User Interface

This study investigates the relationship between the user interface and problem-solving towards the continuous intention to use the services. New products or services will always face tough challenges for the customer, especially when the new procedures require them to learn and change some behaviors. Chatbots are also facing the same situation in Malaysia, where customers refuse to accept using chatbots to represent their physical presence. To understand customer behaviors, a quantitative survey was designed. Four hundred twenty-two data were collected from the online survey method. As per the results, the predictors of chatbot continuous intention are user interface and problem-solving. Apart from that, this study also measures the role of mediator, namely trust and customer satisfaction. This study contributes to unique academic and practical insights that can be used to explore the effectiveness of chatbots. The results revealed that both predictors were significant towards the continuous intentions. Besides, the role of the mediator was found to be significant and relevant in the relationship between trust and customer satisfaction and customer satisfaction and trust towards continuous attention.

Individuals with Spinal Cord Injuries (SCI) encounter substantial barriers in accessing digital media content. Artificial Intelligence-based User Interfaces (AI UIs) possess the potential to mitigate these barriers; however, the role of creativity in their actual user experience remains underexplored. This qualitative study, aiming to analyze the impact of creativity within AI UIs on facilitating media access, investigated the experiences of 18 Iranian users with SCI through in-depth semi-structured interviews and thematic analysis. Findings indicate that AI UIs, by offering innovative interaction modalities, significantly enhance user autonomy and reduce physical impediments (a manifestation of positive creativity). However, significant challenges persist concerning accuracy, reliability, speed, complexity of use, and customization (stemming from inadequate creativity in implementation). Users articulate a demand for highly reliable, fast, simple, adaptable interfaces with adequate support. It is concluded that AI UIs hold considerable empowering potential; however, to fully realize this potential, a user-centered, inclusive design approach and a focus on operational creativity are imperative to address real-world challenges and enhance the user experience.

Purpose: This research aims to evaluate the user interfaces of the English web pages of selected national digital libraries, based on the established criteria found in the resources to propose a suitable interface for the Payame Noor University digital library. Method: This research employed a survey and descriptive methodology. A checklist included 10 main criteria and 114 sub-criteria was used for evaluation. The study population included digital libraries from various countries including America, Australia, France, Swiss, New Zealand, Netherland, Poland, Japan, India and Italy. Data analysis was performed using SPSS software and Excel. The hypotheses and questions were tested by t-test and Friedman-test. Findings: The conclusions indicated that 50% of criteria were met by 50% of libraries. The American library ranked first, meeting 70.40% of criteria, followed by France at 62.07% and Swiss at 40.12%. Also the interface language criterion was the most frequently implemented, with a usage rate of 6.68%. User control was the least implemented used also at 6.68%. Conclusion: The research findings indicate that the most libraries have been successful with the general criteria, and the majority of points earned pertain to adherence to these general criteria on their website pages. In particular, no attention has been paid to the criteria encompassing the scope of digital libraries’ duties, as per definitions. As observed in the findings, the interface language criterion shows the highest level of compliance. One possible reasons for this consistency across all libraries may be that the primary language in these countries is not English, leading to efforts aimed at enhancing user convenience and greater interaction of the user through careful attention to writing-related aspects on the pages. Furthermore, compliance with writing points and brevity of sentences is a key category in web pages design.

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.