Purpose: This study presents a user interface model for library websites tailored to visually impaired (VI) users, leveraging the potential of artificial intelligence (AI). Method: Through exploratory observation of 33 visually impaired users performing three real tasks on library websites, key factors affecting usability were identified. Data collection involved formal usability testing combined with the think-aloud protocol. The interfaces of four prominent Iranian library websites were analyzed. Content analysis supported by MAXQDA software was used to interpret the data, and Cohen’s kappa coefficient was employed to measure inter-coder reliability. Findings: The main findings of this study revealed that a logical webpage structure and clear descriptive headings have the most significant impact on usability. Additionally, inconsistent labeling, search and results presentation complexity, lack of interface customization options, and technical challenges were identified as major accessibility barriers for visually impaired users. AI-based solutions such as automatic error correction, intelligent voice assistants, AI-powered question answering, result clustering, smart filtering, text and image processing, summarization, and interface personalization were proposed to enhance the user experience. Overall, by integrating user feedback and cutting-edge AI technologies, libraries can create more inclusive digital environments that cater effectively to the needs of visually impaired patrons, setting a precedent for future developments in accessible information retrieval systems. Conclusion: Improving library website usability for visually impaired users requires a nuanced understanding of their specific needs. This research contributes by identifying underexplored AI-based strategies that can significantly enhance accessibility and user satisfaction. Future studies should assess the long-term effectiveness of these approaches and explore additional enhancements.
Azam Najafgholinejad (Thu,) studied this question.