Translanguaging Practices and Perception of Tertiary Lecturers and Learners in Thailand: A Case Study at Buriram Rajabhat University
Bibliographic record
Abstract
Translanguaging refers to the practice of utilizing several languages and various forms of communication to create knowledge and encourage the use of multiple modes of language education. This study aims to investigate the tertiary lecturers’ and students’ translanguaging practice and their perception of using classroom translanguaging. The sample consisted of 30 lecturers and 60 students from the English Program, Business English Program. Education English, and other programs, Buriram Rajabhat University, Thailand. They were selected using the purposive sampling method.The tools were a questionnaire survey and a semi-structured interview. The data collected from the questionnaire were analyzed using the frequency, percentage, mean, and standard deviation. The interview was analyzed utilizing qualitative content analysis. According to the assessments of three experts, the research instruments obtained an IOC score of 0.67. The findings from the first objective indicated that the lecturers had a positive attitude towards the use of translanguaging in their teaching, as shown by the average score of 4.12. In addition, the students expressed their support for the incorporation of translanguaging in the English as a Foreign Language (EFL) classroom, as indicated by the overall average score of 4.22. The results from the second objective indicated that the lecturers strongly supported the notion of integrating translanguaging in the English as a Foreign Language (EFL) course, with the mean score of 4.13, Similarly, all of the students reached a consensus to incorporate translanguaging in the English as a Foreign Language (EFL) classroom, with the average score of 4.22. In addition, the analysis of the interview responses revealed that both the lecturers and students held similar perspectives on the use of translanguaging in the EFL classroom. The findings of this study will offer a thorough foundation for formulating a future plan and strategy on English language instructions in the specific context of Thailand.
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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 | 0.001 | 0.000 |
| 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".