Student and Instructor Perceptions of a First Year in Active Learning Classrooms
Bibliographic record
Abstract
This article presents evaluation of an active learning classroom (ALC) initiative at the University of Ottawa. Preliminary results indicate three broad trends to inform future practice and classroom design: 1) Despite advances in educational technology, there remains a strong appetite for low-tech, interactive learning opportunities. 2) Instructors feel that consistent institutional support is necessary to foster innovation in the classroom, particularly for course redesign. 3) a collaborative strategy, bringing together multiple institutional stakeholders, is necessary to ensure a whole-of-university approach to optimal use of the ALCs. This article briefly reviews ALC research, outlines the methodology of the program-evaluation protocol, discusses the three central findings, and concludes with potential directions in ALC research. Nous examinons ici une initiative, menée à l’Université d’Ottawa, de classe d’apprentissage actif (CAA). Les résultats préliminaires permettent de dégager trois tendances qui permettront d’orienter les pratiques et la configuration de la classe : 1) malgré les avancées dans les technologies éducatives, l’intérêt pour les méthodes simples et pour l’apprentissage interactif ne se dément pas; 2) Les enseignants croient que l’innovation en classe, et tout particulièrement la refonte des cours, sont tributaires d’un soutien institutionnel constant; 3) pour utiliser toutes les ressources de l’université et ainsi faire un usage optimal des CAA, il doit y avoir une stratégie de collaboration regroupant différents intervenants de l’établissement. Dans notre article, après avoir survolé la recherche au sujet des CAA et défini la méthodologie du protocole d’évaluation de programme, nous présentons les trois résultats principaux et nous proposons, en guise de conclusion, trois avenues possibles pour la recherche sur les CAA.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".