Search Results (235)

Content caching and recommendation for content delivery over the Internet are two key techniques for improving the content delivery effectiveness determined by delivery efficiency and user satisfaction, which is increasingly important in the booming Internet of Things (IoT). While content caching seeks the “greatest common denominator” among users to reduce end-to-end delay in content delivery, personalized recommendation, on the contrary, emphasizes users’ differentiation to enhance user satisfaction. Existing studies typically address them separately rather than jointly due to their contradictory objectives. They focus mainly on heuristics and deep reinforcement learning methods without the provision of performance guarantees, which are required in many real-world applications. In this paper, we study the problem of joint optimization of caching and recommendation in which recommendation is performed in the cached contents instead of purely according to users’ preferences, as in the existing work. We show the NP-hardness of this problem and present a greedy solution with a performance guarantee by first performing content caching according to user request probability without considering recommendations to maximize the aggregated request probability on cached contents and then recommendations from cached contents to incorporate user preferences for cache hit rate maximization. We prove that this problem has a monotonically increasing and submodular objective function and develop an efficient algorithm that achieves a $1-{\displaystyle \frac{1}{e}}\approx 0.63$ approximation ratio to the optimal solution. Experimental results demonstrate that our algorithm dramatically improves the popular least-recently used (LRU) algorithm. We also show experimental evaluations of hit rate variations by Jensen–Shannon Divergence on different parameter settings of cache capacity and user preference distortion limit, which can be used as a reference for appropriate parameter settings to balance user preferences and cache hit rate for Internet content delivery. Full article

The growing global demand for energy has resulted in a demand for innovative strategies for residential energy management. This study explores a novel framework—MELISSA (Modern Energy LLM-IoE Smart Solution for Automation)—that integrates Internet of Things (IoT) sensor networks with Large Language Models (LLMs) to optimize household energy consumption through intelligent automation and personalized interactions. The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. A 12-month randomized controlled trial was conducted with 100 households, which were stratified across four socioeconomic quintiles in metropolitan areas. The experimental design included the continuous collection of IoT data. Baseline energy consumption was measured and compared with post-intervention usage to assess system impact. Statistical analyses included k-means clustering, multiple linear regression, and paired t-tests. The system achieved its intended goal, with a statistically significant reduction of 5.66% in energy consumption (95% CI: 5.21–6.11%, $p<0.001$) relative to baseline, alongside high user satisfaction (mean = 7.81, SD = 1.24). Clustering analysis ($k=4$, silhouette = 0.68) revealed four distinct energy-consumption profiles. Multiple regression analysis ($R^2=0.68$, $p<0.001$) identified household size, ambient temperature, and frequency of user engagement as the principal determinants of consumption. This research advances the theoretical understanding of human–AI interaction in energy management and provides robust empirical evidence of the effectiveness of LLM-mediated behavioral interventions. The findings underscore the potential of conversational AI applications in smart homes and have practical implications for optimization of residential energy use. Full article

This study investigates consumer satisfaction in e-learning services by addressing a specific gap in the literature: the limited integration of sustainability principles and behavioral modeling in understanding satisfaction drivers in online education. While existing studies have explored engagement and usability, few have considered how sustainability-related factors influence satisfaction in digital learning environments. Based on a conceptual model involving system quality, service quality, motivation, and cognitive engagement, we applied structural equation modeling (WarpPLS) to a sample of 312 university students from Romania, using mainstream learning management systems (LMS). Data were collected from students at the Bucharest University of Economic Studies using a convenience sampling method. The results show that service quality and cognitive engagement are the strongest predictors of satisfaction. This study offers practical recommendations for improving sustainable digital marketing strategies in e-learning, such as enhancing support services and aligning platform features with eco-conscious consumer expectations. Full article

In higher education, the emotional intelligence (EI) of university professors, defined as the ability to perceive, understand, manage and utilize emotions effectively, is increasingly recognized as a pivotal factor in enhancing students’ academic achievement and psychological well-being. However, the scarcity of studies directly linking professors’ EI to students’ well-being highlights a critical research gap. This systematic review investigates how professors’ emotional competencies influence student outcomes—such as academic performance, engagement, motivation, and mental health—and identifies the factors that mediate or moderate these effects. Findings indicate that professors’ EI, particularly empathy, emotional regulation, and interpersonal skills, significantly enhances student engagement, motivation, and academic satisfaction, with indirect effects on psychological well-being. Cultural context, teaching modality (e.g., online vs. in-person), and professors’ age and experience moderate these effects and influence effect sizes. Qualitative synthesis further highlighted contextual gaps in the literature. The limited focus on well-being and outcomes and reliance on self-report measures underscore the need for longitudinal, culturally diverse studies and performance-based EI assessments. The value of this research lies in its potential to inform evidence-based educational practices and institutional policies. By elucidating the role of professors’ EI, the review lays the groundwork for developing faculty training programs aimed at strengthening emotional competencies and fostering inclusive, supportive learning environments that promote student growth and resilience. This is especially relevant given the growing prevalence of stress, anxiety, and disengagement among university students, exacerbated by post-pandemic challenges and academic pressures. Understanding the impact of EI can inform culturally responsive interventions, improve student retention, and enhance institutional effectiveness, thereby addressing a pressing need in contemporary higher education. In today’s rapidly evolving technological, social, and cultural landscape, universities have both the opportunity and the responsibility to act as catalysts for the creation of an educational culture that promotes social well-being. This requires adopting educational and organizational models that prioritize human care and the quality of interpersonal relationships. To be effective, these priorities must be integrated into all university operations, from governance to student support and talent development. Full article

This study presents an analysis of England’s 2023 national assessment of assistive technology (AT) access and use, with a particular focus on the qualitative impact of AT as described by users. It aims to address limitations in conventional AT impact assessments, which often prioritize clinical outcomes or user satisfaction, by offering a deeper account of how impact is experienced in everyday life. Drawing on data from a nationally representative survey of 7000 disabled adults and children, as well as six focus group discussions and 28 semi-structured interviews with stakeholders across the WHO 5Ps framework (People, Providers, Personnel, Policy, and Products), the study applies Amartya Sen and Martha Nussbaum’s Capability Approach to explore these experiences. Using inductive thematic analysis, we identify three main domains of user-reported impact: Functions and Activities (e.g., mobility, communication, vision, leisure, daily routines, and cognitive support), Outcomes (e.g., autonomy, quality of life, safety, social participation, wellbeing, and work and learning), and Lived Experience (e.g., access barriers, essentiality, identity and emotional connection, peace of mind, and sense of control and confidence). These findings offer a more user-centered understanding of AT impact and can inform the development of future measurement tools, research design, and government-led interventions to improve AT provision. Full article

Background/Objectives: The COVID-19 pandemic has significantly restricted clinical training for midwifery students, highlighting the need for alternative teaching methods. With the disruption of traditional face-to-face education, online simulation-based training has emerged as an effective alternative for developing essential clinical skills. The acquisition of hands-on skills has a direct impact on students’ self-confidence and clinical performance. Interactive online simulations support the learning process by enhancing both theoretical knowledge and practical competencies. This study aims to evaluate the impact of online simple simulation-based episiotomy repair training on students whose clinical practice was limited due to the COVID-19 pandemic. Methods: A mixed-method approach was used, considering the outcomes from 61 midwifery students. Data were collected via observational questionnaires, which provide an online learning readiness scale and scales for student satisfaction and self-confidence. The analysis included descriptive statistics, McNemar’s, binary logistic regression, and the Mann–Whitney U test. Results: Students who trusted themselves in both opening and repairing an episiotomy after training had more readiness for online learning (t(43) = 2.73, p = 0.009; t(43) = 2.40, p = 0.02). Students with better training performance are more likely to obtain higher scores on the final exam of the Clinical Practice module (rho = 0.33, p = 0.01). Additionally, their performance was a positive and significant predictor of achieving a full mark (b = 0.11, s.e. = 0.05, p = 0.01). Conclusions: Interactive online simulation training improved midwifery students’ hand skills and self-confidence in clinical practice. Such methods should be promoted in circumstances like COVID-19. Full article

Background/Objectives: All countries face a shortage of qualified nurses. Based on the social cognitive career theory (SCCT), it is assumed that individual and environmental aspects are interlinked and determinants in career choice and vocational behaviors. This study aims to determine if nursing students differ in their perceptions of nursing as a career. Furthermore, this study wants to determine if the students in a cluster differed in their outcome expectations, job satisfaction, and informal workplace learning. Methods: This study employed a mixed-methods design consisting of two phases: the first involving a pre-study with experts (N = 10) and the second comprising a cross-sectional questionnaire survey. The goal of the pre-study was to find relevant characteristics of the nursing profession. In a cross-sectional study with an online questionnaire, 230 nursing students (N = 230) participated. An inclusion criterion was that participants were enrolled in vocational training to become a nurse. In the questionnaire validated scales were used to ask participants about the characteristics of the nursing profession, their perceptions of nursing as a career, outcome expectations, informal workplace learning, and job satisfaction. Analysis: Data analysis included descriptive statistics (e.g., percentage distributions), hierarchical cluster analysis, and analysis of variance (ANOVA). Results: The LCA results based on Schwarz’s BIC showed a two-cluster solution (Akaike Information Criterion (AIC) 251.984, Bayesian information criterion (BIC) 265.296, and adjusted Bayesian information criterion (aBIC) 252.622). The results of the ANOVA showed significant differences regarding outcome expectations (F = 22.738; <0.001), the perception of nursing as a career (F = 36.231; <0.001), and the engagement in informal workplace learning activities (F = 20.62; <0.001). For job satisfaction, no significant differences were found. Conclusions: Nursing vocational education and training is a vital socialization process in which supervisors can arrange a positive learning climate. Full article

This paper presents the design and evaluation of e-SoundWay, a cross-platform serious game developed to improve English phonetic competence through a multimodal and narrative-driven approach. While the platform is specifically tailored to meet the needs of Spanish-speaking learners, it is adaptable for a wider range of English as a Foreign Language (EFL) users. e-SoundWay offers over 600 interactive multimedia minigames that target three core competencies: perception, production, and transcription. Learners progress along a gamified version of the Camino de Santiago, interacting with characters representing diverse English accents. A mixed-methods evaluation combining pre- and post-tests with a user experience questionnaire revealed statistically significant improvements across all domains, particularly in perception. Reduced post-test variability indicated more equitable learning outcomes. User satisfaction was high, with 64% of participants reporting satisfaction with their phonetic progress and 91% stating they would recommend the platform. These findings highlight the educational effectiveness, accessibility, and motivational value of e-SoundWay, reinforcing the role of serious games and multimodal technologies in delivering inclusive and engaging pronunciation instruction. Full article

Background/Objectives: Traditional nutrition education can increase children’s exposure to healthy foods, but preschool teachers face barriers such as limited time and competing priorities (e.g., kindergarten readiness). Integrating nutrition into other learning domains (e.g., science) has been identified as a potential solution. However, teachers need more professional development. We developed the More PEAS Please! program to support preschool teachers’ integration of food-based learning (FBL) and science, seeking to improve children’s science learning, language development, and dietary quality. Methods: In this pilot study, we used a mixed-methods process evaluation to assess the program in five Head Start centers (n = 23 classrooms) across three rural North Carolina counties. We collected teacher data via surveys and interviews. Results: A total of 24 teachers participated in the full intervention by attending a one-day workshop, completing at least one of four core learning modules, and implementing 16 food-based science learning activities in their classrooms. Teachers were Black/African American (81.1%) and 43.56 (11.89) years old. Teachers reported varying engagement levels and high satisfaction with the program, sharing increased confidence in FBL and science integration. However, barriers such as time, technology, and the coronavirus disease (COVID-19) limited full participation. Conclusions: Our findings suggest that the program is feasible and well received in Head Start settings and has promising impacts on classroom teaching practices. The findings will guide revisions to the PEAS program. Future research evaluating the revised program using a comparison group will be explored. Full article

Augmented Reality (AR) seamlessly blends the real-world environment with digitally generated content, creating an interactive hybrid experience where both realities coexist. This paper explores an augmented reality application developed for natural heritage education, specifically designed to enhance indoor learning. The focus is on a learning activity titled Exploring the Aquarium, implemented by the Education Centre for the Environment and Sustainability (E.S.E.C.) of Kastoria as part of an environmental education program. The activity enriches students’ knowledge and experiences during their aquarium visit, fosters active participation in the learning process, stimulates cognitive interest, and encourages actions that support the ecological restoration of aquatic ecosystems. This paper presents the application’s design criteria, thematic focus, learning objectives, and core functionalities. Additionally, the paper presents findings from quantitative research evaluating the learning experience. A questionnaire tailored for AR applications was employed to assess aspects such as challenge, educational value (knowledge gained), user collaboration, and intention to reuse the app. Data were collected from 148 K-12 students during the 2023–2024 school year. Descriptive statistical analysis revealed that all factors were evaluated highly. The results indicate that the AR-enhanced educational activity captured the students’ interest and facilitated a collaborative learning environment. The application was positively rated for its functionality, usability, informational content, and the satisfaction it provided, as well as its ability to encourage cooperation and future reuse. Full article

Cultural factors shape students’ expectations and perceptions within diverse educational settings. The perceived quality of a Higher Education Institution (HEI) is crucial to its success, with student satisfaction determined mainly by their overall experiences. The concept of Student eXperience (SX) can be analyzed through the lens of Customer eXperience (CX) from a Human–Computer Interaction (HCI) perspective, positioning students as the “customers” of the institution. SX encompasses academic and physical interactions and students’ emotional, social, and psychological responses toward an institution’s systems, products, and services. By accounting for factors such as emotions, socioeconomic status, disabilities, and, importantly, cultural background, SX provides a comprehensive measure of student experiences. Building upon our previous SX model and Hofstede’s national culture model, we have developed a Student eXperience evaluation methodology that serves as a diagnostic tool to assess both student satisfaction and how effectively HEIs serve a diverse student population. This methodology ensures that all students, regardless of their background, are considered in the evaluation process, facilitating the early identification of institutional strengths and weaknesses. Incorporating cultural aspects into the assessment delivers more precise results. Furthermore, our approach supports HEIs in promoting equity, diversity, and inclusion by addressing the needs of minority students and students with disabilities, as well as reducing gender disparities. These objectives align with UNESCO’s Sustainable Development Goals, contributing to fostering an equitable learning environment. By adopting such inclusive evaluation practices, HEIs can enhance the perceived quality of education and their responsiveness to the needs of an increasingly multicultural student body. Full article

As a major source of food and plastic waste and a large consumer of water and energy, the hospitality sector is key to combating climate change. Sustainable practices in the hospitality sector optimize food production and use, introduce innovative solutions and increase employee satisfaction in running environmentally friendly restaurants. This study examines the changes required for a restaurant to make a sustainable transition and the role of key stakeholders (i.e., chefs, head sommeliers, owners and main suppliers) in this process. It focuses on a prestigious Slovenian restaurant that has been awarded a Michelin Green Star and is 80% self-sufficient. The single case study uses semi-structured interviews, the critical incident method and participant observation to collect data. The results showed that in the case of the analyzed restaurant, the lifestyle of the owner/chef decisively shapes the culture of the restaurant, laying the foundation for its sustainable transformation. The success of the transformation itself, however, depends significantly on the employees’ ability to learn and innovate and their active involvement in the change process itself, which impacts both day-to-day business processes and relationships between stakeholders. The latter is reflected in the role the restaurant plays in the local environment as a driver for sustainable community and sustainable entrepreneurship development. Full article

In the past years, the education sector has suffered from repeated epidemics and their spread, and COVID-19 is a good example of this. Therefore, the search for other educational methods has become necessary. Therefore, e-learning is one of the best methods to replace traditional education. In this study, we found it necessary to conduct a comprehensive st udy on the perceptions of Iraqi university students toward e-learning and the factors affecting its use by students’ interest in being used consistently to increase learning effectiveness and the influence of educational presentations. In this research, the Expectation−Confirmation Model was used as a framework, and SPSS v21 and AMOS v21 were used to analyze the questionnaire obtained from 360 valid samples. According to the findings, students’ perceptions of the usefulness of e-learning systems are influenced by factors such as system quality, content quality, and confirmation. In addition, the findings show that technical support has no effect on perceived usefulness. In addition, content quality, system quality, and technical support are three critical antecedents of confirmation. In addition, we found that satisfaction was positively affected by both confirmation and perceived usefulness. We also found that the continuance intention to use e-learning was positively affected by both satisfaction and perceived usefulness. Full article

Introduction: The educational landscape has been expanded to disadvantaged and distant areas through online courses. These online courses have gained extensive interest yet there are limited studies available in the literature. The emergence of massive open online courses (MOOCs) has allowed sustainability educators to glimpse the light. Online education is gaining popularity and, with the introduction of MOOCs, would be beneficial for knowledge building and sharing, and the development of learned society. Objective: This study investigated the mediating (indirect) effects of media richness and user-based use motives on the extended UTAUT model, use behavior (UB), and actual use (AU) of MOOCs on health informatics and administration sustainability education among educators and students in Saudi higher learning institutions (HLIs). A theoretical model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and Channel Expansion Theory (CET) was used to investigate the factors that affect the adoption of MOOCs in health informatics and administration education. Methodology: A survey design approach was applied. Cross-sectional data were collected from health informatics educators and students from HLIs in Saudi Arabia. A non-probability convenience sampling technique was used for sampling. Data were collected online using Google Forms. A total of 145 completed questionnaires were used in the analysis. PLS-SEM(Version 4.1.1.2) was used for statistical analysis. To investigate the reliability and validity, a measurement model was developed and confirmatory factor analysis (CFA) was conducted. To test the hypotheses, a structural model was run using bootstrapping, coefficients, standard errors (SE) t-values, p values, and lower and upper-level confidence intervals. Results/Findings: The findings were that system quality and user satisfaction is an important factor in the UTAUT model and the inclusion of media richness and user-based use motives significantly mediated between the expanded UTAUT model and the UB and AU of MOOCs. Moreover, media richness and user-based use motives were found to be dominant factors in the overall study model to predict use behavior and actual use of health informaticians in Saudi Arabia. Conclusions: The combination of these two theories i.e., the UTAUT and CET, can effectively enhance the adoption, use behavior, and actual use of MOOCs in the emerging field of health informatics in Saudi Arabia. Full article

The rapid growth in the global apparel market and the rise of online consumption underscore the necessity for intelligent clothing recommendation systems that balance visual compatibility with personalized preferences, particularly price sensitivity. Existing recommendation systems often neglect nuanced consumer price behaviors, limiting their ability to deliver truly personalized suggestions. To address this gap, we propose DeepFMP, a multimodal deep learning framework that integrates visual, textual, and price features through an enhanced DeepFM architecture. Leveraging the IQON3000 dataset, our model employs ResNet-50 and BERT for image and text feature extraction, alongside a comprehensive price feature module capturing individual, statistical, and category-specific price patterns. An attention mechanism optimizes multimodal fusion, enabling robust modeling of user preferences. Comparative experiments demonstrate that DeepFMP outperforms state-of-the-art baselines (LR, FM, Wide & Deep, GP-BPR, and DeepFM), achieving AUC improvements of 1.6–12.2% and NDCG@10 gains of up to 3.2%. Case analyses further reveal that DeepFMP effectively improves the recommendation accuracy, offering actionable insights for personalized marketing. This work advances multimodal recommendation systems by emphasizing price sensitivity as a pivotal factor, providing a scalable solution for enhancing user satisfaction and commercial efficacy in fashion e-commerce. Full article