Movement Guided Learning as an Efficacious, Effective, and Evidence‐based Teaching Strategy Within the Undergraduate Anatomy Classroom
Notice bibliographique
Résumé
Within the anatomy classroom, physical movements and stretches can turn a student's own body into their personal educational tool. Such direct relevance can be useful for the undergraduate junior learner as they attempt to truly understand musculoskelatal anatomy in a meaningful way. This presentation describes the longitudinal, iterative scholarship that went in to developing, piloting, refining, and experimentally assessing Movement Guided Learning (MGL)©, a self‐directed learning workbook that guides students through applications of musculoskeletal anatomy including physical movements/stretches, surface palpations/visualizations, and extensions of knowledge with case‐based scenarios. Most recently, components of the refined MGL workbook were fully integrated as adjunct teaching activities into a large undergraduate classroom within health sciences. Using a randomized control design, the entire curriculum of muscular anatomy was divided into three equal groups; students received MGL activities for 1/3 rd of the taught muscles, students received multiple choice style review questions for 1/3 rd of the taught muscles (as an active, time‐matched control), and students received no additional learning material for 1/3 rd of taught muscles (as a non‐active control). To facilitate full integration of supplementary teaching materials, the course instructor was been made aware of group allocations, provided with all teaching materials, and embedded those materials during in‐class lecture time and during independent student activities. Final exam scores will be segmented and compared in agreement with the three experimental groups, allowing for an intra‐individual superiority assessment of MGL. Student survey responses will allow for MGL efficacy to be further assessed against student learning preferences as well as self‐reported strategy utilization. To control for inadvertent instructor‐bias, time spent on each muscle will be quantified (using video lecture capture software) and compared across the three groups There are currently 187 undergraduate students enrolled in the course with the majority of them enrolled in a global health degree (~75%) in their first year of undergraduate studies (~90%). MGL efficacy will be determined using the aforementioned mixed‐methods assessment strategies following the fall semester final exam. Based on previously reported MGL success, it is hypothesized that the MGL activities will be a useful learning adjunct, especially for students who display kinesthetic learning preferences. Support or Funding Information none to declare
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 | 0,001 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 ».