UniER: A Unified Benchmark for Item-level and Path-level Exercise Recommendation
Personalized exercise recommendation dynamically aligns pedagogical resources with individual knowledge mastery, which is crucial for satisfying students' dynamic learning needs in modern education. The field is currently driven by two dominant paradigms: Item-Level Exercise Recommendation (ILER) optimizes for immediate single-step state transitions, while Path-Level Exercise Recommendation (PLER) constructs coherent learning paths to maximize cumulative gains. Despite sharing the same ultimate objective, disparate evaluation setups have kept these two lines of research isolated, hindering unified benchmarking and fair comparison. To fill the gap, in this paper, we present a Unified Bench...
| Authors | Xinghe Cheng, Guiyong Zhuang, Yusheng Xie et al. |
|---|---|
| Primary category | cs.IR |
| Published | 16 May 2026 |
| Last updated at source | 16 May 2026 |
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