Encouraging Metacognition & Self-Regulation in MOOCs through Increased Learner Feedback

Conference paper (2016)

Authors

D.J. Davis Web Information Systems - EEMCS
G. Chen Web Information Systems - EEMCS
I. Jivet Electrical Engineering, Mathematics and Computer Science
C. Hauff Web Information Systems - EEMCS
G.J.P.M. Houben Web Information Systems - EEMCS
Research Group
Web Information Systems (EEMCS) (TU Delft)
Self-Regulated Learning Learning Analytics Learner Feedback Study Planning
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Published Date

01-04-2016

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Web Information Systems

Abstract

Learning analytics for learners has the ability to greatly improve learners' self-regulation. Current learner dashboards are mostly providing learners with an isolated view of their learning behavior, while we believe learners will gain more
from a comparison of their own behavior with that of successful peer learners. In this work-in-progress demonstration we describe our design of a Learning Tracker widget that provides MOOC learners with timely and goal-oriented (i.e. towards passing the course) feedback in a manner that encourages reflection and self-regulation. We also present some preliminary ndings which show how exposure to feedback can signicantly increase student success and engagement.