Digital Competence in Quebec’s Teacher Education Programs: Toward a Critical Perspective
Bibliographic record
Abstract
Digital competence, beyond core content knowledge, is a key skill for many teachers in this day and age, and several frameworks for this have been proposed internationally. In Canada, some provinces and territories are currently implementing rules and guidelines regarding the digital competencies of teachers. However, only Quebec has an actual one that is linked to teachers, with specific dimensions integrating critical knowledge and attitudes. This interpretive study examines Quebec’s teacher reference and digital-competency frameworks by exploring their integration into teacher-education programs. Two qualitative data-collection methods, namely, semi-structured interviews and document analysis, were used in this study. The sample included seven university professors from the education departments at different Quebec universities and 34 descriptions of digital technologies courses in Quebec’s teacher-education programs. The main results indicate that digital competence is included in at least one course in teacher-education programs, and that instrumental elements are prioritized over critical and ethical digital dimensions. The findings also highlight professors’ awareness of the importance of further developing these less prominent dimensions. The challenges associated with this integration are acknowledged, and the need for future research to develop pedagogical strategies that promote the acquisition of these competencies is emphasized.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".