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Create free accountWhitepaperGames and Learning Alliance Conference (GALA)
Distilling the key insights…
Mobile Learning Games (MLGs) offer significant potential for enhancing student engagement and learning outcomes, yet their adoption by educators remains constrained by the lack of accessible, reusable authoring tools. Current solutions often force a trade-off between technical power and usability, leaving teachers to choose between complex, programming-heavy environments or overly simplistic tools that lack necessary pedagogical features.
The analysis evaluates five publicly available authoring tools—ARIS, App Inventor 2, Pocket Code, Furet Factory, and mLearn4web—using a criteria grid based on technical features and Human-Computer Interaction (HCI) usability standards. The assessment involved five teachers who specialize in educational field trips. Findings reveal a clear dichotomy: tools like ARIS and App Inventor 2 provide robust technical capabilities but suffer from high cognitive loads and steep learning curves, while simpler platforms like Furet Factory offer intuitive interfaces but lack the depth required for effective game design.
To address these barriers, the proposed solution involves a multi-view authoring environment based on a nested design process. This approach utilizes the concept of hidden complexity, where advanced features are progressively revealed to the user based on their expertise level. The design includes a standard view for rapid, basic scenario creation, an intermediate view for configuring game mechanics, and an expert view for advanced customization and logic. By tailoring the interface to the teacher’s specific needs and experience, this model aims to lower the barrier to entry for MLG development, allowing educators to create effective learning experiences without requiring extensive technical or game-design backgrounds. Future work focuses on prototyping this multi-view system and evaluating its efficacy across broader educational contexts.
European Conference on Games Based Learning (ECGBL) · 2026