A Large-Scale Observational Study on Obtaining Lightweight, Randomized Weekly Student Feedback
Yunsung Kim, Hansol Lee, Candace Thille, and Chris Piech

TL;DR
This large-scale observational study examines the impact of the HRCF feedback method on student course evaluations across diverse course sizes over four years.
Contribution
It provides empirical evidence on the effects of sustained lightweight, randomized weekly feedback on student perceptions in higher education.
Findings
First-time HRCF use shows no significant change in ratings.
Continued HRCF use correlates with small improvements in learning-related ratings for small/medium courses.
No significant effects observed for large courses or on instructional quality and organization.
Abstract
Conventional methods of obtaining student feedback on course experience face a fundamental tradeoff between feedback frequency and quality: as feedback requests become more frequent, participation often declines, and responses become less thoughtful over time. To obtain both timely and thoughtful feedback from students, Kim and Piech (Learning at Scale, 2023) recently proposed a simple, lightweight course feedback mechanism: surveying each student a small number of times per term during randomly selected weeks. Named High-Resolution Course Feedback (HRCF), this method has been shown to elicit feedback that instructors find helpful without imposing excessive burden on students. An important question, however, remains unanswered: is the use of this simple method associated with measurable improvements in students' actual course experiences? We study HRCF use across 103 course offerings,…
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