Students' Perceptions of the Script Concordance Test and Its Impact on Their Learning Behavior: A Mixed Methods Study
Bibliographic record
Abstract
The Script Concordance Test (SCT) is increasingly used in postgraduate and undergraduate education as a method of summative clinical assessment. It has been shown to have high validity and reliability but there is little evidence of its use in veterinary education as assessment for learning. This study investigates some students' perceptions of the SCT and its effects on their approaches to learning. Final-year undergraduates of the School of Veterinary Medicine and Science (SVMS) at the University of Nottingham participated in a mixed-methods study after completing three formative SCT assessments. A qualitative, thematic analysis was produced from transcripts of three focus group discussions. The quantitative study was a survey based on the analyses of the qualitative study. Out of 50 students who registered for the study, 18 participated in the focus groups and 28 completed the survey. Clinical experience was regarded as the most useful source of information for answering the SCT. The students also indicated that recall of facts was perceived as useful for multiple-choice questions but least useful for the SCT. Themes identified in the qualitative study related to reliability, acceptability, educational impact, and validity of the SCT. The evidence from this study shows that the SCT has high face validity among veterinary students. They reported that it encouraged them to reflect upon their clinical experience, to participate in discussions of case material, and to adopt a deeper approach to clinical learning. These findings strongly suggest that the SCT is potentially a valuable method for assessing clinical reasoning and enhancing student learning.
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 | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 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".