TPACK in Elementary and High School Teachers’ Self-reported Classroom Practices with the Interactive Whiteboard (IWB) | Connaissances abordées dans les pratiques déclarées d’enseignants du primaire et du secondaire qui exploitent le tableau numérique interactif (TNI) en classe
Bibliographic record
Abstract
The interactive whiteboard (IWB) is increasingly used for teaching and learning in the classroom. Nevertheless, the ways that teachers incorporate this tool within their teaching practices remain poorly understood. This paper examines elementary and high school teachers’ self-reported practices with the IWB. The conceptual framework centers on teachers’ self-reported practices as well as the Technological Pedagogical Content Knowledge (TPACK) model, a framework for successful integration of technology into teaching. Data were collected from discussion groups with 30 teachers. Overall, the results show a predominance of technological pedagogical knowledge (TPK) and technological knowledge (TK) regardless of grade level, gender, or years of teaching experience.Le recours au tableau numérique interactif (TNI) à des fins d’enseignement et d’apprentissage à l’école est de plus en plus fréquent. Cependant, les pratiques des enseignants qui exploitent l’outil sont encore mal connues. L’objectif de cette recherche est de rendre compte des connaissances que des enseignants du primaire et du secondaire mobilisent dans leurs pratiques déclarées au regard du TNI. Le cadre conceptuel repose sur des pratiques enseignantes déclarées et des connaissances (modèle TPaCK) à déployer pour assurer une intégration réussie des outils technologiques. Les données ont été recueillies auprès de 30 enseignants participant à des groupes de discussion et traitées selon une analyse de contenu. Globalement, les résultats montrent une prédominance de connaissances technopédagogiques (TP) et technologiques (T) chez les participants, peu importe l’ordre d’enseignement, le genre de l’enseignant ou l’expérience en enseignement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".