Investigating the Reliability and Validity of Self and Peer Assessment to Measure Medical Students’ Professional Competencies
Bibliographic record
Abstract
The use of peer assessment through a multisource feedback process has gained recognition as a reliable and valid method to assess the characteristics of professionals and trainees. A total of 168 first-year medical students completed a 15-item questionnaire to self-assess their professional work habits and interpersonal abilities. Each student was expected to identify 8 first-year classmates to complete a corresponding 15-item peer assessment. Although the self and peer assessment questionnaires had strong reliability (Cronbach’s α = 0.85 and 0.91, respectively), an exploratory factor analysis resulted in a 3- and 2- factor solution, respectively. The third factor was associated with items related to students’ personal attributes. Significantly lower mean score differences for the self-report assessment were found for all 15 items (Cohen’s d = 0.27 to 1.39, p gards to the construct validity and stability of measures between self and peer assessment measures. The need for self-awareness of students’ strengths and limitations, however, is recommended as part of their development in a profession that emphasizes self-regulation.
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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 | 0.040 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".