Conference Program
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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A.09. Citizenship, Social Justice and Playful Learning for Economic Awareness and Social Change Location: Edificio ex Tumminelli (C007): Sala Sociologia Convenor(s): Liliana Silva (University of Modena and Reggio Emilia, Italy); Ennio Bilancini (Imt -Scuola Alti Studi – Lucca, Italy); Leonardo Boncinelli (University of Firenze, Italy) | |
| Presentation 4 | |
A Framework For An AI-Supported Design Of Game-Based Learning Units Aimed At Enhancing Prosocial Behaviour And Recognition Of The Others Università degli Studi Guglielmo Marconi, Italy The paper presents a theoretical framework and specific prompts useful for AI generation of game-based Learning Unit aimed at developing prosocial and recognition of the others skills. The framework is that of peace education, seen as a culture of relationships that is built through educational processes and social experiences in which individuals learn to confront the plurality of differences. In this context, it is possible to leverage the potential of board games and video games, included within appropriately designed Learning Units as a whole, which include within themselves playful activities and activities around the game (Andreoletti & Tinterri, 2023). While board games constitute symbolic systems governed by explicit and shared norms within which participants act, make decisions, play roles, and engage with others, video games, while presenting risks in terms of aggression, can in some cases increase prosocial behavior and recognition of others (Katsarov et al., 2019, Lopez-Naranjo et al., 2025). The contribution is based on a theoretical framework that contemplates three dimensions, directivity, sociality and projectivity (Ugolini & Morreale, 2023; forthcoming), linked respectively to the problem scenario, social scenario and identity scenario of Hanghoj (2013) and to the qualification function, socialization function and subjectification function of Education (Biesta, 2009). In this paper, we focus this framework on prosociality and on recognition of the other. Through this framework, it is possible to train Generative AI (Ugolini et al., 2025), which, through appropriate prompts, is able to generate the project of a competence-oriented Learning Unit, in a secondary school context, based on a gaming experience and linked to curricular objectives, above all those defined for civic education. The research proposes an analysis involving expert teachers and game designers, of the AI-generated Learning Unit projects in order to evaluate their feasibility in context, both from the point of view of design coherence and from the point of view of the validity of the theoretical reference model. | |
