Jointly Predicting Courses and Grades Using a Transformer-Based Model
Existing predictive models in learning analytics often treat student academic history as a simple sequence, overlooking the concurrent nature of courses taken within a semester. This simplification can lead to inaccurate performance predictions, particularly for students with heavy or challenging course loads. This paper introduces a TRansformer for Academic Course-grade Estimation (TRACE) that addresses this limitation by jointly predicting both the set of courses a student will take and their
Record details
Published: 13 August 2026
Source: arXiv cs.AI
Category: Research
Topics: Children & education
Retrieved: 14 August 2026
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ethics.ai (13 August 2026), “Jointly Predicting Courses and Grades Using a Transformer-Based Model,” evidence record 19444, https://ethics.ai/record/19444 (originally published by arXiv cs.AI).
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