Foreign Language Anxiety and Student Interpreters’ Learning Outcomes: Implications for the Theory and Measurement of Interpretation Learning Anxiety
Bibliographic record
Abstract
Although anxiety has been documented as an important variable in both interpretation performance and second language acquisition, there has been virtually no research on the interconnections between the anxiety reactions induced by these two cross-linguistic / cultural endeavors. A review of the literature on anxiety and interpretation performance finds that most of the existing studies have treated the anxiety induced by interpretation as a transfer of other general types of anxieties, such as trait anxiety, without considering the probable role of second language anxiety in interpretation performance. In order to determine the role of foreign language anxiety in 213 Chinese-English interpretation students’ learning outcomes, which were indexed by the participants’ mid-term exam scores and semester grades, this study employed Spielberger’s (1983) Trait Anxiety Inventory to measure the students’ trait anxiety, while utilizing Horwitz, Horwitz et al.’s (1986) Foreign Language Classroom Anxiety Scale (FLCAS) to measure the participants’ foreign language anxiety. Results of correlation analyses showed that a) trait anxiety was not related to either mid-term exam scores or semester grades, b) foreign language anxiety was significantly and negatively associated with both outcome measures, c) after controlling for the effect of trait anxiety, the relationship between foreign language anxiety and interpretation learning outcomes remained significant, and d) a vast majority of the FLCAS items had significant and negative associations with both outcome measures. Implications for developing a theory of and a measurement instrument for interpretation learning anxiety are suggested.
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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 | 0.038 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".