Pursue symbolic, hybrid, and metaverse-based AI approaches to address gaps left by subsymbolic AI in collaborative learning¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The review recommends directing future research toward underrepresented AI methodologies. It notes that existing literature is centred on "a subsymbolic kind of AI, like in machine learning and natural language processing" and has mostly disregarded symbolic reasoning systems and hybrid models, which have high potential to improve collaboration outcomes. It also points to metaverse, augmented and virtual reality environments for immersive collaborative learning.

Design Implications¶

Context¶

Requirements¶

• Institutional and cultural acceptance, not only technical readiness, for successful integration of generative AI technologies

Constraints¶

• The review's findings are status-quo in nature, reflecting the present state of research rather than the full potential of AI in education

Target Learners¶

• higher education students

Target Learning Goals¶

• collaborative learning
• deep cognitive processing
• group interaction

Related Strategies¶

• Four-part research agenda: longitudinal studies, hybrid frameworks, ethical frameworks, and underrepresented STEM domains
• Design AI decision-support systems that are transparent, context-sensitive, and hybrid-intelligence oriented
• Reinvigorate bottom-half AI×Ed research: AI literacy for reflection on learning, machine teaching, and agent-based models of learning

Examples¶

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Key Sources¶

• Kovari, A. (2025). A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade. Social Sciences & Humanities Open, 11, 101335. https://doi.org/10.1016/j.ssaho.2025.101335