Challenges in online English language learning: a study of an English medium instruction school in Thailand
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The challenges in online English learning in a Thai secondary school context are the focus of the study where English is used as a medium language for instruction by adapting Hijazi and AlNatour’s (2021) and Sukman and Mhunkongdee’s (2021) frameworks to explore the challenges in online English learning perceived by students and students’ challenges perceived by teachers in a secondary school in Samut Sakhon province. The participants in this study were 77 Thai students and 20 teachers including 10 Thais, eight Filipinos, one Canadian, and one Australian. The adapted questionnaires were completed by the participants. Afterwards, the data gained from the questionnaires were analysed using SPSS statistics. The results showed that the biggest challenge in online English learning for both groups of the participants was social aspects. Motivation and willingness came up as the second biggest challenges among the groups. However, the third challenge for students was teaching methods, whereas the third challenge perceived by teachers was online English learning. The findings of this study may be useful for future planning for schools, teachers, students, and other stakeholders. Recommendations and implications of the findings are also provided.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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 it