The Implementation of the 21st Century Pedagogical Elements in Jawi Teaching: A Review Study
Bibliographic record
Abstract
The skills to implement the 21st century pedagogy in teaching become a necessity for Islamic Studies teachers to produce effective Jawi teaching. This study aims to analyse the pedagogical elements of the 21st century in terms of pedagogical skills, knowledge acquisition, student-based learning, cooperative and collaborative learning as well as student-centered learning which have been implemented by the Islamic Studies teachers in Jawi teaching. This study is a quantitative study which used survey design. A five-point Likert scale questionnaire has been used to collect the data and was distributed to 217 Islamic Studies teachers who were selected as the sample of this study. A pilot study was conducted to show the reliability of 0.877 for the whole constructs. This study obtained the highest mean value for the following constructs; pedagogical skills (mean=4.063), knowledge acquisition (mean=3.900), student-based learning (mean=4.174), cooperative and collaborative learning (mean=4.038) and student-centered learning (mean=4.115). The overall mean value for all constructs was 4.875 and this concluded that the level of pedagogical elements of the 21st century by the Islamic Studies teachers in Jawi teaching was high and these elements have been implemented well in Jawi lessons. However, due to the rapid transformation of education in this globalization era, Islamic Studies teachers have to be more progressive in practicing the 21st century pedagogical skills in their teaching to become competent and dynamic educators in the 21st century.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".