Worldwide Trends in Bilingual Education Research: A Half-Century Overview
Bibliographic record
Abstract
Despite the wealth of studies on bilingual education, there is a dearth of meta-research on the worldwide development and trends of this area of investigation over the past few decades. The occupation of this gap allows scholars to take stock of current states of research, get overviews of the contributions made to the field, foresee future research trends, and identify research needs and gaps that may be addressed in future investigation. This study analyses the evolution and trends of bilingual education research during a 50-year period (1969–2018) from a bibliometric perspective. The results show a steady increase in the number of publications, and was exponential in the last decade, mainly in the form of research articles, which makes bilingual education a truly consolidated and increasingly evolving research field. The US is the leading country with respect to the number of publications, affiliations, and sponsors, followed, primarily, by some other North American (e.g., Canada), European (e.g., UK and Spain), and Asian (e.g., China) countries, as well as Australia. There is a large research network cluster led by the US involving intercontinental interaction among institutions from Europe, Asia, and, to a lesser extent, South America. However, a scant level of internationalisation of scholars publishing works on bilingual education was observed, with most author collaboration being limited to different US institutions. The most influential authors belong to institutions from the US, Canada, Spain, and Israel, and, to a lesser extent, Australia. The main research topics in the field depend on the contexts and include regulations of language institutions, bilingual education models, language skills, pedagogical strategies, education levels, and ages, among others. These results may contribute to the identification of new research needs and therefore, to the development of future directions in bilingual education research.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.049 | 0.078 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".