Perfectionism in Language Learners
Bibliographic record
Abstract
The pressures inherent in trying to be perfect can undermine learning and exacerbate anxiety in certain students. In the current article, we review existing research and theory on the role of perfectionism in language learning anxiety and performance deficits. Our analysis highlights the complexities inherent in the perfectionism construct, including the key distinction between personal and interpersonal perfectionism and the relevance of various components of the perfectionism construct when seeking to account for anxiety in language learners. A central theme in our analysis is how the cognitive tendencies as well as social pressures and self-presentational concerns that accompany perfectionism can exacerbate language learning anxiety and the subsequent emotional self-regulation responses of anxious learners. We outline a multifaceted model of perfectionism in language learning anxiety and language learning performance that incorporates trait perfectionism, perfectionistic cognitions, perfectionistic self-presentation, and individual differences in self-efficacy. Whereas personality is usually seen as a distal factor that contributes to language learning anxiety, we suggest that perfectionism can also act proximally by amplifying state-related, current concerns over making mistakes in language learning, especially in highly visible situations. The theoretical and practical implications of this theoretical framework are discussed. We conclude with a series of specific recommendations for teachers and school psychologists who must try to reduce levels of perfectionism and its impact among people trying too hard to minimize mistakes during the learning process.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".