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Eye Tracking in Science Education Research: Comprehensive Literature Review.

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Title: Eye Tracking in Science Education Research: Comprehensive Literature Review.
Authors: Tóthová, Martina1 (AUTHOR), Rusek, Martin1 (AUTHOR) martin.rusek@pedf.czni.cz
Source: Science & Education. Dec2025, Vol. 34 Issue 6, p4583-4626. 44p.
Subject Terms: *Science education, *Cognitive psychology, *Student engagement, *Teaching methods, Eye tracking, Selectivity (Psychology)
Abstract: Eye-tracking technology has emerged as a powerful tool in science education research, providing unparalleled insights into learners' visual attention, cognitive processing, and engagement with complex visual stimuli. This systematic review synthesises findings from 170 studies published in Web of Science-indexed journals, selected from an initial pool of 525 articles. The analysis reveals that most studies were conducted in Europe (with physics education dominating at 34%) and primarily targeted university students (55%), while only 22% focused on younger learners, including preschool and lower-secondary students. The median sample size across studies was 36 participants, highlighting a methodological constraint that merits attention. The results identify key research themes: the processing of scientific representations (29%), reading behaviours in learning materials (28%), problem-solving tasks (19%), experiments and simulations (18%), and video-based learning environments (6%). Eye-tracking metrics such as fixation duration, dwell time, and transition patterns were predominantly used to measure learners' attention and cognitive load. Findings underscore the critical influence of learner expertise, prior knowledge, and spatial abilities on visual processing patterns. Novice learners exhibited surface-level engagement, frequent switching between representations, and difficulty integrating visual and textual information, whereas experts demonstrated focused, deeper processing. Instructional interventions were shown to enhance learners' comprehension and performance significantly. However, challenges persist, including methodological inconsistencies, small sample sizes, and underexplored factors like emotional responses and self-regulation. The review highlights the pressing need for further research that utilises meta-analytical approaches, addresses diverse learner populations, and explores complex learning environments with eye-tracking technology. By offering actionable insights for instructional design and visual learning strategies, this review advances our understanding of how visual stimuli shape learning in science education and paves the way for evidence-based pedagogical innovations. [ABSTRACT FROM AUTHOR]
Copyright of Science & Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Eye Tracking in Science Education Research: Comprehensive Literature Review.
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  Data: Eye-tracking technology has emerged as a powerful tool in science education research, providing unparalleled insights into learners' visual attention, cognitive processing, and engagement with complex visual stimuli. This systematic review synthesises findings from 170 studies published in Web of Science-indexed journals, selected from an initial pool of 525 articles. The analysis reveals that most studies were conducted in Europe (with physics education dominating at 34%) and primarily targeted university students (55%), while only 22% focused on younger learners, including preschool and lower-secondary students. The median sample size across studies was 36 participants, highlighting a methodological constraint that merits attention. The results identify key research themes: the processing of scientific representations (29%), reading behaviours in learning materials (28%), problem-solving tasks (19%), experiments and simulations (18%), and video-based learning environments (6%). Eye-tracking metrics such as fixation duration, dwell time, and transition patterns were predominantly used to measure learners' attention and cognitive load. Findings underscore the critical influence of learner expertise, prior knowledge, and spatial abilities on visual processing patterns. Novice learners exhibited surface-level engagement, frequent switching between representations, and difficulty integrating visual and textual information, whereas experts demonstrated focused, deeper processing. Instructional interventions were shown to enhance learners' comprehension and performance significantly. However, challenges persist, including methodological inconsistencies, small sample sizes, and underexplored factors like emotional responses and self-regulation. The review highlights the pressing need for further research that utilises meta-analytical approaches, addresses diverse learner populations, and explores complex learning environments with eye-tracking technology. By offering actionable insights for instructional design and visual learning strategies, this review advances our understanding of how visual stimuli shape learning in science education and paves the way for evidence-based pedagogical innovations. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Science & Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Dec2025
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