Assessment as Learning in Medical Education: Feasibility and Perceived Impact of Student-Generated Formative Assessments
Notice bibliographique
Résumé
BACKGROUND: Self-regulated learning (SRL) is gaining widespread recognition as a vital competency that is desirable to sustain lifelong learning, especially relevant to health professions education. Contemporary educational practices emphasize this aspect of undergraduate medical education through innovative designs of teaching and learning, such as the flipped classroom and team-based learning. Assessment practices are less commonly deployed to build capacity for SRL. Assessment as learning (AaL) can be a unique way of inculcating SRL by enabling active learning habits. It charges students to create formative assessments, reinforcing student-centered in-depth learning and critical thinking. OBJECTIVE: This study aimed to explore, from the learners' perspectives, the feasibility and perceived learning impact of student-generated formative assessments. METHODS: This study relied on a convergent mixed methods approach. An educational intervention was deployed on a cohort of 54 students in the second year of a 6-year undergraduate medical program as part of a single-course curriculum. The AaL intervention engaged students in generating assessments using peer collaboration, tutor facilitation, and feedback. The outcomes of the intervention were measured through quantitative and qualitative data on student perceptions, which were collected through an anonymized web-based survey and in-person focus groups, respectively. Quantitative survey data were analyzed using SPSS (IBM), and qualitative inputs underwent thematic analysis. RESULTS: The students' overall score of agreement with the AaL educational intervention was 84%, which was strongly correlated with scores for ease and impact on a 5-point Likert-type scale. The themes that emerged from the qualitative analysis included prominent characteristics, immediate gains, and expected long-term benefits of engagement. The prominent characteristics included individuals' engagement, effective interdependencies, novelty, and time requirements. The identified immediate gains highlighted increased motivation and acquisition of knowledge and skills. The expected long-term benefits included critical thinking, problem solving, and clinical reasoning. CONCLUSIONS: As a form of AaL, student-generated assessments were perceived as viable, constructive, and stimulating educational exercises by the student authors. In the short term, the activity provided students with a fun and challenging opportunity to dive deeply into the content, be creative in designing questions, and improve exam-taking skills. In the long term, students expected an enhancement of critical thinking and the inculcation of student-centered attributes of self-regulated lifelong learning and peer collaboration, which are vital to the practice of medicine.
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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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 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 ».