Conaldi, Guido ORCID: https://orcid.org/0000-0003-3552-7307 and De Vita, Katharina ORCID: https://orcid.org/0000-0002-5030-5588 (2025) From innovation challenges to active learning: GenAI as partner in experiential education. In: Advance HE AI Symposium 2025, 25th February, 2025, Online.

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Abstract

This presentation examines how GenAI can enhance collaborative knowledge construction through structured innovation challenges, building on recent work on social learning theories in GenAI integration (Zhou and Schofield, 2024) and co-regulated learning networks (Lodge et al., 2023). Our project explores how GenAI, used as a dialogical tool, enables learners to build upon their existing knowledge and experiences to construct new knowledge through active, collaborative and experiential learning processes with both GenAI and peers. The core of our approach is a series of 'innovation quests' that position GenAI as a collaborative partner in active learning. These structured challenges deliberately move beyond surface-level GenAI use, instead fostering what Rasul et al. (2023) describe as constructivist learning facilitation through AI tools. The quests create experiential learning spaces where students actively engage with peers and GenAI to address scenarios - some developed with industry partners playing an active role in those challenges - reflecting the kind of collaborative learning environments that Essien et al. (2024) identify as crucial for developing critical thinking skills. We have implemented these quests across three delivery modes at three different institutions. The quests’ format is iteratively refined through student feedback and collaboration. Each format maintains core constructivist principles while adapting to different collaborative contexts, aligning with recent research on technology-supported constructivist learning (Kasneci et al., 2023): (1) Intensive in-class collaborations with immediate hands-on practice: 90-minute innovation challenges where teams use GenAI to develop and refine concepts in real-time; (2) Extended hybrid learning experiences allowing for deeper reflection cycles: Week-long challenges combining in-person and online collaboration with structured GenAI consultation point; (3) Virtual collaborative spaces enabling real-time experimentation: Synchronous online quests where teams engage with GenAI tools to develop innovative solutions. Our findings demonstrate several key insights about GenAI's role in collaborative knowledge creation:(1) Structured AI integration supports active knowledge construction rather than passive consumption; (2) Clear collaborative frameworks help students navigate AI as a 'critical friend'; (3) Multi-modal delivery enables deeper exploration of collaborative learning possibilities; (4) Active learning engagement increases when students experience GenAI as a collaborative tool; (5) Higher-order thinking skills are enhanced as students employ advanced cognitive skills like synthesis and evaluation to critique and integrate GenAI outputs with their existing knowledge, representing a shift from passive consumption to active intellectual partnership. Drawing from Bloom's taxonomy (Anderson & Krathwohl, 2001), these cognitive skills are particularly important as students engage in iterative cycles of knowledge construction—critically examining GenAI outputs, synthesising them with existing knowledge, and developing new insights through this dialogical process (Kim et al., 2024). This work demonstrates how GenAI can facilitate constructivist learning by scaffolding knowledge creation (Zhou and Schofield, 2024). Student engagement patterns support what Lodge et al. (2023) describe as a 'network of co-regulation' where learners actively construct knowledge through interaction with both peers and AI tools. The presentation will share concrete examples demonstrating how educators can implement similar approaches, addressing common challenges in integrating GenAI into collaborative learning experiences. Our findings offer insights for educators seeking to create collaborative learning experiences that meaningfully integrate GenAI while maintaining focus on active knowledge construction.

Item Type:	Conference or Conference Paper (Speech)
Uncontrolled Keywords:	generative AI, social constructivism, collaborative learning, innovation challenges, higher education, co-regulated learning, experiential education, knowledge co-creation.
Subjects:	H Social Sciences > H Social Sciences (General) L Education > L Education (General) T Technology > T Technology (General)
Faculty / School / Research Centre / Research Group:	Greenwich Business School Greenwich Business School > Networks and Urban Systems Centre (NUSC) Greenwich Business School > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA) Greenwich Business School > School of Business, Operations and Strategy
Last Modified:	28 Apr 2025 11:10
URI:	http://gala.gre.ac.uk/id/eprint/50221

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