That's Not the Feedback I Need! -- Student Engagement with GenAI Feedback in the Tutor Kai

TL;DR

This study investigates how undergraduate students engage with Generative AI feedback in a programming education context, revealing differences based on experience and highlighting challenges in comprehension and effective use.

Contribution

The paper provides empirical insights into student attention and perception of GenAI feedback in programming tasks, comparing it with traditional compiler feedback and analyzing experience-based differences.

Findings

GenAI feedback attracts significant visual attention, especially among inexperienced students.

Inexperienced students struggle to understand and effectively utilize GenAI feedback.

More experienced students use GenAI feedback more efficiently and request it less frequently.

Abstract

The potential of Generative AI (GenAI) for generating feedback in computing education has been the subject of numerous studies. However, there is still limited research on how computing students engage with this feedback and to what extent it supports their problem-solving. For this reason, we built a custom web application providing students with Python programming tasks, a code editor, GenAI feedback, and compiler feedback. Via a think-aloud protocol including eye-tracking and a post-interview with 11 undergraduate students, we investigate (1) how much attention the generated feedback received from learners and (2) to what extent the generated feedback is helpful (or not). In addition, students' attention to GenAI feedback is compared with that towards the compiler feedback. We further investigate differences between students with and without prior programming experience. The findings indicate that GenAI feedback generally receives a lot of visual attention, with inexperienced students spending twice as much fixation time. More experienced students requested GenAI less frequently, and could utilize it better to solve the given problem. It was more challenging for inexperienced students to do so, as they could not always comprehend the GenAI feedback. They often relied solely on the GenAI feedback, while compiler feedback was not read. Understanding students' attention and perception toward GenAI feedback is crucial for developing educational tools that support student learning.