Medical Students’ Perception and Perceived Value of Peer Learning in Undergraduate Clinical Skill Development and Assessment: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: The effectiveness of peer learning in clinical skill development is well recognized and researched, given the many benefits gained such as enhanced learning, alleviation of the burden on faculty, and early development of teaching skills for future doctors. However, little is known in terms of its effectiveness as an assessment tool and the extent to which peer assessment can be relied upon in the absence of faculty support. OBJECTIVE: This study was conducted to assess medical students' perception toward peer learning, which is based on self-regulated learning as a tool of assessment, and to compare peer evaluation with faculty evaluation of clinical skill performance. METHODS: A cohort of 36 third-year medical students were exposed to peer learning (same-level) in clinical skills education for 3 months. A convergent mixed methods approach was adapted to collect data from 3 sources, namely, students' perception of peer learning, performance scores, and reflective observational analysis. A 5-point Likert-type scale was used to assess students' (n=28) perception on the value of peer learning. The students were asked to assess their peers by using a preset checklist on clinical skill performance, and scores were compared to faculty assessment scores. Reflective observational data were collected from observing video recordings of some of the peer learning sessions. The findings from all 3 sources were integrated using joint display analysis. RESULTS: Out of 28 students, 25 students completed the survey and 20 students perceived peer learning as valuable in clinical skills education. The mean score of peer assessment was higher than that of faculty assessment. There was a significant difference in student performance between supervised teaching and peer learning groups (P=.003). Most students focused on the mastery of skill with little attention to the technique's quality. Further, students were unable to appreciate the relevance of the potential clinical findings of physical examination. CONCLUSIONS: Peer learning in clinical skills education, based on self-regulated learning, empowers students to develop a more responsible approach toward their education. However, peer assessment is insufficient to evaluate clinical skill performance in the absence of faculty support. Therefore, we recommend that peer learning activities be preceded by supervised faculty-taught sessions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".