Accuracy of self‐monitoring: does experience, ability or case difficulty matter?
Notice bibliographique
Résumé
CONTEXT: The ability to self-monitor one's performance in clinical settings is a critical determinant of safe and effective practice. Various studies have shown this form of self-regulation to be more trustworthy than aggregate judgements (i.e. self-assessments) of one's capacity in a given domain. However, little is known regarding what cues inform learners' self-monitoring, which limits an informed exploration of interventions that might facilitate improvements in self-monitoring capacity. The purpose of this study is to understand the influence of characteristics of the individual (e.g. ability) and characteristics of the problem (e.g. case difficulty) on the accuracy of self-monitoring by medical students. METHODS: In a cross-sectional study, 283 medical students from 5 years of study completed a computer-based clinical reasoning exercise. Confidence ratings were collected after completing each of six cases and the accuracy of self-monitoring was considered to be a function of confidence when the eventual answer was correct relative to when the eventual answer was incorrect. The magnitude of that difference was then explored as a function of year of seniority, gender, case difficulty and overall aptitude. RESULTS: Students demonstrated accurate self-monitoring by virtue of giving higher confidence ratings (57.3%) and taking a shorter time to work through cases (25.6 seconds) when their answers were correct relative to when they were wrong (41.8% and 52.0 seconds, respectively; p< 0.001 and d > 0.5 in both instances). Self-monitoring indices were related to student seniority and case difficulty, but not to overall ability or student gender. CONCLUSIONS: This study suggests that the accuracy of self-monitoring is context specific, being heavily influenced by the struggles students experience with a particular case rather than reflecting a generic ability to know when one is right or wrong. That said, the apparent capacity to self-monitor increases developmentally because increasing experience provides a greater likelihood of success with presented problems.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».