Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing

Eason Chen; Yuen Hsien Tseng; Yu Tang You; Kuo Ping Lo; Chris Lin

doi:10.1007/978-3-031-11647-6_119

Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing

Eason Chen^*, Yuen Hsien Tseng, Yu Tang You, Kuo Ping Lo, Chris Lin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

When sitting in front of a computer screen for online learning, students can be easily distracted by other sources on the Internet. To help students improve their online learning experience, we implemented a highly accessible AI service, which collected facial data from the web camera to assist self-regulated learning for students with privacy protection by way of edge computing. The service can capture self-learning metrics such as eye gazing points and facial expressions. Then the captured facial streaming data can be played back by the user. All steps are done locally at the users’ browser. The learners can review their online learning process to improve their learning efficiency through an interactive interface. Our preliminary evaluation showed promising feedback from real users.

Original language	English
Title of host publication	Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings
Editors	Maria Mercedes Rodrigo, Noburu Matsuda, Alexandra I. Cristea, Vania Dimitrova
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	577-581
Number of pages	5
ISBN (Print)	9783031116469
DOIs	https://doi.org/10.1007/978-3-031-11647-6_119
Publication status	Published - 2022
Event	23rd International Conference on Artificial Intelligence in Education, AIED 2022 - Durham, United Kingdom Duration: 2022 Jul 27 → 2022 Jul 31

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13356 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	23rd International Conference on Artificial Intelligence in Education, AIED 2022
Country/Territory	United Kingdom
City	Durham
Period	2022/07/27 → 2022/07/31

Keywords

Artificial Intelligence (AI)
E-learning
Edge computing
Eye Tracking
Online learning
Self-regulated learning

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-11647-6_119

Cite this

Chen, E., Tseng, Y. H., You, Y. T., Lo, K. P., & Lin, C. (2022). Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing. In M. M. Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings (pp. 577-581). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13356 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-11647-6_119

Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing. / Chen, Eason; Tseng, Yuen Hsien; You, Yu Tang et al.
Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings. ed. / Maria Mercedes Rodrigo; Noburu Matsuda; Alexandra I. Cristea; Vania Dimitrova. Springer Science and Business Media Deutschland GmbH, 2022. p. 577-581 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13356 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chen, E, Tseng, YH, You, YT, Lo, KP & Lin, C 2022, Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing. in MM Rodrigo, N Matsuda, AI Cristea & V Dimitrova (eds), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13356 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 577-581, 23rd International Conference on Artificial Intelligence in Education, AIED 2022, Durham, United Kingdom, 2022/07/27. https://doi.org/10.1007/978-3-031-11647-6_119

Chen E, Tseng YH, You YT, Lo KP, Lin C. Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing. In Rodrigo MM, Matsuda N, Cristea AI, Dimitrova V, editors, Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 577-581. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-11647-6_119

Chen, Eason ; Tseng, Yuen Hsien ; You, Yu Tang et al. / Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings. editor / Maria Mercedes Rodrigo ; Noburu Matsuda ; Alexandra I. Cristea ; Vania Dimitrova. Springer Science and Business Media Deutschland GmbH, 2022. pp. 577-581 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Preliminary Design of an AI Service to Assist Self-regulated Learning by Edge Computing

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Keywords

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