The relationship between English language proficiency test scores and academic achievement: A longitudinal study of two tests
Bibliographic record
Abstract
English-medium universities often accept scores from various English language proficiency (ELP) tests as evidence of ELP from non-English background students. This practice raises the question of how these tests compare in terms of their ability to predict academic achievement. This longitudinal study addresses this question by examining the strength of the associations between total scores on the IELTS Academic and the TOEFL iBT, on one hand, and the academic achievement of 6481 non-English background undergraduate students in the first 10 semesters of their study at a Canadian, English-medium university, on the other. Findings revealed that the association between ELP and academic achievement varied across ELP tests and disciplines. Furthermore, students with different IELTS scores exhibited significantly different grade point average (GPA) trajectories over time. Specifically, students with lower IELTS scores tended to exhibit a more substantial decline in GPA over the 10 semesters compared to students with higher scores who displayed less decline in GPA, suggesting greater resilience. The findings and their implications for research concerning the relationship between ELP and academic achievement over time are discussed.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".