User Experience Research Articles

A Study of Mobility as a Service for Mobility Management System in the Education Sector

The initiative of the Peru provides robust assistance for promoting mobility to facilitate the discovery of training or employment prospects. It is imperative to discover solutions for limited mobility during widespread disease outbreaks. A practical approach would be establishing a collaborative platform that facilitates cooperation in both professional and educational domains. This research seeks to determine the essential elements to develop a new ecosystem to promote Peru’s academic mobility. This research utilized qualitative and quantitative techniques, specifically interviews, to gather data from 150 participants. The researchers employed the NVivo applications, notably its Word Frequency Query tool, to discern pertinent attributes within the four primary groups: competency acquisition, teaching methods, organization, and technologies. The results indicate that focusing on acquiring skills relevant to the future job marketplace is essential. Learners show a preference for activities that incorporate gamification. The platform ought to be designed to facilitate effortless searching for jobs and training opportunities. In general, learners have a good perception of material that focuses on the future, motivates them, and includes various technical activities. The user experience study might be expanded to encompass a cohort of educators and administrative staff involved in educational Mobility as a Service (MaaS) endeavors.

User Sentiment Analysis Towards Islamic Banking Applications in Indonesia

This study aims to analyze user sentiment towards Islamic banking applications in Indonesia, focusing on Islamic banking applications that have the lowest ratings on Google Playstore. The analysis was conducted to understand perceptions, satisfaction, and factors that influence user experience towards both applications in the context of Islamic economics. The research method used is a quantitative approach with sentiment analysis techniques on user reviews taken from Google Playstore. Data was collected by scraping user reviews and analyzed using the Natural Language Processing (NLP) method to identify positive and negative sentiments. In addition, descriptive analysis was used to explore the main themes that emerged in the user reviews. The results showed that the trust factor was the main contributor to positive sentiment, reaching 45.16% of the total positive sentiment. The feature factor was also significant, contributing 27.90%, while the Sharia aspect factor contributed 6.29%. The technical and service factors contributed 11.61% and 5.97%, respectively. These findings indicate that trust in the application, including security and integrity, as well as relevant features, is an essential element in shaping positive user sentiment. This study provides valuable insights for Islamic banking application developers and related parties to understand user needs and expectations. In addition, these findings highlight the importance of improving aspects of trust and application features to increase user satisfaction and loyalty. These findings contribute to the literature on Islamic economics and Islamic banking app development in the digital era and provide practical guidance to improve application performance in the Indonesian digital banking market.

Analysis and Research on the Difference of Urban Park Usage Experience of Obese People

Analysis and Research on the Difference of Urban Park Usage Experience of Obese People

WebMRT: An online tool to predict summertime mean radiant temperature using machine learning

Mean Radiant Temperature (Tmrt) is the most critical atmospheric variable influencing outdoor human thermal exposure and comfort in hot, dry environments. However, accurately quantifying Tmrt requires time-consuming field measurements with expensive equipment or complex, resource-intensive computations. We introduce WebMRT, an online tool to predict Tmrt using a data-driven approach. It features an intuitive interface using air temperature, shading status, and built environment features as predictors of Tmrt for a user-selected summer day, time, and location. Utilizing a tree-based ensemble model, WebMRT is trained on state-of-the-art human-biometeorological data collected by MaRTy using LightGBM after evaluating its performance against several candidate machine learning regressors. Feature engineering was applied to the day and time input, and two additional temporal features were derived: ‘Solar Altitude’ and ‘Minutes-from-Sunrise’. These inputs are integrated into the user interface, emphasizing simplicity and easy access for users at the frontend. After training the regressor on MaRTy datasets and employing k-fold cross-validation with ten folds, the model demonstrated strong predictive power (R2=0.92) with acceptable error (RMSE=3.43, MAPE=5.33) and bias (MBE=0.20). WebMRT also features optional fisheye photo uploads, processed using transfer learning techniques for image segmentation, further enhancing the tool's predictive accuracy, user experience, and applications towards climate action decision-making processes.

Blockchain Based Secure File Transfer System with Password Protection

The need of secure file transfer systems is higher nowadays. In order to enhance the security and privacy of private information transferred over the internet, our paper presents a blockchain-based secure file transfer system (BSFTS) with password protection. This system takes advantage of the decentralized and immutable properties of blockchain technology to ensure that every file transfer is Safe and Secure, offering verifiable audit trails that can minimize the threats associated with data tampering and unauthorized access. Through forcing people to use strong, unique passwords for decryption as well as encryption, the combination of password protection further secures files by ensuring that only specified people may access the information. In addition to enhancing data confidentiality, this dual-layer strategy increases defences against possible cyberthreats, including phishing and brute force attacks. Research shows that the blockchain-based secure file transfer system with password protection far exceeds standard file transfer techniques in terms of security and user experience. The results illustrate that password protection and blockchain technology work together to build a robust framework for secure file sharing. For companies trying to enhance their data protection plans in the face of changing security threats in the world of technology, this study provides helpful data

Analysis of User Satisfaction with the Netflix Application as an Entertaiment Medium Using the UX Method

This research was conducted to analyze user satisfaction with the Netflix application using the UX Honeycomb method. The UX Honeycomb method is used to evaluate various aspects of user experience, such as usability, aesthetic value, sustainability, accessibility, satisfaction, and diversity. This study involved data collection through online surveys and interviews with active Netflix users. Data analysis was conducted using statistical techniques and qualitative interpretation. The UX Honeycomb method was employed to understand the essential aspects of user experience within the application. The results of this study are expected to provide valuable insights for other streaming service providers to enhance their service quality and create a better user experience. Additionally, the contribution of the UX Honeycomb methodology in assessing user satisfaction can serve as a foundation for further research in the context of digital entertainment applications.

Parkinson’s Disease (PD) Management in a Tertiary Irish Hospital

Abstract Background There is no Irish platform for operationalizing services for People with Parkinson’s and associated disorders (PwP). The UK-wide Parkinson’s clinical audit was developed in 2009, to address concerns about the quality of care provided to PwP. Our aim was to use the UK Parkinson’s Audit cycles to drive quality improvement in our service, providing the first Irish data on quality of care for PwP. Methods The audit’s service descriptor was completed in June 2022. A sample of PwP attending Movement-Disorder clinics completed patient reported experience measure questionnaires between May - July 2022. We retrospectively collected patient data using the audit tool, which was submitted electronically. This was directly compared to our service audit data from 2019. Results In 2019, we included 30 patients in our audit – average age 67yrs, 57% male, 100% Caucasian, average duration PD 7yrs. In 2022, we included 40 patients of similar demographics. The data collected showed our services had improved or remained stable across all domains from 2019 to 2022 including medication documentation, advanced care planning, multi-disciplinary team input, non-motor, activities of daily living and bone health assessments. The service user experience remained unchanged. In 2019, our service fell in the lowest quartile of standards amongst the cohort of services audited. We improved to the top half of services audited in 2022. This was achieved by mentoring from exemplar UK services, generating a proforma to standardize assessments in outpatients, providing information to clinicians regarding local services and engaging with patients in an annual ‘Have Your Say’ day. Conclusion Our data demonstrates that repeated national audit cycles, with the patient voice at the centre, are crucial in driving quality improvement across services for PwP. As the only Irish participant in the Parkinson’s UK Audit, it's clear a National Irish Audit would be the first step in optimizing care for PwP nationally.

Development of a T2D App for Elderly Users: Participatory Design Study via Heuristic Evaluation and Usability Testing

Diabetes management applications effectively help patients monitor blood glucose levels and adjust diet and exercise plans. However, most diabetes management apps, including the SugarShift application developed in 2023, use generalized designs that often fail to consider the unique cognitive and physiological characteristics of elderly users, thereby impacting their acceptance and usage. This paper proposes an enhancement for the SugarShift application by introducing a mode specifically designed for elderly users. This proposed enhancement aims to directly involve elderly patients so as to meet their needs better through a participatory design approach. A heuristic evaluation conducted with six experts identified 126 usability issues and 179 heuristic violations in the current version, which has led to the recommendation to develop optimization strategies tailored for elderly users. Subsequent usability testing with 28 elderly patients and six experts emphasized the importance of interface simplicity, logical operation, and interaction quality in enhancing user experience. These factors improve usability, facilitate information processing, and reduce cognitive load. Despite the overall usability of SUS scores, significant challenges still need to be addressed in information display, system feedback, and user interaction. Recommendations for future enhancements include simplifying data entry and presentation, improving readability, and providing timely feedback to enhance usability and user satisfaction, ultimately increasing user retention.

Feminist Impact via Chinese Social Media

This paper discusses the impact of feminism on women through the Chinese social media and e-commerce platform—Xiaohongshu. Sentiment and themes were categorized for 50 top posts of feminism, which ranged from feminism Comment, female power education to analysis of movie and news. The research reveals that different content categories, emotional tones, and commentator feedback significantly influence user engagement. This study is also an indication of active engagement and diversity of ideas on issues of feminism by young Chinese women. These findings offer valuable insights for content creators and platform operators, emphasizing the need to consider emotional and categorical dynamics in strategy development to optimize user experience and content dissemination on Xiaohongshu.

A theoretical framework for human-centered intelligent information services: A systematic review

Intelligent Information Services (IIS) employ Artificial Intelligence (AI)-based systems to provide information that matches the user's needs in diverse and evolving environments. Acknowledging the importance of users in AI-empowered IIS success, a growing number of researchers are investigating AI-empowered IIS from a user-centric perspective, establishing the foundation for a new research domain called “Human-Centered Intelligent Information Services” (HCIIS). Nonetheless, a review of user studies in AI-empowered IIS is still lacking, impeding the development of a clear definition and research framework for the HCIIS field. To fill this gap, this study conducts a systematic review of 116 user studies in AI-empowered IIS. Results reveal two primary research themes in user studies in AI-empowered IIS: human-IIS interaction (including user experience, system quality, user attitude, intention and behavior, information quality, and individual task performance) and IIS ethics (e.g., explainability and interpretability, privacy and safety, and inclusivity). Analyzing research gaps within these topics, this study formulates an HCIIS research framework consisting of three interconnected elements: human values and needs, environment, and service. The interconnections between each pair of elements identify three key research domains in HCIIS: interaction, ethics, and evolution. Interaction pertains to the facilitation of human-IIS interaction to meet human needs, encompassing topics including human-centered theory, evaluation, and the design of AI-empowered IIS interaction. Ethics emphasize ensuring AI-empowered IIS alignment with human values and norms within specific environments, covering topics like general and context-specific AI-empowered IIS ethical principles, risk assessment, and governance strategies. Evolution focuses on addressing the fulfillment of human needs in diverse and dynamic environments by continually evolving intelligence, involving the enhancement of AI-empowered IIS environmental sensitivity and adaptability within an intelligent ecosystem driven by technology integration. Central to HCIIS is co-creation, situated at the intersection of interaction, evolution, and ethics, emphasizing collaborative information creation between IIS and humans through hybrid intelligence. In conclusion, HCIIS is defined as a field centered on information co-creation between IIS and humans, distinguishing it from IIS, which focuses on providing information to humans.

Mental Model-Based Designs: The Study in Privacy Policy Landscape

Users’ mental models influence secure and privacy-preserving behavior in a computing environment. Prior studies on users’ mental models of Internet, security tools, and digital privacy show that there is no one-size-fits-all solution when it comes to security and privacy design. However, little study to date has explored the ways to translate users’ mental models into interactive security and privacy designs. As we begin to address this gap, we focus on privacy policy in this paper. The typical text-based privacy policy suffers from poor readability and usability. A recent study proposed a Visual Interactive Privacy Policy (VIPP), showing promise to offer a better user experience as compared to prior designs – we used VIPP as a control condition and compared that with our mental model (MM)-based designs, inspired by users’ privacy mental models explored in the existing literature. We iteratively improved our MM-based designs through a series of user studies in the lab setting. We evaluated our updated designs in an online study with 182 participants over Amazon Mechanical Turk. The participants rated MM-based designs significantly better than the control in most of our evaluation parameters. Furthermore, we found that when a design is centered around the mental model of participants, study participants rated it higher in terms of personal connection to the design, perspicuity, attractiveness, being stimulated towards privacy protection, as well as the propensity for real-life adoption. Based on our findings, we discussed the successes and challenges of MM-based designs and provided guidelines on the scope of leveraging mental models in the broader area of privacy and security designs.

Game Difficulty Prediction Based on Facial Cues and Game Performance

Current research on game difficulty prediction mainly uses heuristic functions or physiological signals. The former does not consider user data, while the latter easily causes interference to the user. This paper proposes a difficulty prediction method based on multiple facial cues and game performance. Specifically, we first utilize various computer vision methods to detect players’ facial expressions, gaze directions, and head poses. Then, we build a dataset by combining these three kinds of data and game performance as inputs, with the subjective difficulty ratings as labels. Finally, we compare the performance of several machine learning methods on this dataset using two classification tasks. The experimental results showed that the multilayer perceptron classifier (abbreviated as MLP) achieved the highest performance on these tasks, and its accuracy increased with the increase in input feature dimensions. These results demonstrate the effectiveness of our method. The proposed method could assist in improving game design and user experience.

Enhancing Recommendation Diversity and Novelty with Bi-LSTM and Mean Shift Clustering

In the digital age, personalized recommendation systems have become crucial for information dissemination and user experience. While traditional systems focus on accuracy, they often overlook diversity, novelty, and serendipity. This study introduces an innovative recommendation system model, Time-based Outlier Aware Recommender (TOAR), designed to address the challenges of content homogenization and information bubbles in personalized recommendations. TOAR integrates Neural Matrix Factorization (NeuMF), Bidirectional Long Short-Term Memory Networks (Bi-LSTM), and Mean Shift clustering to enhance recommendation accuracy, novelty, and diversity. The model analyzes temporal dynamics of user behavior and facilitates cross-domain knowledge exchange through feature sharing and transfer learning mechanisms. By incorporating an attention mechanism and unsupervised clustering, TOAR effectively captures important time-series information and ensures recommendation diversity. Experimental results on a news recommendation dataset demonstrate TOAR’s superior performance across multiple metrics, including AUC, precision, NDCG, and novelty, compared to traditional and deep learning-based recommendation models. This research provides a foundation for developing more intelligent and personalized recommendation services that balance accuracy with content diversity.

Sistem Informasi Penyewaan Arena Futsal dan Alarm Permainan dengan Menggunakan Laravel Berbasis Web di Kota Kraksaan Kabupaten Probolinggo

The advancement of information technology has transformed the management of futsal businesses, simplifying processes such as court reservations, schedule management, payments, and providing automated notifications to users through a game alarm feature. This system also includes an automatic reporting feature that generates accurate and real-time rental summaries. This study aims to design and implement a web-based futsal rental information system using the Laravel framework, featuring a game alarm to enhance management efficiency. The system is designed to address limitations in futsal rental management and time scheduling, as well as simplify the reporting process, which is currently done manually. The system development follows the waterfall model, which includes requirements analysis, system design, implementation, testing, and maintenance stages. The results show that the implementation of this web-based system significantly improves the efficiency of futsal court management in Kraksaan City, particularly in managing game time, rental reporting, and real-time financial management. The game alarm feature effectively reduces time conflicts between users, while the automatic reporting feature helps business owners track revenue and rental trends easily. The implementation of this system is expected to improve service quality and provide a better user experience, while assisting business owners in managing their operations more efficiently.

Research progress on key technologies of flexible wearable electronic devices

Flexible wearable device is an innovative technology product, using soft, lightweight material design, can fit the curve of the human body, providing a comfortable wearing experience. These devices typically integrate a variety of sensors, batteries, and connectivity technologies to enable biometric monitoring, motion tracking, communication, and other intelligent functions. Traditional electronic products tend to give a "stiff" impression that they cannot withstand bending, twisting and stretching. In recent years, under the background of the integration of electronic technology and modern material science technology, the emerging flexible electronic wearable device has become a research hotspot with its more flexible material, more sensitive and accurate signal transmission, and more extensive monitoring range. The development of flexible electronic technology has greatly improved the user's wearing experience and is more suitable for the free movement of the human body. This paper summarizes the basic principle and classification of key technologies of wearable electronic devices, and introduces the research progress and research trend.

Assessment of the Effectiveness of the E-Government System in Camarines Norte Provincial Hospital

The research focuses on evaluating the effectiveness of the e-government system at Camarines Norte Provincial Hospital. It assesses the system's performance using the System Evaluation Questionnaire aligned with the ISO 25010-2011 system/software quality model indicators, which include functionality, reliability, usability, performance efficiency, compatibility, portability, and security. The study's findings indicate that iHOMIS performs exceptionally well at Camarines Norte Provincial Hospital, particularly excelling in functionality, reliability, usability, and security. This suggests that the system is robust, user-friendly, and meets users' needs effectively, with users expressing confidence in the system's data protection and privacy measures.However, the results for performance efficiency, compatibility, maintainability, and portability are satisfactory but suggest areas for improvement. Overall, the findings point to a positive user experience at Camarines Norte Provincial Hospital, although there is potential for further enhancements to achieve consistent excellence across all evaluated criteria. The study concludes that iHOMIS is well-suited to meet the e-governance needs of government facilities like Camarines Norte Provincial Hospital. The successful implementation of iHOMIS at CNPH demonstrates the significant impact of the Department of Health's initiative in improving hospital operational efficiency and patient outcomes. CNPH's digital transformation journey serves as a model for other government healthcare facilities aiming to enhance patient outcomes through digital means. The insights from this study are expected to be pivotal in advancing e-government initiatives nationwide.

Artificial Intelligence-Based Electric Vehicle Smart Charging System in Malaysia

The worldwide transition to electric vehicles (EVs) is gaining momentum, propelled by the imperative to reduce carbon emissions and foster sustainable transportation. In Malaysia, the government is facilitating this transformation through targeted initiatives aimed at promoting the use of electric vehicles (EVs) and developing the required infrastructure. This paper investigates the crucial role of artificial intelligence (AI) in developing intelligent electric vehicle (EV) charging infrastructure, specifically focusing on the context of Malaysia. The paper examines the current electric vehicle (EV) charging infrastructure in Malaysia, highlights advancements led by artificial intelligence (AI), and references both local and international case studies. Fluctuations in the Total Industry Volume (TIV) and Total Industry Production (TIP) reflect changes in market demand and production capabilities, with notable peaks in March 2023 and March 2024. The research reveals that AI technologies, such as machine learning and predictive analytics, can enhance charging efficiency, improve user experience, and support grid stability. A mathematical model for an AI-based smart charging system was developed, and the implemented system achieved 30% energy savings and a 20.38% reduction in costs compared to traditional methods. These findings underscore the system’s energy and cost efficiency. In addition, we outline the potential advantages and challenges associated with incorporating artificial intelligence (AI) into Malaysia’s electric vehicle (EV) charging infrastructure. Furthermore, we offer recommendations for researchers, industry stakeholders, and regulators. Malaysia can enhance the uptake of electric vehicles and make a positive impact on the environment by leveraging artificial intelligence (AI) to enhance its electric vehicle charging system (EVCS).

Assessing Creativity and User Experience in Immersive Virtual Reality with Cultural Heritage Learning

Virtual reality (VR) technology is widely used in the field of education and cultural heritage learning. However, few studies have focused on the impact on creativity regarding the use of different interaction modalities by users in cultural heritage learning. Furthermore, it is controversial whether VR can enhance user experience and learning outcomes. The study utilized a mixed research approach combining qualitative and quantitative methods, where qualitative data was collected using open-ended interviews, simultaneously quantitative data was collected using learning outcomes, intrinsic motivation, workload, self-report of creativity and expert assessments of creativity. A mixed research approach combining qualitative and quantitative methods was used; creativity self-reports were used to collect qualitative data, and learning outcomes, intrinsic motivation, and workload data were collected for the quantitative findings.90 university students were randomly assigned to the text group (TG), the video group (VG), and the immersive virtual reality group (IVRG), with 30 students in each group. The study assessed whether creativity, user experience and learning outcomes differed when using different interaction modalities in a cultural heritage context. The results demonstrated that the text interaction modality outperformed the other two groups in learning outcomes and expert assessments of creativity performance, while the IVRG performed better in self-report of creativity and user experience. In addition, participants in TG had higher workloads and poorer user experiences compared to the other two interaction modalities. This study encourages that different interaction modalities should be selected more appropriately depending on the purpose. The study found that interaction modalities creativity can be applied to digital cultural heritage and education and informs interaction design for the HCI community.

Development and evaluation of an emergency department serious game for undergraduate medical students

BackgroundSerious games are risk-free environments training various medical competencies, such as clinical reasoning, without endangering patients’ safety. Furthermore, serious games provide a context for training situations with unpredictable outcomes. Training these competencies is particularly important for healthcare professionals in emergency medicine.MethodsBased on these considerations, we designed, implemented, and evaluated a serious game in form of an emergency department, containing the features of a virtual patient generator, a chatbot for medical history taking with self-formulated questions, artificially generated faces based on an artificial intelligence algorithm, and feedback for students. The development process was based on an already existing framework resulting in an iterative procedure between development and evaluation. The serious game was evaluated using the System Usability Scale and the User Experience Questionnaire.ResultsThe System Usability Scale provided a substantial result for the usability. In terms of the user experience, four scales yielded positive results, whereas two scales yielded neutral results.ConclusionThe evaluation of both usability and user experience yielded overall positive results, while simultaneously identifying potential areas for improvement. Further studies will address the implementation of additional game design elements, and testing student learning outcome.

Challenges of Creating a Peer Support Online Community for Patients With Diabetes-A Case Study.

This study aims to explore the challenges and strategies in creating online communities for individuals with diabetes, emphasizing their role in fostering connections among individuals facing similar health conditions. Using a single-case approach, we investigated the design process of a diabetes online community using the classic waterfall model. Participants were recruited from a diabetes local association, and usability was assessed using the System Usability Scale and the think-aloud method. Subsequently, semistructured interviews were conducted to evaluate functionality and user experience. Data collection was conducted from August until December 2023. The development of the community unveiled significant usability challenges, highlighting the need for user feedback and improvement. Ethical considerations, including anonymity, usage conditions, privacy terms, and health information sharing, emerged as critical areas requiring meticulous attention. Furthermore, healthcare professional moderation was deemed essential to ensure a secure environment. Users expressed strong interest in enhanced interaction features and personalized notifications. Although online diabetes communities hold potential for peer support, addressing usability challenges, ethical considerations, and moderation issues is essential. This study emphasizes the ongoing necessity for research to enhance the development of patient communities, ensuring accessibility, mitigating ethical risks, and leveraging nurses as moderators.