Correct-answer-trap cases concentrate in specific question types where common flawed reasoning happens to produce the correct numerical answer, with the top two question types accounting for 71% of all TM cases¶
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Evidence · 1 study · associationalr?·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
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q2 i? In the Eedi dataset, the top two question types alone account for 71% of all true-misconception (TM) cases, rather than failures distributing uniformly across questions. → Moiz Imran and Sahan Bulathwela 2026
Evidence¶
Moiz Imran and Sahan Bulathwela 2026¶
Moiz Imran and Sahan Bulathwela. (2026). Catching TheCorrectAnswerTrap: Characterising AI Tutor Blind Spots When Analysing Student Reasoning. arXiv preprint. https://arxiv.org/abs/2605.23925 doi:10.48550/arxiv.2605.23925
q2 · i? · associational · r?
Analysis of the Eedi benchmark of 20,964 real student responses, with 343 TM cases labelled by expert raters. The authors report that "The top two question types alone account for 71% of all TM cases", visualised in Fig. 1.
"Table 1 shows that TM cases concentrate in specific question types rather than distribute uniformly. The top two question types alone account for 71% of all TM cases."
Discussion¶
Related Claims¶
- CAT concentration is item-driven, not category-driven: removing the two vulnerable items collapses the procedural/conceptual odds ratio from 5.6 to 1.0 — related
- On the PRM800K validation dataset, detection rates dropped by 10.5 percentage points when final answers were correct, consistent with the correct answer trap extending beyond the Eedi data — related
- A task-specific prompt with explicit guidance about correct-answer cases significantly outperforms literature-based PedCoT prompting on TM test cases (84% vs 59% accuracy) — related
- LLMs systematically underestimate fraction items whose difficulty is driven by misconceptions (the \"Easy Trap\") — related
- A student's incorrect 1/3 response to a shaded-region task still shows correct command of fraction notation — related
- Student errors on underestimated fraction items reflect systematic misconception patterns rather than random error — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
cat-failures-concentrate-in-two-question-types |
title |
Correct-answer-trap cases concentrate in specific question types where common flawed reasoning happens to produce the correct numerical answer, with the top two question types accounting for 71% of all TM cases |
description |
Correct-answer-trap cases concentrate in specific question types where common flawed reasoning happens to produce the correct numerical answer, with the top two question types accounting for 71% of all TM cases |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — moiz-imran-and-sahan-bulathwela-2026 |
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