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<p>This paper responds to Richard E. Mayer’s (2025) commentary on our FoRe-Squares model of technology-augmented instruction (Eitel et al., 2025), a model that builds on the foundational contributions of the Cognitive Theory of Multimedia Learning (Mayer, 2022) and Cognitive Load Theory (Sweller, 2010). We advocate for two key contributions the model makes: First, it conceptualizes cognition and motivation in a highly integrative way, aiming for a comprehensive understanding of what makes (technology-augmented) instruction effective. Second, it highlights two main predictor constructs that underlie effective instruction—focus support and reward—aiming for high parsimony and a construct-based understanding of instructional effectiveness. We position the FoRe-Squares model to guide further research by providing a complementary rationale for explaining and predicting the effects of instructional techniques and their combinations on processing and learning outcomes. In addition, we position the FoRe-Squares model to provide practitioners with a parsimonious heuristic for designing and evaluating instruction.</p>

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Advocating the FoRe-Squares Model of Technology-Augmented Instruction: a Reply to Mayer (2025)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月4日

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  • Alexander Eitel,
  • Anna Kienitz,
  • Marie-Christin Krebs,
  • Claudia Schöne

摘要

This paper responds to Richard E. Mayer’s (2025) commentary on our FoRe-Squares model of technology-augmented instruction (Eitel et al., 2025), a model that builds on the foundational contributions of the Cognitive Theory of Multimedia Learning (Mayer, 2022) and Cognitive Load Theory (Sweller, 2010). We advocate for two key contributions the model makes: First, it conceptualizes cognition and motivation in a highly integrative way, aiming for a comprehensive understanding of what makes (technology-augmented) instruction effective. Second, it highlights two main predictor constructs that underlie effective instruction—focus support and reward—aiming for high parsimony and a construct-based understanding of instructional effectiveness. We position the FoRe-Squares model to guide further research by providing a complementary rationale for explaining and predicting the effects of instructional techniques and their combinations on processing and learning outcomes. In addition, we position the FoRe-Squares model to provide practitioners with a parsimonious heuristic for designing and evaluating instruction.