NASC: network analytics to uncover socio-cognitive discourse of student roles
| Autor: | Máverick André Dionísio Ferreira, Rafael Ferreira Mello, Vitomir Kovanovic, André Nascimento, Rafael Lins, Dragan Gasevic |
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| Přispěvatelé: | Ferreira, Máverick, Ferreira Mello, Rafael, Kovanovic, Vitomir, Nascimento, André, Lins, Rafael Dueire, Gasevic, Dragan, 12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022 21-25 March 2022 online |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
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| Popis: | Refereed/Peer-reviewed Roles that learners assume during online discussions are an important aspect of educational experience. The roles can be assigned to learners and/or can spontaneously emerge through student-student interaction. While existing research proposed several approaches for analytics of emerging roles, there is limited research in analytic methods that can i) automatically detect emerging roles that can be interpreted in terms of higher-order constructs of collaboration; ii) analyse the extent to which students complied to scripted roles and how emerging roles compare to scripted ones; and iii) track progression of roles in social knowledge progression over time. To address these gaps in the literature, this paper propose a network-analytic approach that combines techniques of cluster analysis and epistemic network analysis. The method was validated in an empirical study discovered emerging roles that were found meaningful in terms of social and cognitive dimensions of the well-known model of communities of inquiry. The study also revealed similarities and differences between emerging and script roles played by learners and identified different progression trajectories in social knowledge construction between emerging and scripted roles. The proposed analytic approach and the study results have implications that can inform teaching practice and development techniques for collaboration analytics. |
| Databáze: | OpenAIRE |
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