ME-BIPLP - the development of a Malay-English bilingual language practices questionnaire for Malaysian parents and caregivers
Bibliographic record
Abstract
Parental language practices are crucial in shaping children’s language development, especially in creating a bilingual environment at home. Although Malaysia promotes Malay-English bilingualism (i.e., Malay as the National Language and English as the Second Official Language), many children still fall behind in acquiring both languages simultaneously and sequentially. This highlights the urgent need for effective, accessible guidance for parents and caregivers to support bilingual development at home. However, many families lack sufficient knowledge of appropriate language strategies. To address this gap, the Malay-English Bilingual Parent Language Practices (ME-BiPLP) Questionnaire was developed as a practical, parent-friendly tool to guide Malaysian parents in fostering bilingualism. Grounded in four theoretical frameworks – Bandura’s Social Learning Theory, Skinner’s Theory of Learning, Vygotsky’s Social Development Theory, and Krashen’s Input Hypothesis – ME-BiPLP was created using an adopt-and-adapt method. A total of 60 items were compiled from five existing tools: Across Culture School Language Profile, Alberta Language Environment Questionnaire (ALEQ), Early Language Scales (ELS), Language Express, and CAT/CLAMS. The items were refined to 35 questions and validated by experts in Linguistics, Child Psychiatry, and Early Language Education. Following expert review, five items were revised. A pilot study involving 25 parents and caregivers demonstrated high reliability in Cronbach’s Alpha (0.849). As the first dual-language parental questionnaire in Malaysia, ME-BiPLP is novel, accessible, and culturally appropriate. ME-BiPLP assists parents and caregivers with the knowledge to foster early bilingual development, in line with the Sustainable Development Goal 4: quality education (i.e., literacy) for all children. ME-BiPLP findings will contribute to future development of national language guidelines .
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".