VAFUG: A Model for Designing Educational Activities Grounded in Game Studies and Aesthetics

The paper introduces VAFUG, an analytical model designed to help educators examine commercial video games and build learning activities around their expressive and affective qualities. Developed through a Design-Based Research process, the model organizes analysis into three components: Visual and Auditory Environment, Fictional Universe, and Core Gameplay, each paired with two indicators. Its stated objectives are to support teachers who are not specialists in Game Studies in conducting rigorous analysis, and to generate guiding questions that foster dialogue with students, particularly around socioemotional and civic competences. The model is positioned as complementary to existing serious-game frameworks such as LM-GM, with its focus on independent commercial titles not originally designed for education.

The work covers only the first three phases of a planned DBR cycle: problem analysis, theory-informed solution development, and initial testing and refinement. Testing consisted of applying the model to the indie title Neva, an exercise the authors describe as a preliminary validation of the model's descriptive and heuristic dimensions. The paper reports no classroom implementation, teacher feedback, or empirical data from students, and the authors explicitly state that design principles and classroom evaluation remain pending. Preliminary findings therefore suggest the model is adaptable and may encourage context-aware use of games in education, but these claims rest on a single case study and an author-led analysis.

The paper frames VAFUG as a foundational prototype rather than a validated instrument. Its principal contribution lies in bridging theoretical work from Game Studies and Aesthetics with practical classroom design, responding to a noted scarcity of research on commercial off-the-shelf games in education. Future cycles involving diverse educational settings are identified as essential to test the model's robustness and to refine both its analytical framework and its pedagogical applications.