Search Results (45)

Background: Maintaining physical activity (PA) is vital for older people, particularly those with frailty and mobility limitations. Wearable activity trackers and digital feedback tools show promise for encouraging PA, but their feasibility and acceptability in aged care remain underexplored. This study evaluated the feasibility and acceptability of using wearable and mobile devices for step tracking and examined the usability of three interfaces (Fitbit, mobile app, and website) for reviewing PA progress in aged care. Methods: This is a user experience and feasibility study that does not involve objective physical activity quantification or device performance analysis. It is a mixed-methods feasibility study conducted with 14 participants aged ≥65 years from residential and community aged care services in metropolitan and regional New South Wales, Australia. Participants used a Fitbit Inspire 3 linked to a study website and a mobile phone step-counting app to monitor their steps across the three interfaces for four weeks. Feasibility was evaluated through enrolment and retention, and acceptability through a facilitator-led survey. Quantitative items on usability, comfort, motivation and device preference were summarised descriptively; open-ended responses were analysed thematically to identify user experiences, benefits, and barriers. Results: Step tracking was feasible, with 82% enrolment and 93% retention. Participants preferred the Fitbit over the mobile phone or website due to its ease of use, visibility and more enjoyable experience. Step tracking increased awareness of PA and supported confidence to move more. Participants valued reminders, rewards and opportunities for social sharing. Reported barriers included illness, usability challenges and occasional technical issues. Conclusions: Wearable step trackers show promise for supporting PA among older people receiving aged care. Despite the small sample and short follow-up, strong acceptability signals suggest that simple digital tools could enhance the reach and sustainability of mobility-promoting interventions into aged care systems. Future studies should examine long-term adherence, usability across diverse mobility and cognitive needs, and conditions for successful scale-up. Full article

Although emerging technologies are increasingly adopted in teaching and learning, their potential to enhance educational administration remains underexplored. In particular, few studies examine how conversational agents, virtual reality (VR), and robotic process automation (RPA) can jointly streamline administrative workflows in multilingual and multicultural university environments. This study addresses this gap by presenting an integrated solution deployed on the website of an engineering faculty where programs are delivered in foreign languages. The proposed system combines a multilingual chatbot, a VR-based administrative guide and virtual tour, and RPA modules supporting certificate generation, password resets, and exam scheduling. Through an A/B usability test, usage analytics, and qualitative feedback, we evaluate the effectiveness of these technologies in improving access to information, reducing response time, and lowering administrative workload. Results show that this triad significantly enhances efficiency and student experience, particularly for international students requiring continuous support. The paper contributes a replicable model for leveraging emerging technologies in educational administration and offers insights for institutions seeking scalable and student-centered digital transformation. Full article

Background: Social media, especially Instagram, spreads nutrition-related information that often lacks scientific rigor. Many women report feeling inadequately informed about women’s health by healthcare professionals, turning to social media, increasing exposure to misinformation. Objectives: The NutriWomen platform aims to assess the quality, methodological soundness, and credibility of nutritional health claims and dietary recommendations on Instagram targeting women across different life stages. Its goal is to develop a systematic and scientifically grounded evaluation framework to assess Instagram nutrition-related claims and the methodological quality and interpretability of their supporting evidence, and to translate the results into accessible outputs that help women make informed nutrition decisions across life stages. Methods: This study follows a five-stage design Stage 1 involves a retrospective content analysis of Instagram posts containing nutrition-related claims targeted at women, identified through the “Top posts” function and screened using predefined criteria. Stage 2 assesses information quality using a validated 14-item tool. Stage 3 evaluates the scientific accuracy of claims by formulating PI(E)CO(TS) questions, selecting key outcomes, retrieving evidence from PubMed and the Cochrane Database, and appraising systematic reviews with a modified AMSTAR-2 tool incorporating GRADE ratings, when available. Stage 4 develops the NutriWomen website platform to translate assessments into accessible visual summaries. Stage 5 conducts a mixed-methods study with peri-, meno-, and postmenopausal women to explore information needs and evaluate platform usability through focus groups. Conclusions: The NutriWomen platform will be the first website to systematically publish the results of evaluations assessing the scientific quality of nutritional health claims on Instagram targeted at women across different life stages. It will provide a replicable methodology, and a digital tool designed to empower women with trustworthy nutrition information, with the potential to enhance health literacy and promote better health outcomes. Full article

Effective website usability assessment is crucial for improving user experience, driving customer satisfaction, and ensuring business success, particularly in the competitive e-commerce sector. Traditional methods, such as expert reviews and user testing, are resource-intensive and often fail to fully capture the complex interplay between a site’s aesthetic design and its technical performance. This paper introduces an end-to-end multimodal deep learning framework that automates the usability assessment of fashion e-commerce websites. The framework fuses structured numerical indicators (e.g., load time, mobile compatibility) with high-level visual features extracted from full-page screenshots. The proposed framework employs a comprehensive set of visual backbones—including modern architectures such as ConvNeXt and Vision Transformers (ViT, Swin) alongside established CNNs—and systematically evaluates three fusion strategies: early fusion, late fusion, and a state-of-the-art cross-modal fusion strategy that enables deep, bidirectional interactions between modalities. Extensive experiments demonstrate that the cross-modal fusion approach, particularly when paired with a ConvNeXt backbone, achieves superior performance with a 0.92 accuracy and 0.89 F1-score, outperforming both unimodal and simpler fusion baselines. Model interpretability is provided through SHAP and LIME, confirming that the predictions align with established usability principles and generate actionable insights. Although validated on fashion e-commerce sites, the framework is highly adaptable to other domains—such as e-learning and e-government—via domain-specific data and light fine-tuning. It provides a robust, explainable benchmark for data-driven, multimodal website usability assessment and paves the way for more intelligent, automated user-experience optimization. Full article

This study examines the feasibility of applying eye tracking as a rigorous method for assessing user experience in web design. A controlled experiment was conducted with 102 participants, who interacted with both guideline-compliant websites and systematically degraded variants violating specific principles of Material Design 2. Eleven websites were presented in A/B conditions with modifications targeting three design dimensions: contrast, link clarity, and iconography. Eye-tracking indicators—time to first fixation, fixation duration, fixation count, and time to first click—are examined in conjunction with subjective ratings and expert assessments. Mixed-effects models are employed to ensure robust statistical inference. The results demonstrate that reduced contrast and unclear links consistently impair user performance and increase search effort, whereas the influence of icons is more context-dependent. The study contributes by quantifying the usability costs of guideline deviations and by validating a triangulated evaluation framework that combines objective, subjective, and expert data. From a practical perspective, the findings support the integration of eye tracking into A/B testing and guideline validation, providing design teams with empirical evidence to inform and prioritize improvements in user interfaces. Full article

Nowadays, a pedestrian navigation system using a smartphone has become popular as a useful tool to reach an unknown destination. When the destination is the office of a person, a detailed map information is necessary on the target area such as the room number and location inside the building. The information can be collected from various sources including Google maps, websites for the building, and images of signs. In this paper, we propose a map information collection tool for a pedestrian navigation system. To improve the accuracy and completeness of information, it works with the four steps: (1) a user captures building and room images manually, (2) an OCR software using Google ML Kit v2 processes them to extract the sign information from images, (3) web scraping using Scrapy (v2.11.0) and crawling with Apache Nutch (v1.19) software collects additional details such as room numbers, facilities, and occupants from relevant websites, and (4) the collected data is stored in the database to be integrated with a pedestrian navigation system. For evaluations of the proposed tool, the map information was collected for 10 buildings at Okayama University, Japan, a representative environment combining complex indoor layouts (e.g., interconnected corridors, multi-floor facilities) and high pedestrian traffic, which are critical for testing real-world navigation challenges. The collected data is assessed in completeness and effectiveness. A university campus was selected as it presents a complex indoor and outdoor environment that can be ideal for testing pedestrian navigations in real-world scenarios. With the obtained map information, 10 users used the navigation system to successfully reach destinations. The System Usability Scale (SUS) results through a questionnaire confirms the high usability. Full article

Due to new treatment options, the number of patients living longer with advanced cancer is rapidly growing. While this is promising, many long-term responders (LTRs) face difficulties adapting to life with cancer due to persistent uncertainty, feeling misunderstood, and insufficient tools to navigate their “new normal”. Using the Person-Based Approach, this study developed and evaluated a website in co-creation with LTRs, healthcare professionals, and service providers, offering evidence-based information and tools for LTRs. We identified the key issues (i.e., living with uncertainty, relationships with close others, mourning losses, and adapting to life with cancer) and established the website’s main goals: acknowledging and normalizing emotions, difficulties, and challenges LTRs face and providing tailored information and practical tools. The prototype was improved through repeated feedback from a user panel (n = 9). In the evaluation phase (n = 43), 68% of participants rated the website’s usability as good or excellent. Interview data indicated that participants experienced recognition through portrait videos and quotes, valued the psycho-education via written text and (animated) videos, and made use of the practical tools (e.g. conversation aid), confirming that the main goals were achieved. Approximately 90% of participants indicated they would recommend the website to other LTRs. The Dutch website—Doorlevenmetkanker (i.e., continuing life with cancer) was officially launched in March 2025 in the Netherlands. Full article

With the increasing online activity of Arabic speakers, the development of effective CAPTCHAs (Completely Automated Public Turing Tests to Tell Computers and Humans Apart) tailored for Arabic users has become crucial. Traditional CAPTCHAs, however, are increasingly vulnerable to machine learning-based attacks. To address this challenge, we introduce a method for generating adversarial handwritten Arabic CAPTCHAs that remain user-friendly yet difficult for machines to solve. Our approach involves synthesizing handwritten Arabic words using a simulation technique, followed by the application of five adversarial perturbation techniques: Expectation Over Transformation (EOT), Scaled Gaussian Translation with Channel Shifts (SGTCS), Jacobian-based Saliency Map Attack (JSMA), Immutable Adversarial Noise (IAN), and Connectionist Temporal Classification (CTC). Evaluation results demonstrate that JSMA provides the highest level of security, with 30% of meaningless word CAPTCHAs remaining completely unrecognized by automated systems falling to 6.66% for meaningful words. From a usability perspective, JSMA also achieves the highest accuracy rates, with 75.6% for meaningless words and 90.6% for meaningful words. Our work presents an effective strategy for enhancing the security of Arabic websites and online interfaces against bot attacks, contributing to the advancement of CAPTCHA systems. Full article

Behavioral changes are critical for addressing sustainability challenges, which have become increasingly urgent due to the growing impact of global greenhouse gas emissions on ecosystems and human livelihoods. However, translating awareness into meaningful action requires practical tools to bridge this gap. Mobile applications, utilizing strategies from human–computer interaction (HCI) such as gamification, nudging, and persuasive technologies, have proven to be powerful in promoting sustainable behaviors. To support designers in developing effective apps of this kind, theory-based design guidelines were created, drawing on established theories and design approaches aimed at shaping and encouraging virtuous user behaviors fostering sustainability. To make these guidelines more accessible and enhance their usability during the design phase, this study presents their transformation into the SBAM card deck, a deck of 11 design cards. The SBAM cards aim to simplify theoretical concepts, stimulate creativity, and provide structured support for design discussions, helping designers generate solutions tailored to specific project contexts. This study also evaluates the effectiveness of the SBAM cards in the design process through two workshops with design students. Results show that the cards enhance ideation, foster creativity, and improve designers’ perceived self-efficacy compared to the exploitation of the same design guidelines information presented in traditional textual formats. This paper discusses the SBAM cards design and evaluation methodology, findings, and implications, offering insights into how the SBAM design cards can bridge the gap between theory and practice in sustainability-focused mobile app development. To ensure broader accessibility, the SBAM cards have been made available to the public through a dedicated website. Full article

This study introduces a novel evaluation framework for predicting web page performance, utilizing state-of-the-art machine learning algorithms to enhance the accuracy and efficiency of web quality assessment. We systematically identify and analyze 59 key attributes that influence website performance, derived from an extensive literature review spanning from 2010 to 2024. By integrating a comprehensive set of performance metrics—encompassing usability, accessibility, content relevance, visual appeal, and technical performance—our framework transcends traditional methods that often rely on limited indicators. Employing various classification algorithms, including Support Vector Machines (SVMs), Logistic Regression, and Random Forest, we compare their effectiveness on both original and feature-selected datasets. Our findings reveal that SVMs achieved the highest predictive accuracy of 89% with feature selection, compared to 87% without feature selection. Similarly, Random Forest models showed a slight improvement, reaching 81% with feature selection versus 80% without. The application of feature selection techniques significantly enhances model performance, demonstrating the importance of focusing on impactful predictors. This research addresses critical gaps in the existing literature by proposing a methodology that utilizes newly extracted features, making it adaptable for evaluating the performance of various website types. The integration of automated tools for evaluation and predictive capabilities allows for proactive identification of potential performance issues, facilitating informed decision-making during the design and development phases. By bridging the gap between predictive modeling and optimization, this study contributes valuable insights to practitioners and researchers alike, establishing new benchmarks for future investigations in web page performance evaluation. Full article

The digital transformation of museums has elevated their websites from mere informational tools to dynamic platforms that foster cultural engagement, inclusivity, and preservation. This study evaluates the performance of 234 museum websites worldwide, focusing on critical dimensions such as accessibility, usability, SEO, and speed. By employing a comprehensive diagnostic framework of evaluation metrics, the research reveals disparities between mobile and desktop versions, highlights regional variations, and identifies key performance drivers. Generally, desktop sites outperform their mobile counterparts, underscoring the necessity for tailored optimization strategies that strike a balance between fast-loading, visually stable mobile pages and content-rich desktop experiences. A key contribution of this study is the development of an easy-to-adopt and inclusive evaluation framework that unites fragmented approaches, enabling museums of all sizes to enhance their digital presence. Furthermore, the research provides actionable insights for administrators, particularly those in resource-constrained institutions, through a cost-free, user-friendly toolkit that simplifies technical metrics and promotes internal staff capacity building in digital analytics. Ultimately, the findings help empower museums to bridge digital performance gaps while ensuring they continue to function as vibrant cultural hubs in a rapidly changing digital landscape. Full article

The universities website has become an established tool, serving as an interface between an organization and its audience. For university websites, they act as portals for information and communication with students, facilitating educational and research objectives while promoting the institution’s image. Based on this perspective, the authors conducted a strategic monitoring/documentation process, employing both quantitative and qualitative methodologies to analyze the vast textual content from the websites of 101 universities in Romania. Data collection occurred from January 2021 to March 2022. These websites were monitored and analyzed comparatively for quality based on Minerva EU principles, which serve as the analytical standard, utilizing predefined categories: identification, relevance, maintenance, accessibility, user orientation, responsiveness, multilingualism, and interoperability. Additionally, the study assesses whether the websites provide useful information for students’ specific activities, including accessible informational and documentary resources within the university library’s digital environment. The results indicate that state universities (54 in total, both civilian and military) are the most relevant. They continually enhance their websites to serve as a vital access point for specific informational resources, including administrative, educational, documentary, and cultural resources. Full article

N6-methyladenosine (m⁶A) plays a crucial regulatory role in the control of cellular functions and gene expression. Recent advances in sequencing techniques for transcriptome-wide m⁶A mapping have accelerated the accumulation of m⁶A site information at a single-nucleotide level, providing more high-confidence training data to develop computational approaches for m⁶A site prediction. However, it is still a major challenge to precisely predict m⁶A sites using in silico approaches. To advance the computational support for m⁶A site identification, here, we curated 13 up-to-date benchmark datasets from nine different species (i.e., H. sapiens, M. musculus, Rat, S. cerevisiae, Zebrafish, A. thaliana, Pig, Rhesus, and Chimpanzee). This will assist the research community in conducting an unbiased evaluation of alternative approaches and support future research on m⁶A modification. We revisited 52 computational approaches published since 2015 for m⁶A site identification, including 30 traditional machine learning-based, 14 deep learning-based, and 8 ensemble learning-based methods. We comprehensively reviewed these computational approaches in terms of their training datasets, calculated features, computational methodologies, performance evaluation strategy, and webserver/software usability. Using these benchmark datasets, we benchmarked nine predictors with available online websites or stand-alone software and assessed their prediction performance. We found that deep learning and traditional machine learning approaches generally outperformed scoring function-based approaches. In summary, the curated benchmark dataset repository and the systematic assessment in this study serve to inform the design and implementation of state-of-the-art computational approaches for m⁶A identification and facilitate more rigorous comparisons of new methods in the future. Full article

Nowadays, e-commerce websites have become part of people’s daily lives; therefore, it has become necessary to seek help in assessing and improving the usability of the services of e-commerce websites. Essentially, usability studies offer significant information about users’ assessment and perceptions of satisfaction, effectiveness, and efficiency of online services. This research investigated the usability of two e-commerce web-sites in Saudi Arabia and compared the effectiveness of different behavioral measurement techniques, such as heuristic evaluation, usability testing, and eye-tracking. In particular, this research selected the Extra and Jarir e-commerce websites in Saudi Arabia based on a combined approach of criteria and ranking. This research followed an experimental approach in which both qualitative and quantitative approaches were employed to collect and analyze the data. Each of the behavioral measurement techniques identified usability issues ranging from cosmetic to catastrophic issues. It is worth mentioning that the heuristic evaluation by experts provided both the majority of the issues and identified the most severe usability issues compared to the number of issues identified by both usability testing and eye-tracking combined. Usability testing provided fewer problems, most of which had already been identified by the experts. Eye-tracking provided critical information regarding the page design and element placements and revealed certain user behavior patterns that indicated certain usability problems. Overall, the research findings appeared useful to user experience (UX) and user interface (UI) designers to consider the provided recommendations to enhance the usability of e-commerce websites. Full article

This paper delves into the complex task of evaluating a website user interface (UI) and user experience (UX), a process complicated by gaps in research. To bridge this, we introduced an innovative human–computer interaction (HCI) framework that synergizes expert cognitive walkthroughs and user surveys for a comprehensive view. We transformed user responses into three key domains—control, engagement, and goal. Our work also generalized an extract of four context-level data metrics for a robust evaluation. The numerical evidence, such as a C1 score of 4.1, surpassing the expert usability benchmark, indicated our framework’s effectiveness. Our research not only addresses an essential gap by integrating assessments from both users and experts, but also offers actionable insights for UI/UX design. The findings extend beyond this specific context, providing a potent evaluation tool for website usability across various websites. Lastly, the research underscores the importance of prioritizing users’ needs and expert recommendations in design principles, significantly contributing to the broader domain of website usability and user experience. Full article