Feedback is a critical component of the student learning process. However, for instructors, particularly in large courses, it can be a daunting task to provide effective, tailored feedback based on each student’s unique learning trajectory, needs, and performance. Effective feedback facilitates the development of self-assessment and reflection, enabling students to adjust their learning behavior if needed. In undergraduate courses in higher education, instructors often provide students with a variety of resources to help them understand the course material. They also design tasks for students to practice and apply their understanding prior to major assessments such as exams and projects. Critically, most instructors have limited insight into students’ learning processes and engagement with these learning materials or tasks outside of lectures or class meetings. This lack of visibility makes it challenging for instructors to provide timely feedback on students’ learning processes.

This project aims to address the following three questions through collecting survey data and gathering learning material transactional and performance data:

1. How do students perceive LA-based, personalized feedback?
2. How do LA-based personalized feedback messages affect student engagement with course assignments and materials?
3. How do LA-lased, personalized feedback messages affect student learning outcomes?

Research and Analytics will assist you in implementing LA-based personalized feedback and in disseminating it in your disciplines.

Presentations and Publications

Russell, J. E., Smith, A., George, S., & Brummett, A. (2024, March). Personalized feedback leveraging learning analytics in a large lecture course. A poster presentation at LAK Annual Conferences in Kyoto Japan.

Russell, J. E., Smith, A., George, S., Brummett, A., & Nasrollahian, S. (2023, April). Personalized feedback leveraging learning analytics in a large lecture course. A paper presentation at AERA Annual Conferences in Chicago Illinois.