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In STEM education, game-based learning environments (GBLEs) have become prominent platforms to scaffold students’ self-regulated learning (SRL) strategies. This study challenges the assumption that all engagement in GBLEs is equally beneficial by distinguishing cognitive from behavioral engagement within the Integrative Model of Multidimensional SRL Engagement (IMMSE). We analyzed data from 227 high-school students playing Crystal Island, a narrative-centered microbiology GBLE, to examine how these engagement types during the forethought and performance SRL phases predict learning gains and problem-solving accuracy. Overall, results showed that cognitive engagement significantly predicts learning gains, whereas behavioral engagement does not. This result supports IMMSE’s distinction between surface-level actions and deeper processing, indicating that meaningful learning depends on strategic cognitive engagement. We discuss implications for designing adaptive scaffolds that dynamically balance engagement dimensions across early SRL phases to optimize both efficiency and effectiveness.

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Efficiency or Effectiveness in Game-Based Learning: Is Engagement Enough?

  • 会议论文

  • 发表日期：

    2026年

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  • Maral Karimi,
  • Megan Wiedbusch,
  • Natalie Blaize,
  • James Lester,
  • Roger Azevedo

摘要

In STEM education, game-based learning environments (GBLEs) have become prominent platforms to scaffold students’ self-regulated learning (SRL) strategies. This study challenges the assumption that all engagement in GBLEs is equally beneficial by distinguishing cognitive from behavioral engagement within the Integrative Model of Multidimensional SRL Engagement (IMMSE). We analyzed data from 227 high-school students playing Crystal Island, a narrative-centered microbiology GBLE, to examine how these engagement types during the forethought and performance SRL phases predict learning gains and problem-solving accuracy. Overall, results showed that cognitive engagement significantly predicts learning gains, whereas behavioral engagement does not. This result supports IMMSE’s distinction between surface-level actions and deeper processing, indicating that meaningful learning depends on strategic cognitive engagement. We discuss implications for designing adaptive scaffolds that dynamically balance engagement dimensions across early SRL phases to optimize both efficiency and effectiveness.