Review On: Collaboration Intelligence in Education

Abstract

This review synthesizes current research on human-AI collaboration, particularly within educational and decision-making environments, to evaluate when and how partnerships between humans and artificial intelligence outperform individuals alone. While AI technologies—such as machine learning, natural language processing, and recommender systems—have demonstrated significant potential to enhance personalized learning and collaborative educational outcomes, evidence indicates a nuanced relationship between human-AI interactions and task effectiveness. Meta-analytic findings reveal that human-AI collaborations often underperform compared to the best individual agent, especially in decision-making tasks, whereas content creation tasks benefit from such synergy. Key factors influencing successful collaboration include the relative strengths of humans and AI, task design, emotional and social engagement, and the balance between automation and human control. Additionally, ethical considerations surrounding transparency, data privacy, and stakeholder involvement remain critical in the deployment of AI systems in education. This review underscores the importance of targeted human-centerd design and active end-user participation to harness AI’s potential effectively, advocating for future research that integrates cognitive science insights to optimize human-AI teamwork and enhance learning and decision-making outcomes.