Search Results (2,356)

The rapid integration of generative AI in education often frames teachers as technology users who primarily need technical training. Existing prompt engineering frameworks offer technical guidance but have limited grounding in theories of teacher professional development or reflective practice. This misses a key feature of prompt engineering: prompting can externalize pedagogical thinking, making AI interaction a process of knowledge externalization. Through systematic conceptual analysis, this paper proposes a reconceptualization of prompt engineering from a technical competency to a reflective professional practice. The methodology integrates three theoretical traditions: Schön’s reflective practice theory (for externalizing tacit knowledge), Wiggins and McTighe’s backward design (for structuring instructional decisions), and Celik’s AI-TPACK framework (as integrated knowledge base). This synthesis suggests that effective prompting can be understood as an act of pedagogical externalization requiring integrated professional knowledge. The paper develops a seven-strategy framework (RPE framework) as an analytic lens for examining prompt engineering sophistication. This theoretical framework offers theory-derived hypotheses that require future empirical validation rather than presenting verified outcomes. Ultimately, the RPE framework offers a conceptual basis for potentially shifting the focus from technical training to teacher professional development by repositioning educators as AI-assisted instructional designers rather than mere AI users. Full article

This study investigates how South Korean meditation teachers conceptualize core professional competencies in digitally delivered and AI-mediated contemplative contexts, addressing a gap in prior research that has emphasized effectiveness and technological scalability over teachers’ own understandings of authority and professionalism. Using Q methodology, the study identified shared subjective meaning structures among 21 certified meditation teachers in South Korea. From 133 competency-related statements derived from academic literature and practitioner sources, a 33-item Q sample was developed and analyzed through by-person factor analysis. The analysis revealed four distinct perception types of meditation teaching competencies: 1. Embodied Practice-Grounded, prioritizing the depth of personal meditative practice; 2. Relational Presence-Grounded, emphasizing intersubjective attunement between teacher and practitioner; 3. Pedagogical Judgment-Grounded, focusing on the strategic integration of theory and coaching practice; and 4. Ethical Self-Reflection-Grounded, centering on ongoing moral reflexivity and inner examination. The findings indicate that, in the face of AI-driven automation, meditation teaching competence is perceived not as a set of technical skills or digital literacy, but as a “way of being” rooted in the triadic integration of ethical self-awareness, relational presence, and embodied practice. Furthermore, the study suggests that in AI-mediated contemplative environments, professional competence in AI-mediated contemplative environments is defined less by technological adoption than by ethical discernment and responsibility for non-delegable aspects of guidance, advancing a practitioner-centered account of spiritual authority in the era of artificial intelligence. Full article

This article explores the incorporation of linguistic landscape (LL) studies into English for General Academic Purposes (EGAP) courses, emphasizing its potential to enhance language learning through real-world engagement. This study highlights the growing interest in LL as a sociolinguistic phenomenon that reflects urban multilingualism and cultural dynamics. The goal of this article is to analyze pedagogical benefits of integrating LL into language education, such as fostering critical thinking, pragmatic competence, intercultural awareness among students, and creating situations in which the target language is used in natural communication. Through a case study conducted at the Guangdong Technion–Israel Institute of Technology, the author presents specific classroom activities and reports on how they can be combined with fieldwork conducted by students. The goal of the tasks was to let students analyze language use in public spaces, classifying the surrounding signs into top-down and bottom-up, and informative and regulatory, and discuss how social prestige of languages is reflected in multilingual signs. In documenting written language in public places, creating their own signs and assessing their peers’ work, students were practicing both receptive and productive skills. Most of the work was done in small groups, which contributed to the students’ ability to collaborate with peers. The findings suggest that LL projects can effectively bridge classroom learning with lived language experiences, although challenges remain in implementation due to time constraints and pedagogical ideologies. Full article

Background: Endometriosis is associated with infertility and impaired assisted reproductive technology (ART) outcomes, potentially due to an altered follicular microenvironment characterized by chronic inflammation. This study investigates the systemic and local inflammatory profiles in women with endometriosis and assesses their impact on oocyte and embryo quality using both static and dynamic embryo evaluation. Methods: A prospective, monocentric observational study enrolled 47 women undergoing controlled ovarian stimulation for ART, including 29 with laparoscopically confirmed endometriosis and 18 controls with tubal or male-factor infertility. Serum and follicular fluid cytokines (TGF-β1, NF-κB, IL-10, HIF-1α) were quantified. A sub-study analyzed embryo quality and development in 36 patients subdivided into static morphological assessment and dynamic time-lapse monitoring cohorts. Results: Endometriosis patients exhibited significantly elevated pro-inflammatory cytokines (TGF-β1, NF-κB) and reduced anti-inflammatory IL-10 in serum, alongside decreased NF-κB in follicular fluid. These alterations correlated with diminished ovarian reserve, reduced oocyte yield, and lower fertilization rates. Embryos from endometriosis patients showed increased multinucleation and persistent fragmentation, features more sensitively detected via dynamic time-lapse imaging. Clinical pregnancy rates were significantly lower in the endometriosis group. Conclusions: Endometriosis induces a dysregulated inflammatory follicular milieu that adversely affects oocyte competence and embryo morphodynamics. Dynamic embryo assessment provides enhanced detection of subtle developmental abnormalities. Integration of immunomodulatory strategies and advanced embryo monitoring may improve ART success in this population. Full article

The use of Information and Communication Technologies is considered an ideal tool for ensuring attention to diversity in the classroom due to their multiple teaching possibilities, ranging from accessibility and adaptability to heterogeneity of learning profiles. However, to use it properly, teachers need to have a range of skills and abilities, as well as an appropriate attitude. This study aims to understand the training that future teachers receive in the application of technology focused on attention to diversity, as well as to gather their opinions and analyse differences in the data obtained based on certain demographic categories. To this end, a subscale of the DPTIC-AUT-Q questionnaire was administered to 547 students enrolled in the Early Childhood Education and Primary Education degree programmes at the University of Granada. The results obtained show how technologies applied for addressing diversity generate positive opinions among participants and can be very beneficial if used appropriately and with relevant training, although many future teachers claim not to have the necessary skills to do so. This should be considered when reformulating curricula, including content that facilitates the acquisition of the necessary skills and competencies. Full article

Background/Objectives: Integrating technology with caring is essential in modern healthcare, yet the clinical applicability of nursing theories remains underexplored. Locsin’s Technological Competency as Caring in Nursing (TCCN) theory emphasizes the competent use of technology to address patients holistically, rather than focusing solely on health concerns. Here, we explored the interpretive clarity of the TCCN Instrument–Revised for Practice (TCCNI-RePract) items and identified the conceptual barriers encountered by psychiatric nurses when engaging with its theoretical constructs. Methods: This concurrent mixed-methods study surveyed 291 psychiatric nurses across five large hospitals in the Kansai region of Japan. Quantitative data on the TCCNI-RePract perception dimension were examined using descriptive statistics and normality testing. Qualitative open-ended responses were analyzed using reflexive thematic analysis. To ensure rigor and integration, a joint display was utilized to bridge both data strands. Results: Quantitative findings indicated that nurses strongly endorsed core values of caring (high agreement) but perceived theoretical constructs (wholeness and technological knowing) as significantly more difficult to interpret than concrete, behavior-oriented items. Qualitative analysis revealed four major themes: (1) fragmented understanding of “technology and caring,” (2) struggles with abstract and philosophical language, (3) moral and emotional tensions in caring relationships, and (4) contextual barriers to integrating caring and technology. We found a “semantic gap,” where the professional endorsement of caring values was not automatically translated into the mastery of theoretical lexicon. Conclusions: While psychiatric nurses identify with the moral core of TCCN, a substantial gap exists between abstract theory and clinical practice. For effectiveness, middle-range theories require “clinical translation” that resonates with the moral, emotional, and organizational realities of psychiatric settings. Full article

This article adopts a focused comparative perspective on two medical schools to illuminate shared strengths and systemic challenges across educational and regulatory contexts. Undergraduate medical education at the University of New Mexico Health Sciences Center (USA) and the Universidad Miguel Hernández (Spain) is analyzed, highlighting common strengths, including solid biomedical foundations, early clinical exposure, and the growing adoption of competency-based approaches. Despite these assets, both institutions face convergent challenges, including rigid curricula, faculty constraints, and difficulties sustaining student engagement in active learning, exacerbated by rapid digital transformation. The analysis supports recommendations to increase curricular flexibility and personalized instruction, strengthen student-centered and interprofessional learning, optimize educational technology, and reform assessment toward continuous feedback and the demonstration of clinical competence. Full article

With the development of the digital intelligence era, generative AI is being widely used in scientific research, and its impact on graduate students’ research competence has attracted much attention from the academic community. Based on cognitive distribution theory and self-efficacy theory, this study classifies AI applications into three levels from basic to advanced—technical support AI use, text development AI use, and transformation AI use—explores their effects on graduate students’ research competence, and examines the mediating effect of critical thinking and the moderating effect of research self-efficacy. The results of the empirical analysis show that all three types of AI use behaviors are significantly correlated with research competence, with the strongest correlation for text development type and the weakest for technical support type. In the relationship between the three types of AI use behaviors and research competence, critical thinking plays a significant positive mediating role, and research self-efficacy plays a significant moderating role. Universities and tutors should guide students to focus on higher-order AI use behaviors in the text development and transformation categories, promoting the use of critical thinking to avoid technology misuse and improving research self-efficacy to help students accumulate confidence and support their research. Full article

Learning environments are increasingly expected to enable students to develop competencies necessary for addressing complex social, environmental, and technological challenges in sustainable societies. Within this context, instructional approaches that are inclusive, flexible, and learner-centered have gained increasing importance. This study investigates the effects of project-based learning (PBL) informed by Universal Design for Learning (UDL) principles on secondary school students’ 21st-century skills. Employing a mixed-methods embedded design, the quantitative component utilized a quasi-experimental pretest–posttest control group model. The study was conducted with 60 eleventh-grade students enrolled in a public high school, with one group receiving UDL-informed PBL instruction and the other following the standard curriculum. Data were collected using the 21st Century Learner Skills Usage Scale and analyzed through paired-samples t-tests, independent-samples t-tests, and ANCOVA. The findings revealed statistically significant improvements in the experimental group’s overall 21st-century skills, particularly in cognitive skills and collaboration and flexibility, with medium to large effect sizes. In contrast, the control group showed no meaningful gains, and a decline was observed in innovation skills. The results indicate that project-based learning informed by UDL principles constitutes an effective pedagogical approach for fostering inclusive and sustainable learning environments that support the development of future-oriented learner competencies. These findings further suggest that integrating UDL principles into project-based instructional models may contribute to competency-oriented and inclusive secondary education systems aligned with sustainability frameworks. Full article

Adaptability and flexibility in teaching with digital technologies are essential for instructors to navigate dynamic and ever-evolving educational contexts. However, little has been done to investigate the underlying competencies required of instructors to fluently integrate technologies into their instructional practices. This study employed the Delphi method to address this gap and identify the competencies of a digitally fluent educator in higher education. Through three rounds of data analysis, 36 experts across multiple higher education institutions reached consensus on 14 competencies, including 8 knowledge, 3 skills, and 3 dispositions as indicators of an educator fluent in applying digital tools. The final list of competencies highlights the importance of metacognitive skills, conditional knowledge, and a disposition to be adaptable when defining fluency in digital instruction. The findings indicate a differentiation between digital fluency and previous paradigms such as digital literacy and digital competency. Implications for competency-based professional development opportunities and future research are discussed. Full article

The digital carbon footprint denotes the environmental impact generated by digital technologies throughout their lifecycle. Industry 4.0 manufacturing environments rely extensively on data processing, information storage, and artificial intelligence, thereby increasing energy demand and associated carbon emissions. These conditions have intensified interest in Green AI, particularly in applications such as predictive maintenance and collaborative human–machine systems. This research investigates determinants of behavioural intention to adopt Green AI through an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model tailored to Industry 4.0 and sustainability contexts. The framework incorporates performance expectancy, Industry 4.0 eligibility, technology influence, digital manufacturing competence, sustainability conditions, Green AI recognition, and green manufacturing concern. Data were obtained from an anonymous survey of 1003 Generation Z students enrolled in technical disciplines and preparing for manufacturing-oriented careers. Relationships among constructs were analysed using partial least squares structural equation modelling (PLS-SEM). The model demonstrates strong explanatory and predictive capability. Adoption intention is primarily associated with performance expectancy, Industry 4.0 eligibility, and digital manufacturing competence, while sustainability-oriented perceptions play a contextual rather than direct behavioural role. The study offers a domain-specific empirical extension of UTAUT within pre-workforce technical education rather than proposing a new acceptance theory. The findings reflect intention formation prior to labour-market entry and require validation in operational manufacturing settings before broader generalisation. Full article

Background/Objectives: Dutch legislation sets requirements for the safe reporting of and learning from incidents. It also specifies the required competence of nurses in using medical technology. However, not all certified homecare nurses are adequately trained in patient safety. Patient safety management is reflected at different levels within homecare organisations. This study aimed to report on initial consensus among homecare nurses on responsibilities in quality and safety management at organisational, team and individual levels. It also explored nurses’ educational needs related to the use of advanced medical technologies (AMTs) in homecare. Methods: An exploratory qualitative study using consensus-oriented member checking was conducted. Building on research into incidents and safety management practices of AMTs, two semi-structured group interviews were conducted online with 11 homecare nurses from across the Netherlands. In a second round, feedback and comments were solicited on the resulting conclusions and statements in writing. Results: Distinguishing between high-risk and low-risk incident reports enhances the efficiency and effectiveness of safety management for AMTs in homecare. Team-based discussions increase the likelihood of incident reporting. Nurses advocate for periodic, mandatory assessments for technical homecare teams, conducted by an external body. They also emphasise individual responsibility for maintaining up-to-date knowledge and skills and taking action accordingly. Conclusions: In this study, key statements on which Dutch technical homecare nurses reached consensus are presented. The results underscore the importance of a safe organisational and team culture for incident reporting, as well as the need for an effective and efficient incident management system at a team level. An effective learning organisation contributes to enhancing patient safety. Full article

The rapid expansion of generative artificial intelligence (AI) has significantly transformed educational practice worldwide. While early research documented teachers’ initial reactions to AI tools, less is known about how their attitudes, competencies, and professional practices evolve once these technologies become normalized in schools. This study addresses this gap by examining the development of Czech primary and secondary school teachers’ attitudes and practices related to AI in 2025 and comparing them with findings from 2023. A quantitative survey analyzed teachers’ frequency and purposes of AI use, perceived readiness, institutional support, and experiences with student misuse. The results indicate a substantial acceleration in AI adoption, increased participation in professional development, and a shift from experimental exploration toward more structured and pedagogically grounded use. At the same time, ethical concerns and issues related to student misuse remain significant. The findings highlight the transition from uncertainty to pragmatic integration and underline the importance of systematic methodological support and clear ethical frameworks for responsible AI implementation in education. Full article

The Fourth Industrial Revolution reshapes manufacturing and workforce demands, yet a persistent gap remains between industry needs and engineering education. While proficiency in industrial robotics, adaptive control, and automation becomes critical, traditional education struggles to bridge the theory–practice divide. This systematic review examines technology transfer from factory to classroom to develop authentic Industry 4.0 competencies. Following PRISMA 2020 guidelines, we synthesized 52 empirical studies (2019–2025) focusing on technology complexity, pedagogical approaches, and learning outcomes. Random-effects meta-analysis of 12 representative studies reveals large positive effects: Hedges’ g of 0.786 (95% CI: 0.726–0.846, p < 0.001) with homogeneous effects ($I^2$ = 0.00%, p = 0.464), indicating robust generalizability. However, critical gaps emerged: only 7.7% employ actual industrial manipulators versus educational kits, adaptive control pedagogy remains limited, and fault-tolerant systems teaching receives minimal attention. Technology complexity analysis reveals clear progression from educational kits through semi-industrial platforms to industrial systems, with significant differential effects on transferable skills (r = 0.68, p < 0.001). This study proposes the ARC Framework integrating technology taxonomy, competency progression, pedagogical strategies, and assessment rubrics. Cost–effectiveness analysis demonstrates remote labs optimize impact-per-investment ratios ($45 vs. $280 per student), providing an evidence-based framework for technology transfer in engineering education. Full article

This study analyses the degree of organisational innovation (OI) in Spanish universities and its relationship with institutional competitiveness, proposing a robust analytical framework for its assessment. A mixed, sequential and explanatory design was used, integrating a documentary analysis of R&D indicators, semi-structured interviews with 15 university managers and the validation of an OI questionnaire applied to 387 engineering students and graduates. Qualitative data were analysed with ATLAS.ti 9 and quantitative data were analysed using confirmatory factor analysis and structural equation modelling (SEM) in AMOS v.27, obtaining satisfactory fit indices (CFI = 0.970; RMSEA = 0.051). The results reveal moderate development of OI (Organisational Innovation), with significant differences between institutions according to their level of digitisation, strategic policies and organisational culture. Creativity emerged as the main predictor of key competencies such as active learning and technological design, while excessive institutional openness had negative effects on self-management. Full article