Search Results (8,281)

The integration of emerging technologies is reshaping the teaching skills required in the 21st century, yet little evidence exists on how contextualized training supports rural teachers in adopting active methodologies and critically incorporating AI into entrepreneurship education. This study evaluated the impact of a 40-h professional development program implemented in Educational District 15D01 in the Ecuadorian Amazon. Thirty-nine secondary school teachers participated (mean age = 43.1 years); 36% lacked prior entrepreneurship training, and 44% had not recently mentored student projects. A sequential explanatory mixed-methods design was employed. The quantitative phase employed a 22-item questionnaire that addressed four dimensions: entrepreneurial knowledge, competencies, methodological strategies, and AI integration. Significant pre–post improvements were found (p < 0.001), with large effects for knowledge (d = 1.43), methodologies (d = 1.39), and AI integration (d = 1.30), and a moderate effect for competences (d = 0.66). The qualitative phase analyzed 312 open-ended responses, highlighting greater openness to innovation, enhanced teacher agency, and favorable perceptions of AI as a resource for ideation, prototyping, and evaluation. Overall, the findings suggest that situated, contextually aligned training can strengthen digital equity policies, foster pedagogical innovation, and empower educators in underserved rural communities, contributing to sustainable pathways for teacher professional development. Full article

This research presents a comprehensive analysis of green development policies in the building industry in New South Wales (NSW), Australia, examining their evolution and development over the past two decades. The research adopts a structured methodology comprising a policy review to identify relevant policy documents, content analysis to trace the policy framework, and SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to evaluate the policy development, and then generate evidence-based recommendations. As the first comprehensive assessment of green development policy in the Australian building industry, the study proposes targeted policy recommendations based on analyzing the SWOT factors, including policy for the non-residential sectors and construction phase, education and training, financial support and incentives, and innovation and technology adoption. The insights offer guidance for policymakers to strengthen policy integration and accelerate the transition toward a low-carbon building industry. Full article

Trust plays a pivotal role in individuals’ interactions with technological systems, and those incorporating artificial intelligence present significantly greater challenges than traditional systems. The current landscape of higher education is increasingly shaped by the integration of AI assistants into students’ classroom experiences. Their appropriate use is closely tied to the level of trust placed in these tools, as well as the strategies adopted to critically assess the accuracy of AI-generated content. However, scholarly attention to this dimension remains limited. To explore these dynamics, this study applied the POTDAI evaluation framework to a sample of 132 engineering and social sciences students at Camilo José Cela University in Madrid, Spain. The findings reveal a general lack of trust in AI assistants despite their extensive use, common reliance on inadequate verification methods, and a notable skepticism regarding professors’ ability to detect AI-related errors. Additionally, students demonstrated a concerning misperception of the capabilities of different AI models, often favoring less advanced or less appropriate tools. These results underscore the urgent need to establish a reliable verification protocol accessible to both students and faculty, and to further investigate the reasons why students opt for limited tools over the more powerful alternatives made available to them. Full article

In educational technology environments, the ability to customize digital text presentation offers opportunities to enhance learning experiences through typographical adjustments. This study investigated how digital letter spacing (LS) manipulations affect reading comprehension (RC), reading speed, calibration of comprehension (CoC), and preferences in emergent readers. We examined 163 second graders and 126 third graders as they read digital texts in Hebrew under two conditions: standard LS (100%) and increased LS (150%). The results revealed developmental differences in response to spacing manipulations: increased LS significantly improved RC in second graders, whereas it showed an opposite trend for third graders. Reading rate remained stable across conditions for both groups. Children also demonstrated more accurate CoC under their individually optimal LS condition, suggesting that their comprehension monitoring was responsive to typographical features that supported reading. Preferences analysis indicated a higher numerical proportion of participants favoring the standard LS condition over the increased LS condition in both grades. These findings imply that by integrating adaptive typographical features into educational technology, educators can enhance performance in developing readers, supporting differentiated instruction in increasingly digital learning environments. Full article

The rapid advancement of Artificial Intelligence (AI) technologies is driving a profound transformation in higher education, shifting traditional learning toward digital, remote, and AI-mediated environments. This shift—accelerated by the COVID-19 pandemic—has made computer-supported collaborative learning (CSCL) a central pedagogical model for engaging students in virtual, interactive, and peer-based learning. However, while these environments enhance access and flexibility, they also introduce new emotional, social, and intercultural challenges that students must navigate without the benefit of face-to-face interaction. In this evolving context, Social and Emotional Learning (SEL) has become increasingly essential—not only for supporting student well-being but also for fostering the self-efficacy, adaptability, and interpersonal competencies required for success in AI-enhanced academic settings. Despite its importance, the role of SEL in higher education—particularly within CSCL frameworks—remains underexplored. This study investigates how SEL, and specifically cultural empathy, influences students’ learning experiences in multicultural CSCL environments. Grounded in Bandura’s social cognitive theory and Allport’s Contact Theory, this study builds on theoretical insights that position emotional stability, social competence, and cultural empathy as critical SEL dimensions for promoting equity, collaboration, and effective participation in diverse, AI-supported learning settings. A quantitative study was conducted with 258 bachelor’s and master’s students on a multicultural campus. Using the Multicultural Social and Emotional Learning (SEL CASTLE) model, the research examined the relationships among SEL competencies and self-efficacy in CSCL environments. Findings reveal that cultural empathy plays a mediating role between emotional and social competencies and academic self-efficacy, emphasizing its importance in enhancing collaborative learning experiences within AI-driven environments. The results highlight the urgent need to cultivate cultural empathy to support inclusive, effective digital learning across diverse educational settings. This study contributes to the fields of intercultural education and digital pedagogy by presenting the SEL CASTLE model and demonstrating the significance of integrating SEL into AI-supported collaborative learning. Strengthening these competencies is essential for preparing students to thrive in a globally interconnected academic and professional landscape. Full article

Background/Objectives: Coupling mobile health (mHealth) technology with community-based nutrition programs may enhance diet quality in adolescents. This pilot study evaluated the feasibility, acceptability, and preliminary efficacy of integrating PortionSize Ed (PSEd), an image-assisted dietary assessment and education app, into the six-week Hawaiʻi Food and Lifeskills for Youth (HI-FLY) curriculum delivered via Supplemental Nutrition Assistance Program Education (SNAP-Ed). Methods: Adolescents (grades 6–8) from two classrooms were cluster-randomized into HI-FLY or HI-FLY + PSEd. Both groups received HI-FLY and completed Youth Questionnaires (YQ) and food records (written or app-based) at Weeks 0 and 7. Feasibility and acceptability were assessed via enrollment, attrition, and User Satisfaction Surveys (USS). Diet quality was measured using Healthy Eating Index-2020 (HEI-2020) scores and analyzed via mixed-effects models. Results: Of 50 students, 42 (84%) enrolled and attrition was minimal (2.4%). The sample was 49% female and 85% at least part Native Hawaiian or Pacific Islander (NHPI). PSEd was acceptable, with average USS scores above the scale midpoint. No significant HEI-2020 changes were observed, though YQ responses indicated improvements in sugary drink intake (p = 0.03) and use of nutrition labels in HI-FLY + PSEd (p = 0.0007). Conclusions: Integrating PSEd into SNAP-Ed was feasible, acceptable, and demonstrated potential healthy behavior change among predominantly NHPI youth in Hawaiʻi. Full article

While researchers of children in early years education promote the development of computational thinking (CT) abilities, many teachers are unaware of, or resistant to, the idea of teaching CT to such young children. This study explored the possibility of utilising everyday items and topics to develop CT abilities in a class of 24 four-to-five-year-old children. Over six weekly sessions, the children took part in innovative guided play activities integrated with class topics: Celebrations, Forest School and Christmas. Each session consisted of two activities: Task A consisted of deconstructing, evaluating and choosing equipment or items, and Task B consisted of sequencing and debugging the order of the activity, e.g., wrapping a birthday present. Two methods of assessment were utilised: quantitative where children were asked to do simple pencil and paper tasks and the sequencing or placement of pictures to record their accuracy; and qualitative where children were individually asked to explain their results. The findings indicate progress was made in task performance and the development of children’s logical reasoning and thinking abilities. Full article

Continuous technological, ecological, and digital transformations reshape urban mobility systems. While sustainable mobility has become a dominant keyword, there are many different approaches and policies to help achieve lasting and properly functioning change. This study applies a comprehensive qualitative policy analysis to influential and leading sustainable mobility approaches (i.a. Mobility Justice, Avoid–Shift–Improve, spatial models like the 15-Minute City and Superblocks, governance frameworks such as SUMPs, and tools ranging from economic incentives to service architectures like MaaS and others). Each was assessed across structural barriers, psychological resistance, governance constraints, and affective dimensions. The results show that, although these approaches provide clear normative direction, measurable impacts, and scalable applicability, their implementation is often undermined by fragmentation, Policy Layering, limited intermodality, weak Future-Readiness, and insufficient participatory engagement. Particularly, the lack of sequencing and pacing mechanisms leads to policy silos and societal resistance. The analysis highlights that the main challenge is not the absence of solutions but the absence of a unifying paradigm. To address this gap, the paper introduces CalmMobility, a conceptual framework that integrates existing strengths while emphasizing comprehensiveness, pacing–sequencing–inclusion, and Future-Readiness. CalmMobility offers adaptive and co-created pathways for mobility transitions, grounded in education, open innovation, and a calm, deliberate approach. Rather than being driven by hasty or disruptive change, it seeks to align technological and spatial innovations with societal expectations, building trust, legitimacy, and long-term resilience of sustainable mobility. Full article

This study explores Hong Kong residents’ perceptions of their city’s smart city transformation, set against a backdrop of political and economic changes. It investigates residents’ awareness and support for Hong Kong’s development as a smart city and their familiarity with the Smart City Blueprint. Despite the global emphasis on smart city initiatives, there is a significant gap in understanding residents’ perceptions, with the existing literature often focusing on technological and policy aspects while neglecting citizen voices. Employing a mixed-methods research design, the study integrates quantitative survey data (N = 808) with qualitative interviews (N = 25) and focus group discussions (4 groups, N = 43) to capture diverse perspectives. The findings reveal a generally low level of understanding of the Smart City Blueprint among residents, alongside a positive attitude towards its key dimensions like mobility, living, and the environment. Older citizens, those with lower educational attainment, and individuals from mainland China showed greater understanding and support. Interviews highlighted concerns about coordination, bureaucratic processes, data privacy, and public involvement. Focus group discussions revealed varied viewpoints, with some participants drawing comparisons to smart city developments in mainland China and expressing privacy concerns. The study underscores the importance of aligning smart city initiatives with residents’ needs and preferences through inclusive communication strategies and addressing concerns about data privacy and job displacement. Methodological triangulation enhances the validity and reliability of the research, revealing complex patterns and contradictions. Full article

This study investigates the effectiveness of virtual simulations in developing intercultural competence (IC) among pre-service teachers in Israel. In the context of cultural diversity and historical conflict, 283 Arab and Jewish students participated in a course utilizing either a 3D virtual world (VW) or video conferencing via Zoom. The mixed-methods research combined quantitative surveys with qualitative interviews. Quantitative results showed a modest but significant increase in intercultural competence for both groups, with no significant difference between VW and Zoom platforms. Qualitative findings revealed that while VW participants faced more technical challenges, they also reported more opportunities for empathy development and cross-cultural understanding. Both groups valued the exposure to different cultures and expressed a desire for face-to-face encounters. This study highlights the potential of virtual simulations in fostering IC, emphasizing the importance of collaborative problem-solving and intercultural interaction, regardless of the specific digital platform used. These findings contribute to the growing body of research on technology-mediated intercultural education and offer insights for designing effective virtual learning environments in multicultural contexts. Full article

Extended Reality (XR) technologies—including Virtual Reality, Augmented Reality, and Mixed Reality—are increasingly applied in the food industry to simulate sensory environments, support education, and influence consumer behavior, while robotics addresses labor shortages, hygiene, and efficiency in production. This review uniquely synthesizes their convergence through digital twin frameworks, combining XR’s immersive simulations with robotics’ precision and scalability. A systematic literature review and keyword co-occurrence analysis of over 800 titles revealed research clusters around consumer behavior, nutrition education, sensory experience, and system design. In parallel, robotics has expanded beyond traditional pick-and-place tasks into areas such as precision cleaning, chaotic mixing, and digital gastronomy. The integration of XR and robotics offers synergies including risk-free training, predictive task validation, and enhanced human–robot interaction but faces hurdles such as high hardware costs, motion sickness, and usability constraints. Future research should prioritize interoperability, ergonomic design, and cross-disciplinary collaboration to ensure that XR–robotics systems evolve not merely as tools, but as a paradigm shift in redefining the human–food–environment relationship. Full article

As organizations increasingly turn to machine learning for customer segmentation and targeted marketing, concerns about fairness and algorithmic bias have become more urgent. This study presents a comprehensive fairness audit and mitigation framework for predictive marketing models using the Bank Marketing dataset. We train logistic regression and random forest classifiers to predict customer subscription behavior and evaluate their performance across key demographic groups, including age, education, and job type. Using model explainability techniques such as SHAP and fairness metrics including disparate impact and true positive rate parity, we uncover notable disparities in model behavior that could result in discriminatory targeting. We implement three mitigation strategies—reweighing, threshold adjustment, and feature exclusion—and assess their effectiveness in improving fairness while preserving business-relevant performance metrics. Among these, reweighing produced the most balanced outcome, raising the Disparate Impact Ratio for older individuals from 0.65 to 0.82 and reducing the true positive rate parity gap by over 40%, with only a modest decline in precision (from 0.78 to 0.76). We propose a replicable workflow for embedding fairness auditing into enterprise BI systems and highlight the strategic importance of ethical AI practices in building accountable and inclusive marketing technologies. technologies. Full article

Smallholder farmers in developing countries often face barriers to market participation due to information asymmetry and limited access to marketing channels. This study investigates the impact of internet technology on farmers’ agricultural sales and its heterogeneity, using data from the China Family Panel Studies (CFPS) covering 14,577 agricultural households. Propensity score matching and unconditional quantile regression are employed for empirical analysis. The results show that (1) internet adoption significantly improves agricultural sales performance, increasing average sales output by 4680 CNY (Chinese Yuan, the official currency of China); (2) the effects of internet adoption are heterogeneous across industry types, education level, income level, social ties, and internet access devices; (3) the marginal impact of internet use grows with higher sales levels, with the strongest effect observed at the 95% quantile. This study highlights the impact of rural internet technology on increasing market transaction efficiency. Full article

AI chatbots have the potential to facilitate students’ academic progress and enhance knowledge accessibility in higher education, yet learners’ attitudes toward these technologies vary amid AI-driven disruptions, with factors influencing acceptance remaining debated. The current study constructs an integrated model based on Technology Acceptance Model 3 (TAM3), an extension of the original TAM, incorporating factors including Self-Efficacy, Perceived Enjoyment, Anxiety, Perceived Ease of Use, Perceived Usefulness, Output Quality, Social Influence, and Behavioral Intention, to explore determinants and mechanisms influencing learners’ acceptance of AI chatbots. This addresses key challenges in AI-augmented learning, such as personalization benefits versus risks like information inaccuracy and ethical concerns. Results from the questionnaire survey analysis with 265 valid responses reveal significant relationships: (1) self-efficacy significantly predicts perceived ease of use; (2) both perceived enjoyment and perceived ease of use positively influence perceived usefulness; and (3) self-efficacy, perceived usefulness, and social influence collectively exert significant effects on behavioral intention. Measurement invariance tests further indicate significant differences in acceptance between undergraduate and graduate students, suggesting academic level moderates behavioral intentions. Findings offer principled guidance for designing inclusive AI tools that mitigate accessibility barriers and promote equitable adoption in educational environments. Full article

This study investigates the challenges of promoting accessibility for deaf teachers and students in higher education, focusing on the development of inclusive teaching materials. A qualitative case study was conducted in ten teacher training programmes at the Federal University of Alagoas (Brazil), including nine distance learning courses and one face-to-face LIBRAS programme. Analysis of the Virtual Learning Environment revealed a predominance of text-based content, with limited use of Libras videos, visual resources, or assistive technologies. The integration of Brazilian Sign Language into teaching practices was minimal, and digital translation tools were rarely used or contextually appropriate. Educators reported limited training, technical support, and institutional guidance for the creation of accessible materials. Time constraints and resource scarcity further hampered inclusive practices. The results highlight the urgent need for institutional policies, continuous teacher training, multidisciplinary support teams, and the strategic use of digital technologies and Artificial Intelligence (AI). Compared with previous studies, significant progress has been made. The present study highlights the establishment of an Accessibility Centre (NAC) and an Accessibility Laboratory (LAB) at the university. These facilities are designed to support the development of policies for the inclusion of people with disabilities, including deaf students, and to assist teachers in designing educational resources, which is essential for enhancing accessibility and learning outcomes. Artificial intelligence tools—such as sign language translators including Hand Talk, VLibras, SignSpeak, Glove-Based Systems, the LIBRAS Online Dictionary, and the Spreadthesign Dictionary—can serve as valuable resources in the teaching and learning process. Full article