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A Framework for Predicting Mentoring Needs in Digital Learning Environments

Cathleen Stuetzer; Ralf Klamma; Milos Kravcik
In: Bella Struminskaya; Florian Keusch; Otto Hellwig; Stefan Oglesby; Cathleen M. Stützer; Alexandra Wachenfeld-Schell (Hrsg.). 22th General Online Research Conference (GOR). General Online Research Conference (GOR-2020), September 10-11, online, ISBN 978-3-9815106-9-0, Deutsche Gesellschaft für Online-Forschung (DGOF) e.V. 9/2020.


Modeling online behavior is a common tool for studying social “ecolo- gies” in digital environments. For this purpose, most of the existing models are used for analysis and prediction.More prediction tools are needed for providing evidence especially for exploring online social behavior to depict the right target group within the right contexts. As a prominent use case In higher education research, the quality of le- arning processes shall be ensured by providing suitable instruments like mentoring for the pedagogical and social support of students. But how can we identify mentoring needs in digital learning environ- ments? And to what extent can predictive models contribute to the quality assurance of learners’ progress?


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