Analysis of Careless Mistakes Using Gaze Information

Careless mistakes are caused by a lack of concentration, time pressure, and information overload due to multitasking.If we predict careless errors, they could be helpful in various situations, such as learning support, business efficiency improvement, and medical diagnosis support.However, it is challenging to reproduce careless error situations, and few studies have been on predicting careless errors.Therefore, we focus on Shogi (Japanese chess), where situational awareness is complex, and players must maintain long periods of concentration, making careless mistakes.In this study, we collected eye-tracking data of players during a game and annotated careless errors based on the game's contents and surveys from the players.By analyzing this data, we have examined the conditions under which careless mistakes occur).

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Publication Details

Journal
Proceedings of International Conference on Artificial Life and Robotics
Published
2025-02-13
DOI
https://doi.org/10.5954/icarob.2025.gs5-2
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of Careless Mistakes Using Gaze Information

Noriko Takemura, Ryota Yabe
Proceedings of International Conference on Artificial Life and Robotics
Gaze Tracking and Assistive Technology
article

Analysis of Careless Mistakes Using Gaze Information

Noriko Takemura, Ryota Yabe
article en

Abstract

Careless mistakes are caused by a lack of concentration, time pressure, and information overload due to multitasking.If we predict careless errors, they could be helpful in various situations, such as learning support, business efficiency improvement, and medical diagnosis support.However, it is challenging to reproduce careless error situations, and few studies have been on predicting careless errors.Therefore, we focus on Shogi (Japanese chess), where situational awareness is complex, and players must maintain long periods of concentration, making careless mistakes.In this study, we collected eye-tracking data of players during a game and annotated careless errors based on the game's contents and surveys from the players.By analyzing this data, we have examined the conditions under which careless mistakes occur).

Proceedings of International Conference on Artificial Life and RoboticsVol. 30
Kyushu Institute of Technology (JP)
Openalex Percentile: Top 84%
Gaze Tracking and Assistive Technology
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