Examining the Potential of a University-Accredited Islamic Education Teacher Training Program: A Conceptual Exploration
Bibliographic record
Abstract
Public schools (K-12) are experiencing a remarkable decline in enrollment across Canada. More and more parents are choosing independent schools for their children’s education. Muslim parents, in particular, are transferring their children to Islamic schools as they are increasingly losing faith in public schools. Muslim students in the public school systems, wherever they are on the continuum of practice—from secular to orthodox—do not perceive their schools to be responsive to their religious beliefs, values, behaviours, and practices. However, Islamic schools are stuck in normative, secular, and reductive pedagogies, with most, if not all, Islamic teachers lacking training in Islamic pedagogy. This article is a conceptual exploration of various approaches to offering an Islamic teacher training program in Canada by an accredited university, including reintroducing the Islamic Teacher Education Programme (ITEP), which offered a one-year professional learning certificate. Another approach is establishing a stream in teacher education programs similar to the Catholic stream. The article serves as a stepping stone to initiate dialogue and collaborative efforts toward creating a comprehensive approach that includes all stakeholders tailored to the unique needs of Islamic school teachers in Ontario, Canada.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.023 | 0.026 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".