Detecting Mind-Wandering from Eye Movement and Oculomotor Data during Learning Video Lecture

Jang, Dongmin; Yang, Il Ho; Kim, Seong Un

doi:10.3390/educsci10030051

Cited by 8 publications

(5 citation statements)

References 32 publications

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“…In one study involving a reading task, eye movements became slower or less frequent during a period prior to a participant's report of mind-wandering compared with a period prior to reporting of being on-task (concentrating) (Uzzaman & Joordens, 2011). Another study reported that the saccade frequency was lower and the fixation dispersion was more limited in mind-wandering states than in attentive states during video lectures (Jang et al, 2020). Therefore, compared with the task phase, people are likely to be in a mind-wandering state in the after-task phase because no specific goal is given.…”

Section: Introductionmentioning

confidence: 99%

Non-goal driven eye movement after a visual search task

Takemoto

Nakazawa

Kumada

2022

JEMR

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We investigated the functions and mechanisms of non-goal-driven eye movements, which are defined as eye movements induced when looking at visual stimuli on a display without engaging in a specific task or looking at a display without any visual stimuli or tasks. In our experiment, participants were asked to perform a visual search task on a display, which was followed by a rest period in which stimuli remained on the display or all stimuli were erased. During the rest period, the participants were asked to only look at the displays without engaging in any visual or cognitive tasks. We mainly analyzed the gaze-shift patterns in both task and rest periods, in which eye movements were classified in accordance with the angles of saccade directions in two consecutive saccades. The results indicate a significant difference between goal-driven eye movements, which were observed in the task period, and non-goal-driven eye movements, which were observed in the rest period. Scanning gaze-shift patterns dominated the task period, and backward and corrective-saccade-like gaze-shift patterns dominated the rest period. The gaze-shift pattern was affected by the task-difficulty during the task period. From these findings, we propose a model describing the oculomotor system in terms of goal-driven and non-goal-driven eye movements. In this model, the engagement levels of top-down and bottom-up control change along with task difficulty and are affected by the gaze-shift patterns during a visual search task. Decoupling of top-down control from the oculomotor system during a rest period induces backward saccades, resulting in fixation around the central part of a display. Therefore, we suggest that non-goal-driven eye movements play a crucial role in maintaining the readiness of the oculomotor system for the next search task.

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Section: Introductionmentioning

confidence: 99%

Non-goal driven eye movement after a visual search task

Takemoto

Nakazawa

Kumada

2022

JEMR

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“… 7 Wang et al ( 2020b ) Fixation dispersion Dispersion on the screen divided by the maximum dispersion. 3 Jang et al ( 2020 ) …”

Section: Resultsmentioning

confidence: 99%

“…While an increase in fixation count may imply that an AOI is prominent (Kokoç et al, 2020 ), the same metric can also represent a higher level of difficulty when processing an AOI (Wang et al, 2019b ). A longer fixation duration on an AOI can evince the investment of more cognitive resources (Pi et al, 2020a ), but it can also be used to approximate mind-wandering (Jang et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

A review of eye tracking research on video-based learning

Deng

Gao

2022

Educ Inf Technol

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Eye tracking technology is increasingly used to understand individuals’ non-conscious, moment-to-moment processes during video-based learning. This review evaluated 44 eye tracking studies on video-based learning conducted between 2010 and 2021. Specifically, the review sought to uncover how the utilisation of eye tracking technology has advanced understandings of the mechanisms underlying effective video-based learning and what type of caution should be exercised when interpreting the findings of these studies. Four important findings emerged from the analysis: (1) not all the studies explained the mechanisms underlying effective video-based learning through employing eye tracking technology, and few studies disentangled the complex relationship between eye tracking metrics and cognitive activities these metrics represent; (2) emotional factors potentially serve to explain the processes that facilitate video-based learning, but few studies captured learners’ emotional processes or evaluated their affective gains; (3) ecological validity should be improved for eye tracking research on video-based learning through methods such as using eye tracking systems that have high tolerance for head movements, allowing learners to take control of the pacing of the video, and communicating the learning objectives of the video to participants; and (4) boundary conditions, including personal (e.g. age, prior knowledge) and environmental factors (e.g. the topic of videos, type of knowledge), must be considered when interpreting research findings. The findings of this review inspire a number of propositions for designing and interpreting eye tracking research on video-based learning.

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“…The restricted field of view displayed on the screen during microscopic ear surgery, slows down gaze exploration, leading to a reduced perception of the middle ear anatomy. Moreover, several authors reported long average fixation duration to be an indicator of either a participant’s difficulty extracting information from a display or mind wandering (21–24). Long and steady fixations increase visual fatigue leading to higher perceived discomfort during video observation (25,26).…”

Section: Discussionmentioning

confidence: 99%

Video Learning of Surgical Procedures: A Randomized Comparison of Microscopic, 2- and 3-Dimensional Endoscopic Ear Surgery Techniques

et al. 2022

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BackgroundVideo learning of surgical procedures helps trainees gain an initial understanding of the complex anatomy and the surgical procedure. Because no comparative studies have yet examined which microsurgical approach to the middle ear is most suitable for video learning, the authors investigated objective and subjective outcomes for medical trainees observing microscopic, 2-dimensional (2D) endoscopic, and 3- dimensional (3D) endoscopic ear surgeries.MethodsSixty-two medical students (min. 3rd year) from the University Hospital of Bern watched three standardized videos of a type I tympanoplasty surgery recording, conducted with a microscope, a 2D endoscope, and a 3D endoscope, respectively. The authors measured participants’ learning outcome, eye movements, cognitive load, and subjective preferences.ResultsOf the 62 participants included in the study, 14 were male (22.58%), and mean age was 24.44 years (range: 21–29). Learning outcome was highest after watching the 3D endoscopic video (mean [SD], 59.48% [20.57%]). Differences in score were statistically significant: 2D endoscopic video (mean difference: –6.56%, 95% CI: –13.02 to –0.10%), microscopic video (mean difference: –13.82%, 95% CI: –20.27 to –7.36%). Participants showed lowest average eye fixation duration when watching the 3D endoscopic video (mean [SD], 307 ms [109 ms]), with statistically significant differences to the 2D endoscopic video (mean difference: –139 ms, 95% CI: –185 to –93 ms), and the microscopic video (mean difference: –264 ms, 95% CI: –310 to –218 ms). Participants reported lowest cognitive load for the 2D and 3D endoscopic videos. Ratings on discomfort, usability, naturalness, depth perception, and image quality were in favor of the 3D endoscopic video.ConclusionThe 3D endoscopic technique offers many advantages for video learning in terms of knowledge gain, visual field exploration, and subjective evaluation. To optimize learning effects in trainees, the authors recommend the use of endoscopes in middle ear surgery and, if available, using 3D technology.

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Detecting Mind-Wandering from Eye Movement and Oculomotor Data during Learning Video Lecture

Cited by 8 publications

References 32 publications

Non-goal driven eye movement after a visual search task

Non-goal driven eye movement after a visual search task

A review of eye tracking research on video-based learning

Video Learning of Surgical Procedures: A Randomized Comparison of Microscopic, 2- and 3-Dimensional Endoscopic Ear Surgery Techniques

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