Gaze-based assessment of dyslexic students' motivation within an e-learning environment

Ruijie Wang; Liming Chen; Aladdin Ayesh; Jethro Shell; Ivar Solheim

doi:10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142

Gaze-based assessment of dyslexic students' motivation within an e-learning environment

Ruijie Wang, Liming Chen, Aladdin Ayesh, Jethro Shell, Ivar Solheim

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

4 Citations (Scopus)

Abstract

This paper proposes a gaze-based motivation analysis approach for evaluation of motivational strategies and assessment of motivational factors for students with dyslexia in an e-learning environment. We first collect real-time eye movement data from dyslexic learners during their e-learning practices. We then use statistic tests to evaluate four typical motivational strategies with the eye-tracking data and use logistic regressions for the assessment of motivation. Initial results show that eye-tracking data is effective at evaluating the effects of the studied motivational strategies, and adding eye-tracking features significantly improves the model accuracy which has reached to a correct prediction rate of between 72.0% and 81.3%.

Original language	English
Title of host publication	Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	610-617
Number of pages	8
ISBN (Electronic)	9781728140346
DOIs	https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142
Publication status	Published - 9 Apr 2020
Event	2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 - Leicester, United Kingdom Duration: 19 Aug 2019 → 23 Aug 2019

Publication series

Name	Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019

Conference

Conference	2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
Country/Territory	United Kingdom
City	Leicester
Period	19/08/19 → 23/08/19

Keywords

Dyslexia
Eye gaze
Motivation
Strategies

Access to Document

10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142

Cite this

Wang, R., Chen, L., Ayesh, A., Shell, J., & Solheim, I. (2020). Gaze-based assessment of dyslexic students' motivation within an e-learning environment. In Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 (pp. 610-617). [9060422] (Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142

Gaze-based assessment of dyslexic students' motivation within an e-learning environment. / Wang, Ruijie; Chen, Liming; Ayesh, Aladdin et al.

Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019. Institute of Electrical and Electronics Engineers Inc., 2020. p. 610-617 9060422 (Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019).

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

Wang, R, Chen, L, Ayesh, A, Shell, J & Solheim, I 2020, Gaze-based assessment of dyslexic students' motivation within an e-learning environment. in Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019., 9060422, Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019, Institute of Electrical and Electronics Engineers Inc., pp. 610-617, 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019, Leicester, United Kingdom, 19/08/19. https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142

Wang R, Chen L, Ayesh A, Shell J, Solheim I. Gaze-based assessment of dyslexic students' motivation within an e-learning environment. In Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019. Institute of Electrical and Electronics Engineers Inc. 2020. p. 610-617. 9060422. (Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019). doi: 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142

Wang, Ruijie ; Chen, Liming ; Ayesh, Aladdin et al. / Gaze-based assessment of dyslexic students' motivation within an e-learning environment. Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 610-617 (Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019).

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abstract = "This paper proposes a gaze-based motivation analysis approach for evaluation of motivational strategies and assessment of motivational factors for students with dyslexia in an e-learning environment. We first collect real-time eye movement data from dyslexic learners during their e-learning practices. We then use statistic tests to evaluate four typical motivational strategies with the eye-tracking data and use logistic regressions for the assessment of motivation. Initial results show that eye-tracking data is effective at evaluating the effects of the studied motivational strategies, and adding eye-tracking features significantly improves the model accuracy which has reached to a correct prediction rate of between 72.0% and 81.3%.",

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AB - This paper proposes a gaze-based motivation analysis approach for evaluation of motivational strategies and assessment of motivational factors for students with dyslexia in an e-learning environment. We first collect real-time eye movement data from dyslexic learners during their e-learning practices. We then use statistic tests to evaluate four typical motivational strategies with the eye-tracking data and use logistic regressions for the assessment of motivation. Initial results show that eye-tracking data is effective at evaluating the effects of the studied motivational strategies, and adding eye-tracking features significantly improves the model accuracy which has reached to a correct prediction rate of between 72.0% and 81.3%.

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Gaze-based assessment of dyslexic students' motivation within an e-learning environment

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