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Enregistrement W3170957831 · doi:10.1096/fasebj.2021.35.s1.02770

Synchronous vs. Asynchronous Anatomy Content Delivery during COVID‐19: Comparing Student Perceptions and Impact on Student Performance

2021· article· en· W3170957831 sur OpenAlexaffabout
Christopher J. Ramnanan, Gabrielle Di Lorenzo, Selina X. Dong, Victor Pak, Samantha Visva

Notice bibliographique

RevueThe FASEB Journal · 2021
Typearticle
Langueen
DomaineEngineering
ThématiqueAnatomy and Medical Technology
Établissements canadiensCanadian Network for Innovation in EducationUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésPerceptionThematic analysisCoronavirus disease 2019 (COVID-19)PreferencePsychologyMedical educationAsynchronous communicationMedicineMedical physicsMultimediaComputer sciencePathologyQualitative researchNeuroscienceMathematics

Résumé

récupéré en direct d'OpenAlex

Introduction/Objective While both asynchronous (ASYNCH) and synchronous (SYNCH) approaches have been used for online medical anatomy teaching during the COVID‐19 pandemic, it is unclear how ASYNCH vs. SYNCH approaches are differentially perceived by medical students, or whether these methods have any differential impact on anatomy learning. The purpose of this study was to compare first year (M1) and second year (M2) medical student perceptions and exam performance between ASYNCH and SYNCH‐delivered anatomy content. Materials/Methods University of Ottawa M1 and M2 perceptions were surveyed (with both close‐ and open‐ended items) regarding musculoskeletal (MSK; delivered to M1) and gastrointestinal/reproductive (GI/REPRO; delivered to M2) anatomy content delivery in Fall 2020. In both cohorts, approximately 50% of the sessions were delivered in each of ASYNCH (prerecorded lectures) and SYNCH (real‐time Microsoft Teams lectures) formats. Final examinations were also analyzed, comparing items that related to content from ASYNCH and SYNCH formats, with 50% of exam items tied to each approach. For both M1 and M2 cohorts, both ASYNCH‐ and SYNCH‐related examination components featured image‐based, multiple choice question (MCQ) items, with similar proportions of structure identification items and clinical application items. Results In M1 (n=101; response rate = 62%) and M2 (n=66; response rate = 40%) groups, the percentage of students indicating a preference for ASYNCH, a preference for SYNCH, or no preference regarding content delivery, was 45%, 38%, and 18%, for M1 students, and 48%, 32%, and 20% for M2 students, respectively. Thematic analysis of open‐ended feedback revealed strengths (more engaging formative assessment; being part of a learning community) and limitations (technical issues; time‐inefficient; more difficult to review) of SYNCH delivery. Similarly, commentary also revealed strengths (time efficiency; flexibility/control) and limits (less engaging formative assessment) of ASYNCH delivery. Commentary also revealed that many students were fine with either approach. While some students noted their preferred approach was beneficial to their learning, assessment data revealed no statistical differences in class performance between ASYNCH‐ vs. SYNCH‐delivered content, for either M1 (MSK) or M2 (GI/REPRO) anatomy. Conclusion While medical students may have indicated a slight preference for ASYNCH (vs. SYNCH) anatomy learning, medical students were generally satisfied with both approaches. While open‐ended commentary revealed strengths and limitations regarding both formats, the perceived notion that either SYNCH or ASYNCH was more beneficial to student learning was not supported by assessment data. Significance/Implication This study provides evidence to suggest that both ASYNCH and SYNCH approaches are appropriate for delivering anatomy content to medical students, given unique strengths attributed to each format, and that both approaches lead to similar performance on knowledge assessments. As such, medical anatomy educators should feel confident in choosing either ASYNCH and/or SYNCH formats when delivering their lectures.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,257
Score d'incertitude au seuil0,601

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,275
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2021
Routes d'admission2
Résumé présentoui

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