Student perceptions and lessons learned from flipping a masters level public health course | Perceptions des étudiants et leçons tirées d’une classe inversée pour un cours de maîtrise en santé environnementale et professionnelle
Bibliographic record
Abstract
The flipped classroom instructional model has emerged as an alternative to conventional lecture-based teaching that has dominated higher education for decades. In 2013, a cohort of graduate-level public health students participated in a flipped environmental and occupational health course. We present the design, implementation, and evaluation of this course. Using data collected from a post-course survey, focus group sessions, and classroom observation, we examine student perceptions of the flipped classroom instructional model and synthesize lessons learned from flipping the classroom more broadly. Post-course survey data indicate that students had generally positive perceptions towards the flipped classroom instructional model. Four major themes emerged from the focus group data in relation to perceptions of the flipped classroom: knowledge application, content delivery, innovation, and connecting the online and in-class components. These results are promising and suggest that this approach warrants further consideration and research. Le modèle pédagogique de la classe inversée a émergé comme solution de rechange à l’enseignement traditionnel par cours magistraux qui a dominé l’éducation supérieure pendant des décennies. En 2013, une cohorte d’étudiants en santé publique aux cycles supérieurs a participé à un cours inversé sur la santé environnementale et professionnelle. Nous présentons la conception, la mise en œuvre et l’évaluation de ce cours. À l’aide de données recueillies par l’entremise d’un sondage après le cours, lors de séances de discussion en groupe et d’observation en classe, nous examinons les perceptions qu’ont les étudiants du modèle pédagogique de la classe inversée et résumons les leçons tirées qui sont pertinentes pour les cours inversés en général. Les données du sondage réalisé après le cours indiquent que les étudiants avaient des perceptions pour la plupart positives du modèle pédagogique de la classe inversée. Quatre thèmes principaux ont émergé des données du groupe de discussion relativement aux perceptions sur la classe inversée : mise en application des connaissances, diffusion du contenu, innovation et lien entre les composantes en ligne et en classe. Ces résultats sont prometteurs et suggèrent que cette approche devrait faire l’objet de plus de considération et de recherche.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".