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MOOC-CS Prerequisite Benchmark

MOOC-CS is a computer-science-focused prerequisite-relation benchmark assembled from Massive Open Online Course (MOOC) materials, originating from Pan et al. (ACL 2017). It comprises Coursera lecture captions in the Data Structures and Algorithms and Machine Learning domains, with course core concepts extracted from the captions and manually annotated ordered concept pairs labeled as prerequisite or not. Each course release provides three file types: a JSON Captions file (tokenized, POS-tagged video transcripts), a Core_concepts file listing per-domain concepts, and a Labeled file storing concept pairs with their prerequisite labels. The benchmark is used to evaluate prerequisite-link retrieval systems, with a fixed candidate concept pool and ranking metrics such as Recall@kk. The default release is English-only, which is why graph-aware retrieval studies report separately on language-matched query and encoder controls when extending evaluations to multilingual MOOC settings.

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Updated 2026-05-17

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Auditable Strict-Parity Evaluation of Prerequisite-Graph Retrieval for RAG under Leakage Controls

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