Abstract
This paper outlines the linking of a multi-modal sensing platform with an Intelligent Tutoring System to perceive the motivational state of the learner during STEM tasks. Motivation is a critical element to learning but receives little attention in comparison to strategies related to cognitive processes. The EMPOWER project has developed a novel platform that offers researchers an opportunity to capture a learner’s multi-modal behavioral signals to develop models of motivation problems that can be used to develop best practice strategies for instructional systems.
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DiNinni, R., Rizzo, A. (2022). Sensing Human Signals of Motivation Processes During STEM Tasks. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. AIED 2022. Lecture Notes in Computer Science, vol 13356. Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6_28
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DOI: https://doi.org/10.1007/978-3-031-11647-6_28
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