Search Results (1,604)

Drawing on research on self-regulated learning, metacognition, and cognitive aspects of writing, this study examines whether structured free writing can function as a scaffold for developing writing self-regulation, affective engagement, and genre-based performance. While free writing has traditionally been conceptualized as a creativity-enhancing or pre-writing activity, its role in fostering self-regulatory and metacognitive processes associated with intelligent performance remains underexplored. A convergent parallel mixed-methods design was employed with preservice teachers enrolled in a seven-week writing workshop in higher education. Quantitative data included validated measures of writing self-regulatory efficacy and attitudes toward free writing, along with analytic assessments of informative and narrative writing performance. Qualitative data were obtained through semi-structured interviews examining participants’ regulation of their writing processes. Findings indicate significant improvements in self-regulatory efficacy, more adaptive attitudes toward writing, and gains in genre-specific performance. Qualitative results further suggest that structured free writing supports metacognitive awareness, reduces writing-related anxiety, and enhances sustained cognitive engagement. By conceptualizing free writing as a mechanism for developing self-regulatory capacities underlying intelligent behavior, this study contributes to research on individual differences in learning and highlights the integration of cognitive and affective processes in academic performance. Full article

This paper presents the Master’s Dissertation Marking Framework (MDMF), a longitudinally developed framework designed to support fairer and more transparent master’s dissertation assessment. The framework was developed through a multi-phase, design-based research framework, comprising a literature review, a survey and in-depth interviews (2022) conducted prior to the emergence of generative AI, and follow-up empirical phases between 2023 and 2025. Across these phases, the framework evolves from an initial focus on procedural consistency and bias mitigation to a broader sociotechnical perspective that incorporates ethical boundaries, professional judgement, institutional responsibility, and the disruptive effects of generative AI on assessment practice. The paper traces the progression of the framework to MDMF Version 5, the final iteration, which consolidates six interdependent components: ethical boundaries and AI policy clarity; fairness and equity issues; pre-marking tasks and calibration; marker allocation; marking processes, culture, and well-being; and technology as both enabler and disruptor. Drawing on empirical evidence from academic staff involved in MSc dissertation marking in the post-generative-AI context, the framework brings together these components to address both longstanding and emerging challenges in assessment. The findings demonstrate that fairness in dissertation marking cannot be achieved through procedural mechanisms or technological solutions alone. Instead, the MDMF supports fairer assessment by structuring human judgement, enabling calibration, and clarifying ethical boundaries in AI-mediated contexts. The framework offers a coherent yet adaptable model for institutions seeking to maintain valid and defensible assessment practices in the age of generative AI. Full article

This article analyses the transformation of the competitiveness of the European Union in the context of geopolitical fragmentation, geo-economic rivalry and the growing importance of economic security in contemporary economic governance. The article argues that the traditional efficiency-oriented understanding of competitiveness, associated primarily with productivity growth, market efficiency and trade openness, is increasingly complemented by a resilience-oriented governance framework that emphasizes strategic autonomy, technological capabilities, economic security and long-term adaptive resilience. Using a conceptually oriented qualitative research design based on interpretive analysis and analytically focused comparison, we integrate knowledge from studies of competitiveness, political economy, geo-economics and European economic governance. The research draws on academic literature primarily available in the Web of Science and Scopus databases, EU strategic documents and legislation, and selected aggregated indicators related to productivity, innovation, trade openness, technological development and sustainability. The findings show that geopolitical fragmentation, supply chain vulnerabilities, technological competition and strategic dependencies are increasingly changing the structural foundations of European competitiveness. Innovation and technological capabilities remain key determinants of long-term competitiveness, but their strategic importance is increasingly linked to resilience, technological sovereignty and economic security. The results also show that the European Union is gradually moving towards a hybrid governance model that combines market openness with strategic coordination, industrial policy and resilience-oriented adaptation. At the same time, significant asymmetries between Member States continue to limit the EU’s ability to adapt in a coordinated manner. The article contributes to current debates on competitiveness by establishing an integrated analytical framework linking competitiveness, resilience, economic security, strategic autonomy and sustainable development in the context of geo-economic transformation. Full article

Drawing on mindset theory, self-regulated learning theory, learner autonomy, and adaptive intelligence theory, this study tested an integrated structural model of the associations between academic growth mindset and self-perceived adaptive intelligence among Jordanian undergraduates. In this study, self-perceived adaptive intelligence refers to students’ perceived wisdom-related, social/practical, creative, and uncertainty-navigation tendencies; it is not an objective or performance-based measure of cognitive ability. The hypothesized sequential mediation structure was retained, but it was estimated and interpreted as a set of theoretically ordered indirect associations through learning motivation, metacognitive awareness, self-regulated learning strategies, and academic adaptation. Learner autonomy was examined as a moderator of the association between self-regulated learning strategies and academic adaptation. Data were obtained from 640 undergraduate students enrolled in Jordanian universities and analyzed using partial least squares structural equation modeling with WarpPLS 8.0. Academic growth mindset was positively associated with learning motivation and metacognitive awareness. Both constructs were positively associated with self-regulated learning strategies, which, in turn, were positively associated with academic adaptation; academic adaptation, in turn, was positively associated with self-perceived adaptive intelligence. The theoretically ordered sequential indirect associations through the motivational and metacognitive routes were statistically significant, whereas learner autonomy did not significantly moderate the association between self-regulated learning strategies and academic adaptation. Because the data were single-wave and self-reported, the term “sequential” refers to the theory-imposed ordering of paths in the statistical model, not to an observed temporal or developmental progression. Accordingly, the findings represent structural associations and do not establish causal sequencing. The findings contribute to intelligence and higher-education research by distinguishing domain-specific academic adaptation from broader self-perceived adaptive intelligence informed by Sternberg’s adaptive intelligence framework. Full article

Higher education institutions (HEIs) generate substantial volumes of academic data, yet the visualization infrastructure required to transform this data into decision-relevant representations remains underdeveloped in most Latin American university contexts. This study addresses that gap through the design, development, and expert validation of the Institutional Data Visualization Model (IDVM) for academic management at Universidad Tecnológica Israel (UISRAEL). A mixed-methods design was employed, combining a quantitative survey instrument (N = 216) administered to faculty, students, and administrative staff with structured interviews with five institutional authorities analyzed thematically. Diagnostic findings revealed that perceived adequacy of data visualization practices ranged from moderate to adequate, with the lowest scores concentrated in accessibility and data provenance, and qualitative evidence confirming a pattern of data richness coexisting with representational poverty. The IDVM was developed through a four-phase iterative process aligned with design-based research methodology, operationalizing a three-level hierarchical visualization structure, six academic data domains aligned with national accreditation criteria, and an explicit data governance framework. Expert validation through a three-round Delphi process (n = 5 experts) produced a final Kendall concordance coefficient of W = 0.924 (p < 0.001). The IDVM provides a theoretically grounded, empirically derived, and locally adapted framework for improving academic data governance in Ecuadorian and Latin American higher education. Full article

An increase in penetration of photovoltaic (PV) systems in a distribution system causes voltage regulation issues that create serious problems for the On-Load Tap Changer (OLTC) of the power transformer, leading to higher tap-changing frequency and reduced transformer life. Traditional voltage control methods are ineffective when PV penetration exceeds load demand, and more sophisticated control methods are needed. This paper combines a systematic literature review conducted in accordance with the PRISMA 2020 guidelines with a case study on operational issues of OLTC transformers under both normal and non-normal operating conditions. It entails a detailed examination of the effect of PV integration on the operating characteristics of OLTC in a systematic approach and also dwells upon coordination processes between OLTC and Flexible AC Transmission Systems (FACTS) devices, such as Distribution Static Synchronous Compensator (D-STATCOM) or Static VAR Compensator (SVC), which are highly effective in reducing tap operations. The future directions covered in the review include the operation of hybrid systems, cost-effective implementations, weather effects, predictive analytics, adaptive control techniques, etc. The case study included online monitoring of OLTC performance in two scenarios at the cement factory. First, under supply changes and load changes. Second, including PV penetration. The results show that OLTC increases the average daily tapping frequency (90 taps/day) by about 60%, with full PV penetration. It is concluded that this can’t be applied without coordinated control among OLTC, D-STATCOM, and PV inverters to maintain transformer life, improve reliability, and provide stable voltage profiles even under highly variable PV generation conditions. These results aim to provide a comprehensive resource for academics and practitioners, facilitating the advancement of advanced voltage control methods to support the transition to sustainable energy systems. Full article

Student mental health, stress, and success are interconnected, yet the mechanisms linking them remain insufficiently understood. Drawing on Stress Optimization and Self-Regulated Learning (SRL) theories, this study examined how stress appraisals and learning practices jointly contribute to student mental health and academic functioning in post-secondary students, supporting a view of student success that comprises both feeling well psychosocially and functioning well academically. Using a sample of 226 university students, the study replicated prior work on the predictive roles of coping self-efficacy (CSE) and stress mindset (SM) across indicators of student success, including flourishing mental health, motivation-related challenges, social-emotional challenges, and GPA. It extended this work by testing whether metacognitive monitoring and adaptation, and academic social engagement, mediated these relationships. Results showed that neither CSE nor SM significantly predicted GPA, suggesting that stress appraisals alone may be insufficient to explain academic achievement. However, both CSE and SM significantly predicted flourishing mental health, and CSE was additionally associated with fewer motivation-related and social-emotional challenges. Mediation analyses indicated that metacognitive monitoring partially explained the relationship between CSE and reduced motivation challenges, while academic social engagement mediated relationships between stress appraisals and social-emotional challenges and mental health. Findings underscore the value of integrating psychosocial and educational perspectives in promoting student success. Full article

Robo-advisors have expanded access to automated investment services, but many platforms continue to rely on relatively static onboarding procedures and limited forms of user interaction. This study examines how participants with investment experience respond to two next-generation robo-advisory design features: financial digital twins, understood as dynamic investor profiles that integrate goals, risk tolerance, cash-flow patterns, and anticipated life events, and conversational artificial intelligence (AI), understood as an interactive interface for explaining recommendations. Using a scenario-based randomized 2 × 2 online experiment, 336 adult respondents with self-reported investment experience, recruited through professional and academic networks, were assigned to one of four robo-advisor scenarios that varied the personalization architecture, standard profile versus digital twin, and the interface style, plain dashboard versus conversational AI, while holding the portfolio recommendation constant. The results show that digital-twin personalization increases perceived personalization and privacy concern, indicating that more adaptive advisory architectures may be viewed as both more relevant and more data-intensive. Conversational AI increases the perceived interactive quality of the advisory experience, while selected willingness-related patterns, especially in the combined digital-twin and conversational-AI condition, are treated as exploratory because several secondary composites displayed limited internal consistency. The strongest confirmatory emphasis is therefore placed on perceived personalization and privacy concern, and the remaining findings are best interpreted as scenario-based investor responses rather than evidence of actual adoption behavior or confirmed psychological mechanisms. The study contributes to behavioral FinTech research by clarifying the personalization–privacy tension in AI-enabled robo-advisory services and by offering design implications for more transparent, interactive, and responsibly personalized digital wealth-management systems. Full article

Digital transformation and artificial intelligence are reshaping nursing education by changing how students access information, complete academic tasks, and engage with technology-mediated learning. However, evidence on digital competencies, AI-related constructs, mediating mechanisms, and academic performance remains fragmented and methodologically uneven. This systematic review of empirical studies synthesized how digital competencies and AI-related constructs are associated with academic performance and learning-related outcomes in nursing education. Following PRISMA 2020 guidelines adapted to social science research, searches were conducted in Scopus and Web of Science Core Collection in March 2026, covering 2022–2026. Twenty-five empirical studies were included: 18 quantitative, 4 qualitative, and 3 mixed-methods studies. The evidence was concentrated in the Middle East and North Africa, Asia, and Europe. Findings suggest that digital competencies are associated with academic and learning-related outcomes mainly through self-efficacy, academic motivation, cognitive presence, and learning flow. AI-related evidence remains emerging, mixed, and context-dependent. Although some AI-assisted interventions reported favorable outcomes, one experimental study found greater knowledge gains with traditional text-based study than with ChatGPT-assisted learning. Therefore, AI integration should not be considered universally beneficial, but contingent on pedagogical design, task type, teacher guidance, AI literacy, responsible use, and critical verification. Full article

Background: The increasing prevalence of diabetes mellitus and metabolic risk factors among young adults has become a major public health concern. University students are particularly vulnerable to unhealthy lifestyle changes, including sedentary behavior, insufficient physical activity, and academic stress, all of which may be associated with an elevated risk of metabolic disorders. Objective: This study aimed to examine the associations of academic stress, physical activity, and sedentary behavior with diabetes risk among university students. Methods: A cross-sectional analytical study was conducted among 264 university students recruited through an online survey. Academic stress was assessed using a six-item Likert-scale instrument, while diabetes risk was evaluated using a composite score derived from indicators adapted from the modified Finnish Diabetes Risk Score (modified FINDRISC). Statistical analyses included descriptive statistics, Cronbach’s alpha reliability testing, exploratory factor analysis (EFA), Spearman’s correlation analysis, and multivariable logistic regression. Results: The academic stress instrument demonstrated good internal consistency (Cronbach’s alpha = 0.85). Exploratory factor analysis supported the construct validity of the instrument, with all six items loading substantially on a common academic stress factor. Correlation analysis revealed that academic stress was positively associated with sedentary behavior and diabetes risk, whereas physical activity was negatively associated with diabetes risk. Multivariable logistic regression showed that academic stress was significantly associated with an increased risk of diabetes (adjusted odds ratio [aOR] = 1.18, 95% confidence interval [CI]: 1.02–1.36; p = 0.028). Moderate-to-vigorous physical activity was associated with a lower risk of diabetes (aOR = 0.74, 95% CI: 0.60–0.92; p = 0.011), while longer sitting duration was associated with an increased risk of diabetes. Conclusions: Academic stress, sedentary behavior, and physical activity were significantly associated with diabetes risk among university students. These findings highlight the importance of developing university-based health promotion programs that integrate stress management, physical activity promotion, and sedentary behavior reduction to support the prevention of metabolic risk factors in young adults. Full article

The proliferation of generative artificial intelligence (GenAI) has precipitated an urgent, global reassessment of how higher education evaluates critical thinking, creative agency, and academic integrity. However, scholarly and institutional responses remain fragmented across cultural contexts, impeding the development of robust, flexible, and discipline-adaptable assessment frameworks. Responding to the imperative to move beyond the traditional standardized assessment paradigm, this study conducts a comparative discourse analysis of 5368 academic articles in Anglophone/Western scholarly discourse (Web of Science, WoS) and Chinese (CNKI). Using LDA topic modeling and Word2Vec-enhanced semantic analysis, the study identifies two divergent orientations: an Anglophone/Western discourse that frames AI as an instrument for cognitive augmentation, efficiency optimization, and functional human–AI collaboration; and a Chinese discourse that emphasizes epistemic sovereignty, the reconstruction of creative subjectivity, and systemic institutional rebuilding against technological alienation. These pathways are mapped onto a tripartite framework of Tools, Creative Subjectivity, and Organizational Ecosystems. The findings demonstrate that AI integration is culturally embedded rather than technically determined, carrying profound implications for assessment validity, academic integrity policy, and equitable access to AI-enhanced learning. The study synthesizes these insights into a culturally responsive assessment framework that redirects evaluation from standardized, product-centric outputs toward process-oriented, transparent, and ethically governed human–AI co-authorship. By centering critical autonomy, AI literacy, and epistemological diversity, this framework offers actionable strategies for inclusive assessment redesign, institutional policy development, and sustainable competency cultivation in the GenAI era. Full article

This study examines how future mathematics teachers perceive the importance of AI-related and digital competencies and their self-reported performance in these areas. The study was conducted in a Mathematics Education course in Spain with 198 Primary Education students. Using an Importance–Performance Map Analysis (IPMA) framework, the questionnaire assessed six dimensions: AI awareness, AI usage, AI evaluation, AI ethics, AI trust, and digital skills, with items adapted from previous studies. The results showed that students assigned higher importance to all competencies than the level of performance they reported. AI evaluation, AI trust, and digital skills received the highest importance scores, whereas AI awareness obtained the lowest scores. The IPMA identified AI usage as the main priority for improvement, as students considered it relevant but reported comparatively lower performance. Differences by academic year and self-reported AI knowledge level suggest that students’ stage of training and perceived AI knowledge influenced their perceptions. These findings reveal a gap between the importance future teachers assign to AI-related competencies and their perceived level of development. The study highlights the need for more specific and pedagogically grounded AI training in Mathematics Education and offers practical implications for teacher education curricula in response to the demands of 21st-century classrooms. Full article

High school is often an academically demanding environment that exposes adolescents to elevated emotional challenges. Yet the development of academic emotions across the full high school period, as well as the potential protective role of adaptive coping strategies such as shift-and-persist, remains insufficiently understood. To address this gap, the present study tracked 608 students (305 males; M_age = 15.56, SD = 0.58) from a public senior high school in Chongqing, China, over three consecutive years. Latent growth modeling showed that negative academic emotions increased steadily, whereas positive emotions remained relatively stable. Cross-lagged panel analyses further revealed that greater use of shift-and-persist strategies—a coping approach integrating cognitive reappraisal with optimistic persistence—was prospectively associated with more favorable emotional outcomes, reflected in higher positive and lower negative emotions. In contrast, academic emotions did not predict later use of S-P. These findings point to the cumulative emotional challenges adolescents face in competitive academic settings and highlight S-P as a stable psychological resource. The study extends the control-value framework by identifying a cognitive-affective pathway associated with emotional well-being and emphasizes the potential value of promoting S-P-related coping skills within educational settings. Full article

The rapid expansion of generative AI (GenAI) in higher education offers transformative opportunities but raises complex ethical concerns that demand rigorous examination. The existing literature is dominated by Global North perspectives, with African contexts accounting for only 11.4% of studies and Ghana for only 2.8%, leaving significant gaps in understanding ethical GenAI integration in post-colonial, multilingual and resource-constrained environments. This review synthesises global and African evidence to examine the ethical considerations, stakeholder responses, institutional frameworks, and future research priorities for the responsible use of GenAI in higher education. Guided by the PRISMA framework, this review analysed 246 studies published between 2018 and 2025, using narrative synthesis, thematic analysis, and framework synthesis to integrate the empirical and theoretical contributions. Five ethical domains consistently emerged: academic integrity, privacy and data security, transparency and accountability, equity and access, and AI literacy. These concerns manifest differently across contexts, with African institutions highlighting issues such as Ubuntu-informed ethics, infrastructural constraints, digital sovereignty and epistemic justice. Institutional responses remain uneven, and Ghanaian institutions show limited systematic governance. This review highlights the need for contextualised ethical frameworks, curriculum redesign, authentic assessments, capacity building and adaptive governance to ensure equitable and responsible GenAI integration, particularly in African higher education. Full article

The development of digital learning technologies has introduced innovative tools to enhance science and chemistry education, including PhET simulations. This study aims to evaluate the effectiveness of PhET simulations on students’ learning outcomes through a systematic literature review following the PRISMA 2020 guidelines. A systematic search of Scopus and Crossref databases was conducted (last search: January 2026) using predefined keywords. Eligible studies were empirical research published between 2020 and 2026 that investigated PhET simulations in science-related education and reported learning outcomes, while non-empirical studies and non-Scopus-indexed articles were excluded. Risk of bias was assessed using an adapted Joanna Briggs Institute critical appraisal tool. Due to heterogeneity in study designs and outcome measures, the results were synthesized using a narrative approach. A total of 14 studies across elementary to higher education levels were included. The findings indicate that PhET simulations consistently improve learning outcomes, particularly academic achievement and conceptual understanding, with effects generally favoring simulation-based instruction over traditional methods. However, higher-order skills and affective outcomes such as motivation and attitude remain less frequently investigated. The evidence is limited by variability in study designs, incomplete reporting of non-cognitive outcomes, and the absence of quantitative synthesis. Overall, PhET simulations demonstrate strong potential as an effective interactive learning medium, although their impact depends on instructional design, teacher facilitation, and technological accessibility. Full article