Are Highly Motivated Learners More Likely to Complete a Computer Programming MOOC?

The International Review of Research in Open and Distributed Learning

View Publication Info
 
 
Field Value
 
Title Are Highly Motivated Learners More Likely to Complete a Computer Programming MOOC?
 
Creator Luik, Piret
Lepp, Marina
 
Subject MOOC
motivation
programming
clusters
completion
 
Description Computer programming MOOCs attract people who have different motivations. Previous studies have hypothesized that the motivation declared before starting the course can be an important predictor of distinctive dropout rates. The aim of this study was to outline the main motivation clusters of participants in a computer programming MOOC, and to compare how these clusters differed in terms of intention to complete and actual completion rate. The sample consisted of 1,181 respondents to the pre-course questionnaire in the Introduction to Programming MOOC. A validated motivation scale, based on expectancy-value theory and k-means cluster analysis, was used to form the groups. The four identified clusters were named as Opportunity motivated (27.7%), Over-motivated (28.6%), Success motivated (19.6%) and Interest motivated (24.0%). Comparison tests and chi-square test were used to describe the differences among the clusters. There were statistically significant differences among clusters in self-evaluated probability of completion. Also, significant differences emerged among three clusters in terms of percentages of respondents who completed the MOOC. Interestingly, the completion rate was the lowest in the Over-motivated cluster. A statistically significant higher ratio of completers to non-completers was found in the Opportunity motivated, Success motivated, and Interest motivated clusters. Our findings can be useful for MOOC instructors, as a better vision of participants’ motivational profiles at the beginning of the MOOC might help to inform the MOOC design to better support different needs, potentially resulting in lower dropout rates.
 
Publisher Athabasca University Press
 
Date 2021-03-11
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed, double-blind
 
Format text/html
application/epub+zip
application/pdf
 
Identifier http://www.irrodl.org/index.php/irrodl/article/view/4978
10.19173/irrodl.v22i1.4978
 
Source The International Review of Research in Open and Distributed Learning; Vol. 22 No. 1 (2021); 41-58
1492-3831
 
Language eng
 
Relation http://www.irrodl.org/index.php/irrodl/article/view/4978/5454
http://www.irrodl.org/index.php/irrodl/article/view/4978/5467
http://www.irrodl.org/index.php/irrodl/article/view/4978/5468
 
Rights http://creativecommons.org/licenses/by/4.0
 

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