Search Results (404)

The rapid proliferation of misinformation on social media underscores the urgent need for scalable digital-literacy instruction. This study presents the design and evaluation of a Generative AI-enhanced serious game system that integrates Large Language Models (LLMs) to drive adaptive non-player characters (NPCs). Unlike traditional scripted interactions, the system employs role-based prompt engineering to align real-time AI dialogue with the Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) framework, enabling dynamic scaffolding and authentic misinformation scenarios. A mixed-method experiment with 60 undergraduate students compared this AI-driven approach to traditional instruction using a 40-item digital-literacy pre/post test, the Intrinsic Motivation Inventory (IMI), and open-ended reflections. Results indicated that while both groups improved significantly, the game-based group achieved larger gains in credibility-evaluation performance and reported higher perceived competence, interest, and effort. Qualitative analysis highlighted the HCI trade-off between the high pedagogical value of adaptive AI guidance and technical constraints such as system latency. The findings demonstrate that Generative AI can be effectively operationalized as a dynamic interface layer in serious games to strengthen critical reasoning. This study provides practical guidelines for architecting AI-NPC interactions and advances the theoretical understanding of AI-supported educational informatics. Full article

Current approaches to gaming disorder prevention remain comparatively narrow, and prevention efforts are frequently underdeveloped and fragmented. Using the socio-ecological model (SEM), this qualitative study mapped frontline practitioners’ perceived obstacles and opportunities to develop a multi-level, practice-grounded framework for policy and implementation. Semi-structured interviews were conducted with 18 prevention professionals in Flanders (Dutch-speaking Belgium), recruited via purposive and snowball sampling. A hybrid inductive–deductive analysis—iterative coding guided by Layder’s adaptive theory—organized findings across SEM levels. At the public policy level, participants highlighted insufficient sustainable funding but saw potential in coordinated frameworks moving prevention beyond substance-focused agendas. At the community level, a clear knowledge gap emerged, with opportunities in integrating gaming within broader digital well-being efforts. Institutionally, the absence of practical tools and clear referral pathways was noted, in addition to high participation barriers, whereas accessible programs with targeted outreach were viewed as promising. Interpersonally, parental disengagement was common, but early involvement and pedagogical guidance were seen as key levers. At the intrapersonal level, limited self-insight and emotion regulation impeded change, while resilience, self-confidence, and offline activities were protective. This first empirical application of the SEM to gaming disorder prevention highlights the need for a multi-level, context-sensitive framework that bridges public health and digital media perspectives. Full article

In recent years, the application of augmented reality digital technology in brands has transformed the way consumers interact with brands. This study focuses on the impact of augmented reality (AR) technology on consumption behavior and brand communication related to intangible cultural heritage products, integrating the TAM and UTAUT2 theories to construct a research model. This study employed a time–location sampling method, utilizing SPSS and AMOS software for data analysis based on valid questionnaires completed by 305 AR-experiencing consumers in Changsha City, Hunan Province. Results indicate that the presence and novelty of AR technology significantly and positively influence consumers’ attitudes toward using AR technology, which in turn affects their purchase intent, social media sharing behavior, and brand attitudes. The study confirms that emotional factors and consumer perceptions play a guiding and decisive role in the new consumption reality enabled by AR technology. These research findings have practical significance and value for ICH brand building and AR marketing, demonstrating that AR is an effective means to enhance the visibility and influence of the ICH brand. They inject new vitality into promoting more sustainable ICH protection and popularization, as well as the development of the digital creative industry. Full article

Sentiment analysis (SA) has become an essential tool for analyzing social media content in order to monitor public opinion and support digital analytics. Although transformer-based SA models exhibit remarkable performance, they lack mechanisms to mitigate hallucinated sentiment, which refers to the generation of unsupported or overconfident predictions without explicit linguistic evidence. To address this limitation, this study presents a hallucination-aware SA model by incorporating semantic grounding, interpretability-congruent supervision, and neuro-symbolic reasoning within a unified architecture. The proposed model is based on a fine-tuned Open Pre-trained Transformer (OPT) model, using three fundamental mechanisms: a Sentiment Integrity Filter (SIF), a SHapley Additive exPlanations (SHAP)-guided regularization technique, and a confidence-based lexicon-deep fusion module. The experimental analysis was conducted on two multi-class sentiment datasets that contain Twitter (now X) and Reddit posts. In Dataset 1, the suggested model achieved an average accuracy of 97.6% and a hallucination rate of 2.3%, outperforming the current transformer-based and hybrid sentiment models. With Dataset 2, the framework demonstrated strong external generalization with an accuracy of 95.8%, and a hallucination rate of 3.4%, which is significantly lower than state-of-the-art methods. These findings indicate that it is possible to include hallucination mitigation into transformer optimization without any performance degradation, offering a deployable, interpretable, and linguistically complex social media SA framework, which will enhance the reliability of neural systems of language understanding. Full article

The current debate on digital education is at a crossroads between the need for technological innovation and the growing concern about the impact of passive screen use. In this context, identifying sustainable pedagogical models that integrate Information and Communication Technologies (ICT) in a meaningful and inclusive way is an urgent need. This article presents a case study of the Amara Berri System (ABS), aiming to analyze how inclusive and sustainable digital innovation is operationalized within the system and whether teachers’ length of service is associated with the implementation and perceived impact of inclusive ICT practices. The investigation is based on a mixed-methods sequential design. A questionnaire was administered to a sample of 292 teachers to collect data on their practices and perceptions. Subsequently, a focus group with eight teachers was conducted to further explore the meaning of their practices. Quantitative results show that the implementation and positive evaluation of inclusive ICT practices correlate significantly with teachers’ seniority within the system, which suggests that the model is formative in itself. Qualitative analysis shows that ICTs are not an end in themselves within the ABS, but an empowering tool for the students. The “Audiovisual Media Room”, managed by students, functions as a space for social and creative production that gives technology a pedagogical purpose. The study concludes that the sustainability of digital innovation requires coherence with the pedagogical project. Findings offer valuable implications for the design of teacher training contexts that foster the integration of technology within a framework of truly inclusive education. Full article

Gastronomic tourism has emerged as a significant driver of destination competitiveness, cultural preservation, and sustainable development. This comprehensive review synthesizes the scientific literature published between 2010 and 2025, examining the evolution of gastronomic tourism research, global trends, sustainability dimensions, and emerging challenges. Through systematic analysis of 150 peer-reviewed articles from major academic databases, this paper identifies key themes including cultural heritage preservation, sustainability practices, digital transformation, and educational innovations. The findings reveal a growing recognition of gastronomy as intangible cultural heritage, increased focus on farm-to-fork practices, and the transformative role of social media in destination branding. Despite the rapid growth of gastronomic tourism research, important gaps remain. The literature lacks standardized sustainability indicators, limiting comparability across studies, while cross-cultural comparative research and interdisciplinary integration remain insufficiently developed. Addressing these gaps is essential for advancing theoretical coherence and supporting evidence-based practice in gastronomic tourism. Full article

Background: Health education is a vital component of preventative care; however, rural Filipino adults often face structural, linguistic, and access barriers to obtaining reliable health information. Designing equitable and culturally relevant health education programs requires understanding which sources are most significant and how context affects them. Objective: To identify preferred sources of health education among adults in rural Philippine communities and investigate the contextual factors that influence these preferences. Methods: A cross-sectional mixed-methods study included 1203 adults from disadvantaged Luzon and Visayas barangays. Participants completed a self-administered survey on the importance of neighborhood health fairs, native-language instructional tools, and social media. Descriptive statistics (mean ± standard deviation) were used to aggregate importance ratings, and exploratory comparisons were made using paired and independent-samples t-tests. A subsample of 60 semi-structured interviews was analyzed using thematic analysis to interpret qualitative data. Results: Community health fairs were identified as the primary source of health education, with a mean rating of 8.5 ± 1.6, followed by native-language educational materials, which received a mean rating of 5.5 ± 2.4. In contrast, social media was rated the lowest, with a mean of 3.5 ± 2.3. Preference patterns were consistent across regions and sociodemographic groups, with only slight variation in rating magnitudes. Qualitative analysis revealed four themes influencing source preferences: accessibility and proximity, cultural and linguistic relevance, confidence in local health providers, and structural obstacles to digital access. Conclusions: In rural Philippine communities, intimacy, confidence, and cultural congruence influence health education preferences more than online platforms do. Strengthening community-based, locally integrated health education strategies may enhance the reach and contextual relevance of preventive health communication in underserved settings. Full article

In an era where environmental consciousness increasingly shapes consumer behaviour, the tourism industry faces the dual challenge of promoting destinations while ensuring ecological sustainability. This study explores how web analytics and big data can be leveraged to enhance the visibility and attractiveness of eco-friendly destinations. Building upon digital marketing and sustainability frameworks, the authors develop a data-driven methodology that integrates website performance metrics, search behaviour patterns, and social media engagement indicators. After data collection, statistical and content analyses were implemented, followed by a Fuzzy Cognitive Map (FCM) to visualise the interrelationships between online user behaviour, environmental awareness, and destination appeal. Full article

Informal learning in institutional settings plays a vital role in lifelong education by fostering self-directed knowledge acquisition. With the increasing integration of digital media into these environments, augmented reality (AR) has emerged as a particularly promising technology due to its ability to overlay virtual content in real-time and across multiple sensory modalities. This systematic literature review investigates the use of AR in institutional informal learning places (IILPs) from 2018 to 2025, aiming to synthesize findings across the following overall research questions: (1) In which IILP contexts has AR been implemented, and what are the characteristics of the technology? (2) What learning-relevant functions and (3) outcomes are associated with AR in these settings? (4) Which learning theories underpin the design of AR interventions? Following the PRISMA guidelines, empirical studies were identified through comprehensive database searches (Scopus, Web of Science, IEEE Xplore, FIS Bildung) and cross-referencing. Forty-four studies were analyzed via qualitative content analysis. The goal is to provide a descriptive overview of findings, patterns, and relationships. Findings indicate that AR is widely adopted across diverse domains and institutional contexts, primarily through mobile-based AR applications for K–12 learning. Native app development signals growing technological maturity. AR enhances both cognitive and emotional-motivational outcomes, though its potential to support social interaction remains insufficiently investigated. The predominant function of AR is the provision of information. Most of the examined studies are grounded in constructivist or cognitivist learning theories, particularly the Cognitive Theory of Multimedia Learning. Only limited references to emotional-motivational frameworks and minimal references to behaviorist frameworks were found. Full article

This study aims to assess the perceived quality of telecommunication services in Portugal and examine how governance practices influence organizational performance, addressing the lack of empirical evidence on service quality gaps in the Portuguese telecommunications sector. Specifically, it investigates the alignment between customers’ expectations and perceptions of service delivery among major telecommunications providers in northern Portugal. A convenience sample of 119 subscribers was collected through an online questionnaire disseminated via social media and email. The survey measured service quality across the five SERVQUAL dimensions (tangibles, reliability, responsiveness, assurance, and empathy), and sociodemographic variables (gender, age, and education) were recorded to explore their influence on customer satisfaction and perceived quality. Results reveal a consistent gap between expectations (6.51) and perceptions (5.54), particularly in reliability and responsiveness, despite generally positive evaluations of tangibility and assurance. Sociodemographic factors significantly influenced satisfaction levels and perceptions of service quality, highlighting the importance of tailored governance strategies. These findings demonstrate that effective governance and quality management are interdependent drivers of sustainable competitiveness in technology-intensive sectors. By identifying specific quality gaps and their drivers, this study provides actionable insights for improving service delivery. Enhancing organizational reliability, responsiveness, and empathy—supported by transparent communication and data-driven decision-making—is essential for improving customer trust, operational resilience, and long-term performance. By integrating continuous quality assessment into administrative strategy, telecommunications firms can enhance service excellence and contribute to broader goals of sustainable economic development and digital transformation. Full article

Social media addiction (SMA) and social phobia (SP) are significant adolescent mental health concerns. In Saudi Arabia, despite high social media penetration, the association between these two constructs remains under-researched, particularly in the Aseer region. This cross-sectional study, conducted from January to March 2025, recruited 384 Saudi adolescents aged 11–19 from schools in the Aseer region using multistage cluster sampling. Participants completed validated self-report measures, including the Social Phobia Inventory (SPIN) and the Al-Menayes Social Media Addiction Scale. A refined “Core SMA” subscale was created based on expert consensus criteria to enhance measurement precision. The prevalence of moderate-to-severe social phobia was 15.6%. A significant, moderate positive correlation emerged between SP and SMA (Spearman’s ρ = 0.294, p < 0.001). After adjusting for age, gender, and family income, adolescents with moderate social phobia had 2.15 times the odds of probable SMA compared to those with no SP (adjusted odds ratio [AOR] = 2.15, 95% CI: 1.15–4.04, p < 0.05), and this effect was more pronounced for those with severe social phobia (AOR = 2.56, 95% CI: 1.04–6.30, p < 0.05). This study demonstrates a clear relationship between social phobia severity and social media addiction among Saudi adolescents in the Aseer region. These findings support the urgent need for integrated mental health and digital literacy interventions that proactively screen for both conditions. Full article

The rapid evolution of innovative materials and their 4D printing on fabrics allows textiles to change shape or properties when exposed to external stimuli. This work reviews the fundamentals of 4D printing, briefly revisiting additive manufacturing technology and materials, as both are extensively described in various articles and reviews. It also outlines the advancements in smart textiles and their functionality as multifunctional fabrics. The review focuses primarily on reviewing the technical foundations and emerging applications of 4D-printed smart polymers and their integration onto passive textiles for smart applications. Finally, a critical review is presented, emphasizing the numerous individual developments undertaken not only in academia but also by young students, independent engineers, and entrepreneurs who showcase their progress and various challenges through social media. Easy access to knowledge, digital communication, and an interest in creating new materials and structures with a relatively low budget will allow the advancement and development of 4D printing processing strategies for functional materials, promoting the creation of intelligent and adaptive textile systems. Full article

Background: Aging in Western societies poses a growing challenge, placing increasing pressure on healthcare costs. Early identification of infections in elderly nursing home residents is crucial to reduce complications, mortality, and the burden on emergency departments. Methods: We performed a comparative analysis of machine learning models using XGBoost classifiers for infection detection, addressing incomplete daily physiological measurements (Heart Rate, Oxygen Saturation, Body Temperature, and Electrodermal Activity) through strict imputation protocols. We evaluated three model variants—Basic (clinical only), Air Pollution-added, and Social Media-integrated—while incorporating a novel Basal Module to personalize physiological baselines for each resident. Results: Results from the binary model indicate that physiological data provides a necessary baseline for immediate screening. Notably, social media integration emerged as a powerful forecasting tool, extending the predictive horizon to a 6-day lead time with an F1-score of 0.97. Complementarily, air pollution data ensured robust immediate detection (“nowcasting”). In the multiclass scenario, external data resolved the “semantic gap” of vital signs, improving sensitivity for specific infections (e.g., acute respiratory and urinary tract infections) to over 90%. Conclusions: These findings highlight that the strategic integration of environmental and digital signals transforms the system from a reactive monitor into a proactive early warning tool for long-term care facilities. Full article

This study provides a systematic overview of Natural Language Processing (NLP)-based frameworks for Cyber Threat Intelligence (CTI) and the early prediction of cyberattacks in Industry 4.0. As digital transformation accelerates through the integration of IoT, SCADA, and cyber-physical systems, manufacturing environments face an expanding and complex cyber threat landscape. Following the PRISMA 2020 systematic review protocol, 80 peer-reviewed studies published between 2015 and 2025 were analyzed across IEEE Xplore, Scopus, and Web of Science to identify methods that employ NLP for CTI extraction, reasoning, and predictive modelling. The review finds that transformer-based architectures, knowledge graph reasoning, and social media mining are increasingly used to convert unstructured data into actionable intelligence, thereby enabling earlier detection and forecasting of cyber threats. Large Language Models (LLMs) demonstrate strong potential for anticipating attack sequences, while domain-specific models enhance industrial relevance. Persistent challenges include data scarcity, domain adaptation, explainability, and real-time scalability in operational-technology environments. The review concludes that NLP is reshaping Industry 4.0 cybersecurity from reactive defense toward predictive, adaptive, and intelligence-driven protection, and it highlights the need for interpretable, domain-specific, and resource-efficient frameworks to secure Industry 4.0 ecosystems. Full article

This study examines the development of scientific dissemination skills in initial teacher education through a sequential explanatory mixed-methods design (QUANTITATIVE→QUALITATIVE). The purpose was to explore how the integration of Project-Based Learning (PBL) and Experiential Learning (EL) fosters the acquisition of cognitive, communicative, media–digital, and ethical–social competencies related to scientific communication. Seventy-nine students from Early Childhood Education (n = 36) and Primary Education (n = 43) degrees at the University of Valladolid participated during the 2024–2025 academic year. In the quantitative phase, a validated questionnaire was administered to assess four dimensions of competence, while the qualitative phase included systematic observations and focus groups. Data analysis combined descriptive and inferential statistics with thematic analysis and convergent integration. The results showed significant improvements in all dimensions, particularly in communicative and media–digital skills, with qualitative evidence explaining the mechanisms underlying this progress. The integration of findings revealed the transformation of students from passive recipients to active mediators of scientific knowledge. It is concluded that the combination of PBL and EL constitutes an effective pedagogical framework for promoting responsible scientific dissemination in higher education and reinforcing the social responsibility of teacher training. Full article