Contracting Students for the Reduction of Foreign Language Classroom Anxiety: An Approach Nurturing Positive Mindsets and Behaviors
Bibliographic record
Abstract
The quasi-experimental study as reported in this paper investigated whether contracting students’ speaking in the foreign language (FL) classroom could effectively mitigate their FL classroom anxiety. It also explored the working mechanisms of this approach to the reduction of classroom anxiety and examined the attitudes FL students had towards it. To these ends, 42 Chinese-as-the-first language university students learning English as a foreign language (EFL) were recruited and placed into the experimental (n = 20) and comparison groups (n = 22). Both groups were tested for anxiety before and after completing a 1-week contract and a non-contracting treatment respectively. The experimental group participants’ diaries were also collected and their attitudes towards the intervention were elicited. Results showed that the experimental group’s level of anxiety decreased significantly more as compared with that of the comparison group’s, suggesting the better efficacy of contracting speaking in FL anxiety reduction. Diary analyses also suggested that contracting speaking could increase learners’ FL learning engagement, enhance their self-efficacy, facilitate their self-reflection of weaknesses and strengths as an FL learner, cultivate their character strengths and positive emotions, and diminish their fear, nervousness, and worries in class. Furthermore, the experimental group participants generally did not feel uncomfortable with the intervention. These findings were discussed in relation to classroom pedagogy for more effective delivery of FL education.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".