Work

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

Year: 2017

Type: article

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. 29.03.2017 | Karl Ledermüller & Irmgard Fallmann

Source: Zeitschrift für Hochschulentwicklung

DOI: 10.3217/zfhe-12-01/05

Authors: Ledermüller, Fallmann

Institution: Vienna University of Economics and Business

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W2605464513

FWCI: 2.294

Cites:

Cited by: 14

Related to: 10