LLMs provide more detailed explanations for incorrect answers than correct ones in dental licensing examinations¶
Claim · All claims
Evidence · 1 study · quant-synthesisr2·q2
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person · recheck by 2028: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Two included studies reported that LLMs provided longer and more detailed explanations for incorrect answers than for correct ones in dental licensing examinations. → Liu Mingxin 2025
Evidence¶
Liu Mingxin 2025¶
Liu Mingxin, Okuhara Tsuyoshi, Huang Wenbo, Ogihara Atsushi, Nagao Hikari Sophia, Okada Hiroko, Kiuchi Takahiro. (2025). Large Language Models in Dental Licensing Examinations: Systematic Review and Meta-Analysis. International Dental Journal. https://doi.org/10.1016/j.identj.2024.10.014
q2 · i? · quant-synthesis · r2
Narrative finding from the systematic review's discussion section, attributed to two included studies. The review reports that "LLMs provided longer and more detailed explanations for incorrect answers than for correct ones".
"Two included studies mentioned that LLMs provided longer and more detailed explanations for incorrect answers than for correct ones."
Discussion¶
Related Claims¶
- Gen-AI hallucinates sources and values and produces convincing but incorrect explanations, risking student misinformation — related
- LLMs perform worse on dental licensing examinations than on medical licensing examinations — related
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by process:wiki-ingest on 2026-10-31 |
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