An exploratory study of college and university students with visual impairment in Canada: Grades and graduation
Bibliographic record
Abstract
The purpose of this investigation was to explore predictors and correlates of grades and intention to graduate among junior/community college and university students with visual impairments in Canada, and to compare students with low vision to students who are blind on variables related to academic success. In all, 66 junior/community college and university students with visual impairments (17 blind, 49 with low vision) in Canada completed an online questionnaire inquiring about grades, intention to graduate, and demographic, school-related, and personal aspects. Stepwise regression, discriminant, and correlational analyses of the data revealed that the following variables were associated with better grades and stronger intention to graduate: higher course self-efficacy expectations, greater perceived behavioral control over graduation, reporting a single rather than multiple disabilities, and more favorable attitude toward graduation. Students who are blind and those with low vision did not differ on most variables studied although a much larger proportion of students with low vision reported having additional disabilities. Recommendations are made to enhance course self-efficacy beliefs which include, providing a campus atmosphere that is welcoming, and ensuring that students with visual impairments have adequate opportunities to dialogue with faculty and fellow students. Postsecondary student services professionals need to ensure that workshops which teach study, research, and time management skills are inclusive and accessible to students with visual impairments.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".