Perfectionism and L2 Achievement: The Mediating Roles of Motivation and Self-Regulated Learning Among Iranian High School Students
Bibliographic record
Abstract
The current study investigated how perfectionism can be related to L2 learners’ achievement with motivation and two aspects of self-regulated learning as possible mediators. This study also evaluated the factor structure of the Big Three Perfectionism Scale (BTPS) in an Iranian sample. The participants were 495 Iranian high school students who completed six BTPS sub-scales and measures of self-determined motivation and self-regulated learning. Psychometric analyses indicated that rigid perfectionism and self-critical perfectionism as two higher order factors have construct validity. Structural equation modeling indicated that rigid perfectionism positively predicted L2 achievement, while self-critical perfectionism negatively predicted L2 achievement. Mediational models indicated that neither autonomous-mastery/performance motivation nor controlled motivation mediated the path from perfectionism to L2 achievement. However, both aspects of self-regulated learning, namely, deep learning and persistence could mediate the relationship between perfectionism and L2 achievement. Specifically, higher levels of rigid perfectionism were positively related to deep learning and persistence that, in turn, were related to higher L2 achievement. In contrast, self-critical perfectionism was negatively related to deep learning and persistence, that, in turn, were related to lower L2 achievement. The results are discussed in terms of the practical implications for L2 teachers and parents.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".