The Application of Code-switching, Code-mixing, and the need for Bilingual Pedagogy in Brunei Religious (Ugama) Schools: A Qualitative Study Involving Generation X and Millennial Teachers
Bibliographic record
Abstract
Religious (Ugama) education is a compulsory form of education apart from the mainstream education Brunei Darussalam. The Ugama schools are of autonomous management under Jabatan Pengajian Islam (JPI), a department under Brunei Ministry of Education. The classes are often conducted in a separate specified school during the weekdays and the enforced medium of instruction is the Malay language as opposed to English for the mainstream education. This research is interested in the trending application of code-switching and code-mixing in lower and upper primary level as teaching and communicating strategies employed by the teachers. The study also aims to acquire the Millennial teachers’ and Generation X teachers’ perspectives on the increasing use of the English language in Malay-medium oriented schools and its possible effects to the religious curriculum. Using in-depth interview and classroom observations as research methods, this study not only found a ‘normalized’ view on code-switching and code-mixing in lower primary level and less in upper primary level, but also majority of Generation X participants’ call for the need of formal training for English language. The Millennial participants, on the other hand, called for a move towards bilingual pedagogy for religious education to keep abreast with the mainstream education and so it could stop being viewed as secondary. The study also discovered the individual teachers’ concern for the diminishing use of the Malay language to affect the significance of religion due to the impact of cultural globalization, specifically disseminated by the internet and pop culture media. Moreover, the study also found some probable evidence of students identify English as their mother tongue, instead of Malay.
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How this classification was reachedexpand
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".