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ERIC Number: EJ1037514
Record Type: Journal
Publication Date: 2014-Jul
Pages: 16
Abstractor: As Provided
Reference Count: 79
ISSN: ISSN-2211-1662
Educational Data Mining and Learning Analytics: Applications to Constructionist Research
Berland, Matthew; Baker, Ryan S.; Blikstein, Paulo
Technology, Knowledge and Learning, v19 n1-2 p205-220 Jul 2014
Constructionism can be a powerful framework for teaching complex content to novices. At the core of constructionism is the suggestion that by enabling learners to build creative artifacts that require complex content to function, those learners will have opportunities to learn this content in contextualized, personally meaningful ways. In this paper, we investigate the relevance of a set of approaches broadly called "educational data mining" or "learning analytics" (henceforth, EDM) to help provide a basis for quantitative research on constructionist learning which does not abandon the richness seen as essential by many researchers in that paradigm. We suggest that EDM may have the potential to support research that is meaningful and useful both to researchers working actively in the constructionist tradition but also to wider communities. Finally, we explore potential collaborations between researchers in the EDM and constructionist traditions; such collaborations have the potential to enhance the ability of constructionist researchers to make rich inferences about learning and learners, while providing EDM researchers with many interesting new research questions and challenges.
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A