Designing AI-Enhanced Educational Digital Escape Room Games (EDERGs): A Framework for Teacher Implementation

In recent years, educational digital escape room games (EDERGs) have become a dynamic method for fostering problem-solving, collaboration, and engagement in learning environments. Simultaneously, artificial intelligence (AI) has emerged as a powerful tool to enhance personalization, adaptivity, and real-time feedback in educational contexts. While both domains hold significant pedagogical potential, teachers often lack accessible guidance on how to meaningfully integrate AI into the design of educational games. This study addresses this gap by proposing a design and development research (DDR) project aimed at constructing a step-by-step framework to support teachers in designing AI-enhanced EDERGs. The research explores the question: How can teachers design AI-enhanced EDERGs? Drawing on insights from previous professional development sessions with in-service teachers, this study adopts a qualitative approach to capture educators' experiences, needs, and reflections. Through iterative cycles of analysis, design, evaluation, and refinement, we develop a practical and theoretically grounded framework that combines game-based learning principles with AI-enhanced instructional strategies. The proposed framework outlines key design steps, including setting pedagogical goals, crafting meaningful narratives, designing puzzles aligned with learning outcomes, and integrating AI components such as adaptive hints, automated feedback, and learner analytics. Teacher feedback collected through interviews and reflection journals informs the refinement of the model, ensuring its usability and relevance in real classroom settings. This paper presents the initial version of the framework along with examples of how it can be applied by teachers with varying levels of technical expertise. By bridging the gap between game-based learning and AI integration, the framework aims to empower educators to create more engaging and responsive learning experiences. The study contributes to the field by offering both a practical design guide for educators and a foundation for future research on AI-supported educational game development.

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Publication Details

Journal
European Conference on Games Based Learning
Published
2025-09-26
DOI
https://doi.org/10.34190/ecgbl.19.1.4154
Primary Topic
Educational Games and Gamification
Type
article
Field-Weighted Citation Impact
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article

Designing AI-Enhanced Educational Digital Escape Room Games (EDERGs): A Framework for Teacher Implementation

Zeynep Cömert, Yavuz Samur, Merve Kara
European Conference on Games Based Learning
Educational Games and Gamification
article

Designing AI-Enhanced Educational Digital Escape Room Games (EDERGs): A Framework for Teacher Implementation

Zeynep Cömert, Yavuz Samur, Merve Kara
article en

Abstract

In recent years, educational digital escape room games (EDERGs) have become a dynamic method for fostering problem-solving, collaboration, and engagement in learning environments. Simultaneously, artificial intelligence (AI) has emerged as a powerful tool to enhance personalization, adaptivity, and real-time feedback in educational contexts. While both domains hold significant pedagogical potential, teachers often lack accessible guidance on how to meaningfully integrate AI into the design of educational games. This study addresses this gap by proposing a design and development research (DDR) project aimed at constructing a step-by-step framework to support teachers in designing AI-enhanced EDERGs. The research explores the question: How can teachers design AI-enhanced EDERGs? Drawing on insights from previous professional development sessions with in-service teachers, this study adopts a qualitative approach to capture educators' experiences, needs, and reflections. Through iterative cycles of analysis, design, evaluation, and refinement, we develop a practical and theoretically grounded framework that combines game-based learning principles with AI-enhanced instructional strategies. The proposed framework outlines key design steps, including setting pedagogical goals, crafting meaningful narratives, designing puzzles aligned with learning outcomes, and integrating AI components such as adaptive hints, automated feedback, and learner analytics. Teacher feedback collected through interviews and reflection journals informs the refinement of the model, ensuring its usability and relevance in real classroom settings. This paper presents the initial version of the framework along with examples of how it can be applied by teachers with varying levels of technical expertise. By bridging the gap between game-based learning and AI integration, the framework aims to empower educators to create more engaging and responsive learning experiences. The study contributes to the field by offering both a practical design guide for educators and a foundation for future research on AI-supported educational game development.

European Conference on Games Based LearningVol. 19(1)
Bahçeşehir University (TR)
Openalex Percentile: Top 54%
Educational Games and Gamification
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