Digital Opportunities Within the Aboriginal Teacher Education Program: A Study of Preservice Teachers' Attitudes and Proficiency in Technology Integration
Bibliographic record
Abstract
This article explores changes that occurred in preservice teachers' thinking about the use of educational technology in a post-secondary, Aboriginal, elementary teacher education program. The research explores relationships associated with changes in preservice teachers' attitudes and perceived proficiency with technology integration. Quantitative results indicate significant increases in several attitude constructs as well as overall computer proficiency over the course of the project. Supplemental qualitative analysis reveals participants' perception of technology integration as a contributing factor in this positive change. The findings from this study represent a research effort to better prepare teachers to meet the educational needs of Aboriginal students in a 21st century context. Cet article explore l’évolution dans les idées des stagiaires quant à l’emploi des technologies éducatives dans un programme postsecondaire de formation pour enseignants autochtones à l’élémentaire. La recherche porte sur des rapports associés aux changements dans les attitudes des stagiaires et leur perception de leur compétence relative à l’intégration technologique. Les résultats quantitatifs révèlent des augmentations significatives tant dans les attitudes que la compétence technologique globale au cours du projet. Une analyse qualitative supplémentaire indique que la perception des participants quant à l’intégration technologique constitue un facteur contributif dans ce changement positif. Les résultats de cette étude représentent un effort de recherche visant une meilleure préparation des enseignants de sorte à répondre aux besoins pédagogiques des étudiants autochtones au 21e siècle.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".