Determination of Appropriate IELTS Writing and Speaking Band Scores for Admission into Two Programs at a Canadian Post-Secondary Polytechnic Institution
Bibliographic record
Abstract
This study aimed to determine the appropriate IELTS band scores in Writing and Speaking for admission to and success in Computer Systems Technology (CST) and Computer Information Technology (CIT) programs at a large Canadian polytechnic post-secondary institute. A second aim was to explore whether the quality of admissions decisions could be enhanced by aligning their processes more closely with the English language demands of actual tasks required within their target programs. This was done by examining course materials, activities, and assignments in which students are required to read, write, speak, and listen in English and then comparing the required proficiency in English for those tasks to band score descriptors provided by the IELTS measure. Data consisted of student interviews, faculty interviews, observations of lectures and labs, and course documents. Because of the small number of interviewees and the limited depth and scope of content analysis, results should be viewed as indicative rather than conclusive.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".