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 › Conference contribution › peer-review

8 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	2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Place of Publication	Leicester, UK
Publisher	IEEE Xplore
Pages	610-617
Number of pages	7
ISBN (Electronic)	978-1-7281-4034-6
ISBN (Print)	978-1-7281-4035-3
DOIs	https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142
Publication status	Published (in print/issue) - 19 Aug 2019
Event	2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation(SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) - Leicester, United Kingdom Duration: 19 Aug 2019 → 23 Aug 2019

Conference

Conference	2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation(SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Period	19/08/19 → 23/08/19

Keywords

Electronic learning
eye
gaze tracking
handicapped aids
human factors
medical discorders
regression analysis
statistical testing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

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

https://ieeexplore.ieee.org/document/9060422/

Cite this

Wang, R., Chen, L., Ayesh, A., Shell, J., & Solheim, I. (2019). Gaze-Based Assessment of Dyslexic Students' Motivation within an E-Learning Environment. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 610-617). IEEE Xplore. https://doi.org/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. 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). Leicester, UK : IEEE Xplore, 2019. pp. 610-617

@inproceedings{de9470127aa444939a4f6db09c3500d5,

title = "Gaze-Based Assessment of Dyslexic Students' Motivation within an E-Learning Environment",

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\%.",

keywords = "Electronic learning, eye, gaze tracking, handicapped aids, human factors, medical discorders, regression analysis, statistical testing",

author = "Ruijie Wang and Liming Chen and Aladdin Ayesh and Jethro Shell and Ivar Solheim",

year = "2019",

month = aug,

day = "19",

doi = "10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142",

language = "English",

isbn = "978-1-7281-4035-3",

pages = "610--617",

booktitle = "2019 IEEE SmartWorld, Ubiquitous Intelligence \& Computing, Advanced \& Trusted Computing, Scalable Computing \& Communications, Cloud \& Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)",

publisher = "IEEE Xplore",

address = "United States",

note = "2019 IEEE SmartWorld, Ubiquitous Intelligence \& Computing, Advanced \& Trusted Computing, Scalable Computing \& Communications, Cloud \& Big Data Computing, Internet of People and Smart City Innovation(SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) ; Conference date: 19-08-2019 Through 23-08-2019",

}

Wang, R, Chen, L, Ayesh, A, Shell, J & Solheim, I 2019, Gaze-Based Assessment of Dyslexic Students' Motivation within an E-Learning Environment. in 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE Xplore, Leicester, UK, pp. 610-617, 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation(SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 19/08/19. 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.
2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). Leicester, UK: IEEE Xplore, 2019. p. 610-617.

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

TY - GEN

T1 - Gaze-Based Assessment of Dyslexic Students' Motivation within an E-Learning Environment

AU - Wang, Ruijie

AU - Chen, Liming

AU - Ayesh, Aladdin

AU - Shell, Jethro

AU - Solheim, Ivar

PY - 2019/8/19

Y1 - 2019/8/19

N2 - 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%.

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%.

KW - Electronic learning

KW - eye

KW - gaze tracking

KW - handicapped aids

KW - human factors

KW - medical discorders

KW - regression analysis

KW - statistical testing

UR - https://www.scopus.com/pages/publications/85072983528

U2 - 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142

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

M3 - Conference contribution

SN - 978-1-7281-4035-3

SP - 610

EP - 617

BT - 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)

PB - IEEE Xplore

CY - Leicester, UK

T2 - 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation(SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)

Y2 - 19 August 2019 through 23 August 2019

ER -

Wang R, Chen L, Ayesh A, Shell J, Solheim I. Gaze-Based Assessment of Dyslexic Students' Motivation within an E-Learning Environment. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). Leicester, UK: IEEE Xplore. 2019. p. 610-617 doi: 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00142

Gaze-Based Assessment of Dyslexic Students' Motivation within an E-Learning Environment

Abstract

Conference

Keywords

UN SDGs

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