Using Q‐Methodology to Evaluate Student Perceptions of Online Anatomy in the Time of COVID‐19
Notice bibliographique
Résumé
Background Since the seventeenth century, the primary approach to teaching anatomy has involved hands‐on learning using cadaveric specimens. However, the ability to use this long‐standing tradition was curtailed in the 2020‐2021 school year due to the COVID‐19 pandemic. Many institutions closed physical classrooms entirely, launching experiential courses, such as anatomy, into the online space. Hypothesis We hypothesized that Q‐methodology could be used to uncover student perceptions of an introductory anatomy and physiology course that was offered online for the very first time. Methods Q‐methodology, considered the study of subjectivity, is an approach that statistically uncovers groups of individuals with shared perceptions within a larger cohort. Instructors can use Q‐methodology to identify groups of students with shared needs, allowing for more specific and productive course reform. In the current study, Q‐methodology was used as a means of course evaluation in the fall 2020 and winter 2021 semesters. Students were asked to sort 44 opinion‐based statements in a quasi‐normal table based on their level of agreement. By‐person factor analysis of 166 responses revealed three statistically distinct groups of students. Results The three groups were assigned the following monikers: Connected and Contented (CC), Disconnected and Disgruntled (DD), and Interconnected and Collaborative (IC). CC students (n=66) felt generally ambivalent toward course components and were comfortable with the technology skills required to participate in the online course space. DD students (n=50) were deeply unhappy with several elements of the course, including lectures, assignments, and evaluations. These students also felt as if they were teaching themselves. Finally, IC students (n=29) looked favourably upon the tutorial space and the role of teaching assistants. Analysis also revealed that some sentiments were shared across all three groups, including the preference for physical rather than virtual specimens, and the desire for more practice questions from faculty in order to prepare for bellringer exams. Interestingly, cohort opinions did not remain static across both semesters. There was a positive attitude shift as more students felt “Disconnected and Disgruntled” in the fall, and “Connected and Contented” in the winter. Conclusions These findings are useful for anatomy instructors interested in transitioning courses to an online or blended space, particularly in the face of ever evolving public health restrictions. The current study also models the wealth of information that can be uncovered using Q‐methodology ‐ useful for anyone interested in the previously amorphous study of subjectivity.
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 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 | 0,000 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».