Usability of the Management System of Public Libraries of Iran (SAMAN) from the perspective of Visually Impaired Users
Bibliographic record
Abstract
Objective: The purpose of this research is to assess the usability of the management system of public libraries (Saman) from the perspective of visually impaired users. Method: The research was applied a formal usability testing. The usability of the system was evaluated through exploratory observation of users with visual impairments (think-aloud protocol) by defining three real tasks. 10 users were selected by purposeful sampling method. Task completion was monitored using screen recording software. Data analysis was conducted using Excel and MAXQDA. Guba and Lincoln's criteria were employed to ensure data credibility. Results: On average, each user spent approximately 30.9 minutes locating a resource, over 11 minutes for electronic membership requests, and about 7 minutes for sending inquiries to librarians. Few users were able to navigate the system without assistance, and some users were unsuccessful in completing their tasks. Ninety percent of users rated the ease of use of the system as poor and expressed dissatisfaction with the time spent on task completion. Key usability barriers were identified across 177 codes and five categories. The most frequent barriers included accessibility of combo boxes or dropdown menus, proper design, keyboard accessibility, logical heading structure, search complexity, system messages, and conveying information with senses. Conclusions: Usability is a fundamental condition for the sustained performance of websites. Libraries and inclusive websites focus on diverse stakeholders. Engaging real end-users is a vital aspect of user-centered design, highlighting the need for continuous assessment of their expectations.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".