User Experience Research Articles

Informatization of Educational Management in Private Colleges of Guangdong Province: Challenges, Investments, and Infrastructure Improvements

This study explores the state of informatization in educational management within private colleges in Guangdong Province, using H College as a case study. Despite recent advancements, the informatization process faces significant challenges, including misconceptions about digital management, insufficient investment, a lack of digital sharing mechanisms, and suboptimal user experiences for both students and faculty. Through a comprehensive analysis of educational indicators, investment patterns, and the current status of digital resources, this paper highlights the critical need for a strategic approach to educational management informatization. The findings underscore the importance of fostering a service-oriented framework that prioritizes the needs of teachers and students while advocating for increased investment in infrastructure and digital platforms. Ultimately, the research aims to contribute to the ongoing efforts to modernize educational governance in private higher education institutions, ensuring they can effectively meet the demands of the evolving educational landscape.

Monitoring system for physical activity and fitness based on service robots and biomechanics

Exercise is one of the important ways for people to exercise, with characteristics such as sociality and strong participation. Especially with the improvement of the level of economic development and the improvement of the quality of life of the people, more and more people begin to attach importance to the maintenance of their own health. Physical fitness monitoring, as an effective means, is widely used in daily life, especially among the elderly. However, most of the existing monitoring methods are relatively simple, lacking pertinence, and the data collection process is relatively cumbersome and unstable, which cannot meet current needs. Therefore, it is very necessary to explore a new type of equipment that can more comprehensively and accurately monitor various physiological parameters of the human body to replace existing traditional detection technologies. Service Robots are currently the most promising intelligent hardware products. They mainly provide personalized services centered on users, sensing user behavior and implementing intelligent decision-making based on their characteristics, thereby better meeting the needs of different groups of people. This article focused on the research and development of Service Robots, and designed a comprehensive solution for Service Robots based on theories such as the Internet of Things, cloud computing, big data technology, and artificial intelligence. This article compared existing intelligent monitoring systems with fitness monitoring systems based on Service Robots, and proved that the user experience of fitness monitoring with robot participation has improved by about 4.68%. Its application scenarios were richer and its effects were more significant, enabling it to better complete tasks such as analysis and prediction of physical fitness status, real-time warning, etc., reducing the risk of people suffering from diseases, and enhancing individual protection awareness.

Enhancing Cognitive Fit: Exploring the Potential of Mixed Reality for Developing Mental Rotation Skills

Mixed Reality is a promising venue for spatial ability training, allowing participants to engage in problem-solving through gesture-based interactions with holographic objects. 3-D measurement of learning in Mixed Reality environments may result in a better cognitive fit than 2-D. This mixed-method study measures and enhances mental rotation ability and investigates user experience in Mixed Reality. To assess mental rotation ability, we adapted the Purdue Spatial Visualization Test:Rotation for Microsoft HoloLens 2, creating a measurement tool for our Mixed Reality-based training program, Holomental. Comparing 2-D and 3-D tests, we explored how stimulus dimensionality influences accuracy and cognitive load. Our findings indicate that Holomental enhances mental rotation performance, both in 2-D and 3-D. Cognitive load in the 3-D test was lower than in the 2-D test. Semi-structured interviews revealed participants’ appreciation for the representational and interactional affordances of the training environment. This study provides valuable insights into the effectiveness of 3-D spatial training, with implications and suggestions for future design considerations.

Analysis Sentiment & Topic Modelling using Latent Semantic Indexing

The proliferation of digital news platforms has transformed information consumption, making user experience (UX) a key success factor for Detik.com, a leading news application in Indonesia. This research aims to explore the relationship between UX and news through sentiment analysis and topic modelling. The methods include web scraping for data collection, descriptive analysis for sentiment, and Latent Semantic Indexing (LSI) for topic modelling. Out of 14,320 reviews analyzed, 45.6% were positive, focusing on the speed of updates and news quality. Conversely, 41.18% of reviews were negative, highlighting disruptive ads and login issues, while 13.76% were neutral. LSI identified eight main topics, including user experience and ad complaints. Visualizations through heatmaps, distance maps, and word clouds emphasized terms like "news" and "ads." This research recommends that Detik.com developers reduce ad disruptions, fix technical problems, and understand frequently discussed topics to enhance user satisfaction.

Exploring users' fluidity and adaptation in virtual worlds: metaverse features and interaction of awe and realism

PurposeMetaverse technology has attracted much attention in many contexts, including industry, education, marketing and business. Some recent studies have focused on qualitative studies based on the actual definition of the metaverse. However, practical research related to metaverse platforms remains in its infancy. This study provides actionable insights into the determinants of metaverse adoption by using perceived fluidity.Design/methodology/approachA two-stage structural equation modeling (SEM) approach and Hayes’ Macro approach are used to examine the proposed hypotheses.FindingsResults show that technology features (e.g. real-time rendering, interactivity and immersion) increase users’ perceived fluidity, which in turn leads to positive intentions to use the metaverse. A high level of perceived realism is not an advantage for metaverse technology and plays a negative moderating role in this mechanism. The interaction of awe with technological features can enhance the negative moderating effects of realism.Originality/valueThis study pioneers the examination of perceived fluidity as a key determinant of metaverse adoption, offering a novel perspective beyond traditional factors. It uniquely identifies the paradoxical role of perceived realism, demonstrating its potential negative impact on user experience. In addition, the research highlights the reinforcing effect of awe on this relationship.

Cybersickness Abatement from Repeated Exposure to VR with Reduced Discomfort.

Cybersickness, or sickness induced by virtual reality (VR), negatively impacts the enjoyment and adoption of the technology. One method that has been used to reduce sickness is repeated exposure to VR, herein Cybersickness Abatement from Repeated Exposure (CARE). However, high sickness levels during repeated exposure may discourage some users from returning. Field of view (FOV) restriction reduces cybersickness by minimizing visual motion in the periphery, but also negatively affects the user's visual experience. This study explored whether CARE that occurs with FOV restriction generalizes to a full FOV experience. Participants played a VR game for up to 20 minutes. Those in the Repeated Exposure Condition played the same VR game on four separate days, experiencing FOV restriction during the first three days and no FOV restriction on the fourth day. Results indicated significant CARE with FOV restriction (Days 1-3). Further, cybersickness on Day 4, without FOV restriction, was significantly lower than that of participants in the Single Exposure Condition, who experienced the game without FOV restriction only on one day. The current findings show that significant CARE can occur while experiencing minimal cybersickness. Results are considered in the context of multiple theoretical explanations for CARE, including sensory rearrangement, adaptation, habituation, and postural control.

Exploring the Impact of Game Elements and Technological Platforms on Dementia Rehabilitation: A Scoping Review

One effective strategy to improve the quality of life for people with dementia (PWD) is rehabilitation, though patients often show reluctance due to the disease’s effects. A trending motivational approach is gamification. However, most research in this field has focused on the medical or technical aspects of system development, with less attention given to the role of game elements in the patient experience. In this study, a scoping review based on the PRISMA method was conducted on gamified rehabilitation systems, focusing on gamification elements, and interaction with technological platforms. By reviewing 46 studies, we extracted game elements based on the gamification pyramid, technological platforms, and rehabilitation methods, and compared them with previous studies on PWD interactions. This analysis identified opportunities and challenges for future research. Additionally, nine factors to improve user experience in the design of gamification systems for dementia rehabilitation were presented based on the review results.

Framework and policy recommendations for the design of metaverse platforms in support of Saudi Vision 2030

Purpose This paper suggests a framework that describes the critical features and design elements that should be considered when creating a metaverse platform. This metaverse framework will assist in achieving the goals of Saudi Vision 2030, specifically in making the applied technology transformation goal a reality. In addition, this paper offers valuable recommendations and insights for policymakers to guarantee the actualization of the digital transformation associated with the metaverse in Saudi Vision 2030. Design/methodology/approach This research plans to address the gaps by conducting a thorough literature review to examine the characteristics and design elements of the latest metaverse platforms. It proposes a suggested framework that discusses the distinctive features that should be considered when creating any metaverse platform. In addition, the research provides policymakers with important recommendations and insights to ensure effective contribution to the digital transformation goals of Saudi Vision 2030, thereby supporting the scientific development of the metaverse platform Findings After a deep review of the literature, this paper proposes a conceptual framework as described in Figure 1, which identifies the most important design features and elements that need to be considered when building a metaverse platform, which will be a critical component of the digital infrastructure. These design elements include immersive engineering, accessibility, privacy, security, interoperability, digital assets and regulations. They are essential to developing a powerful metaverse platform that has all the features of this virtual reality environment. Immersive engineering concepts in the metaverse world aim to improve user experience by creating more realistic, interactive and engaging virtual environments. Research limitations/implications The findings of this study provide valuable insights into the development and implementation of metaverse platforms in Saudi Arabia by proposing a suggested framework that discusses the distinctive features that should be considered when creating metaverse platform and provides policymakers with some important recommendations and insights to ensure that effectively contributes to the realization of digital transformation, which is the one of Saudi Vision 2030. This paper carries several implications. First, this paper has an impact on future technology research, as it presented the most important design elements and advanced technologies for implementing metaverse platforms. In addition, it sheds the light on the limitations faced by Saudi Arabia metaverse platforms. Second, this research also has an impact on public policy in Saudi Arabia. This paper presented the most important recommendations that need to be taken into consideration when applying metaverse in Saudi Arabia [see section Recommendation]. Finally, it is seen that the presence of the metaverse not only facilitates but also supports digital transformation and the application of new technology. This research also has an indirect impact on society and the economy, as it is delineating the enhancements within these environments following the metaverse’s adoption, as elucidated in section Discussion. Social implications Metaverse platforms have societal impacts such as social engagement, entertainment, education, accessibility and cultural promotion. They can enhance inclusivity, improve well-being, showcase cultural heritage and boost tourism-related industries. Originality/value Proposed framework for metaverse platforms: The research proposes a suggested framework that outlines the distinctive features necessary for creating metaverse platforms. This framework is based on a thorough literature review and aims to guide the development of metaverse platforms that can support the objectives of Saudi Vision 2030. Policy recommendations: The study offers important recommendations and insights for policymakers. These recommendations are designed to ensure that policymakers can effectively contribute to the realization of the digital transformation goals of Saudi Vision 2030, particularly in the context of applied technology transformation.

Intentional or Designed? The Impact of Stance Attribution on Cognitive Processing of Generative AI Service Failures.

With the rapid expansion of the generative AI market, conducting in-depth research on cognitive conflicts in human-computer interaction is crucial for optimizing user experience and improving the quality of interactions with AI systems. However, existing studies insufficiently explore the role of user cognitive conflicts and the explanation of stance attribution in the design of human-computer interactions. This research, grounded in mental models theory and employing an improved version of the oddball paradigm, utilizes Event-Related Spectral Perturbations (ERSP) and functional connectivity analysis to reveal how task types and stance attribution explanations in generative AI influence users' unconscious cognitive processing mechanisms during service failures. The results indicate that under design stance explanations, the ERSP and Phase Locking Value (PLV) in the theta frequency band were significantly lower for emotional task failures than mechanical task failures. In the case of emotional task failures, the ERSP and PLV in the theta frequency band induced by intentional stance explanations were significantly higher than those induced by design stance explanations. This study found that stance attribution explanations profoundly affect users' mental models of AI, which determine their responses to service failure.

Ecommerce and Public Health: Managing the Digital Transformation of Healthcare Services

The study investigates the impact of demographic factors, usage frequency, and professional roles on user satisfaction with digital health platforms. A sample of 300 participants, including healthcare professionals, platform operators, and patients, was analyzed to assess the role of age, gender, professional role, and frequency of platform use on satisfaction levels. The results show that the gender did not significantly influence satisfaction, suggesting that platforms may cater equally to both male and female users. Multivariate Analysis of Variance (MANOVA) revealed that professional role also significantly influenced perceptions of digital healthcare transformation and willingness to adopt new services, with platform operators displaying the most positive views. Patients, however, showed more reluctance to adopt new services, suggesting that additional trust-building measures are needed for wider adoption. The study concludes that digital health platforms must prioritize user experience across demographics, particularly focusing on older users and patients, to increase satisfaction and engagement. Collaborating with healthcare professionals in platform development and enhancing communication about the benefits of digital health services can drive greater adoption and satisfaction.

AI-Driven context classification in mobile computing: methodologies and technologies for enhanced user experience

AI-Driven context classification in mobile computing: methodologies and technologies for enhanced user experience

The Design and Implementation of Personalized Learning Platform Based on Android

Through an investigation and analysis of learning platforms, the author designed and implemented the personalized learning platform based on Android, adhering to the design principles. The platform is customized to learners’ learning styles and ubiquitous learning. Learners may receive personalized recommendations from the platform and get optimized user experience, which in turn enhances learners’ motive and efficiency in learning and supports teachers’ teaching.

Taking what you get or Getting what you Need: A Qualitative Study on Experiences with Mental Health and Welfare Services in Long-Term Recovery in First-Episode Psychosis.

How people in long-term recovery (clinical and personal) in first-episode psychosis (schizophrenia and bipolar spectrum disorders) experience the mental health and welfare services they interact with is not frequently studied but has significant implications. We therefore aimed to explore which aspects of these services people with FEP evaluate as important for their long-term recovery. Twenty participants in clinical and/or personal recovery from two Norwegian long-term follow-up studies after FEP (TOP 10-year and TIPS 20-year) were sampled for this interview-based qualitative study. The research-team included service user experience. A deductive analysis based on personal accounts of recovery generated five service aspects. Few specific types of interventions were reported to promote recovery although medications, psychotherapy and employment support were mentioned. Participants valued services based in collaboration and that focused on their resources rather than limitations. The importance of long-term follow-up with a consistent aim was highlighted, as was the inclusion of caregivers and peers. Welfare services contributed to recovery by supporting basic needs and safety, but some experienced social exclusion when not participating in the labor market. This study is unique in exploring the role of services, including welfare, in long-term FEP recovery from service user perspectives. Participants evaluated that services played a more indirect role in long-term recovery by supporting their personal resources, although what they needed from services had frequently not been offered. Their expertise by experience contributes valuable knowledge. Better service coordination and consistent implementation of this knowledge are crucial to support recovery in FEP.

Performance Evaluation on E-Commerce Recommender System based on KNN, SVD, CoClustering and Ensemble Approaches

E-commerce recommender systems (RS) nowadays are essential for promoting products. These systems are expected to offer personalized recommendations for users based on the user preference. This can be achieved by employing cutting-edge technology such as artificial intelligence (AI) and machine learning (ML). Tailored recommendations for users can boost user experience in using the application and hence increase income as well as the reputation of a company. The purpose of this study is to investigate popular ML methods for e-commerce recommendation and study the potential of ensemble methods to combine the strengths of individual approaches. These recommendations are derived from a multitude of factors, including users' prior purchases, browsing history, demographic information, and others. To forecast the interests and preferences of users, several techniques are chosen to be investigated in this study, which include Singular Value Decomposition (SVD), k-Nearest Neighbor Baseline (KNN Baseline) and CoClustering. In addition, several evaluation metrics including the fraction of concordant pairs (FCP), mean absolute error (MAE), root mean square error (RMSE) and normalized discounted cumulative gain (NDCG) will be used to assess how well different techniques work. To provide a better understanding, the outcomes produced in this study will be incorporated into a graphical user interface (GUI).

Performance Evaluation on E-Commerce Recommender System based on KNN, SVD, CoClustering and Ensemble Approaches

E-commerce recommender systems (RS) nowadays are essential for promoting products. These systems are expected to offer personalized recommendations for users based on the user preference. This can be achieved by employing cutting-edge technology such as artificial intelligence (AI) and machine learning (ML). Tailored recommendations for users can boost user experience in using the application and hence increase income as well as the reputation of a company. The purpose of this study is to investigate popular ML methods for e-commerce recommendation and study the potential of ensemble methods to combine the strengths of individual approaches. These recommendations are derived from a multitude of factors, including users' prior purchases, browsing history, demographic information, and others. To forecast the interests and preferences of users, several techniques are chosen to be investigated in this study, which include Singular Value Decomposition (SVD), k-Nearest Neighbor Baseline (KNN Baseline) and CoClustering. In addition, several evaluation metrics including the fraction of concordant pairs (FCP), mean absolute error (MAE), root mean square error (RMSE) and normalized discounted cumulative gain (NDCG) will be used to assess how well different techniques work. To provide a better understanding, the outcomes produced in this study will be incorporated into a graphical user interface (GUI).

Research on Improved Image Segmentation Algorithm Based on GrabCut

The classic interactive image segmentation algorithm GrabCut achieves segmentation through iterative optimization. However, GrabCut requires multiple iterations, resulting in slower performance. Moreover, relying solely on a rectangular bounding box can sometimes lead to inaccuracies, especially when dealing with complex shapes or intricate object boundaries. To address these issues in GrabCut, an improvement is introduced by incorporating appearance overlap terms to optimize segmentation energy function, thereby achieving optimal segmentation results in a single iteration. This enhancement significantly reduces computational costs while improving the overall segmentation speed without compromising accuracy. Additionally, users can directly provide seed points on the image to more accurately indicate foreground and background regions, rather than relying solely on a bounding box. This interactive approach not only enhances the algorithm’s ability to accurately segment complex objects but also simplifies the user experience. We evaluate the experimental results through qualitative and quantitative analysis. In qualitative analysis, improvements in segmentation accuracy are visibly demonstrated through segmented images and residual segmentation results. In quantitative analysis, the improved algorithm outperforms GrabCut and min_cut algorithms in processing speed. When dealing with scenes where complex objects or foreground objects are very similar to the background, the improved algorithm will display more stable segmentation results.

Different Perception and Use of ChatGPT in Writing Between American and International Students

The emergence of AI writers has significantly affected and reshaped the environment of academic research and paper writing in the world. Many university students relying on these AI tools for searching information and assisting their writing. However, there will be a difference existed in the utilization and perceptions of AI writers between American and international students. To find out potential difference, this study seeks to delve into the underlying factors that may contribute to this contrast. Employing the Technology Acceptance Model (TAM) as a theoretical framework, which investigates users' acceptance and adoption of technology, the research employs a mixed-method approach comprising surveys and interviews conducted among students from both American and international contexts. By integrating TAM into the methodology, the study aims to investigate the motivations to use of ChatGPT, an AI writing tool, and examine how linguistic and cultural differences influence the user experience of AI writers. Through this approach, the research sheds light on the nuanced ways in which AI writers are integrated into the academic workflows of students from diverse backgrounds. By comparing and contrasting the perspectives and practices of American and international students, the study will provide valuable insights into the interplay between technology, language, and culture in the educational domain. Ultimately, this research will contribute to a deeper understanding of the complex dynamics shaping the adoption and usage of AI writers among higher education students worldwide.

Contactless Service: Artificial Intelligence Applications of Airports

Airports are an essential part of the airline value chains. Artificial intelligence (AI) technologies are widely used at airports; they utilize two technologies: face detection and recognition. The study examines how passengers' performance expectancy and emotions affect satisfaction and willingness to adopt the AI service of passengers via familiarity. Based on the AI device, it uses acceptance and socio-technical systems perspectives; participants who adopted the AI service in airports in Beijing, Taipei, and Singapore who have the potential to use AI service usage experience more than three times; 387 completed questionnaires. A satisfaction model was analyzed using the partial least squares approach; this study used purposed sampling to collect data based on the passenger volume analysis by those airports, and 387 completed questionnaires were analyzed. With the rise of AI innovation services in airports, passengers can quickly complete boarding procedures through AI innovative services. The research findings point out that passengers' performance expectancy and emotions positively affect familiarity with AI services for passengers. AI innovations provide a service change driver for and have the potential to replace human tasks and intelligence and analytics applications at airports. AI services are a powerful tool for airports to serve their passengers efficiently, and airports will collaborate with airlines to serve passengers with AI.

ARCHIVES COMMUNICATION: MUTATIONS OF A FUNCTION

Objective: The objective of this article is to examine the evolving communication function of archives in the context of new information and communication technologies. It aims to identify the impact of digitalization on archival practices, focusing on how these changes enhance the accessibility and usability of archival materials for the public and researchers. By exploring the emerging practices of archivists and their role in facilitating effective communication, this article seeks to highlight the significance of communication in the archival profession and to provide insights into the best practices for ensuring a positive user experience in the consultation of archival documents. Theoretical Framework: This article explores the communication of archives in the digital age, focusing on communication theory, digital archive science, user-centered design, social constructivism, and information behavior. It emphasizes the importance of understanding historical and cultural contexts, user needs, and information behavior to design effective communication strategies. Method: This article uses a qualitative research approach to examine the evolving communication function of archives in the context of digital technologies. It uses literature review, case studies, interviews with archivists, user surveys, and content analysis to understand the impact of digitalization on archives and identify best practices for archivists. Results and Discussion: The literature review, case studies, interviews, user surveys, and content analysis reveal a significant shift in archival practices towards digital communication. Key themes include accessibility, user engagement, and the role of digital technologies in transforming traditional functions. Successful examples include digitization of collections, innovative outreach strategies, and collaborations between archivists and technology experts. Key themes include a user-centered approach, balancing digital and traditional practices, ongoing training, and collaboration between archivists, technology professionals, and user communities. Research Implications: This study highlights the need for further research in archival science and communication to explore digital practices, user experience, collaboration models, social media's impact, training for archivists, ethical considerations, and long-term impact on research outcomes. It emphasizes the need for in-depth studies on user experience, collaboration models, social media's role, and the impact of training on professional development and broader societal impact. Originality/Value: This article explores the evolving communication function of archives in response to digital advancements. It integrates theoretical frameworks with practical insights from case studies, interviews, and user surveys. The research emphasizes user-centered approaches, empirical evidence, and best practices for archivists. It contributes to ongoing discourse on the future of archives and raises ethical considerations, addressing challenges faced by archivists.

Integration of Chatbots in Additional Language Education: A Systematic Review

<p style="text-align:justify">This comprehensive systematic review delves into the increasing prevalence of integrating chatbots into language education. The general objective is to assess the current landscape of knowledge regarding chatbot utilisation and its influence on three crucial elements: students' skills, attitudes, and emotions. Additionally, the review seeks to scrutinise the advantages linked to incorporating chatbots in foreign language teaching, exploring their potential benefits while considering limitations and potential negative impacts on specific skills or user experiences. Consequently, this research offers valuable insights into the application of chatbots in foreign language education, shedding light on their potential advantages and areas that warrant further exploration and enhancement. The integration of chatbots in language learning, despite certain limitations, generally yields positive outcomes and enhances educational results in students' skills. Its characteristics can also influence a language learner's attitude, impacting factors such as motivation, interest, autonomy in learning, and engagement or even their sense of fun. Additionally, chatbots prove to be helpful in creating emotionally positive learning environments and can contribute to boosting students' self-esteem and self-confidence.</p>