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The main objective of this paper is to report on the impact of a game-based museum school visit on player experience while solving complex problems about food production. We used a mixed-methods approach, combining quantitative analysis of digital traces with qualitative case studies to assess how players engage with the mixed reality game AL2049. The data includes digital traces from 174 games and video recordings collected via on-board cameras. Our results reveal clusters characterizing attitudes towards complexity, identifying four categories of players: Explorers, Rushers, Strategists, and Inactive. Through case studies of these categories, using a dedicated model, we identified the dimensions that characterize their subjective experiences. This model highlights player experiences across four main dimensions: actions, information processing, knowledge, and emotions. Our results highlight the tension that can arise in game-based learning between the way the game is designed and the way it is played. They also underscore the value of using mixed methods to analyze the player’s experience.

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Understanding Player Experience in Museum-Based Learning Games: A Mixed-Methods Analysis

  • 会议论文

  • 发表日期：

    2025年

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  • Simon Morard,
  • Elsa Paukovics,
  • Eric Sanchez

摘要

The main objective of this paper is to report on the impact of a game-based museum school visit on player experience while solving complex problems about food production. We used a mixed-methods approach, combining quantitative analysis of digital traces with qualitative case studies to assess how players engage with the mixed reality game AL2049. The data includes digital traces from 174 games and video recordings collected via on-board cameras. Our results reveal clusters characterizing attitudes towards complexity, identifying four categories of players: Explorers, Rushers, Strategists, and Inactive. Through case studies of these categories, using a dedicated model, we identified the dimensions that characterize their subjective experiences. This model highlights player experiences across four main dimensions: actions, information processing, knowledge, and emotions. Our results highlight the tension that can arise in game-based learning between the way the game is designed and the way it is played. They also underscore the value of using mixed methods to analyze the player’s experience.