Aug 2026· International Conference on Artificial Intelligence in Education· Vol 2, pp. 91-109· 0 citations· 42 references
Computer Science
Abstract
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 individual policy proposals focused on appropriate and ethical use of GenAI, then collaboratively refined them by incorporating diverse stakeholder perspectives. The following research questions guided the study: (1) what practical factors do students prioritize in their GenAI use policies, and how do they justify these choices? and (2) how do participants reflect on the policy design process? Participants first completed readings, then used GenAI to brainstorm initial policy ideas. Next, they articulated their own perspectives through a written assignment and a course policy they designed individually. Finally, they incorporated diverse stakeholder perspectives by collaborating with peers to develop a collective policy.
Analysis of student artifacts and group discussions showed that participants prioritized training for students and instructors, standardized procedures for disclosing AI use, and stronger institutional support. Participants also wanted greater involvement in GenAI-related decision-making. They described the policy design process as a way to engage with multiple perspectives and the inherent trade-offs involved in governing AI use.
This study offers pedagogical insights into how policy Co-design activities can surface student values, concerns, and sensemaking about GenAI in educational contexts.
This phenomenological study examines graduate students’ lived experiences using GenAI as a thinking partner in a fully online master’s-level instructional design course at a regional public university in Florida, highlighting how GenAI mediates reflection, authorship, and learning in authentic design environments.
M. Stork, Krista Bixler· Florida Journal of Education...· 0 citations
This study examined students’ AI literacy, perceived learning benefits, and ethical awareness following participation in a structured, AI-integrated classroom activity. The study also investigated the relationships among these constructs and examined whether perceived learning benefits mediate the relationship betwee...
Dalia Alsaiid Abdelbaki· Frontiers in Education· 0 citations
Within a university writing instruction context, generative AI (gen AI) is changing how writing is learned, demonstrating positive impact potential through boosting learners’ motivation, automating instructional tasks, and offering instantaneous, personalised feedback. As a result, these are times of unprecedented oppo...
R. Donnelly, Ita Kennelly· Journal of Learning Developm...· 0 citations
Generative artificial intelligence (GenAI) is becoming an increasingly common part of educational practice, raising new questions about how educators determine when AI-generated materials are appropriate for supporting students with diverse needs in inclusive classrooms. This mixed-methods study examined how 351 educat...
T. De Giuseppe, J. Delello· European Journal of Special...· 0 citations
This case study examines how a high school US history teacher navigated the purposes and values of history education while integrating supplementary curricular materials designed to center multiple perspectives. Although such materials are widely available online, less is known about how they are enacted in classro...
M. Pol· Social Studies Research and...· 0 citations
Investigating how GenAI shapes creative processes, learning, and ethical practices across multiple course levels provides actionable insights for designing AI-integrated illustration curricula that foster creativity, ethical awareness, and critical engagement.
Cansu Akverdi, G. Baykal· Proceedings of the 14th Nord...· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.