Developing lab activities for an introductory anatomy course: Reflections and recommendations from a student-faculty partnership
Notice bibliographique
Résumé
Engaging students as partners in the development of course curricula can provide a range of educational and professional benefits to both students and faculty.It allows students to participate in the creation of new educational material, which can impact the learning of future students (Matthews et al., 2018).It can also develop mutual trust, respect, and understanding between faculty and students, with all parties appreciating the value of each member's unique viewpoint (Matthews et al., 2018).These benefits are fostered in such relationships, in part because students and faculty share the responsibility of contributing to the learning experience and addressing challenges related to the advancement of teaching and learning (Cook-Sather et al., 2014;Bonney, 2018;Spencer et al., 2021).Students and faculty who are involved in developing course content together are encouraged to engage in selfreflection to further their academic development (Pedrosa-de-Jesus et al., 2017).Self-reflection can also allow all partners engaged in curriculum design and delivery to critically evaluate their efforts and heighten their academic skills.It was with these sentiments foremost in our minds that we embarked upon an exciting students-as-partners experience, the primary objective of which was to design graded lab activities for a large first-year human functional anatomy course in a kinesiology program.Our group was comprised of kinesiology members (five undergraduate students, one graduate student, and one faculty member).Our initial task was to share ideas about what types of lab activities students would enjoy and find meaningful, as well as which labs would contribute to their learning experience.Prior to the development of the new activities, labs for this course consisted of question-and-answer periods, interactions with lab materials (e.g., models, skeletons), and discussions about course content.The graded labs created by our team included a variety of individual and small-group activities that could be delivered in both inperson and online environments.Once we decided on the types of lab activities to offer, the course instructor divided the team into subgroups of two partners each.Each subgroup was responsible for developing several labs, working independently and meeting as needed.The entire group met biweekly to share progress, ask questions, and provide feedback to each other.After developing the activities, all group members reflected in writing on their experiences, guided by questions posed by the faculty partner.The students and faculty partner reflected on developing laboratory activities for incoming students, collaborating together,
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 | 0,000 | 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 | 0,000 |
| 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 ».