UniER: A Unified Benchmark for Item-level and Path-level Exercise Recommendation

TL;DR

UniER is a comprehensive benchmark that unifies item-level and path-level exercise recommendation evaluation, enabling fair comparison and revealing insights into their effectiveness and limitations.

Contribution

The paper introduces UniER, a unified evaluation framework with a new metric and extensive datasets, bridging the gap between ILER and PLER research.

Findings

PLER methods generally outperform ILER in effectiveness.

ILERS show limitations under data sparsity and noise.

UniER facilitates fair comparison across 18 methods.

Abstract

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 Benchmark for Exercise Recommendation (UniER), a comprehensive evaluation framework that unifies ILER and PLER. Specifically, we introduce Weighted Cognitive Gain (WCG) as a unified metric to measure cross-paradigm algorithmic performance. Our benchmark encompasses 9 datasets spanning four generation methods, facilitating the comparison of 18 representative ILER/PLER methods. Through multi-dimensional analyses covering effectiveness, generalizability, robustness, and efficiency, our results reveal the systematic dominance of PLER and expose the pedagogical failure of ILER's fragmented recommendations under extreme sparsity and noise. Furthermore, we provide an open-source codebase of UniER to foster reproducible research and outline potential directions for future investigations.