Willingness to communicate in english as a second language as a stable trait or context-influenced variable
Bibliographic record
Abstract
Whether Willingness to Communicate (WTC) is a permanent trait or is modified by situational context has previously been investigated in various studies (e.g. Cao & Philp, 2006; Kang, 2005; MacIntyre & Legatto, 2011). However, most research into WTC has been quantitative or conducted in the English as a Foreign Language (EFL) or Study Abroad situation in countries such as Canada, Japan, Korea and China. This article reports on the qualitative component of an exploratory mixed methods study in a New Zealand (NZ) university with participants who are permanent migrants from Iran. These students completed a questionnaire and participated in further in-depth semi-structured interviews. The article provides an overview of previous research into WTC and motivation in Iran and NZ as the context for these three case studies. In this study, six factors, both trait and situational, were identified as having an effect on these students’ WTC in both countries: self-perceived competence; personality; anxiety; motivation and the importance of English; and the learning context. Finally, this article discusses the contribution of this study to the WTC field of research, identifying the implications of these results for teachers of English in the ESL (English as a Second Language or migrant) context and possible avenues for future research.
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 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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".