An analysis framework for collaborative problem solving in practice-based learning activities: A mixed-method approach
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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.
Originalsprog | Engelsk |
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Titel | LAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact : Convergence of Communities for Grounding, Implementation, and Validation |
Antal sider | 5 |
Forlag | ACM Association for Computing Machinery |
Publikationsdato | 25 apr. 2016 |
Sider | 84-88 |
ISBN (Elektronisk) | 9781450341905 |
DOI | |
Status | Udgivet - 25 apr. 2016 |
Eksternt udgivet | Ja |
Begivenhed | 6th International Conference on Learning Analytics and Knowledge, LAK 2016 - Edinburgh, Storbritannien Varighed: 25 apr. 2016 → 29 apr. 2016 |
Konference
Konference | 6th International Conference on Learning Analytics and Knowledge, LAK 2016 |
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Land | Storbritannien |
By | Edinburgh |
Periode | 25/04/2016 → 29/04/2016 |
Navn | ACM International Conference Proceeding Series |
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Vol/bind | 25-29-April-2016 |
ID: 256267202