Automatic Detection of Reflective Thinking in Mathematical Problem Solving based on Unconstrained Bodily Exploration

Olugbade, Temitayo, Newbold, Joseph, Johnson, Rose, Volta, Erica, Alborno, Paolo, Niewiadomski, Radoslaw, Dillon, Max, Volpe, Gualtiero and Bianchi-Berthouze, Nadia (2022) Automatic Detection of Reflective Thinking in Mathematical Problem Solving based on Unconstrained Bodily Exploration. IEEE Transactions on Affective Computing, 13 (2). pp. 944-957. ISSN 2371-9850

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For technology (like serious games) that aims to deliver interactive learning, it is important to address relevant mental experiences such as reflective thinking during problem solving. To facilitate research in this direction, we present the weDraw-1 Movement Dataset of body movement sensor data and reflective thinking labels for 26 children solving mathematical problems in unconstrained settings where the body (full or parts) was required to explore these problems. Further, we provide qualitative analysis of behaviours that observers used in identifying reflective thinking moments in these sessions. The body movement cues from our compilation informed features that lead to average F1 score of 0.73 for binary classification of problem-solving episodes by reflective thinking based on Long Short-Term Memory neural networks. We further obtained 0.79 average F1 score for end-to-end classification, i.e. based on raw sensor data. Finally, the algorithms resulted in 0.64 average F1 score for subsegments of these episodes as short as 4 seconds. Overall, our results show the possibility of detecting reflective thinking moments from body movement behaviours of a child exploring mathematical concepts bodily, such as within serious game play.

Item Type: Article
Additional Information: Funding information: Research funded by Horizon 2020 Framework Programme (732391)
Uncontrolled Keywords: Affect sensing and analysis, Education, Emotional corpora, Neural nets
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 09 Jul 2020 14:01
Last Modified: 28 Jun 2022 14:45

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