The exact text we saved

This is the version exactly as it was saved, character for character. The SHA-256 hash below is a 64-character code worked out from that text. Run the same text through SHA-256 and you get the same code; change a single letter and the code comes out completely different. Each version also stores the previous version’s hash, which chains them together so no version can be swapped out quietly.

TRUVACE RECORD VERSION
record: TRV-2026-2786
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:23:43.221780Z
status: published
lens: g_space
sector: education
headline: Meta-analysis of randomized controlled trials comparing outcomes of artificial intelligence-based teaching versus traditional-based teaching in medical education
dek: AIMS: To evaluate comparative outcomes of artificial Intelligence (AI)-based and traditional-based teaching in medical education. METHODS: The literature search was carried out in CENTRAL, CINAHL, Web of Science, MEDLINE, and EMBASE to identify randomized controlled trials (RCTs) comparing AI-based versus traditional-based teachings in medical education. Estimate of effect size was determined for knowledge score, skills score, and teaching satisfaction score via fixed-effect modelling. RESULTS: Fourteen RCTs enr…
gain_title: A meta-analysis of 14 randomized trials with 1,116 medical students found AI-based teaching produced higher knowledge scores (SMD 0.36), skills scores (SMD 0.78) and satisfaction scores (SMD 0.97) than traditional teaching.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 14 randomized trials with 1,116 medical students found AI-based teaching produced higher knowledge scores (SMD 0.36), skills scores (SMD 0.78) and satisfaction scores (SMD 0.97) than traditional teaching.
gain_evidence: AI-based teaching was associated with significantly higher knowledge score (standardized mean difference (SMD): 0.36 | skills score (SMD: 0.78, 95% CI, 0.57-0.99, P < .00001) | teaching satisfaction score (SMD: 0.97, 95% CI, 0.66-1.29, P < .00001)
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis in the Postgraduate Medical Journal pooled 14 randomized controlled trials with 1,116 medical students, split evenly between AI-based teaching (558) and traditional teaching (558). AI-based teaching came out ahead on all three outcomes: knowledge (SMD 0.36), skills (SMD 0.78) and satisfaction (SMD 0.97).

The gains were largest for skills and satisfaction. Subgroup analyses by practical versus theoretical courses and by course length (shorter or longer than one week) matched the main results, and meta-regression showed practical courses added to the effect on knowledge (P = .002) and skills (P = .0001).

The authors rate this as level 1a evidence but caution that results may be affected by publication and reporting bias and by high variation between studies. They call for studies of AI-based teaching in postgraduate, specialty and subspecialty training.
limitation: The authors say the evidence may be subject to publication and reporting bias, with high heterogeneity between studies, and the trials covered medical students rather than postgraduate trainees.
tag: Evidence-backed gain
key_points: Fourteen randomized controlled trials were included, enrolling 1,116 medical students in total. | Students were split evenly: 558 received AI-based teaching and 558 received traditional teaching. | Knowledge scores were higher with AI-based teaching (SMD 0.36, 95% CI 0.24-0.49). | Skills scores showed a larger difference (SMD 0.78, 95% CI 0.57-0.99). | Satisfaction scores showed the largest difference (SMD 0.97, 95% CI 0.66-1.29). | Meta-regression found practical courses significantly increased the effect on knowledge (P = .002) and skills (P = .0001).
rundown: The authors searched CENTRAL, CINAHL, Web of Science, MEDLINE and EMBASE for randomized trials that compared AI-based and traditional teaching in medical education. Effects on knowledge, skills and satisfaction were pooled using fixed-effect modelling.

Subgroup analyses by practical course, theoretical course, and course duration under or over one week agreed with the overall findings. Practical courses showed a significantly larger effect on knowledge and skills scores.

The authors say future work should test AI-based teaching in postgraduate settings, including specialty and subspecialty training, and note that the evidence may be subject to publication and reporting bias with high between-study heterogeneity.
sources:
- peer_reviewed | Postgraduate Medical Journal | https://doi.org/10.1093/postmj/qgag077 | 2026-05-21
prev: 0000000000000000000000000000000000000000000000000000000000000000

SHA-256 hash

349363a7f434abbec563ca775ef5403377fb6c4fe986a1fb1f4ad32dda28416a

Previous version’s hash

0000000000000000000000000000000000000000000000000000000000000000