Characterizing Complexity and Frequency of Feedback Given to Students: What Actually Helps Achieve Learning Outcomes?

This project is aimed at improving learning outcomes in programming courses at UT Austin, specifically targeting ECE312 (Software Design and Implementation I) and ECE360C (Algorithms), but that can potentially be expanded to other programming courses and beyond. The project is designed to enhance students' understanding of fundamental concepts by characterizing the complexity and frequency of feedback provided during completion of assignments. This initiative will also develop a supplemental resource for faculty/instructors, with a focus on aligning feedback with desired learning outcomes rather than simply guiding students to correct solutions.

The project addresses the common issue in courses where feedback often focuses on achieving the "right" solution, particularly in programming assignments where automatic graders return test case results instantaneously. The project will utilize the Autograder tool in Gradescope to explore different levels of feedback complexity and frequency, aiming to find the optimal combination that maximizes students' achievement of learning outcomes. We understand that different types of learning outcomes may require varying combinations of feedback complexity and frequency. The project will thoroughly characterize these combinations and create actionable guidelines for instructors to provide feedback aligned with specific learning outcomes.