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

This paper presents a design and development research study aimed at helping teachers integrate artificial intelligence into the creation of educational digital escape room games (EDERGs). Its central argument is that teachers often lack accessible, pedagogically grounded guidance for combining game-based learning with AI tools, and that a step-by-step, teacher-friendly framework can close this gap. The study draws on four professional development workshops with in-service teachers in Turkey, with participants ranging from 15 to 24 per session, and relies primarily on observation notes and semi-structured interviews analyzed qualitatively through iterative design cycles.

The findings identify two main early obstacles: teachers struggled to link storylines with puzzles and frequently could not finish their games within a reasonable timeframe. Introducing AI-supported content generation, along with templates, sample prompts, and model games, was reported to accelerate the design process, allow teachers to playtest within the same session, and increase their confidence and engagement. Teachers also became more skilled at prompting AI tools over the course of the training. The resulting framework is a cyclical model covering learning objectives, narrative design, puzzle development with AI support, structured game flow, optional AI features such as adaptive hints and analytics, prototyping and revision, classroom launch, and reflection.

The authors acknowledge important limitations: participants were already interested in game-based learning, the outcomes reflect short-term workshop settings, and no measurements of student learning outcomes were taken. The study therefore positions the framework as an initial version, with future work needed to test its effects on student motivation and achievement and its sustainability across broader educational contexts.