STEM in Canadian teacher education: An overview
Bibliographic record
Abstract
Since emerging as a concept in the 1990s STEM and STEM education has become an area of broad interest in Canada in the past 15 years. STEM programs are well-promoted in science faculties at Canadian universities and associated provincial education programs, raising the question as to the degree to which STEM and courses teaching (about) STEM are present in Faculties of Education in Canada. This chapter presents data drawn from Canadian Bachelor of Education (BEd) academic calendars (n = 56), Canadian academic conferences where research on STEM in BEd programs would be presented (n = 17), and publications from the Council of Ministers of Education to understand what STEM opportunities are available to prospective teachers. Four detailed, narrative descriptions of STEM courses at four faculties of education provide examples of the types of offerings available in Canadian teacher training programs. Overall, we report that in Canadian BEd programs few STEM courses are offered—and even fewer STEM programs—raising questions about the support offered by BEd programs for STEM school initiatives that exist both provincially and federally. Implications of this are discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.020 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".