Information and communication technology related needs of college and university students with disabilities. Research in Learning
Bibliographic record
Abstract
Purpose: To explore variables related to how well the information and com-munication technologies (ICTs) related needs of students with different disabilities are being met on campus at institutions of higher education, at home and in e-learning contexts. We also explore the disciplines and programmes pursued by students with different disabilities and the specialised ICTs they use. Method: A total of 1,354 Canadian university and junior/community college students with various disabilities completed the POSITIVES Scale. Results: Post-secondary students often have several disabilities which may affect how easily they can use ICTs. Students ’ disabilities also influence the specialised ICTs they use and how well their ICT-related needs are being met. While the findings indicate that, overall, students ’ ICT-related needs are generally well met, the results also show that these are better met on campus than at home, and at colleges than at universities. This is not related to institution size or to students’ disciplines. Conclusions: Our results show more favourable than unfavourable findings. Nevertheless, there are concerns around the availability of computers with adaptive software/hardware in specialised laboratories as well as with institutional ICT loan programmes; funding for ICTs for personal use; training, both on and off campus; and technical support off campus.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".