INTEGRATION OF TECHNOLOGY IN IMPROVING THE PROFESSIONALISM OF ISLAMIC RELIGIOUS EDUCATION TEACHERS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technological developments have significantly impacted various aspects of life, including education. This research aims to analyze the role of technology in increasing the professionalism of Islamic Religious Education (PAI) teachers. The research uses qualitative methods with a literature study approach, which involves collecting data from various sources such as scientific journals, books, articles, and related documents. Data analysis used a content analysis approach to identify the main themes and relationships between technology and PAI teacher professionalism. The research results show that technology has great potential in the professionalism of PAI teachers in utilizing technology through various innovations, such as interactive media, digital learning applications, and e-learning platforms. Technology helps teachers deliver material more interestingly and efficiently, and supports students to learn independently and collaboratively. In addition, the integration of technology in the professional development of PAI teachers has been proven to increase students' understanding of religious values, strengthen their character, and motivate them to be active in the learning process. This research concludes that optimal use of technology can be a solution to overcome challenges in increasing the professionalism of PAI teachers. It is hoped that these findings will become a reference for developing learning strategies that are more innovative and relevant to the educational needs of the 21st century.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it