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Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)

◐ medium · 2026-06-10generative-ai, llm, ai-literacy, policy-maker, higher-ed, student-experience, intelligent-tutoring, scaffolding, k-12, stem-education

Yifan Liu, Jaime Arguello, Orland Hoeber, Chang Liu et al. — cs.IR, cs.AI, cs.HC

This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS), which examined how GenAI is reshaping academic search systems and research practices. Three thematic clusters emerged: foundations and principles (guiding theories, design principles for human-centered GenAI-enhanced search), applications and opportunities, and search-as-learning — the idea that academic search systems should foster higher-order cognitive processes including synthesis, critical evaluation, and knowledge construction. The workshop emphasized transparency, credibility, research integrity, and long-term scholarly needs. The 'search-as-learning' theme is most directly relevant to AI Literacy and AI Education domains, as it reframes academic search not merely as information retrieval but as a learning activity. This connects to Formative Assessment and Self Regulated Learning research exploring how AI-mediated research tools shape student learning processes.

Connected Concepts

  • AI Literacy
  • AI Education
  • Formative Assessment
  • Self Regulated Learning

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    • Citation

    Liu, Y., Arguello, J., Hoeber, O., et al. (2026). Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS). arXiv:2606.08936.