Search Results (926)

Background/Objectives: Health education plays a vital role in training health professionals and caregivers, supporting both prevention and the promotion of self-care. In this context, technology serves as a valuable ally by enabling continuous and flexible learning. Among the various domains of health education, nutrition stands out as a key element in the management of Amyotrophic Lateral Sclerosis (ALS), helping to prevent malnutrition and enhance patient well-being. Accordingly, this study aimed to evaluate the effectiveness of the teaching and learning processes within a learning pathway focused on food and nutrition in the context of ALS. Methods: This study adopted a longitudinal, quantitative design. The learning pathway, titled “Food and Nutrition in ALS,” consisted of four self-paced and self-instructional Massive Open Online Courses (MOOCs), offered through the Virtual Learning Environment of the Brazilian Health System (AVASUS). Participants included health professionals, caregivers, and patients from all five regions of Brazil. Participants had the autonomy to complete the courses in any order, with no prerequisites for enrollment. Results: Out of 14,263 participants enrolled nationwide, 182 were included in this study after signing the Informed Consent Form. Of these, 142 (78%) completed at least one course and participated in the educational intervention. A significant increase in knowledge was observed, with mean pre-test scores rising from 7.3 (SD = 1.8) to 9.6 (SD = 0.9) on the post-test across all courses (p < 0.001). Conclusions: The self-instructional, technology-mediated continuing education model proved effective in improving participants’ knowledge about nutrition in ALS. Future studies should explore knowledge retention, behavior change, and the impact of such interventions on clinical outcomes, especially in multidisciplinary care settings. Full article

This article addresses the task of building personalized educational recommendations based on a heterogeneous knowledge graph that integrates data from university curricula, job vacancies, and online courses. To solve the problem of course recommendations by their relevance to a user’s competencies, a graph neural network (GNN)-based approach is proposed, specifically utilizing and comparing the Heterogeneous Graph Transformer (HGT) architecture, Graph Sample and Aggregate network (GraphSAGE), and Heterogeneous Graph Attention Network (HAN). Experiments were conducted on a heterogeneous graph comprising various node and relation types. The models were evaluated using regression and ranking metrics. The results demonstrated the superiority of the HGT-based recommendation model as a link regression task, especially in terms of ranking metrics, confirming its suitability for generating accurate and interpretable recommendations in educational systems. The proposed approach can be useful for developing adaptive learning recommendations aligned with users’ career goals. Full article

Knowledge tracing (KT), a core educational data mining task, models students’ evolving knowledge states to predict future learning. In online education systems, the exercises are numerous, but they are typically associated with only a few concepts. However, existing models rarely integrate exercise information with high-order exercise–concept correlations, focusing solely on optimizing models’ final predictive performance. To address these limitations, we propose the Hypergraph-Driven High-Order Knowledge Tracing with a Dual-Gated Dynamic Mechanism (HGKT), a novel framework that (1) captures correlations between exercises and concepts through a two-layer hypergraph convolution; (2) integrates hypergraph-driven exercise embedding and temporal features (answer time and interval time) to characterize learning behavioral dynamics; and (3) designs a learning layer and a forgetting layer, with the dual-gating mechanism dynamically balancing their impacts on the knowledge state. Experiments on three public datasets demonstrate that the proposed HGKT model achieves superior predictive performance compared to all baselines. On the longest interaction sequence dataset, ASSISChall, HGKT improves prediction AUC by least 1.8%. On the biggest interaction records dataset, EdNet-KT1, it maintains a state-of-the-art AUC of 0.78372. Visualization analyses confirm its interpretability in tracing knowledge state evolution. These results validate HGKT’s effectiveness in modeling high-order exercise–concept correlations while ensuring practical adaptability in real-world online education platforms. Full article

In an era where digitalization shapes economic and social landscapes, the intersection of digital skills, ethics, and integrity plays a crucial role in understanding the vulnerability of youth classified as NEET (Not in Education, Employment, or Training). This study explores how risky internet use and digital skill gaps contribute to socio-economic exclusion, integrating a multivariate and spatial approach to assess regional disparities in Europe. This study adopts a systems thinking perspective to explore digital exclusion as an emergent outcome of multiple interrelated subsystems. The research employs logistic regression, Principal Component Analysis (PCA) with Promax rotation, and Geographic Information Systems (GIS) to examine the impact of digital behaviors on NEET status. Using Eurostat data aggregated at the country level for the period (2000–2023) across 28 European countries, this study evaluates 24 digital indicators covering social media usage, instant messaging, daily internet access, data protection awareness, and digital literacy levels. The findings reveal that low digital skills significantly increase the likelihood of being NEET, while excessive social media and internet use show mixed effects depending on socio-economic context. A strong negative correlation between digital security practices and NEET status suggests that youths with a higher awareness of online risks are less prone to socio-economic exclusion. The GIS analysis highlights regional disparities, where countries with limited digital access and lower literacy levels exhibit higher NEET rates. Digital exclusion is not merely a technological issue but a multidimensional socio-economic challenge. To reduce the NEET rate, policies must focus on enhancing digital skills, fostering online security awareness, and addressing regional disparities. Integrating GIS methods allows for the identification of territorial clusters with heightened digital vulnerabilities, guiding targeted interventions for improving youth employability in the digital economy. Full article

Self-regulated learning (SRL) has been widely recognized as a critical skill for academic success in online and blended learning contexts. However, many students experience difficulty in effectively applying SRL strategies in the absence of structured instructional guidance. To address this challenge, this study developed and implemented a learning management system integrated with SRL support (SRL-LMS), specifically designed for the online component of a blended learning course. The SRL-LMS consisted of two sections: a conventional course content section and a SRL training section designed to support students in applying SRL strategies. A quasi-experimental design was adopted with 69 college students assigned to either an experimental group, with access to both course and SRL sections, or a control group, which accessed only the course section. Results indicated that students in the experimental group reported higher levels of self-regulation and showed more frequent and diverse application of SRL strategies compared to the control group. In terms of academic performance, the experimental group performed significantly better than the control group on the first exam, though no significant difference was observed on the second exam. These results highlight the effectiveness of structured SRL interventions within digital learning platforms for improving students’ self-regulatory behaviors. Future implementations should address cognitive load and incorporate strategic approaches to sustain student motivation. This study advances current SRL intervention designs and offers valuable insights for educators and instructional designers aiming to integrate targeted SRL supports in online and blended learning environments. Full article

This entry explores the multifaceted intersections of gender and digital technologies, offering a comprehensive analysis of how structural inequalities are reproduced, contested, and transformed in digital contexts. It is structured into six interrelated sections that collectively address key dimensions of gendered digital contexts. It begins by addressing the gender digital divide, particularly in the Global South, emphasizing disparities in access, literacy, and sociocultural constraints. The second section examines gendered labor in the tech industry, highlighting persistent inequalities in Science, Technology, Engineering, and Mathematics (STEM) education, employment, and platform-based work. The third part focuses on gender representation in digital spaces, revealing how algorithmic and platform design perpetuate biases. The fourth section discusses gender bias in AI and disinformation, underscoring the systemic nature of digital inequalities. This is followed by an analysis of online gender-based violence, particularly its impact on marginalized communities and participation in digital life. The final section considers the potentials and limitations of digital activism in advancing gender justice. These sections collectively argue for an intersectional, inclusive, and justice-oriented approach to technology policy and design, calling for coordinated global efforts to create equitable digital futures. Full article

While prior work has explored learner behavior using learning management systems (LMS) data, few studies provide week-level clustering validated against external engagement labels. To understand and assist students in online learning platforms and environments, this study presents a week-level engagement profiling framework for e-learning environments, utilizing K-means clustering and label-based validation. Leveraging log data from 127 students over a 13-week course, 44 activity-based features were engineered to classify student engagement into high, moderate, and low levels. The optimal number of clusters (k = 3) was identified using the elbow method and assessed through internal metrics, including a silhouette score of 0.493 and R² of 0.80. External validation confirmed strong alignment with pre-labeled engagement levels based on activity frequency and weighting. The clustering approach successfully revealed distinct behavioral patterns across engagement tiers, enabling a nuanced understanding of student interaction dynamics over time. Regression analysis further demonstrated a significant association between engagement levels and academic performance, underscoring the model’s potential as an early warning system for identifying at-risk learners. These findings suggest that clustering based on LMS behavior offers a scalable, data-driven strategy for improving learner support, personalizing instruction, and enhancing retention and academic outcomes in digital education settings such as MOOCs. Full article

The influence of social media personalities has grown significantly, especially among youth audiences who spend substantial time on platforms like TikTok. The emergence and popularity of different types of social media influencers accelerated during the COVID-19 pandemic in many countries, including South Africa. In turn, this period also saw a surge in youth audiences following these influencers. This rapid growth of influencer followings among young people is largely driven by specific types of content that resonate with them, thus encouraging continued engagement. However, the benefits that these young followers gain from engaging with various influencers and the factors driving their preferences for specific influencers remain underexplored, particularly within the context of South African students within higher education. Therefore, this study explores the types of social media influencers most followed by university students at a South African University and investigates the key factors that drive their preferences. A structured online questionnaire was distributed, gathering both multiple-choice and open-ended responses from students. The data were analyzed using categorical frequency counts and thematic analysis. The data highlight how students actively turn to influencers as emotional anchors, role models, and sources of practical guidance. Their engagement reflects a deep need for connection, inspiration, and identity formation in a challenging academic and social environment. These patterns show that influencer content is not just entertainment but plays a critical developmental role. Understanding these motivations helps educators, policymakers, and brands to align better with youth values. The significance of these results lies in how influencer content is now coming in to fill the emotional, cultural, and educational gaps left by traditional systems among the young South African university students in this modern era. Full article

For the majority of human history, humans lived in sustenance hunter–gatherer tribes. Due to rapid cultural evolution in the past few thousand years, our biological evolution has not kept up, and many of the adaptations are, as a result, better suited to ancestral conditions than they are to modern conditions. This is known as evolutionary mismatch. While evolutionary mismatches can be seen across many facets of contemporary human life (e.g., diet, exercise, online communication), evolutionary mismatches are particularly pervasive in our elementary schools. Due to the critical nature of social learning and cultural transmission, there is a long history of learning that has shaped the evolved learning mechanisms of children. Rather than learning from hands-on, collaborative experiences as was typical for our ancestors, children today often learn in age-segregated classrooms through passive instruction and standardized curricula. In this entry, eight common school-related issues are identified and the associated evolutionary mismatch is outlined. The goal is to provide educators with a model of how an evolutionary lens can be used to better understand, and potentially improve, modern schooling systems. Full article

Adaptive learning tailors learning to the specific needs and preferences of the learner. Although studies focusing on adaptive learning systems became popular decades ago, there is still a need for empirical evidence on the usability of adaptive learning in various educational environments. This study uses LMS log data to elucidate an adaptive course design explicitly developed for formal educational environments in higher education institutions. The framework utilizes learning analytics and machine learning techniques. Based on learners’ online engagement and tutors’ assessment of course activities, adaptive learning paths are presented to learners. To determine whether our system can increase learner engagement and prevent failures, learner success and engagement are measured during the learning process. The results show that the proposed adaptive course framework can increase course engagement and success. However, this potential depends on several factors, such as course organization, feedback, time constraints for activities, and the use of incentives. Full article

The growing urgency of the climate crisis has heightened the importance of integrating sustainability into health education. Allied health professionals are well positioned to lead sustainable healthcare efforts, yet evidence suggests a persistent gap between student awareness and formal training. This study explored the perspectives, knowledge, and attitudes of Portuguese allied health students regarding sustainability. An online and anonymous cross-sectional survey was conducted among undergraduate and graduate students across multiple allied health disciplines. The questionnaire assessed general knowledge, perceptions of curricular integration, and attitudes toward sustainable clinical practice. A total of 247 (response rate of 8.23%) students participated, with the majority expressing high concern about climate change and strong support for environmentally responsible healthcare. However, the results revealed inconsistent awareness of healthcare’s environmental footprint and a limited exposure to structured sustainability education. Friedman tests indicated significant variability in students’ knowledge, perceived responsibility, and curricular experiences. Students identified priority themes for curricular inclusion—such as the environmental impact of the health system—and recognized their alignment with the UN Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health) and SDG 13 (Climate Action). The findings highlight the need for the systematic, competency-based integration of sustainability into allied health curricula to support a climate-resilient and ecologically responsible future healthcare workforce. 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

Geoethics emphasizes responsible human interaction with the Earth, promoting ethical practices in the geosciences to ensure sustainability for current and future generations. UNESCO Global Geoparks (UGGps) are designated areas that support sustainable development by integrating geoconservation, geoeducation, and community engagement, thereby raising awareness of geological heritage. This quantitative study employed an online questionnaire (n = 798) to assess geoethical awareness among residents of all nine Hellenic UGGps, with the aim of profiling environmental engagement and perceptions. The results indicate a generally high level of geoethical awareness, with Sitia UGGp exhibiting the highest average mean score (M⁻ = 8.98, SD⁻ = 1.34), reflecting strong community support and effective outreach efforts. In contrast, Lavreotiki UGGp (M⁻ = 8.48, SD⁻ = 1.15) and Psiloritis UGGp (M⁻ = 8.33, SD⁻ = 1.36) scored lower in areas such as community engagement and geotourism, suggesting opportunities for targeted improvement. Regional differences suggest that management, visibility, and local context significantly influence public perceptions. Cluster analysis identified four respondent profiles: (a) highly engaged environmental stewards (28.7%), (b) supportive but selective advocates (40.5%), (c) moderately indifferent participants (26.9%), and (d) disengaged or critical respondents (3.9%). Demographic factors such as age, residence, prior visits to Hellenic UGGps, and education significantly differentiated these groups. Mapping geoethical awareness provides a valuable tool for assessing societal benefits and enhancing the governance of UGGps. Overall, the findings underscore the need to shift from an anthropocentric to a more geocentric worldview that prioritizes the well-being of both humanity and Earth’s systems. Full article

Infectious disease outbreaks amplify the influence of stressors on psychological conditions. The purpose of this study was to analyze the disturbing influence of COVID-19 outbreak-related information and the influence of trust on the Serbian healthcare system and COVID-19 preventive measures on anxiety and depression. An anonymous online questionnaire assessing the demographic information, disturbance level and causes, and levels of anxiety and depression has been distributed to the participants, divided into student and non-student groups. The non-student group was further divided into healthcare, military, and education workers. Anxiety and depression levels, as well as the level of decreased trust in COVID-19-related preventive measures, were higher among students compared to non-students (p = 0.011). Higher anxiety and depression levels, and higher influence of the COVID-19 outbreak on those levels, were observed in education and healthcare workers, compared to military personnel. Medical doctors reported a higher level of trust in the healthcare system compared to nurses (p = 0.023). Trust in the healthcare system increased more frequently compared to the pre-vaccination period among medical doctors, compared to nurses (p = 0.040). Higher anxiety and depression and lower public trust levels in students and workers in education and the healthcare sector indicate a need to focus on these important society members during public health emergencies. Full article

Electronic nicotine delivery systems (vapes) are the most used nicotine products among U.S. adolescents, with usage increasing significantly from 2017 to 2019. School-based prevention programs are a critical strategy for curbing youth vaping. This study utilized a retrospective pre/post survey to evaluate the effectiveness of a two-year school-based vaping prevention program utilizing a condensed version of the Stanford University Tobacco Prevention Toolkit. The program was implemented in-person and online across two years in a southeastern U.S. state. In year one, evalua-tion data were collected from 4252 youths from 20 rural counties who completed the in-person survey during the 2018–2019 program year. In year two, 1347 youths from 13 rural and urban counties completed the survey during the program year of 2019–2020. The key findings indicate significant increases in knowledge about vaping risks post-program. The findings from year one indicate that increases in knowledge about e-cigarettes were negatively related to the frequency of vaping, but this was not replicated in year two. Moreover, knowledge did not influence vaping frequency if youths had already started vaping, while pre-program knowledge did not predict the frequency of vaping in either year. These results suggest that vaping prevention education outcomes among youths are mixed. Full article