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

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.

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:6138
Date29 March 2017
CreatorsLedermüller, Karl, Fallmann, Irmgard
PublisherZFHE
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypeArticle, PeerReviewed
Formatapplication/pdf
RightsCreative Commons: Attribution-Noncommercial-No Derivative Works 3.0 Austria
Relationhttp://dx.doi.org/10.3217/zfhe-12-01/05, https://www.zfhe.at/index.php/zfhe/index, http://epub.wu.ac.at/6138/

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