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Analysing self-regulated learning strategies of MOOC learners through self-reported data
Author(s) -
M. Elena Alonso-Mencía,
Carlos AlarioHoyos,
Iria Estévez Ayres,
Carlos Delgado Kloos
Publication year - 2021
Publication title -
australasian journal of educational technology
Language(s) - English
Resource type - Journals
eISSN - 1449-5554
pISSN - 1449-3098
DOI - 10.14742/ajet.6150
Subject(s) - self regulated learning , adaptation (eye) , massive open online course , mathematics education , computer science , online learning , psychology , educational technology , multimedia , neuroscience
Massive open online courses (MOOCs) require registered learners to be autonomous in their learning. Nevertheless, prior research studies showed that many learners lack the necessary self-regulated learning (SRL) skills to succeed in MOOCs. This research study aimed to gain insights into the relationships that exist between SRL and background information from MOOC learners. To this end, a series of three MOOCs on computer programming offered through edX were used to collect self-reported data from learners using an adaptation of the Motivated Strategies for Learning Questionnaire. Results show significant differences in general learning strategies and motivation by continent, prior computing experience and percentage of completed MOOCs. Men reported higher motivation than women, whereas pre-university learners needed further guidance to improve their learning strategies.

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