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An analysis framework for collaborative problem solving in practice-based learning activities: a mixed-method approach
Auteurs
Mutlu Cukurova
Katerina Avramides
Daniel Spikol
Rose Luckin
Manolis Mavrikis
Institutions
University College London
Malmö University
Année :
2016
Lieu de publication de l'article :
Proc. LAK
Résumé de l'article
Systematic investigation of the collaborative problem solving process in open-ended, hands-on, physical computing design tasks requires a framework that highlights the main process features, stages and actions that then can be used to provide 'meaningful' learning analytics data. This paper presents an analysis framework that can be used to identify crucial aspects of the collaborative problem solving process in practice-based learning activities. We deployed a mixed-methods approach that allowed us to generate an analysis framework that is theoretically robust, and generalizable. Additionally, the framework is grounded in data and hence applicable to real-life learning contexts. This paper presents how our framework was developed and how it can be used to analyse data. We argue for the value of effective analysis frameworks in the generation and presentation of learning analytics for practice-based learning activities.
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Diagnostic
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primary
secondary
higher education
open
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description
diagnostic
prediction
prescription
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environment
distance
face-to-face
hybrid
MOOC
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target
learners
teachers
institutions
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