Search Results (156)

Contemporary education increasingly emphasises transferable competencies that enable learners to analyse situations, evaluate information, and make responsible decisions. This study examined the effects of a structured educational intervention based on inquiry, problem-solving, and role-play activities on the development of decision-making competence in primary school students. A quasi-experimental pre-test–post-test design with a control group was employed. The initial sample consisted of 64 second-grade students, with final analyses conducted on 39 complete cases. Decision-making competence was assessed using a researcher-developed multidimensional scale encompassing six dimensions: identification of alternatives, justification of decisions, anticipation of consequences, autonomy, collaboration, and responsibility. The results indicated a significant improvement in decision-making competence from pre-test (M = 13.23, SD = 1.68) to post-test (M = 20.05, SD = 4.49), t(38) = 8.45, p < 0.001, d = 1.35. Additionally, analysis of covariance revealed a significant effect of group on post-test scores, F(1, 36) = 9.82, p = 0.003, ηp² = 0.21, with the experimental group demonstrating greater improvement than the control group. A 2 × 2 repeated-measures ANOVA further indicated that gains were more pronounced in the cognitive domain than in the socio-emotional domain. These findings suggest that structured classroom activities involving inquiry, problem-solving, and role-play can support primary school students’ ability to analyse situations, generate alternatives, and justify decisions, particularly within the cognitive dimensions of decision-making competence. At the same time, the more moderate gains observed in collaboration and responsibility highlight the need for sustained, interaction-based learning contexts to support the development of socio-emotional dimensions. Full article

This bibliometric study examines the role of ubiquitous computing and intelligent systems in the treatment of mental and neurological disorders. Ubiquitous computing integrates computational intelligence into everyday environments, enabling seamless monitoring and support of patients. Intelligent systems, including wearable devices, environmental sensors, and mobile health applications, collect real-time data on behavior, physiology, and environmental factors. These systems support early detection of symptom changes, adherence to treatment, and crisis prediction through context-aware analysis. Artificial intelligence (AI) processes the collected data to generate personalized therapeutic feedback and notify healthcare providers when intervention is needed. In mental health care, intelligent environments can monitor mood, sleep, and social interaction patterns, providing valuable objective information about mental health status. In the case of neurological conditions such as Parkinson’s disease or epilepsy, intelligent systems facilitate movement tracking, seizure detection, and cognitive assessment outside of the clinical setting. Integration with electronic health records and telemedicine platforms ensures coordinated and responsive care. Ethical design, privacy protection, and patient consent remain key to successful implementation. In this way, ubiquitous computing is transforming care models by increasing autonomy, precision, and continuity in the treatment of complex neurodegenerative diseases, including those related to neurodegeneration in aging. Full article

Generative Artificial Intelligence (GenAI) is reshaping how students engage with learning both within and beyond traditional classroom settings. In a time when the development of transferable skills is essential for enabling students to thrive in varied and rapidly evolving environments, the potential of GenAI to enhance learning engagement remains insufficiently understood. Despite rising interest in interactive, personalised learning companions that enable deep engagement and ongoing skills development, scholarly research remains limited. This gap constrains effective institutional use of GenAI, reinforces black-box thinking, and restricts understanding of meaningful student engagement and skills acquisition. This paper investigates how a GenAI-enabled AI teacher supports student learning engagement, focusing on behavioral engagement as evidenced by learner interaction and participation patterns across diverse international higher education institutions. Using a combination of quantitative engagement metrics and qualitative learner reflections, the study examines how GenAI supports personalised learning, sustained interaction, autonomy, and cognitive engagement among students with varying educational backgrounds. The findings demonstrate that GenAI-based teaching systems can promote meaningful learning engagement, enhance motivation, and strengthen the development of transferable and employability skills. The study contributes empirical evidence to current debates on GenAI integration, teacher practices, and student engagement, offering implications for curriculum design and institutional adoption of GenAI-enabled learning tools. Full article

The growing digitalization of supply chains and increasing sustainability requirements create the need for structured tools that assess organizational readiness for Cognitive Twin (CT) adoption. However, existing digital twin and sustainability maturity models rarely integrate technological architecture, governance, and circularity within a unified framework. To address this gap, the study proposes the Supply Chain Twin Sustainability–Cognitive Maturity Model (SCT-SCMM), a novel framework that explicitly integrates governance structures, sustainability objectives, and a hierarchical system architecture into the assessment of Cognitive Twin readiness. Unlike existing models, the proposed framework captures the interdependencies between technological capabilities, decision intelligence, and governance mechanisms across multiple system layers, providing a systemic perspective on sustainable digital transformation. The framework structures organizational readiness through five interdependent layers: Physical, Control, Communication, Decision-making, and Governance, and defines staged maturity levels reflecting progression toward sustainable cognitive autonomy. This layered architecture enables the simultaneous evaluation of operational automation, digital intelligence, and institutional governance as co-evolving dimensions of Cognitive Twin adoption. The model was developed through a structured literature review and operationalized using a hybrid multi-criteria and fuzzy-based evaluation approach, enabling the evaluation of complex socio-technical systems under uncertainty. The framework was applied in an automated product-to-human warehouse case study to evaluate technological, sustainability, and governance readiness. The results demonstrate the model’s ability to identify maturity gaps, reveal inter-layer dependencies, and prioritize transformation pathways toward more resilient and circular logistics systems. By integrating governance, sustainability, and system architecture into a single maturity model, SCT-SCMM extends existing digital twin maturity approaches and provides a transparent decision-support tool for guiding staged Cognitive Twin adoption in next-generation sustainable supply chains. Full article

This study examined the perceived quality of life of Portuguese gifted students compared with their non-gifted peers using the KIDSCREEN-27, a widely used instrument for assessing health-related quality of life in children and adolescents. Quality of life is the subjective perception of overall well-being resulting from the interaction of physical, psychological, social, and environmental factors. Previous research suggests that high intellectual ability does not necessarily ensure greater well-being and may coexist with social–emotional challenges, including perfectionism, anxiety, and difficulties in social integration. The sample consisted of 102 Portuguese students aged between 10 and 15 years old. They were in two groups (gifted and non-gifted), matched by gender. Gifted participants had previously been identified through psychoeducational assessment and were enrolled in the PEDAIS enrichment program promoted by the National Association for the Study and Intervention in Giftedness (ANEIS). Five quality-of-life dimensions were analyzed: physical well-being, psychological well-being, autonomy and parent relationships, peer social support, and school environment. MANOVA results indicated statistically significant differences between the groups, with gifted students reporting lower scores in physical well-being, autonomy and parent relationships, peer social support, and school environment. There were no significant differences in psychological well-being, indicating similar levels of perceived emotional well-being in both groups. These findings highlight the importance of considering the social and contextual dimensions of well-being in gifted education and reinforce the need for educational strategies that combine cognitive development with social–emotional support. However, the results should be interpreted with caution, as the gifted participants were recruited from a structured enrichment program, which may limit the generalizability of the findings to the broader population of gifted students. Full article

This study presents a comparative analysis of classroom engagement effects on the academic achievement of senior secondary school physics students, focusing on the replication of prior research and contrasting the impacts of guided and minimally guided constructivist instructional approaches. Drawing on established frameworks of inquiry-based instruction, particularly Cognitively Guided Instruction (CGIS) and Cubing Instruction (CIS), the research investigates their relative efficacy in enhancing student learning outcomes. The clustered quasi-experimental pretest–posttest design, involving the Cognitively Guided Instructional Strategy (CGIS) and the Cubing Instructional Strategy (CIS), was adopted by the study. The intact classroom groups of schools purposively selected participated in the study. An achievement test was administered before and after instruction, and the Analysis of Covariance (ANCOVA) and t-tests were used to determine the effects of the intervention while controlling for baseline achievement and mathematical ability. The findings show that the treatment had a significant effect on the students’ achievement (p = 0.030). The t-test result demonstrated that students exposed to the CGIS recorded higher posttest mean scores than those in the CIS group. These outcomes suggests that guided inquiry may offer pedagogical advantages in supporting classroom and conceptual learning. However, the evidence should be cautiously interpreted. The study contributes to the literature as a conceptual replication by providing evidence regarding the effects of guided and minimally guided constructivist approaches in a different instructional setting. The outcomes underscore the importance of balancing instructional guidance and learner autonomy in physics classrooms, as well as the need for further research involving larger samples and diverse contexts to strengthen causal inference. Full article

Self-regulated learning (SRL) is a fundamental competence for academic transition and success in higher education, especially in health sciences, where autonomy and learning management are essential. This systematic review analyzed the relationship between SRL, academic performance, and student well-being among undergraduate health sciences students. Following the PRISMA protocol, 39 articles published between 2015 and 2025 on Web of Science, Scopus, and PubMed databases were selected. The consolidated sample consisted of 24,835 participants. The methodological quality of the selected studies was assessed using the Newcastle–Ottawa scale (NOS). A predominantly positive association was found between high levels of SRL and academic performance (GPA) (with correlation coefficients ranging from r = 0.11 to r = 0.55 in the primary studies). Furthermore, evidence from standardized self-report questionnaires in the reviewed literature indicates that several studies report female students showed higher levels of organization and planning, but these findings were not consistently observed across all studies. SRL acts as a key protective factor against stress, anxiety, and academic burnout. However, a “stagnation paradox” was identified: SRL skills do not always evolve linearly, often showing regression or stagnation in advanced clinical years due to the high cognitive load and insufficient support structure in those environments. Regarding sociodemographic variables, female students reported higher levels of planning and responsibility. SRL does not develop spontaneously with academic progress. Therefore, higher-education institutions must implement systematic and intentional pedagogical strategies from the early years of training to foster student well-being and the development of resilient professionals. Full article

Heavy-load unmanned aerial vehicles (UAVs) are increasingly being applied in logistics, infrastructure installation, and emergency response missions, where complex payload dynamics and unstructured environments pose significant challenges to safe and efficient operation. Conventional manual teleoperation interfaces, such as dual-joystick control, impose a high cognitive workload and provide limited support for expressing high-level operator intent, while fully autonomous solutions remain difficult to deploy reliably under real-world uncertainty. To address these limitations, this paper proposes the Multimodal Fusion Cooperation Network (MFCN), an end-to-end shared autonomy framework that integrates speech commands, visual gestures, and haptic cues through cross-modal feature fusion to infer operator intent in real time. The fused intent representation is translated into dynamically feasible control commands by a cooperative control policy with embedded physics-aware constraints to suppress payload oscillations and ensure flight stability. Extensive semi-physical simulations and real-world experiments demonstrate that the MFCN significantly improves the task success rate, positioning accuracy, and payload stability while reducing the task completion time and operator cognitive workload compared with manual, unimodal, and heuristic multimodal baselines. Full article

Background/Objectives: Dominant models of successful aging emphasize health, autonomy, and active engagement, often excluding older adults belonging to vulnerable groups, such as those living in long-term care facilities (LTCFs). This study aims to address this limitation by exploring how LTCF residents define “aging well” and by examining whether they perceive themselves as aging well according to their own criteria. Methods: A qualitative design was employed using semi-structured interviews with 30 residents aged 67–95 living in three long-term care facilities located in Barcelona, Spain. Interview transcripts were analyzed using inductive thematic analysis. Results: Five core themes emerged in the participants’ definitions of aging well: health, attitude, social ties, security, and activities. Health was the most frequently mentioned domain but was conceptualized in undemanding terms, focusing on basic autonomy and cognitive functioning. Psychological attitudes and meaningful social relationships were also key, alongside contextual factors, such as security and access to activities. Two-thirds of the participants perceived themselves as aging well, with justifications closely aligned with their personal definitions; negative self-perceptions were mainly associated with poor health, loss of autonomy, or loneliness. Conclusions: The findings suggest that, in contrast with academic definitions, LTCF residents define aging well in a broader, more context-sensitive manner, which allows them to view themselves positively despite their limitations. Person-centered care environments may play a crucial role in supporting aging well in institutional settings. Full article

Critical Thinking (CT) is recognized as a foundational competency for professional readiness, innovation, and ethical reasoning in higher education, enabling students to analyze information, evaluate evidence, and make reasoned decisions in complex environments. The rapid integration of Generative Artificial Intelligence (GenAI) tools, such as large language models, presents new opportunities and risks for CT development. This study conducts a systematic literature review to synthesize empirical evidence on the pedagogical implications and cognitive impact of GenAI on students’ CT. Following PRISMA guidelines, and search terms around GenAI Tools, Critical Thinking And Higher Education, on five major education research databases—Web of Science; Scopus; EBSCOhost (Education Source, ERIC, and APA PsycInfo); and Compendex and Inspec (Elsevier)—63 empirical studies published between January 2023 and April 2025 were analyzed across higher education contexts, disciplines, and intervention designs. Results indicate that GenAI offers notable cognitive affordances, including scaffolding reflective reasoning, promoting self-regulation, and facilitating iterative dialogue and argument evaluation. Pedagogical strategies clustered into four primary integration typologies: AI-based feedback prompts, dialogue simulation and reflection, AI-supported peer review, and critical engagement with AI-generated content. Nearly half of the studies reported statistically significant CT improvements, particularly when GenAI use was guided by structured prompts, reflective activities, and performance-based assessment. However, multiple risks persist, including cognitive offloading, uncritical acceptance of AI outputs, and diminished intellectual autonomy, especially in unguided or surface-level usage. This review highlights the need for intentional pedagogical design, validated CT assessment tools, and longitudinal studies to ensure GenAI acts as a catalyst rather than a substitute for human reasoning. By identifying effective integration strategies and outlining potential pitfalls, this study provides evidence-informed guidance for educators and institutions aiming to responsibly leverage GenAI to strengthen students’ CT skills. Full article

Background/Objectives: Mental health challenges are increasingly prevalent among higher education students, with significant implications for academic success and personal development. Emerging research suggests that critical thinking dispositions may support psychological well-being by enhancing resilience and adaptive coping. This study aimed to investigate the relationship between critical thinking dispositions and psychological well-being and to identify key sociodemographic predictors in this context. Methods: A cross-sectional design was employed from December 2024 to May 2025, recruiting 429 students from Portuguese higher education institutions via convenience sampling. Participants completed validated self-report measures: the Critical Thinking Dispositions Scale (CTDS) and the Psychological Well-Being Scale (PWBS), assessing seven critical thinking dispositions and six well-being dimensions, respectively. Sociodemographic data were also collected. Descriptive statistics, independent t-tests, one-way ANOVA, Pearson correlations, and hierarchical multiple regression were used for data analysis. Results: Students demonstrated moderate to high levels of critical thinking and psychological well-being, with higher scores associated with increased age and academic progression. Significant positive correlations were identified between critical thinking dispositions and all well-being dimensions; personal growth, purpose in life, and autonomy exhibited the strongest associations. Regression analysis revealed that confidence in reasoning, cognitive maturity, and open-mindedness were significant predictors of psychological well-being, explaining 28.7% of the variance. Conversely, inquisitiveness showed a negative association with psychological well-being in the multivariate model, an unexpected finding that warrants cautious interpretation and further investigation. Conclusions: Critical thinking dispositions reflect affective tendencies and habitual ways of engaging with thinking. These dispositions appear to protect psychological well-being in higher education students. Integrating the development of emotional awareness and reflective thinking into curricula may therefore foster resilience and academic success. Further longitudinal research is needed to explore causal mechanisms and intervention efficacy in broader academic contexts. Full article

This study explores how immersive e-learning technologies influence entrepreneurial intention among business education students, with a focus on the mediating role of learning satisfaction. Using a quantitative approach, data were collected from 561 final-year undergraduate students enrolled in business and entrepreneurship programs at globally ranked universities. The relationships between immersive learning design features, learning satisfaction, and entrepreneurial intention were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The study draws on Experiential Learning Theory, Self-Determination Theory, and Expectancy–Value Theory to explain how immersive learning experiences shape entrepreneurial motivation. The results show that interactivity, experiential engagement, and personalization positively influence entrepreneurial intention, primarily by enhancing learning satisfaction. Students are more inclined toward entrepreneurial careers when immersive learning environments support autonomy, meaningful engagement, and perceived value. In contrast, high levels of realism and multisensory intensity do not consistently strengthen entrepreneurial intention, suggesting that excessive immersion may create cognitive strain or diminishing motivational returns under certain conditions. These findings highlight the importance of balanced and learner-centered immersive learning design rather than increased technological intensity alone. From a practical perspective, the study suggests that business schools should integrate immersive technologies in ways that emphasize experiential learning, adaptability, and cognitive balance. However, the findings should be interpreted with caution due to the cross-sectional design, reliance on self-reported data, and focus on final-year students. Overall, the study provides a nuanced understanding of how immersive e-learning can support entrepreneurial intention while also identifying important boundary conditions that shape its effectiveness. Full article

The rapid expansion of algorithmic systems has transformed cognition into an increasingly distributed and collective enterprise, giving rise to what can be described as cognitive assemblages, dynamic constellations of humans, institutions, data infrastructures, and artificial agents. This paper traces the historical and conceptual evolution that has led to this shift. First, we show how cognition, once conceived as the property of autonomous individuals, has progressively become embedded in socio-technical networks in which algorithmic processes participate as co-agents. Second, we revisit the progressive awareness of human cognitive limits, from bounded rationality to contemporary theories of extended mind. These frameworks anticipate and help explain today’s hybrid cognitive ecologies. Third, we assess the philosophical implications for Enlightenment ideals of autonomy, rationality, and self-governance, showing how these concepts must be reinterpreted in light of pervasive algorithmic intermediation. Finally, we examine global initiatives that seek to integrate augmented cognitive capacities into large-scale cybernetic forms of societal coordination, ranging from digital platforms and data spaces to AI-driven governance systems. These developments offer new opportunities for steering complex societies under conditions of globalization, environmental disruption, and the rise of autonomous intelligent systems, yet they also raise profound questions regarding control, accountability, and democratic legitimacy. We argue that understanding cognitive assemblages is essential to designing socio-technical systems capable of supporting collective intelligence while preserving human values in an era of accelerating complexity. Full article

The author investigates how digital learning competence (DLC) is bridged to academic achievement (AA) through informal digital learning engagement (IDLE) and how meta-cognitive self-regulation (MSR) shapes these pathways among university students. Grounded in a moderated mediation framework, this research conceptualizes DLC not as a static skill set but as a latent capacity that is channeled into academic outcomes when students autonomously engage in digital environments and regulate their cognition. Survey data were collected from 432 undergraduate students and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that DLC significantly predicts AA both directly and indirectly via IDLE, identifying informal digital learning engagement as a central pathway through which digital learning competence is translated into academic gains. Furthermore, MSR moderates the relationship between DLC and IDLE, such that higher levels of metacognitive self-regulation strengthen the conversion of digital learning competence into productive informal digital learning engagement. These findings support a dynamic view of digital learning competence and underscore the roles of learner autonomy and metacognitive awareness in transforming digital skills into meaningful educational outcomes. By integrating perspectives on digital literacy, self-regulated learning, and informal learning, this study offers implications for the design of digital learning ecosystems that effectively bridge students’ digital capacities with their academic achievement. Full article

Intelligent Clinical Decision Support Systems (ICDSS) are increasingly integrated into healthcare settings to enhance clinical decision-making, efficiency, and patient safety. Despite advances in artificial intelligence-enabled decision support, ICDSS adoption remains inconsistent, particularly in complex clinical environments where professional autonomy, workflow alignment, and accountability are critical. This study examines healthcare providers’ perspectives on ICDSS through a grounded theory approach informed by established Information Systems theories, including the Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Acceptance Model (TAM), Diffusion of Innovation (DOI), and the Human-Organization-Technology fit (HOT-fit) framework. Semi-structured interviews were conducted with 11 providers within a large, integrated healthcare organization, and data were analyzed using open, axial, and selective coding. The findings reveal three interrelated dimensions shaping ICDSS use: provider experience, clinical utility, and adaptation. While ICDSS were perceived as valuable for improving efficiency, supporting treatment decisions, and enhancing patient safety, their adoption was constrained by cognitive overload, workflow misalignment, data quality concerns, and perceived threats to professional autonomy. Trust, explainability, and workflow fit emerged as central mechanisms influencing selective use rather than full adoption. By grounding provider perspectives within a sociotechnical lens, this study extends existing IS theories to the context of AI-enabled clinical decision support and offers empirically grounded insights for designing ICDSS that better align with clinical practice. Full article