Exploring the Relationship Between Motivation and IELTS Reading Proficiency Among Chinese Learners
Bibliographic record
Abstract
This study investigates the impact of motivational factors on the reading test performance of Chinese learners in the IELTS examination. The objectives are to evaluate the motivation levels, analyze the relationship between motivation and IELTS reading achievement, and identify the most influential predictors among intrinsic and extrinsic motivations. Using a quantitative research design and a sample of 242 students from 12 IELTS training centers in southwest China, data were collected through the Motivation in English Reading Questionnaire (MERQ) and Cambridge Practice Tests for IELTS. Pearson correlation coefficients and multiple regression analysis were employed to analyze the data. The results show significant positive correlations between various motivational constructs and IELTS reading scores. Total motivation (r = .634, p < .001), efficacy and engagement (r = .520, p < .001), utility value (r = .459, p < .001), and academic value (r = .424, p < .001) are all positively associated with reading proficiency. Regression analysis indicates that intrinsic motivation, specifically efficacy and engagement (β = 0.504), is the strongest predictor of reading scores, followed by utility value (β = 0.351) and academic value (β = 0.315). These findings underscore the essential role of both intrinsic and extrinsic motivations in improving reading proficiency among Chinese IELTS learners.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".