Retrieval Practice and Study Planning in MOOCs: Exploring Classroom-Based Self-regulated Learning Strategies at Scale

D.J. Davis, Guanliang Chen, Tim van der Zee, Claudia Hauff, Geert Jan Houben

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

42 Citations (Scopus)

Abstract

Massive Open Online Courses (MOOCs) are successful in delivering educational resources to themasses, however, the current retention rates—well below 10%—indicate that they fall short in helping their audience become effective MOOC learners. In this paper, we report two MOOC studies we conducted in order to test the effectiveness of pedagogical strategies found to be beneficial in the traditional classroom setting: retrieval practice (i.e. strengthening course knowledge through actively recalling information) and study planning (elaborating on weekly study plans). In contrast to the classroom-based results, we do not confirm our hypothesis, that small changes to the standard MOOC design can teach MOOC learners valuable self-regulated learning strategies.

Original languageEnglish
Title of host publicationAdaptive and Adaptable Learning
Subtitle of host publication11th European Conference on Technology Enhanced Learning, EC-TEL 2016
EditorsKatrien Verbert, Mike Sharples, Tomaž Klobučar
Place of PublicationCham
PublisherSpringer
Pages57-71
Number of pages15
ISBN (Electronic)978-3-319-45153-4
ISBN (Print)978-3-319-45152-7
DOIs
Publication statusPublished - 2016
Event11th European Conference on Technology-Enhanced Learning, EC-TEL 2016 - Lyon, France
Duration: 13 Sept 201616 Sept 2016

Publication series

NameLecture Notes in Computer Science
Volume9891
ISSN (Print)0302-9743

Conference

Conference11th European Conference on Technology-Enhanced Learning, EC-TEL 2016
Country/TerritoryFrance
CityLyon
Period13/09/1616/09/16

Keywords

  • MOOC
  • Self-regulated learning

Fingerprint

Dive into the research topics of 'Retrieval Practice and Study Planning in MOOCs: Exploring Classroom-Based Self-regulated Learning Strategies at Scale'. Together they form a unique fingerprint.

Cite this