“I’m Happy to Speak with My Accent”: Does Language Attitude Influence Willingness to Communicate?
Bibliographic record
Abstract
Scholarship on students’ language attitudes toward their non-native English accent with respect to their willingness to communicate (WTC) has remained relatively underexplored, especially in the Thai context. Recognizing this gap, this paper examined Thai university students’ language attitudes toward their Thai English accent and their WTC. Drawing on a mixed-methods approach, the study adopted a language attitudes questionnaire and interview questions as research instruments. A total of 30 first-year education students, majoring in English at a Thai autonomous public university, were selected to participate in the study. The quantitative data was collected from the pre-, mid-, and post-surveys, and it was analyzed using one-way ANOVA. Interview responses were examined through content analysis. The findings showed no significant differences across variables. However, the relationship between the two variables analyzed using bivariate correlations showed significant differences in the pre- and post-surveys. Interestingly, the qualitative data revealed positive perceptions toward the language attitude and WTC. It indicated that participants are willing to speak with their Thai English accent in various situations. The outcomes of this study have pedagogical implications and outline further avenues of research.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.002 | 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".