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Record W7103151465 · doi:10.30481/lis.2025.495292.2222

Experience of Visually Impaired Users Interacting with Systems of the Iranian Research Institute for Information Science and Technology (IranDoc): Challenges and Limitations

2025· article· fa· W7103151465 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languagefa
FieldSocial Sciences
TopicDigital Accessibility for Disabilities
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsScreen readerVisually impairedSoftwareCursor (databases)Qualitative researchLegibilityPopulationReading (process)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.009
Scholarly communication0.0020.016
Open science0.0030.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.407
GPT teacher head0.588
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it