Bibliographic record
Abstract
In the second language acquisition domain, researchers have devoted tremendous efforts to studying the relationship between L2 learning and some socio-affective factors, such as anxiety, motivation, etc. However, little research has been done to examine whether and how perfectionism, a psychological trait, affects L2 learning and L2 performance. The present study aims to fill this gap and investigate the relationship between the level of perfectionism and L2 performance among Chinese EFL college learners. Two specific questions are raised: (1) What is the relationship between perfectionism and L2 writing performance in terms of linguistic complexity, accuracy, and fluency? (2) What is the relationship between the six dimensions of perfectionism (Concern over Mistakes, Personal Standards, Parental Expectations, Parental Criticism, Doubts about Actions, Organization) and L2 writing performance in terms of linguistic complexity, accuracy, and fluency? To answer these questions, forty second-year students from Guangdong University of Foreign Studies majoring in English participated in the present study. The participants were required to compose a piece of English argumentative writing on the online system and then complete a 35-item Multidimensional Perfectionism Scale online immediately. The collected data were then processed and analyzed through SPSS (v. 17). The results of the analysis revealed that: (1) one of the measures of syntactic complexity has a significant negative relationship with perfectionism; (2) Personal Standards, one of the six dimensions of perfectionism, has a significant negative relationship with the participants’ L2 writing performance; (3) both Parental Expectations and Parental Criticism are found negatively correlated with the fluency aspect of the writing performance and the relationships have a significant effect. The implications of the findings are suggested for pedagogy and L2 learning.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".