Visual behavior and self-efficacy of game playing: an eye movement analysis

ABSTRACT

This study was to investigate the role of students’ game self-efficacy in their game performance as well as in their visual behavior distributions and transfer patterns during their gameplay. A total of 48 university students were recruited for participating in a gameplaying task while wearing with an ASL Mobile Eye eye-tracker. After the gameplay, each participant was asked to report their self-efficacy of the gameplay. Based on the self-reported game self-efficacy (GSE) score, the participants were divided into the higher and lower GSE groups. Independent t tests were used to compare their game performances and eye-tracking indices for each area of interest. A lag sequential analysis was used to profile the visual transfer pattern for each group. The results showed that the higher GSE group had better performances than the lower GSE group. During the gameplay, the higher GSE students tended to pay more attention to the critical information for a successful play. In addition, the lag sequential analyses revealed different visual transfer patterns for the two GSE groups. The higher GSE group tended to show a critical-factor-centralized visual-trasfer pattern which demonstrated more planning and monitoring gameplaying strategies; while the lower GSE students, probably lacking the self-confidence of gameplaying, tended to pay more attention to the remaining time for the game.This study may provide suggestions for future game-based leraning system designs.

KEYWORDS:

• Eye tracking
• visual behavior
• game self-efficacy
• game-based learning
• lag sequential analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Chung-Yuan Hsu is currently an Associate Professor at the National Pingtung University of Science and Technology. His research focuses on the designs of simulation-based and game-based learning environments, online inquiry learning analytics, and teacher education in educational technology. Recently, he has attempted to use eye-tracking technology to track and analyze how students interacted with the scaffolding designed in game-based learning environments.

Guo-Li Chiou is currently an Associate Professor of the Program of Learning Sciences and the Institute for Research Excellence in Learning Sciences at National Taiwan Normal University. His research focuses on how students learn science, particularly on mental models of physical phenomena and systems. Currently, Professor Chiou is working on how students learn physics in digital environments, with particular emphases on simulation-based and game-based physics learning. In addition, he uses eye-tracking techniques to record and analyze students’ visual behaviors while reading and solving physics problems.

Meng-Jung Tsai is a Professor of the Program of Learning Sciences and the Institute for Research Excellence in Learning Sciences at National Taiwan Normal University. Her research interests include students’ learning strategies utilized in computer literacy education and in various digital learning environments. She has used eyetracking technology to examine learners’ visual behaviors in interactive learning environments, especially online inquiry learning and game-based learning environments. Recently, she is interested in examining the role of human factors such as self-efficacy played in cognitive process.

ORCID

Chung-Yuan Hsu http://orcid.org/0000-0002-0666-6482

Additional information

Funding

This work was supported by Ministry of Science and Technology, Taiwan: [Grant Number 103-2511-S-020-001-MY3,103-2511-S-003-068-MY3,105-2628-S-003-004-MY3, 103-2511-S-011-005-MY3, 106-2511-S-003-064-MY3], and by the “Institute for Research Excellence in Learning Sciences” of National Taiwan Normal University (NTNU) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.