Join RAFT: Research on AI, Feedback + Teaching – a Cross-Institutional Study of AI-Influenced Feedback Practices

Project Overview

Generative AI is rapidly changing how students approach learning, revision, and academic work. At the same time, feedback remains one of the most powerful influences on student learning, yet decades of research demonstrate persistent gaps between instructors’ intentions and students’ engagement with feedback.

This funded multi-institutional research project examines how generative AI is reshaping feedback practices in higher education. Rather than focusing solely on AI policies or academic integrity concerns, the project investigates how AI may influence the ways instructors provide feedback, how students interpret and engage with feedback, and how feedback ultimately supports learning.

The project is supported through a 4-VA Collaborative Research Grant and includes collaborators from George Mason University, the University of Virginia, James Madison University, the College of William & Mary, Trinity University (Texas), and the National University of Singapore.

Research Goals

The project seeks to:

• Understand how instructors make decisions about feedback in AI-rich learning environments.
• Examine how students interpret, use, and respond to feedback when AI tools are available.
• Identify patterns of AI-mediated feedback practices across institutions and disciplines.
• Develop evidence-based recommendations and faculty development resources to support effective, ethical, and learning-centered feedback practices.

Who We Are Looking For

We are seeking three additional faculty collaborators to join the project team.

We are particularly interested in faculty with expertise or experience in one or more of the following areas:

• Quantitative research methods, survey design, statistics, or educational measurement
• STEM disciplines (e.g., engineering, computer science, biology, chemistry, mathematics)
• Professional programs (e.g., business, nursing, health sciences, public health, social work)
• Artificial intelligence, learning technologies, or digital pedagogy
• Assessment, feedback, or student learning research

Prior research experience is welcome but not required.

Role of Faculty Collaborators

Faculty collaborators will serve as content experts and research team members. Activities may include:

• Reviewing and refining research instruments
• Participating in project planning meetings
• Assisting with data collection and interpretation
• Contributing disciplinary perspectives to analysis and sensemaking
• Participating in dissemination activities, including conference presentations and publications

Collaborators will receive a $1,000-$2,000 stipend, depending on their level of participation and leadership in the project.

Anticipated Timeline

Fall 2026

• Instructor and student data collection
• Cross-institutional team meetings
• Preliminary analysis

Spring 2027

• Data analysis
• Development of faculty resources
• Conference proposals and manuscript preparation

Potential Benefits

Collaborators will have opportunities to:

• Participate in a funded, multi-institutional research project
• Contribute to emerging scholarship on AI and teaching and learning
• Build cross-disciplinary and cross-institutional research partnerships
• Co-author conference presentations and publications
• Help shape evidence-based approaches to AI and feedback in higher education

Questions? Contact Breana Bayraktar