The Professionalism of Islamic Religious Education Teachers in Facing the Challenges of Digitalized Learning
Bibliographic record
Abstract
The transformation of digital education presents both challenges and opportunities for Islamic Religious Education (PAI) teachers, particularly in shaping students’ character. This study aims to examine the impact of learning digitalization on the role of PAI teachers, the challenges they face in mastering technology, and the strategies for developing digital-based learning at Tahfizhul Quran Al Kautsar School in Klaten. This research employs a qualitative case study approach through interviews, observations, and documentation conducted in June 2025. The findings indicate that digitalization has shifted the role of teachers to become more active facilitators. However, challenges such as low digital literacy and limited infrastructure remain significant obstacles. Solutions include training, the development of Islamic digital teaching materials, the use of appropriate platforms, and communication with students’ guardians. Collaboration among teachers, schools, and relevant stakeholders is essential to create innovative yet value-driven Islamic education.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".