Article ID Journal Published Year Pages File Type
4936774 Computers & Education 2018 17 Pages PDF
Abstract

•A framework to interpret collaborative problem-solving from nonverbal indexes of physical interactivity is proposed.•Synchrony, equality, individual accountability, and intra-individual variability are key parameters of CPS.•High competence CPS groups show high levels of physical interactivity and low levels of intra-individual variability.•Both of these parameters present smaller variability in high competence CPS groups.•High competence CPS groups present high levels of synchrony in their behaviours.

Collaborative problem-solving (CPS) is a fundamental skill for success in modern societies, and part of many common constructivist teaching approaches. However, its effective implementation and evaluation in both digital and physical learning environments are challenging for educators. This paper presents an original method for identifying differences in students' CPS behaviours when they are taking part in face-to-face practice-based learning (PBL). The dataset is based on high school and university students' hand position and head direction data, which can be automated deploying existing multimodal learning analytics systems. The framework uses Nonverbal Indexes of Students' Physical Interactivity (NISPI) to interpret the key parameters of students' CPS competence. The results show that the NISPI framework can be used to judge students' CPS competence levels accurately based on their non-verbal behaviour data. The findings have significant implications for design, research and development of educational technology.

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