Febriantoro, W; Cukurova, M; (2023) Integrating Physiological Indicators with a Competency Model for Enhanced Collaborative Problem Solving in Small Groups. In: Proceedings of the Third International Workshop on Multimodal Immersive Learning Systems (MILeS 2023) At the Eighteenth European Conference on Technology Enhanced Learning (EC-TEL 2023). (pp. pp. 49-55). CEUR Workshop Proceedings (CEUR-WS.org): Aveiro, Portugal.

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Abstract

Improving the collaboration process has long been a subject of inquiry. Yet, evaluating collaboration quality is a significant challenge for researchers and practitioners. Recently, the generalized competency model of collaborative problem solving (CPS) has been suggested, encompassing facets, sub-facets, and indicators (verbal and nonverbal) that directly align with CPS skills. Here we discuss the integration of physiological data to potentially further improve the detection of cognitive and affective aspects of CPS. This paper aims to bridge the gap between physiological data features or characteristics and collaboration quality. More specifically, we present our attempts to integrate physiological data with verbal and nonverbal indicators of a generalized competence model of CPS in small groups comprising four individuals. Moreover, this integration can be further developed into interventions such as reflective exercises or real-time feedback provided by AI agents, with the goal of enhancing collaborative skills.

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