Teacher Perceptions of Project Based Learning in the Secondary Classroom
Bibliographic record
Abstract
This study examines teacher perceptions of their experiences with Project Based Learning (PBL) at a secondary school in Western Canada. This PBL initiative included English language arts, mathematics, science, and digital literacy courses and all the grade nines at this large secondary school. This article reports on two teacher focus group interviews that were part of a larger mixed-methods study (Creswell & Plano Clark, 2007). Results provide specific details regarding conditions for the successful implementation of PBL, challenges and support for current research into PBL, and areas of additional needed research. Cette étude se penche sur les perceptions qu’ont les enseignants de leurs expériences avec l’apprentissage axé sur les projets (PBL—project based learning) dans une grande école secondaire dans l’Ouest canadien. Cette initiative d’apprentissage actif par les projets impliquait les cours d’anglais, de mathématiques, de sciences et de littératie numérique, ainsi que les tous les élèves de la 9e année. Cet article porte sur un élément de cette étude à méthodologie mixte (Creswell & Plano Clark, 2007), soit deux groupes de discussion/entrevues avec des enseignants. Les résultats fournissent des détails sur les conditions nécessaires à la mise en œuvre réussie du PBL, les défis qui en découlent, l’appui pour la recherche actuelle et les domaines qui restent à étudier plus en profondeur.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".