research-article
Authors: Tarmo Robal, Yue Zhao, Christoph Lofi, and Claudia Hauff
IUI '18: Proceedings of the 23rd International Conference on Intelligent User Interfaces
March 2018
Pages 189 - 197
Published: 05 March 2018 Publication History
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Abstract
A main weakness of the open online learning movement is retention: a small minority of learners (on average 5-10%, in extreme cases <1%) that start a so-called Massive Open Online Course (MOOC) complete it successfully. There are many reasons why learners are unsuccessful, among the most important ones is the lack of self-regulation: learners are often not able to self-regulate their learning behavior. Designing tools that provide learners with a greater awareness of their learning is vital to the future success of MOOC environments. Detecting learners' loss of focus during learning is particularly important, as this can allow us to intervene and return the learners' attention to the learning materials. One technological affordance to detect such loss of focus are webcams---ubiquitous pieces of hardware available in almost all laptops today. In recent years, researchers have begun to exploit eye tracking and gaze data generated from webcams as part of complex machine learning solutions to detect inattention or loss of focus. Those approaches however tend to have a high detection lag, can be inaccurate, and are complex to design and maintain. In contrast, in this paper, we explore the possibility of a simple alternative---the presence or absence of a face---to detect a loss of focus in the online learning setting. To this end, we evaluate the performance of three consumer and professional eye/face-tracking frameworks using a benchmark suite we designed specifically for this purpose: it contains a set of common xMOOC user activities and behaviours. The results of our study show that even this basic approach poses a significant challenge to current hardware and software-based tracking solutions.
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Cited By
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- Dostálová NPlch L(2024)A Scoping Review of Webcam Eye Tracking in Learning and EducationStudia paedagogica10.5817/SP2023-3-528:3(113-131)Online publication date: 2-Apr-2024
- Wakjira ABhattacharya S(2023)Student Engagement Awareness in an Asynchronous E-Learning EnvironmentInternational Journal of Technology-Enabled Student Support Services10.4018/IJTESSS.31621112:1(1-19)Online publication date: 6-Jan-2023
- Hafez ONosseir AMcKee GEl-Seoud S(2023)The Features of Students Paying and Not Paying Attention in Online Classes2023 International Conference on Computer and Applications (ICCA)10.1109/ICCA59364.2023.10401506(1-7)Online publication date: 28-Nov-2023
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Index Terms
Webcam-based Attention Tracking in Online Learning: A Feasibility Study
Human-centered computing
Human computer interaction (HCI)
Empirical studies in HCI
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Published In
IUI '18: Proceedings of the 23rd International Conference on Intelligent User Interfaces
March 2018
698 pages
ISBN:9781450349451
DOI:10.1145/3172944
Copyright © 2018 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [emailprotected]
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- SIGAI: ACM Special Interest Group on Artificial Intelligence
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 05 March 2018
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Author Tags
- eye tracking
- face detection
- moocs
- online learning
Qualifiers
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Conference
IUI'18
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- SIGAI
Acceptance Rates
IUI '18 Paper Acceptance Rate 43 of 299 submissions, 14%;
Overall Acceptance Rate 746 of 2,811 submissions, 27%
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Cited By
View all
- Dostálová NPlch L(2024)A Scoping Review of Webcam Eye Tracking in Learning and EducationStudia paedagogica10.5817/SP2023-3-528:3(113-131)Online publication date: 2-Apr-2024
- Wakjira ABhattacharya S(2023)Student Engagement Awareness in an Asynchronous E-Learning EnvironmentInternational Journal of Technology-Enabled Student Support Services10.4018/IJTESSS.31621112:1(1-19)Online publication date: 6-Jan-2023
- Hafez ONosseir AMcKee GEl-Seoud S(2023)The Features of Students Paying and Not Paying Attention in Online Classes2023 International Conference on Computer and Applications (ICCA)10.1109/ICCA59364.2023.10401506(1-7)Online publication date: 28-Nov-2023
- Teka KShastri D(2023)Towards Automatic Detection of Participant Attention in Virtual Meetings2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE)10.1109/CSCE60160.2023.00445(2731-2733)Online publication date: 24-Jul-2023
- Yang XKrajbich I(2023)Webcam-based online eye-tracking for behavioral researchJudgment and Decision Making10.1017/S193029750000851216:6(1485-1505)Online publication date: 1-Jan-2023
- Asghari PSchindler MLilienthal A(2023)Eye Tracking Auto-Correction Using Domain InformationHuman-Computer Interaction10.1007/978-3-031-35596-7_24(373-391)Online publication date: 23-Jul-2023
https://dl.acm.org/doi/10.1007/978-3-031-35596-7_24
- Kar PChattopadhyay SChakraborty S(2022)Bifurcating Cognitive Attention from Visual Concentration: Utilizing Cooperative Audiovisual Sensing for Demarcating Inattentive Online Meeting ParticipantsProceedings of the ACM on Human-Computer Interaction10.1145/35556566:CSCW2(1-34)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555656
- Sauter MHirzle TWagner THummel SRukzio EHuckauf A(2022)Can Eye Movement Synchronicity Predict Test Performance With Unreliably-Sampled Data in an Online Learning Context?2022 Symposium on Eye Tracking Research and Applications10.1145/3517031.3529239(1-5)Online publication date: 8-Jun-2022
https://dl.acm.org/doi/10.1145/3517031.3529239
- Das SChakraborty SMitra BBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)I Cannot See Students Focusing on My Presentation; Are They Following Me? Continuous Monitoring of Student Engagement through “Stungage”Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531307(243-253)Online publication date: 4-Jul-2022
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- Jamil NBelkacem ABenkhelifa E(2022)Brain-Computer Interface Approach for improving the Pedagogical Practices for Virtual Learning: A Conceptual Framework2022 IEEE Learning with MOOCS (LWMOOCS)10.1109/LWMOOCS53067.2022.9927791(72-77)Online publication date: 29-Sep-2022
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