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Case study reveals distinct learner-centered feedback patterns among computer science students, highlighting tailored guidance across academic levels and performance tiers.
Feedback plays a crucial role in guiding students toward achieving their learning goals. The conceptualization of feedback has shifted from teacher-centered to learner-centered approaches, underscoring the evolving role of educators and students in educational settings. Despite the growing emphasis on learner-centered feedback frameworks, there remains a gap in understanding how these frameworks are implemented in actual teaching practices. This case study addresses this gap by examining the alignment of current feedback practices with learner-centered feedback principles in the Computer Science School at an Australian higher education. We gathered feedback data from the Master of Data Science and Bachelor of Computer Science program that were communicated through the Learning Management System. The dataset included feedback from 4,959 students, provided by approximately 200 instructors across 95 courses. To ensure a representative sample, 10% of feedback entries from each course were analyzed, resulting in 16,408 feedback sentences. The findings reveal a pronounced emphasis on the sensemaking dimension, particularly in evaluating students’ strengths and weaknesses to help them understand their performance. Feedback patterns varied by student performance, with high achievers receiving affirmations, medium achievers receiving actionable suggestions, and low achievers receiving comprehensive evaluations. Feedback in the Master’s program prioritized future impact by offering actionable guidance for advanced tasks, while the Bachelor’s program emphasized fostering agency through active student engagement and participation. • Strong focus on feedback highlighting strengths and weaknesses in both programs. • Master’s program feedback emphasizes guiding students’ future performance. • Bachelor’s program feedback emphasizes fostering student participation and engagement. • Feedback on strengths and weaknesses is typically followed by future guidance.
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Aldino et al. (2025) studied this question.
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