Generative AI is rapidly transforming higher education, yet there is limited real-world data on how students actually use these tools in their learning. This project fills that gap, providing data-informed insights that can inform the development of effective instructional strategies.

This project explores students’ perspectives on the benefits and concerns of AI. It also investigates how students interact with AI tools in the classroom—examining the questions they ask, the ways they engage, and the interaction patterns associated with learning outcomes. 

Research Goals

• Understand students’ experiences with generative AI in the classroom.
• Explore students’ attitudes, beliefs, and expectations regarding AI.
• Analyze how students interact with AI tools—the questions they ask and the nature of their conversations.
• Identify the types of interaction patterns associated with better learning outcomes.

How We’re Answering These Questions

• Analyzing real student and AI interactions: examining actual conversation transcripts for a genuine view of how students use AI tools.
• Integrating multiple data sources: combining conversation data with surveys and performance measures to connect behaviors with attitudes, context, and outcomes.
• Using a large, diverse sample: thousands of students across multiple courses and disciplines for robust, generalizable findings.
• Collaborating across expertise: pairing learning analytics specialists with faculty subject matter experts.
• Applying innovative methods: blending qualitative and quantitative analysis, from hand-coding to advanced AI models like BERT and novel approaches such as Epistemic Network Analysis.

Get Involved

If you plan to implement generative AI for your students’ use in your classroom, we invite you to join our research group. We support projects involving a wide range of AI tools, from chatbots and tutors to custom GPTs. By collaborating, you’ll:

• Gain insight into how your students are engaging with AI tools.
• Help shape the research questions and direction based on your instructional context.
• Be part of presentations and publications that share findings across the academic community.

OTLT Research and Analytics will handle the IRB process, data collection, and analysis, making participation simple and straightforward. Together, we can advance the understanding of AI’s role in education and support its thoughtful, evidence-based integration into teaching and learning. Contact us for more information.