Longitudinal assessment of competency development at The Ohio State University using the competency-based veterinary education (CBVE) model
Notice bibliographique
Résumé
With the development of the American Association of Veterinary Medical Colleges' Competency-Based Veterinary Education (CBVE) model, veterinary schools are reorganizing curricula and assessment guidelines, especially within the clinical rotation training elements. Specifically, programs are utilizing both competencies and entrustable professional activities (EPAs) as opportunities for gathering information about student development within and across clinical rotations. However, what evidence exists that use of the central tenets of the CBVE model (competency framework, milestones and EPAs) improves our assessment practices and captures reliable and valid data to track competency development of students as they progress through their clinical year? Here, we report on validity evidence to support the use of scores from in-training evaluation report forms (ITERs) and workplace-based assessments of EPAs to evaluate competency progression within and across domains described in the CBVE, during the final year clinical training period of The Ohio State University's College of Veterinary Medicine (OSU-CVM) program. The ITER, used at the conclusion of each rotation, was modified to include the CBVE competencies that were assessed by identifying the stage of student development on a series of descriptive milestones (from pre-novice to competent). Workplace based assessments containing entrustment scales were used to assess EPAs from the CBVE model within each clinical rotation. Competency progression and entrustment scores were evaluated on each of the 31 rotations offered and high-stakes decisions regarding student performance were determined by a collective review of all the ITERs and EPAs recorded for each learner across each semester and the entire year. Results from the class of 2021, collected on approximately 190 students from 31 rotations, are reported with more than 55 299 total competency assessments combined with milestone placement and 2799 complete EPAs. Approximately 10% of the class was identified for remediation and received additional coaching support. Data collected longitudinally through the ITER on milestones provides initial validity evidence to support using the scores in higher stakes contexts such as identifying students for remediation and for determining whether students have met the necessary requirements to successfully complete the program. Data collected on entrustment scores did not, however, support such decision making. Implications are discussed.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».