Research strength analysis, pedagogical components, and effectiveness of translanguaging: a systematic literature review
Bibliographic record
Abstract
This systematic literature review examined 61 empirical studies published from 2010 to 2022 on translanguaging. The review explored the trends and scientific strengths of the studies, the reported pedagogical components, and the affordances and challenges of translanguaging. 70.49% of the studies took place in elementary schools and in 65.57% in the U.S. contexts. The majority of the studies employed ethnographic methods (27.87%) to collect data. Only 37 of the reviewed papers endorsed translanguaging’s agenda of promoting equity and social justice. Our evaluation of the reviewed studies was generally favourable with strengths identified in researchers’ articulation of research context and theoretical frameworks, connections to existent literature, and methods of data collection. However, data analysis in certain studies did not contain adequate information regarding how themes, concepts, and categories were derived from data, and data were not presented in a way that enables readers to judge the range of evidence being used. Adopting thematic analysis, the systematic literature review identified 11 major pedagogical components of pedagogical translanguaging and the affordances and challenges of both pedagogical and spontaneous translanguaging. The paper ends with recommendations for future research and pedagogical innovations that aim to buttress bilingual and multilingual students’ fluid meaning-making practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".