Claims

The review reports that an AI-plus-faculty-guidance approach outperformed both AI-only and traditional teaching in ultrasonography training

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

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? In ultrasonography teaching, a combined AI-plus-faculty-guidance approach outperformed both AI-only and traditional teaching, per one included randomized trial the review cites. → Liu Xiaoliu 2026

Evidence

Liu Xiaoliu 2026

Liu Xiaoliu, Pan Jiayue, Zhang Chengyi, Wang Xiaomei, Wan Jinghua, Wang Qiang. (2026). Effectiveness of large language model-based teaching interventions in medical education: a systematic review and stratified meta-analysis of 14 studies. BMC Medical Education. https://doi.org/10.1186/s12909-026-09879-0

q2 · i? · quant-synthesis · r2

Second-hand finding reported in the review's discussion, attributed to Hong et al.'s randomized ultrasonography trial (Hong 2026, n = 45 in Table 1, faculty-guided tutoring mode). The review attributes the result; it was not re-analyzed here, so quality is capped at 2 and no effect size is available.

"In ultrasonography teaching, a combined AI-plus-faculty-guidance approach outperformed both AI-only and traditional teaching [29]."

Discussion

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