Patterns of Using Multimodal External Representations in Digital Game-Based Learning. (January 2023)

• Record Type: Journal Article
• Authors: Pan, Yanjun; Ke, Fengfeng; Dai, Chih-Pu
• Is Part Of: Journal of educational computing research. Volume 60:Number 8(2023)
• Page Start: 1918
• Page End: 1941
• Publication Date: 2023-01
• Subjects: multimodal external representation -- math problem solving -- game-based learning -- cluster analysis -- sequential analysis; Computer literacy -- Periodicals; Computer-assisted instruction -- Periodicals; Computer managed instruction -- Periodicals; Education -- Data processing -- Periodicals; 371.334
• DOI: 10.1177/07356331221087771
• Languages: English
• ISSNs: 0735-6331

Abstract

Although prior research has highlighted the significance of representations for mathematical learning, there is still a lack of research on how students use multimodal external representations (MERs) to solve mathematical tasks in digital game-based learning (DGBL) environments. This exploratory study was to examine the salient patterns problem solvers demonstrated using MERs when they engaged in a single-player, three-dimensional architecture game that requires the acquisition and application of math knowledge and thinking in game-based context problem solving. We recorded and systematically coded the behaviors of using MERs demonstrated by 20 university students during 1.5 hours of gameplay. We conducted both cluster and sequential analyses with a total of 2654 encoded behaviors. The study indicated that the maneuverable visual-spatial representation was most frequently used in the selected architecture game. All of the participants performed a high level of representational transformations, including both treatment and conversion transformations. However, compared to the students in the second cluster who were mostly non-game players, students in the first cluster (composed of mainly experienced video game players) displayed a higher frequency of interacting with various MERs and a more cautious and optimized reflective problem-solving process.