Combining the Knowledge Appropriation Model and epistemic networks to understand co-creation and adoption of learning designs using log data
DOI:
https://doi.org/10.21556/edutec.2020.74.1789Keywords:
learning design, co-creation, adoption, Knowledge Appropriation Model, log data, Epistemic Network AnalysisAbstract
Social practices are well-known mediators in the adoption of educational innovations during professional learning, as postulated by the Knowledge Appropriation Model (KAM). However, understanding how teachers adopt new pedagogical approaches at scale is often difficult due to the lack of evidence available about their daily practices. In that sense, log data from online authoring and learning tools offer the possibility of better understanding the creation process of a learning design that reifies an educational innovation.
This paper explores how statistical models and Epistemic Network Analysis (ENA) can help us understand large-scale patterns in the co-creation and adoption of educational innovations, using KAM as a theoretical framework to analyse log data. More concretely, this paper presents a case study on Go-Lab, an initiative to promote inquiry-based learning at school. Its authoring and learning tool -Graasp- gives us a unique opportunity to track, not only the (co)creation of learning designs, but also their potential implementation in the classroom. The case study uses the aforementioned methodological approach to analyse the role of large-scale support initiatives in the co-creation and adoption of learning designs.
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