Ledermüller, Karl, Fallmann, Irmgard. 2017. Predicting learning success in online learning environments: Self-regulated learning, prior knowledge and repetition . Zeitschrift für Hochschulentwicklung 12 (1), 79-99.

RIS

@ARTICLE{Ledermüller2017,
title = {Predicting learning success in online learning environments: Self-regulated learning, prior knowledge and repetition },
author = {Karl Ledermüller and Irmgard Fallmann},
year = {2017},
doi = {http://dx.doi.org/10.3217/zfhe-12-01/05},
url = {https://www.zfhe.at/index.php/zfhe/article/view/999},
volume = {12},
number = {1},
language = {EN},
pages = {79-99},
journal = {Zeitschrift für Hochschulentwicklung},
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.},
}