Willingness to communicate in the L2 about meaningful photos: Application of the pyramid model of WTC
Bibliographic record
Abstract
Willingness to communicate (WTC) reflects an intersection between instructed second language acquisition and learner psychology. WTC results from the coordinated interaction among complex processes that prepare second language (L2) learners to choose to use their L2 for authentic communication. Prior research has revealed considerable complexity in the influences on dynamic changes in WTC from moment-to-moment. The heuristic ‘pyramid model’ of WTC (MacIntyre et al., 1998) proposes interactions among approximately 30 different variables that may influence WTC. The present study uses the pyramid model to interpret data from three focal participants, all English as a second language (ESL) learners and international students in Canada, with varying degrees of experience in an English-speaking context. Using the idiodynamic method, all participants were recorded while describing a self-selected, personally meaningful photo. Second, participants rated their WTC in English using software that played a recording of their speech and collected continuous WTC ratings. Finally, participants were interviewed about their WTC ratings. Triangulating the data revealed how processes on multiple timescales interact during L2 communication about the photos. WTC changes as speakers’ motivations and emotions are influenced by the deep, personal relevance of the topics under discussion. Pedagogical implications for the results of this study and the use of the idiodynamic method in L2 classrooms are discussed.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".