Script concordance test examinations: Student perception and study approaches
Bibliographic record
Abstract
Introduction: Script concordance test questions (SCTs) are a style of question that has been developed based upon the script theory of information storage and retrieval. SCTs use script theory to examine a clinical reasoning construct purported to be different from that assessed by multiple-choice questions (MCQs). Evidence regarding the construct validity of SCT is somewhat limited, but generally supportive. Methods: This project involved a content-matched MCQ and SCT practice examination delivered to senior medical students (n = 211) from a single institution with an accompanying survey regarding educational consequences of SCT and MCQ examinations. Results:Students’ responses differed significantly between how they would prepare for an MCQ examination as compared to an SCT examination. These differences were present in a number of areas, including greater focus on textbooks and use of websites for MCQ examination preparation (p < 0.001). Students reported that for an SCT examination they would benefit most from in-person teaching from local consultants involved in the process of SCT generation. Students felt that they would also benefit from further instruction regarding key elements of SCT technique, and from opportunities to provide written explanations of their reasoning during the exam. Conclusions:The results suggest that SCTs have educational consequences different from MCQs. Further research into the educational consequences of SCTs, and how these consequences may differ from that of other methods of assessment, is warranted.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| grok | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| opus | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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, unvalidatedLabeled directly by 3 models reading the full record.
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".