Pedagogies in Becoming Muslim: Contemporary Insights from Islamic Traditions on Teaching, Learning, and Developing
Bibliographic record
Abstract
In light of calls to examine, elaborate, and improve pedagogies in teaching and learning Islam, thematic analysis was conducted on literature in English on pedagogies derived from the primary-source texts, the Qur’an and Sunnah. Three themes were constructed, each capturing a distinct pedagogic principle, to suggest an expansive framework of principled, flexible, situated, holistic, and transformative pedagogies. First, Relational Pedagogies center learning and developing in warm human relationships. Second, Pedagogies of Mutual Engagement include doing, speaking, and inquiring together in participatory processes of making meaning. Third, Pedagogies of Conscious Awareness aim to make visible purposes, reasons, and principles behind Islamic practices. These three themes were then used as sensitizing concepts in examining data gathered in a sociocultural study on Muslim educators’ perspectives and practices at a mosque school in Canada. Reflections of the themes in the data—and contradictions—suggest that educators passionately but partially draw from primary-source pedagogies to inform their praxis in a pedagogic diaspora where interpretation and application vary. Further research is required to examine whether the developmental potential of these primary-source pedagogies might be optimized when they are employed together, as a balanced group, and how they might address pedagogical criticisms in teaching and learning Islam.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".