Visual behavior, flow and achievement in game-based learning

Meng Jung Tsai, Li Ju Huang, Huei Tse Hou, Chung Yuan Hsu, Guo Li Chiou

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

This study utilized eye-tracking technology to explore the differences between high- and low-conceptual-comprehension players' visual behaviors and game flows in game-based learning (GBL). A total of 22 university students participated in this study and their eye movements while playing a physics game were recorded by an eye tracker. Along with eye-tracking measures, the participants' prior knowledge, flow and comprehension test scores were collected. Multiple data analysis methods including MWU tests, correlation analyses, heat map analyses and lag sequential analyses were employed in this study. The results indicated that the players in the high comprehension group demonstrated an efficient text-reading strategy and better metacognitive controls of visual attention during game plays; while those in the low comprehension group could have some difficulties in decoding the conceptual representations. In addition, the players with higher comprehension expressed a higher level of game flow in two aspects: the sense of control and concentration. Furthermore, the percentages of fixation for the main task and prompt messages were associated with the players' game flow experience, especially the time distortion feeling. This study successfully applied eye-tracking technology to find learners' visual behavioral patterns in GBL environment and confirmed the flow construct for GBL, which may provide some insights for the learning mechanism of GBL. Future studies have been suggested in this paper.

Original languageEnglish
Pages (from-to)115-129
Number of pages15
JournalComputers and Education
Volume98
DOIs
Publication statusPublished - 2016 Jul
Externally publishedYes

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Keywords

  • Conceptual learning
  • Eye-tracking
  • Flow
  • Game-based learning
  • Visual attention
  • Visual patterns

ASJC Scopus subject areas

  • Computer Science(all)
  • Education

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