Eye Tracking for Digital Storytelling Content in Edutainment

Modern tainment technologies in education are implemented as “hybrid” or a cluster paradigm based on the leverage of certain entertainment elements into the learning process. A variety of digital storytelling content in edutainment encourages to study the effectiveness of its multimodality, including texts, visuals, videos and their combinations. New types of non-verbal research techniques, such as eye tracking, provide a deeper understanding of learners’ behavior, perception patterns and cognitive strategies during their interaction with educational material. Purpose of the study: to investigate the gaze patterns and cognitive strategies used by students when working with learning material consisting of text, visual and combined slides. Research methods: the eye movement tracking experiment using the infrared eye tracker and the post-interview follow-up. Results of the study: processing strategies for presentations containing visual and textual elements differed among students. Cognitive strategies for processing visual and textual elements consisted of multiple patterns and required different processing times. The findings will help educational professionals to structure digital narrative content based on typical gaze patterns and highlight perceptual strategies to make learning material more effective. Conclusions: learning eye tracking metrics such as fixation time, gaze return, average fixation, saccades and their amplitudes, etc., helps to improve digital narrative content based on content perception patterns and learners’ interest in the content, as well as content complexity and cognitive load.

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Published
2025-04-09
DOI
https://doi.org/10.1109/comsds65569.2025.10971304
Primary Topic
Digital Storytelling and Education
Type
article
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article

Eye Tracking for Digital Storytelling Content in Edutainment

Larisa V. Sharakhina, Marianna Yu. Ababkova, Irina Yu. Melnikova
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Digital Storytelling and Education
article

Eye Tracking for Digital Storytelling Content in Edutainment

Larisa V. Sharakhina, Marianna Yu. Ababkova, Irina Yu. Melnikova
article en

Abstract

Modern tainment technologies in education are implemented as “hybrid” or a cluster paradigm based on the leverage of certain entertainment elements into the learning process. A variety of digital storytelling content in edutainment encourages to study the effectiveness of its multimodality, including texts, visuals, videos and their combinations. New types of non-verbal research techniques, such as eye tracking, provide a deeper understanding of learners’ behavior, perception patterns and cognitive strategies during their interaction with educational material. Purpose of the study: to investigate the gaze patterns and cognitive strategies used by students when working with learning material consisting of text, visual and combined slides. Research methods: the eye movement tracking experiment using the infrared eye tracker and the post-interview follow-up. Results of the study: processing strategies for presentations containing visual and textual elements differed among students. Cognitive strategies for processing visual and textual elements consisted of multiple patterns and required different processing times. The findings will help educational professionals to structure digital narrative content based on typical gaze patterns and highlight perceptual strategies to make learning material more effective. Conclusions: learning eye tracking metrics such as fixation time, gaze return, average fixation, saccades and their amplitudes, etc., helps to improve digital narrative content based on content perception patterns and learners’ interest in the content, as well as content complexity and cognitive load.

Peter the Great St. Petersburg Polytechnic University (RU), Saint Petersburg State Electrotechnical University (RU)
Openalex Percentile: Top 89%
Digital Storytelling and Education
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Eye Tracking for Digital Storytelling Content in Edutainment — Larisa V. Sharakhina, Marianna Yu. Ababkova, et al. · (2025) | TGRS Research Map | TGRS