Conditional Gamification and Distributed Learning: A Proposed Theoretical-Pedagogical Model for Adaptive Educational Platforms
DOI:
https://doi.org/10.56200/mentor.v5i5.13452Keywords:
Educational gamification, distributed learning, conditional access, educational artificial intelligence, instructional designAbstract
Educational gamification and distributed learning had independent theoretical foundations and evidence, but their integration into adaptive platforms through playful access conditioned by academic performance remained insufficiently articulated. The objective was to construct and theoretically substantiate a conditional gaming model that integrated educational gamification, distributed learning, and Self-Determination Theory, while establishing pedagogical, technological, and ethical conditions for its future implementation. A documentary review of scientific and institutional literature was conducted on gamification, distributed practice, motivation, educational artificial intelligence, learning analytics, and inclusive design, using sources selected from academic databases and specialized repositories. As a result, a conceptual architecture was formulated, composed of an academic layer, a playful layer, and an adaptive assessment engine under teacher supervision. Preliminary criteria were also defined for game selection, transparency, privacy, digital equity, and prevention of motivational displacement. The article concluded that the model presented theoretical plausibility for future empirical evaluation as an integration strategy between distributed learning and playful experiences conditioned by performance, without supporting claims of proven effectiveness, operational viability, or demonstrated educational impact.
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