Predicting learning success in online learning environments: Self-regulated learning, prior knowledge and repetition

Karl Ledermüller, Irmgard Fallmann

Publication: Scientific journalJournal articlepeer-review

Abstract

The emergence of new trends sometimes carries the risk that established, well-proven concepts rooted in other disciplines are not properly integrated into new approaches. As Learning Analytics seems to be evolving into a highly multidisciplinary field, we would like to demonstrate the importance of embedding classic theories and concepts into a Learning Analytics, system-data-driven setting. Our results confirm that classical factors that are operationalized with the help of system-generated data outperform more recent survey-based models. Therefore, we want to stress the point that system-generated data should not be left behind in the quickly evolving field of Learning Analytics.
Original languageEnglish
Pages (from-to)79 - 99
JournalZeitschrift für Hochschulentwicklung
Volume12
Issue number1
DOIs
Publication statusPublished - 2017

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 503008 E-learning

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