Pedagogical-criterion breakdown shows worked examples in only about 42% of responses, the weakest criterion despite 312 practice problems in the knowledge base¶

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Roughly 65% of responses had fully enumerated steps, 78% correct notation, 42% worked examples, 71% sub-question coverage, and 80% satisfactory depth. → Sushan Adhikari 2026

Evidence¶

Sushan Adhikari 2026¶

Sushan Adhikari. (2026). AlgoRAG: Retrieval-Augmented Generation for Theoretical Computer Science Education — A Comprehensive Evaluation Framework for Algorithm Analysis and Complexity Theory. arXiv preprint. https://arxiv.org/abs/2609.14572 doi:10.48550/arxiv.2609.14572

q2 · i? · design · r2

Rubric-criterion breakdown of the 179 responses. The article reports "approximately 42% of responses" included worked examples, the lowest criterion, noting the knowledge base's 312 practice problems were under-exploited by retrieval; notation was correct in roughly 78% of responses.

"Concrete worked examples appeared in approximately 42% of responses — the criterion with the most headroom for improvement, since the knowledge base contains 312 practice problems that could be retrieved more aggressively."

Discussion¶

Related Claims¶

• AlgoRAG answered all 179 TCS exam-style questions successfully with a mean response time of 38.0 seconds and a pedagogical quality score of 0.7620 — a broader claim this one bears on
• Interleaving category examples improves inductive category learning for visual and mathematical materials, but not for expository texts or word categories — related
• Theoretical quality of agent outputs strongly correlates with benchmark performance (r = 0.656) — related