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https://doi.org/10.1145/360630...
Article . 2023 . Peer-reviewed
License: CC BY
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Commitment Threshold – On Student Retention in MOOCs

Authors: Erkki Kaila; Antti Laaksonen; Emilia Oikarinen; Kjell Lemström;

Commitment Threshold – On Student Retention in MOOCs

Abstract

Learning and teaching at scale became especially topical and important matters due to the COVID-19 pandemic. The obvious way to that end is to use Massive Open Online Courses (MOOCs). However, the pedagogics and student behaviour between online and classroom implementations are far from similar, and successful implementation of a MOOC requires an understanding of this. Typically, the dropout rates of MOOCs are pretty high. Most of the dropouts happen in the very early stages of the course. This paper studies how and when students commit to MOOC courses. For this study, we have selected four courses with different implementations from our extensive portfolio of MOOC courses at University of Helsinki. Based on the results, the students who complete the first two parts (or weeks) of a more prolonged course are usually quite committed to completing the entire course. The behaviour varies slightly between scheduled and unscheduled courses and between courses of different topics. The inner and outer motivations also play a role in commitment. Regardless, it seems that the authors of MOOCs should pay special attention to making the first steps as engaging as possible.

Peer reviewed

Country
Finland
Related Organizations
Keywords

Computer and information sciences

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid