TOWARD ACCESSIBLE COMPUTER‐BASED TESTS: PROTOTYPES FOR VISUAL AND OTHER DISABILITIES
Bibliographic record
Abstract
ABSTRACT There is a great need to explore approaches for developing computer‐based testing systems that are more accessible for people with disabilities. This report explores three prototype test delivery approaches, describing their development and formative evaluations. Fifteen adults, 2 to 4 from each of the six disability statuses—blindness, low vision, deafness, deaf‐blindness, learning disability, and no disability—participated in a formative evaluation of the systems. Each participant was administered from 2 to 15 items in each of one or two of the systems. The study found that although all systems had weaknesses that should be addressed, almost all of the participants (13 of 15) would recommend at least one of the delivery methods for high‐stakes tests, such as those for college or graduate admissions. The report concludes with recommendations for additional research that testing organizations seeking to develop accessible computer‐based testing systems can consider.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".