Teacher identity, Islamic behavior, and project-based learning methods for madrasah teachers: A phenomenological approach
Bibliographic record
Abstract
A project-based learning method is required to develop students' scientific thinking in akidah akhlak (moral theology). This study employed a phenomenological approach to investigate whether and to what extent identity processes and Islamic behavior are developing project-based learning methods for madrasah aliyah teachers of moral theology. It involved twenty moral theology teachers and in-depth interviews to reveal the narrative of teachers' practice in using project-based learning methods. Thematic analysis of twenty teachers' two-group interviews showed that teachers' personal beliefs provided a religiously motivated narrative framework that aided in interpreting one's experiences. Individual Islamic behavior, religiosity, and identity creativity play a role in developing project-based learning methods for moral theology. In addition to attributing creativity from a God-given personality to learning in moral theology, the primary bond in developing project-based learning methods is the application of Islamic principles and Islamic behavior. Following the learning of moral theology, students' identities, Islamic behavior, and scientific thinking, the use of project-based learning methods by madrasah teachers experienced a significant increase in quality. Finally, the findings of this exploratory study indicate that Islamic behavior and personal identity can enhance project-based learning methods. Large-scale research could provide more evidence to reconsider the role of religious education in teacher training as an essential factor in developing project-based learning methods for moral theology teachers.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| 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".