The Correlation between Business English Freshmen's Learning Motivation and Self-efficacy
Bibliographic record
Abstract
Researchers have conducted numerous studies on the phenomenon of learners' motivation in foreign language acquisition; however, there is a paucity of research examining the relationship between English learning motivation and self-efficacy among Business English freshmen. This study aims to address three key questions to explore the correlation between English learning motivation and self-efficacy among Business English majors: (1) What is the level of English learning motivation among first-year business English majors? (2) What is the overall status of self-efficacy in English learning among first-year business English majors? (3) What is the association between English learning motivation and self-efficacy among first-year business English majors? Subsequently, employing SPSS data analysis, this research yields several noteworthy findings: firstly, the level of English learning motivation among first-year business English majors is significantly high; secondly, their perceived self-efficacy in mastering the language falls within a moderate range; finally, the relationship between English learning motivation and self-efficacy demonstrates a positive correlation (R=.595*).
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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 | 0.002 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".