Search Results (1,772)

Generative artificial intelligence (AI) is increasingly used in higher education as an interactive tutoring partner rather than a passive information tool. While AI offers opportunities to support learning, concerns remain regarding cognitive offloading, reduced engagement, and unreflective use. Although instructional scaffolding is a well-established design principle for supporting complex learning, its role in shaping cognitive and metacognitive processes in AI-supported settings remains underexplored. This quasi-experimental pre–post study examined how varying levels of scaffolding influence learning outcomes and motivational, cognitive and metacognitive processes during AI-tutored learning. A total of 175 first-semester students from two faculties and diverse academic backgrounds completed the same academic task within a four-hour university session under one of three conditions: (1) full scaffolding, including a structured prompting template based on the Goal–Context–Constraints (GCC) strategy, iterative refinement, and reflective guidance; (2) light scaffolding, including the GCC prompting template; or (3) no scaffolding template as the control condition. Measures included knowledge gain, motivation, cognitive load, critical thinking, and reflective use. Data were analysed using ANOVAs, ANCOVAs, regression models, and PROCESS moderation and mediation analyses. Across the conditions, students showed significant gains in knowledge, critical thinking, and reflective use, while motivation remained stable and intrinsic and extraneous cognitive load decreased; no significant differences between scaffolding conditions were observed. The scaffolding conditions did not produce significant interaction effects, although descriptive trends suggested higher gains in higher-order knowledge under scaffolded conditions. Overall, the findings suggest that short-term learning gains in AI-supported settings may not depend on scaffolding intensity alone, but rather on how learners engage with AI during the learning process. Full article

Disinformation, amplified by digital platforms and algorithmic distribution systems, represents a growing challenge for media trust, public health communication, and societal stability. This narrative literature review examines disinformation through an integrative psychosocial perspective, focusing on how patterns of exposure interact with individual vulnerability factors—including education, political beliefs, social identity, personality traits, and emotional responses to uncertainty—to influence the processing and acceptance of misleading information. The review synthesises interdisciplinary evidence on how algorithmic amplification and emotionally salient content increase susceptibility to disinformation and shape risk perception, health-related decision-making, and preventive behaviours. Findings indicate that repeated exposure to false or misleading information reinforces perceived credibility through familiarity effects, contributes to declining trust in institutional sources, and intensifies social and political polarisation. Disinformation is therefore conceptualised not only as an informational problem but also as a psychosocial process affecting emotional regulation, cognitive evaluation, and collective responses to crises, particularly in public health contexts. The analysis further highlights a recursive feedback loop in which reduced media trust increases vulnerability to subsequent disinformation, with broader implications for democratic participation and social cohesion. Mitigation strategies discussed include media literacy initiatives, critical thinking education, platform governance, regulatory approaches, and interventions targeting psychosocial drivers of susceptibility. Full article

Integrating artificial intelligence (AI) into design education is no longer optional; it has become an essential tool for enhancing innovative design and preparing students for data-driven practice and rapid technological acceleration. However, ignoring AI risks professional irrelevance; it introduces a range of concerns about students’ cognitive skills and comes with many drawbacks in the education process, as it threatens the attainment of learning outcomes, renders a fair assessment process unachievable, and places academic integrity in a vulnerable position. Using a qualitative case study approach, this research employs semi-structured interviews with 27 senior-year students in the interior design department to gain in-depth academic insights into how AI influenced their design process in their term project and its impact on their cognitive development and decision -making. Instructors’ observations on students’ skills, their pace in the project, and their end-products were documented. This study demonstrates that integrating AI into design education cannot be avoided, making a new paradigm for addressing design education inevitable. Based on the analysis, the paper proposes a conceptual framework outlining key dimensions in teaching and assessing strategies in design education adopting AI, focusing on analysis, critical thinking, reasoning, and process rather than on the end-product and its presentation. Full article

This study examines the effects of a three-month pedagogical intervention that integrated artificial intelligence (AI), social media, and web-based tools to strengthen digital literacy, creativity, and cultural participation among secondary education students in Ecuador. The intervention was theoretically grounded in perspectives of inclusive digital education and Universal Design for Learning (UDL), emphasizing participation, accessibility, and collaborative knowledge construction. The intervention involved 61 students supported by 31 university facilitators and was developed under a mixed-methods action research design with a pre–post (quasi-experimental) approach. Pre- and post-test surveys were administered to assess changes in digital competencies and creativity, while semi-structured interviews explored students’ perceptions of creative expression and their engagement with the cultural and technological ecosystem. Quantitative results showed statistically significant improvements in digital literacy and creativity (p < 0.001), while qualitative findings evidenced increased student empowerment, critical awareness of algorithms, and active cultural participation. The integration of AI and social media promoted an inclusive, student-centered learning environment that enhanced autonomy, reflective thinking, and media engagement. These results suggest that hybrid and culturally contextualized AI-mediated interventions may foster 21st-century competencies, strengthen digital equity, and promote creative agency in educational contexts of the Global South, particularly within emerging digital learning environments in Ecuador. Full article

This study falls within the field of lifelong education and investigates the role of aesthetic-sensory experiences—particularly those mediated by digital visual arts—in the development of critical thinking, a key competence identified in the European LifeComp Framework. In light of contemporary social transformations characterised by complexity, uncertainty, and change, critical thinking emerges as a transversal skill of fundamental importance for the education of conscious and autonomous citizens. The objective of this research is to analyse how digital sensory experiences, integrated with innovative teaching methodologies—such as laboratory-based teaching and collaborative learning—can foster the activation and enhancement of critical thinking in educational contexts. The work is based on a narrative analysis of the literature, conducted through the consultation of academic databases (e.g., Scopus, ERIC, and Google Scholar), and is developed within a theoretical framework encompassing digital education, laboratory didactics, and collaborative learning strategies. Studies published in recent years were selected according to their relevance to digital aesthetic experiences and critical thinking in educational contexts and were analysed through a thematic synthesis of the main conceptual contributions. The knowledge activities include the selection, categorisation, and discussion of recent studies that relate aesthetic experiences to the development of soft skills, in line with the principles of visual education understood as aesthetic and critical literacy in visual languages. The results of the review indicate that the intentional use of aesthetic digital environments, in combination with active and reflective teaching approaches, can stimulate complex cognitive processes and significantly contribute to the formation of critical thinking. The contribution implements an interdisciplinary approach among visual education, digital education, and experiential aesthetics, emphasising the need for further empirical research to consolidate the evidence and guide the implementation of innovative educational practices based on this approach. Full article

Educational escape rooms have been widely used in education in recent years. On the other hand, capture the flag (CTF) competitions have been spreading from the cybersecurity area into other domains. In this paper, a fusion of both concepts is proposed in the form of a CTF-like escape room in order to carry out the assessment of a STEM course. Each puzzle within the escape room consisted of designing a short code snippet as part of a protocol engineering course, with up to three hidden hints available. Each hint incurred a 25% penalty, deducted from the score awarded for solving the puzzle, as is common in CTF environments. This approach can be applied to small problem-solving tasks across many disciplines and educational contexts. Data collection consisted of gathering the marks of all students enrolled in the courses on an anonymized basis, after they had provided informed consent, and data analysis was then performed using descriptive and inferential statistics. The results suggest a statistically significant increase in average academic performance compared to the previous academic year, during which assessment was conducted through written exams. In addition, engagement was measured using the ISA Engagement Scale, showing a high level of student involvement. Nevertheless, further research with a larger sample of students is needed in order to confirm these findings. In summary, a novel approach to STEM assessment is presented, as the solution of each puzzle requires not only recall but also critical thinking, technical proficiency, and application. Full article

Computational thinking (CT) has become a cross-curriculum priority in many educational jurisdictions, yet a growing body of research reports uneven integration in initial teacher education (ITE), limited preservice teacher confidence, and persistent misconceptions that equate CT with coding. Concurrently, generative artificial intelligence (GenAI) has rapidly entered university programmes, offering new possibilities for modelling problem-solving, generating multiple representations, and supporting iterative design. However, while constructs such as self-efficacy, cognitive load, and affect are well established in educational psychology, their specific application to the intersection of CT and GenAI in teacher education remains under-theorised: existing research has not systematically examined how these psychological dimensions interact when preservice teachers learn CT through GenAI-mediated tasks. This thematic literature review synthesises 54 sources across three intersecting domains: CT frameworks and their pedagogical implications, CT integration in preservice teacher preparation, and GenAI in teacher education and learning design. Drawing on Bandura’s social cognitive theory, cognitive load theory, and research on technology-related affect, the review foregrounds the affective, cognitive, and cultural dimensions of preservice teachers’ engagement with CT and GenAI. The review proposes the GenAI-Enabled Computational Thinking for Preservice Teachers (GECT-P) model, which integrates CT dimensions with GenAI-supported learning cycles, psychological mediators, and teacher education outcomes. The model positions prompting as an epistemic and pedagogical practice that can make CT visible, supports cycles of decomposition, abstraction, pattern recognition, and algorithmic design, and embeds critical AI literacy, ethics, affective scaffolding, and classroom enactment. Design principles and practical pathways are offered for teacher educators seeking to prepare graduates who can develop CT with and beyond GenAI across diverse curriculum areas. Full article

Generative Artificial Intelligence (GenAI) is transforming higher education in terms of pedagogy, student involvement, and academic management. This systematic literature review examines 30 peer-reviewed articles published from 2019 to 2025, adhering to PRISMA 2020 and Kitchenham’s methodologies. Descriptive and thematic analyses highlight five opportunities: (a) tailored and adaptive education; (b) deliberate fostering of critical thinking; (c) enhanced accessibility for varied learners; (d) teaching innovation via multimodal content development and feedback; and (e) collaborative methods that regard AI as a co-teacher. Four ongoing challenge categories also surface: (a) risks to academic integrity; (b) excessive dependence on GenAI that may hinder learner independence; (c) inconsistent faculty preparedness and change-management abilities; and (d) differences in infrastructure and policy both regionally and globally. Intersecting ethical issues, such as data privacy, algorithmic bias, transparency, and accountability, highlight the necessity for governance that aligns with institutional risk and reflects societal values. Analyzing the recent literature, this systematic review offers four contributions: (a) a recommendation model for responsible GenAI implementation in higher education institutions; (b) a framework for sustainable integration of GenAI; (c) a highlight of the future research recommendations; and (d) an integrated policy and pedagogical recommendations roadmap. These models emphasize the integration of AI literacy, ethical considerations, and critical thinking goals into educational programs. The review advocates for a strategic, stakeholder-focused approach to implementation that enhances rather than replaces human instruction, thus connecting GenAI’s educational potential with ethical, context-aware avenues for institutional transformation. Full article

Background: Nursing education faces challenges in developing critical thinking and digital literacy among Generation Z students, particularly in maternal–newborn care contexts where evidence-based practice is essential. Objectives: To evaluate the effectiveness of an AI-assisted podcasting intervention on critical thinking and digital literacy among nursing students and explore their experiences. Methods: A convergent mixed-methods design included 48 third-year nursing students who created educational podcasts using AI tools (Sci Space for literature search, Notebook LM for synthesis). Quantitative data were analyzed using paired t-tests; qualitative data from three focus groups (n = 15) underwent thematic analysis. Results: Critical thinking scores increased significantly from 89.71 (SD = 13.43) to 117.29 (SD = 9.94), (t = −13.332, p < 0.001). Digital literacy scores improved from 37.98 (SD = 5.84) to 46.94 (SD = 4.11), (t = −9.407, p < 0.001). Four themes emerged: transformation from anxiety to empowerment, AI as scaffold, distinct tool utility, and future clinical application. Conclusions: These findings suggest that AI-assisted podcasting has the potential to significantly enhance critical thinking and digital literacy among nursing students; however, results should be interpreted with caution given the pre–post design, single-institution sample, and use of researcher-developed instruments. Full article

In social science degree programs, where Statistics is not a core subject, students often experience anxiety and negative attitudes that influence their engagement and may hinder academic performance. This study examines the role of positive emotions in the teaching of Probability Calculus and Inferential Statistics in Business Administration and Management studies, analyzing their relationship with students’ engagement in Problem-Based Learning (PBL). The research is framed as an exploratory single-campus case study conducted with a modestly sized sample of undergraduate students from a single Faculty. Moving beyond traditional approaches that view emotions merely as outcomes of learning, our model assumes that positive emotions, both prior to and following the PBL experience, shape students’ perceptions of its usefulness, their collaborative behaviors, and their communication with instructors. Using Structural Equation Modeling (SEM) and Cluster Analysis, the findings show that positive emotions are a key driver of students’ predisposition toward and engagement with PBL, indicating that cultivating a supportive emotional climate enhances participation and deepens the understanding of statistical concepts. These results suggest that fostering emotional engagement is essential not only for improving motivation and academic outcomes in Statistics but also for developing transversal and sustainability-related competencies such as critical thinking, collaboration, communication, and evidence-based decision-making. The study contributes to current discussions on sustainable and inclusive teaching practices by highlighting the importance of integrating socio-emotional dimensions into active learning methodologies in higher education. Full article

Managers of protected areas (PAs) face growing challenges to conserve biodiversity while responding to multiple land uses such as recreation, tourism, and resource extraction. These pressures are intensified by the impacts of climate change on ecosystems. This highlights the need for planning approaches that support decision-making in the short, medium, and long term. This article profiles Wells Gray Provincial Park as a case study to demonstrate how an ecosystem-based planning approach can be incorporated into PAs planning. Wells Gray is situated in a unique ecosystem in the interior of British Columbia (Canada). We present an innovative model that integrates land cover types, ecosystem mapping, and Biogeoclimatic (BGC) zones derived from the Biogeoclimatic Ecosystem Classification (BEC) system using GIS tools to identify ecosystems and their associated services as Critical Decision Factors (CDFs). By explicitly linking ecosystems, land cover, and spatial patterns, this approach supports the systemic inclusion of ecosystems in management decisions. To account for future uncertainty, BGC zones were projected under climate change scenarios to inform interpretations of potential ecosystem impacts. The results indicate that this integrated analysis can initiate strategic thinking and facilitate dialogue to collaboratively plan with stakeholders. This approach can improve ecosystem-based planning processes in PAs across Canada. Full article

This mixed-methods study explores the views and experiences of 55 English-language teacher candidates in Chile who designed gamified project-based lessons aimed at fostering inclusive learning and social justice in culturally diverse classrooms. Data were collected through lesson plans, semi-structured interviews, and a Likert-scale survey, and were analysed using inductive content analysis and descriptive statistics. The findings reveal that participants valued gamification for enhancing student engagement, collaboration, and critical thinking, and they perceived gains in their ability to integrate social justice themes into language teaching. However, discrepancies emerged when participants had to plan lessons that had a social justice orientation because they perceived they did not have enough competence to approach equity-oriented themes. This study adopts a justice lens that foregrounds power, agency, and digital equity in teacher candidates’ lesson-planning skills to examine how they can redistribute voice, recognise situated knowledges, and expand their capacity to act within and against structural constraints. The study underscores the need for teacher education programmes to move beyond technical and motivational uses of gamification and digital tools. From their lesson plans, teacher candidates were not simply adopting digital tools at a technical level but seem to be designing an integrated pedagogical ecosystem that aligned gamification and project-based learning. However, it is inconclusive whether they are able to design gamified PBL environments that do not reproduce existing social and educational inequalities and ensure that access and participation are carefully scaffolded. Full article

The world evolves continuously across space and time. Massive volumes of data are generated through sensing, simulation, remote observation, and human activities, capturing dynamic processes in environmental, social, economic, and engineered systems. Critical insights are embedded within these large-scale spatiotemporal datasets. Spatiotemporal Data Science provides a conceptual and methodological framework for analyzing such data by integrating spatiotemporal thinking, computational infrastructure, artificial intelligence, and domain knowledge. The field advances methods for data acquisition, harmonization, modeling, visualization, and decision support, enabling applications in natural disaster response, public health, climate adaptation, infrastructure resilience, and geopolitical analysis. By leveraging emerging technologies—including generative Artificial Intelligence (AI), large-scale cloud platforms, Graphics Processing Unit (GPU) acceleration, and digital twin systems—Spatiotemporal Data Science enables scalable, interoperable, and solution-oriented research and innovation. It represents a critical frontier for scientific discovery, engineering advancement, technological innovation, education, and societal benefit. Spatiotemporal Data Science is a transdisciplinary field that studies and models dynamic phenomena across space and time by integrating spatial theory, temporal reasoning, artificial intelligence, and scalable computational infrastructure. It enables the development of adaptive, predictive, and increasingly autonomous systems for understanding and managing complex real-world processes. Full article

Background: Childhood vaccination remains the cornerstone of public health strategies, substantially reducing global morbidity and mortality, yet suboptimal uptake persists in many settings. In South Africa, the challenge is evident, with persistent outbreaks of vaccine-preventable diseases. Addressing localised immunisation shortfalls requires elucidating the complex interplay of factors beyond conventional access barriers. This qualitative study provides context-specific insights into the behavioural and social drivers influencing childhood vaccination uptake among caregivers in Cape Town, South Africa. Methods: Utilising an exploratory qualitative research design, thematic analysis was applied to interview data (n = 25 caregivers) collected via a purposive sampling strategy designed to capture maximum variation in experiences within targeted low-uptake subdistricts. Interpretation of the data was systematically guided by the World Health Organization’s Behavioural and Social Drivers (BeSD) framework. The latter consists of four domains, namely, “Thinking and Feeling”, “Social Processes”, “Motivation”, and “Practical Factors”. Findings: Analysis across BeSD domains reflected a pattern of the intention–behaviour gap, where caregivers are motivated for vaccination but face structural and practical barriers affecting timely uptake. In the Thinking and Feeling domain, widespread conviction regarding the vital benefits of vaccination co-existed with significant anxiety concerning minor side effects (e.g., pain and fever), which sometimes precipitated missed subsequent appointments. Caregivers frequently accept immunisation as a social routine despite having limited knowledge of the diseases it prevents. Social Processes demonstrated that while decision-making authority rested primarily with mothers, compliance relied on the delegation of logistical responsibilities to extended family members. Critically, reports of poor communication, judgment, or negative attitudes among healthcare workers undermined trust and acted as barriers to sustained engagement. Within the Practical Factors domain, structural constraints frequently overshadowed high intent, with pervasive issues such as long waiting times and financial costs cited as the main reasons for missed appointments. Conclusions: Participants generally expressed strong acceptance of vaccination, but attainment of optimal coverage is constrained by systemic failures in patient–provider communication and persistent logistical barriers within the public healthcare delivery system. Strategic public health interventions must therefore move beyond addressing only attitudinal opposition to prioritise targeted efforts that mitigate structural constraints and reinforce personalised, empathetic communication to sustain caregiver confidence and adherence. Full article

Global urbanization has long been hampered by the “metrocentric priority” paradigm, with small towns—core hubs for urban–rural integration—severely undervalued in practical value. Amid China’s transition to high-quality urban–rural integration, unbalanced small town development has become a critical bottleneck for county-level factor flows, demanding systematic research to unlock their strategic value and resolve urban–rural dual predicaments. Existing studies suffer from scientific gaps including unidirectional linear cognition, insufficient complex system thinking, and weak interpretation of regional heterogeneity, remaining at the stage of static correlation description and failing to reveal the two-way reciprocal feedback logic between small towns and urban–rural integration. Meanwhile, the application of complex system theory in urban–rural research is still confined to theoretical narratives, which hinders the advancement of research from descriptive analysis to mechanism interpretation. Taking Henan Province (a typical agricultural and populous province reflecting China’s urban–rural development) as a case, this study builds a “local emergence–global synergy” framework based on complex system theory, establishes a dual indicator system for small towns’ multidimensional performance and county-level urban–rural integration, and integrates spatial statistical analysis, bidirectional regression and coupling coordination models to explore their cross-scale spatiotemporal evolution and reciprocal feedback during 2019–2023. Findings show the following: (1) The multidimensional performance of small towns presents a pattern characterized by polarized expansion of high-value regions and overall improvement of low-value regions, while county-level urban–rural integration evolves into a polycentric structure featured by central dominance and southern growth. (2) There is a significant two-way asymmetric relationship between small towns’ multidimensional performance and county-level urban–rural integration: the positive effect is significantly stronger than the reverse effect, and both direct impacts are significantly weakened after introducing economic variables, indicating that economic development serves as a key transmission channel. (3) The coupling mechanism presents three evolutionary paths with pronounced core–periphery spatial heterogeneity. Grounded in complex system theory, this study constructs a systemic analytical framework of “local emergence of small-town subsystems and global synergy of county-level systems”, verifies the core proposition of two-way interactions between subsystems and the overall system in the urban–rural complex giant system, and enriches the localized application of complex system theory and the urban–rural continuum theory in traditional agricultural regions of China. This study provides a foundational empirical paradigm for the in-depth exploration of nonlinear characteristics and threshold effects in future research. It offers theoretical support for policy formulation of county-level urban–rural integration in traditional agricultural regions of China, and it provides Chinese experiences for the Global South with similar contexts to explore inclusive urbanization pathways, promoting cross-cultural dialogue and practical transformation of urban–rural integration theory. Full article