online and time spent with different content modality material. This paper describes the analytic process, reports data on usage of learning object modules and module elements, identifies significant predictors of learning, and discusses future research directions.

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