Course-based undergraduate research experiences (CUREs) broaden access to authentic scientific inquiry through responsive instructor support as research problems become increasingly complex. Generative artificial intelligence (GenAI) may extend this support by providing individualized assistance that can adapt as student needs change. However, how embedding GenAI within a CURE to provide support across the research process impacts student inquiry, collaboration, and scientific reasoning remains unresolved. Here we use longitudinal qualitative data collected across three semesters of a bioinformatics and genomics CURE to show that GenAI expanded the intellectual reach of the research experience in three distinct ways. First, personalized, on-demand scaffolding allowed students to move beyond the boundaries of instructor expertise and transform their own interests into researchable inquiry, with all teams developing distinct self-directed projects rather than selecting instructor-provided topics. Second, GenAI became part of the distributed cognitive system of research teams, helping novice researchers communicate and coordinate across differentiated expertise without eliminating specialization. Third, expanded capability did not replace the need for disciplinary judgment. Students increasingly validated, revised, or rejected AI-generated contributions, such that research independence emerged through retained intellectual responsibility. Together, these findings suggest that GenAI can extend the reach of CUREs by expanding what novice researchers can investigate, how they can collaborate, and the level of responsibility they can assume while preserving human judgment central to authentic scientific inquiry.
It is argued that the central educational issue is not whether the generative artificial intelligence is beneficial or harmful in itself, but under what conditions AI-assisted performance becomes genuine, transferable research competence.
Mohamad Rami Al Jundi, Bashar Abdulkareem Alali, Rama Alothman et al.· Research Journal of Maaref U...· 0 citations
An assignment developed for a large-enrollment, 100-level, general-education, environmental science course at the University of Arizona that provides students with structured opportunities to experiment with and critically evaluate GenAI tools.
T. Crimmins, K. Prudic· Prompt A Journal of Academic...· 0 citations
As generative AI (GenAI) use among students increases, educators face growing questions about how to support learning while addressing ethical and institutional concerns. This exploratory study examines a guided inquiry activity in which students co-designed a GenAI course policy.
Students first developed in...
Ashish Hingle, Aditya Johri· International Conference on...· 0 citations
This article re-examines the role of assessment within the rapidly evolving landscape of artificial intelligence (AI), focusing specifically on differentiated instruction, and highlights the potential of AI to not only streamline the assessment process but also cultivate a more equitable and student-centered learning e...
H. Trinh· VNU Journal of Foreign Studi...· 0 citations
It is concluded that generative AI adoption is less of a ready-made solution and more of a catalyst that can lead faculty and staff to reexamine teaching, assessment, and institutional evidence-gathering in the age of generative AI.
M. Saxena, J. Reilly, Michelle M. Rego et al.· International Journal of AI...· 0 citations
The results suggest that the pedagogical behavior of AI tutors may not be easily steered through system prompts alone: embedding established SRL and CE frameworks did not produce detectable improvements on any preregistered outcome in a large, ecologically valid deployment.
Maximilian Georg Barth, Sverrir Thorgeirsson, K. Etemadi et al.· International Computing Educ...· 0 citations
Known for his clear and elegant writing style, Bertsekas shaped fields from control and optimization to large-scale computation and artificial intelligence.
MIT News · Artificial Intelligence· news.mit.eduJul 7, 2026
The professor of physics and inaugural director of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions will lead LNS and continue his research in particle physics.
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