Teacher’s Teaching Practices in the Class of Mualaf (New Convert)
Bibliographic record
Abstract
Education is highly emphasized in Islam because it can guide people to live righteous life according to Islamic law. The same also applies to mualaf or converts, who should be provided with proper education and guidance to perform their duties as true Muslims. In Malaysia, an increasing number of individuals are embracing Islam as their way of life. They are given an education and need to attend classes to ensure that they understand and practice the teachings of Islam properly. Therefore, teachers play an important role in achieving this goal by applying interesting and effective teaching methods. This study was conducted to identify the perceptions of mualaf students on their teachers' teaching practices in the classroom to ensure that they understand and practice what they have learned in class, besides strengthening their faith and morals. A total of 124 mualaf students from two educational institutions in one of the states in Malaysia were involved in this study using quantitative methods. Questionnaires were used to collect data based on the objectives of the study. The results showed that students had a positive perception of the teaching methods used by their teachers. This study also discussed some of the problems faced by mualaf students in their learning process. Overall, the findings of the study indicated that most students have a positive view of their teachers’ teaching. The current findings are expected to provide input to relevant agencies and a guide to improving the quality of teaching for mualafs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".