Experience of Visually Impaired Users Interacting with Systems of the Iranian Research Institute for Information Science and Technology (IranDoc): Challenges and Limitations
Bibliographic record
Abstract
Objective: This study aimed to investigate the experiences of visually impaired users when interacting with the Iranian Research Institute for Information Science and Technology (IRANDOC) systems and to identify the challenges they encounter.Methodology: The research employed a qualitative approach using interviews and concurrent think-aloud protocols to observe visually impaired users interacting with IRANDOC systems using assistive technologies. The interactions of 24 visually impaired users were analyzed while performing defined tasks within these systems. The study population consisted of visually impaired individuals with university degrees who could independently interact with the screen using a keyboard or assistive technologies such as screen readers and magnifiers, and had the necessary knowledge to use search engines and websites. MAXQDA software was used to summarize and analyze the qualitative data. The observation notes and participant statements were analyzed using qualitative content analysis, resulting in 394 initial codes categorized into 9 categories and 28 subcategories. Guba and Lincoln's criteria were used to ensure the reliability and validity of the data.Findings: Challenges were identified in information structure and relationships (logical headings, structure of boxes, buttons, radio buttons, checkboxes, and comboboxes, clear and descriptive labels, serial reading of content, and meaningful sequence), text alternatives for graphic and non-text content and security codes/CAPTCHAs, functional principles, design of tables, content in accessible formats, keyboard navigation (shortcuts and cursor cancellation), input assistance (error identification, error suggestion, error prevention, form control labels, and reduced keystrokes), content compatibility with screen reader software (status messages), navigability of pages (page titles and link purpose), predictable performance of page elements (conventional operation and guidance and support), sensory features (accessibility menu, contrast, magnification, use of color, and alignment of options), and time constraints (moving content).Conclusion: This research emphasizes the importance of ongoing efforts to improve the usability of IRANDOC systems for all users, including those with visual impairments. By addressing the identified challenges outlined in this study, IRANDOC can strive to create a more inclusive and equitable information environment for all researchers. This study is one of the first systematic investigations into the interaction of screen reader users with IRANDOC systems. Improving the usability of these systems requires serious efforts to address the identified challenges and implement research recommendations. Much work remains to be done. The issues identified in this study need to be investigated. Design is an iterative process. Redesign and usability testing should continue until we are confident that the new design meets our goals.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".