Usability of the Management System of Public Libraries of Iran (SAMAN) from the perspective of Visually Impaired Users
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.
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.
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 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.006 | 0.002 |
| 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 it