Conference Program

A major paradigm shift in educational research has rethought the definition of creativity: no longer seen as a fixed individual trait, it is now understood as a complex process stimulable through targeted educational interventions (Runco, 2004). However, opportunities to develop creativity are not equally distributed. Students attending schools in geographically marginalised areas often experience reduced access to cultural institutions, extracurricular activities, and advanced digital resources that can nurture creative development (Mangione, 2024). In these settings, structured educational programs aimed at fostering creativity can play a particularly important compensatory role. While different activities aiming to foster creative practices have been proposed in educational scenarios (Clapham, 2003) , their effectiveness is often hindered by limitations such as conformity and production blocking (Zhou & Luo, 2012) or the prevalence of persistent creativity myths and test-focused environments (Plucker et al., 2011). Current research therefore focuses on finding new methods for efficiently empowering students’ creativity. In this scenario, Generative Artificial Intelligence (AI) systems, when guided by a clear pedagogical direction, have the potential to act as cognitive mediators and facilitators of the creative process, while preserving the centrality of the human individual. This paper presents a study exploring an innovative approach to AI integration for creativity fostering in schools. While much of the literature investigates the impact of AI on the creative Person or Process (Rhodes, 1961), this study shifts the focus to the Product and the Press, the sociocultural context framing the evaluation. Specifically, the research addresses the following question: does the creative artifact produced following the intervention, evaluated by a team of domain experts, reach high levels of quality in terms of creativity?

To address this question, the study adopts a quasi-experimental mixed-methods design. The three-week intervention involves students from marginalized areas of Umbria, Italy, tasked with designing a textual storyboard. To support them, the study utilizes a digital platform featuring a Generative AI-enhanced multi-agent system (MAS), designed as a brainstorming chat between the human participant and artificial agents. The pedagogical framework is grounded in Edward De Bono’s Six Thinking Hats model (De Bono, 1985). The brainstorming sessions feature distinct phases where both the student and agents wear the same hat, promoting parallel thinking and minimizing cognitive conflict. As recent literature highlights, MAS function as communities that enable collaboration among multiple agents to address complex tasks exceeding the capabilities of any single entity, effectively generating diverse perspectives that enrich the collaborative dialogue (Lo Presti et al., 2025).

To evaluate the quality of the final storyboards, a subsample of anonymous artifacts is submitted to independent domain experts using Amabile’s (1982) Consensual Assessment Technique (CAT). This allows for a robust measure of Product creativity grounded in expert consensus, which represents the Press. Finally, implementing this intervention in geographically marginalized contexts highlights the potential of pedagogically structured AI to act as a democratic equalizer, providing equitable access to high-level cognitive scaffolding and fostering critical, agentic learning environments.