Search Results (881)

Artificial Intelligence (AI), particularly Generative AI (GenAI) and Large Language Models (LLMs), is rapidly reshaping higher education by transforming teaching, learning, assessment, research, and institutional management. This entry provides a state-of-the-art, comprehensive, evidence-based synthesis of established AI applications and their implications within the higher education landscape, emphasizing mature knowledge aimed at educators, researchers, and policymakers. AI technologies now support personalized learning pathways, enhance instructional efficiency, and improve academic productivity by facilitating tasks such as automated grading, adaptive feedback, and academic writing assistance. The widespread adoption of AI tools among students and faculty members has created a critical need for AI literacy—encompassing not only technical proficiency but also critical evaluation, ethical awareness, and metacognitive engagement with AI-generated content. Key opportunities include the deployment of adaptive tutoring and real-time feedback mechanisms that tailor instruction to individual learning trajectories; automated content generation, grading assistance, and administrative workflow optimization that reduce faculty workload; and AI-driven analytics that inform curriculum design and early intervention to improve student outcomes. At the same time, AI poses challenges related to academic integrity (e.g., plagiarism and misuse of generative content), algorithmic bias and data privacy, digital divides that exacerbate inequities, and risks of “cognitive debt” whereby over-reliance on AI tools may degrade working memory, creativity, and executive function. The lack of standardized AI policies and fragmented institutional governance highlight the urgent necessity for transparent frameworks that balance technological adoption with academic values. Anchored in several foundational pillars (such as a brief description of AI higher education, AI literacy, AI tools for educators and teaching staff, ethical use of AI, and institutional integration of AI in higher education), this entry emphasizes that AI is neither a panacea nor an intrinsic threat but a “technology of selection” whose impact depends on the deliberate choices of educators, institutions, and learners. When embraced with ethical discernment and educational accountability, AI holds the potential to foster a more inclusive, efficient, and democratic future for higher education; however, its success depends on purposeful integration, balancing innovation with academic values such as integrity, creativity, and inclusivity. Full article

This study examined the effects of using specially designed AI-mediated pronunciation application in enhancing the production of English fricative consonants among Thai English for Specific Purposes (ESP) learners. The research utilized a quasi-experimental design involving intact classes of 74 undergraduate students majoring in Thai Dance and Music Education, divided into control (N = 38) and experimental (N = 36) groups. Grounded in Skill Acquisition Theory, the experimental group received pronunciation training via a custom-designed AI application leveraging automatic speech recognition (ASR), offering ESP contextualized practices, real-time, and individualized feedback. In contrast, the control group underwent traditional teacher-led articulatory and teacher-assisted feedback. Pre- and post-test evaluations measured pronunciation for nine target fricatives in ESP-relevant contexts. The statistical analyses revealed significant improvements in both groups, with the AI-mediated group demonstrating substantially greater gains, particularly on challenging sounds absent in Thai, such as /θ/, /ð/, /z/, /ʃ/, and /h/. The findings underscore the potential of AI-driven interventions to address language-specific phonological challenges through personalized, immediate feedback and adaptive practices. The study provides empirical evidence for integrating advanced technology into ESP pronunciation pedagogy, informing future curriculum design for EFL contexts. Implications for theory, practice, and future research are discussed, emphasizing tailored technological solutions for language learners with specific phonological profiles. Full article

This qualitative study explored how elementary preservice teachers (PSTs) in an equity-centered teacher preparation program understood technology’s role in equity pedagogy. Drawing on two focus groups of five PSTs each—organized to reflect the most recent cohort’s division into separate sub-cohorts—and a short reflective writing activity, we examined (1) how the PSTs conceptualized the relationship between technology and equity pedagogy, (2) what opportunities and challenges they perceived at this intersection, and (3) how various aspects of their program shaped their understanding. While PSTs generally viewed technology as a tool for advancing equity pedagogy, their understanding varied considerably between the two sub-cohorts, particularly in terms of their knowledge, confidence, and perceived barriers to teaching at the intersection of these domains. These differences appeared to stem from how well-supported PSTs felt in making connections between these domains across their coursework, field experiences, and peer interactions. This study reinforces the need for more intentionally integrated coursework that equips PSTs to use technology for advancing equity in the K–12 curriculum. Full article

Building Information Modeling (BIM) is a transformative tool in Sustainable Design (SD), providing measurable benefits for efficiency, collaboration, and performance in architectural, engineering, and construction (AEC) practices. Despite its growing presence in academic curricula, a gap persists between students’ recognition of BIM’s sustainability potential and their confidence or ability to apply these concepts in real-world practice. This study examines students’ understanding and perceptions of BIM and Sustainable Design education, offering insights for enhancing curriculum integration and pedagogical strategies. The objectives are to: (1) assess students’ current understanding of BIM and Sustainable Design; (2) identify gaps and misconceptions in applying BIM to sustainability; (3) evaluate the effectiveness of existing teaching methods and curricula to inform future improvements; and (4) explore the alignment between students’ theoretical knowledge and practical abilities in using BIM for Sustainable Design. The research methodology includes a comprehensive literature review and a survey of 213 students from architecture and construction management programs. Results reveal that while most students recognize the value of BIM for early-stage sustainable design analysis, many lack confidence in their practical skills, highlighting a perception–practice gap. The paper examines current educational practices, identifies curriculum shortcomings, and proposes strategies, such as integrated, hands-on learning experiences, to better align academic instruction with industry needs. Distinct from previous studies that focused primarily on single-discipline or software-based training, this research provides an empirical, cross-program analysis of students’ perception–practice gaps and offers curriculum-level insights for sustainability-driven practice. These findings provide practical recommendations for enhancing BIM and sustainability education, thereby better preparing students to meet the demands of the evolving AEC sector. Full article

This paper reports a study conducting an in-depth analysis of the impacts of ethical training on the adoption of AI tools among computer science students in higher vocational colleges. These students will serve as the pivotal human factor for advancing the field of AI. Aiming to explore practical models for integrating AI ethics into computer science education, the research seeks to promote more responsible and effective AI application and therefore become a positive influence in the field. Employing a mixed-methods approach, the study included 105 students aged 20–24 from a vocational college in Guangdong Province, a developed region in China. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, a five-point Likert scale was used to evaluate the participants’ perceptions of AI tool usage based on ethical principles. The Structural Equation Modeling (SEM) results indicate that while participants are motivated to adopt AI technologies in certain aspects, performance expectancy negatively impacts their intention and actual usage. After systematically studying and understanding AI ethics, participants attribute a high proportion of responsibility (84.89%) to objective factors and prioritized safety (27.11%) among eight ethical principles. Statistical analysis shows that habit (β = 0.478, p < 0.001) and hedonic motivation (β = 0.239, p = 0.004) significantly influence behavioral intention. Additionally, social influence (β = 0.234, p = 0.008) affects use behavior. Findings regarding factors that influence AI usage can inform a strategic framework for the integration of ethical instruction in AI applications. These findings have significant implications for curriculum design, policy formulation, and the establishment of ethical guidelines for AI deployment in higher educational contexts. Full article

Reforms in the Chinese National Entrance Examination to Universities (CNEEU) and curriculum standards have significantly influenced national education. This study investigates the evolutionary stages, research trends, and emerging topics in the study of geography examinations for the CNEEU, commonly known as the Gaokao in China. Utilizing CiteSpace software, we analyzed academic journal articles indexed in the China National Knowledge Infrastructure (CNKI) database from 1980 to 2023. The analysis focuses on publication volume, regional distribution, core authors, emergent terms, and keyword trends related to geography examinations. The results reveal the following: (1) Research on geography in the CNEEU has experienced three distinct phases since the 1980s—incipient stage, fluctuating growth period, and adjustment period—each characterized by unique emergent keywords reflecting evolving research priorities. (2) The principal research institutions include middle schools, higher normal colleges, and examination research institutes, with scholars from higher normal universities more likely to establish collaborative research groups. (3) Key research topics focus on the content and characteristics of geography examination questions, teaching guidance, test preparation strategies, and the development of simulation questions. (4) Ongoing reforms in the CNEEU and curriculum have significantly influenced the scope, focus, and format of geography examinations, directly impacting geography teaching and learning practice. (5) Emerging trends, including literacy and value-oriented assessment, interdisciplinary integration, and inquiry-based innovation, are expected to shape future research in this field. This study offers valuable insights to support both theoretical research and practical advancement in the design of geography examinations for CNEEU. Full article

The escalating frequency and complexity of cyber threats have made cybersecurity education a national priority, yet a practical gap persists between theoretical instruction and workforce readiness. This study presents a comprehensive, modular framework for designing and implementing cybersecurity laboratories in academic institutions, environments that foster hands-on learning, skill mastery, and curricular innovation. Using a mixed-methods, multi-stage case study approach, the research combined qualitative analysis of institutional practices and instructional methods with quantitative evaluation of learning outcomes to comprehensively examine technical and pedagogical considerations impacting lab development. Data sources included literature analysis, direct observation, document review, and semi-structured interviews. The study synthesized best practices across these domains into a scalable lab design model grounded in experiential learning theory. Results demonstrate that the framework supports enhanced student performance, instructional adaptability, and simulation fidelity. Case study data revealed measurable gains in participant competency, with all participants achieving at least a 20% improvement in post-training test scores, high engagement levels demonstrated through consistent session attendance and active participation in hands-on exercises, and successful adaptation to logistical and technological barriers, including facility relocations and system downtime incidents. The lab’s modularity enabled curricular alignment, resource efficiency, and expansion to serve workforce training initiatives beyond the classroom. By integrating pedagogical (structured, teacher-guided instructional approaches) and andragogical (adult learning) design with technological scalability, this research contributes an actionable roadmap for institutions seeking to modernize cybersecurity education and respond effectively to evolving digital threats. The findings offer broad implications for future curriculum development, facilitator training, and sustainable program implementation. Full article

In the era of digital intelligence, information literacy (IL) competency has become a critical indicator for measuring the comprehensive quality and sustainable development potential of university’s education. Using Yancheng Institute of Technology as a case study, this study systematically elucidates the connotation and current development status of college students’ IL within the framework of sustainable development. An evaluation index system is constructed, comprising four dimensions: information awareness and attitude, information ethics, law and security, information knowledge and skills, and information integration and innovation. The study employs the Analytic Hierarchy Process (AHP) to determine the weights of indicators at various levels and integrates the Fuzzy Comprehensive Evaluation Method (FCEM) to establish a quantitative assessment model for IL competency. Empirical research demonstrates that the proposed model effectively enables a multidimensional and quantitative evaluation of students’ IL, with results that exhibit sound scientific validity and applicability. Based on the analysis, specific strategies are proposed to enhance students’ IL from the perspectives of curriculum design, teaching models, and library services, thereby providing theoretical references and practical pathways for advancing informatization and sustainable development in higher education. Full article

Multi-UAV cooperative encirclement tasks have attracted considerable attention in areas such as military defense and target interception. Fixed-wing UAVs face substantial challenges due to intrinsic dynamic limits, including their minimum velocity and turning radius, particularly when engaging evasive target and navigating in obstacle environments. This paper presents a hybrid deep reinforcement learning approach, in which a cooperative task environment is developed for fixed-wing UAVs that jointly integrates encirclement and obstacle avoidance. A composite MADDPG framework enhanced with curriculum learning is designed, employing progressive task staging and reward optimization to accelerate convergence and improve policy stability. Simulation results demonstrate that the proposed method achieves single-step encirclement success rates exceeding 80% in complex environments, while maintaining 10-step success rates around 70%, thereby strengthening both encirclement capability and obstacle avoidance safety in fixed-wing UAV swarm. This study provides new insights into the intelligent cooperative control of fixed-wing UAVs in high-risk missions. Full article

The planetary health approach has gained traction in academic and international governance spheres; however, its limited integration into education systems has hindered its emergence as a universal framework for addressing the triple planetary crisis (climate change, biodiversity loss, and pollution) and its impacts on individual well-being and global health systems. We mapped the evolution of the educational approach to planetary health between 2015 and 2025 from a critical and constructive perspective, using a bibliometric and thematic analysis. Through the bibliometric analysis, we found that publications from the Global North predominate, focusing on health programmes and topics such as climate change, One Health, Global Health and Public Health. The thematic analysis, based on inductive categorisation, allowed us to identify criticisms of the educational approach, such as its curricular marginalisation and limited scalability. From an epistemological perspective, these criticisms refer to technoscientific reductionism, the invisibility of non-Western epistemologies and the decoupling of cognition and environment. Given these limitations, we propose a reconstruction of the planetary health approach along three critical dimensions: Motivation, Legitimacy and Epistemology. This reconstruction is projected into short-, medium- and long-term scenarios at the university level, particularly as part of curriculum reform efforts, to broaden the pedagogical impact and promote a more inclusive and transformative vision. Full article

Integrating social and emotional learning (SEL) into academic instruction may improve well-being and achievement. In mathematics—where anxiety and negative attitudes often hinder learning—SEL may be especially useful. This multiple case study examined how a math curriculum that explicitly embeds SEL principles shapes learning environments and teacher/student experiences. Using a multiple case study design, we conducted classroom observations, teacher interviews, and check-ins in six Grade 5–7 classrooms implementing JUMP Math, a program that centers social–emotional well-being. Three themes characterized the SEL-integrated environment: (1) Teaching Energy—steady pacing, enthusiastic delivery, and humor; (2) Learning Harmony—progressing together, peer help, and the normalization of mistakes; and (3) Emotional Stability—supportive feedback, invitations to participate, and respectful, responsive interactions. Teachers reported greater confidence and reduced math anxiety; students showed higher engagement, cooperation, and resilience in problem-solving. Findings indicate that math curricula intentionally designed with SEL can create emotionally supportive classrooms that benefit both teachers and students, while advancing academic goals. The findings contribute to understanding how academic instruction can be leveraged to develop social and emotional competence while maintaining focus on academic achievement. Full article

This study examines the effects of integrating an inquiry-based final project into an early childhood robotics program, focusing on its influence on children’s problem-solving self-efficacy, attitudes toward collaboration, confidence in applying robotics to real-world challenges, and future interest in STEM. A total of 176 first-grade students (aged 6–7) were randomly assigned to either a research group that completed a culminating inquiry-based robotics project or a control group that followed a traditional structured curriculum. A quasi-experimental post-test-only comparison group design was used, and baseline equivalence was confirmed across groups. Results revealed that children who participated in the inquiry-based final project group demonstrated significantly higher problem-solving self-efficacy and more positive attitudes toward peer collaboration, while also being more likely to see the relevance of robotics to real-world problems and to align with inquiry-based learning approaches. Gender analysis showed that these gains were especially pronounced among girls, who exhibited more statistically significant improvements in problem-solving confidence and self-efficacy in inquiry-based problem-solving. The study’s findings highlight the benefits of incorporating inquiry-based final projects into early robotics curricula, addressing a critical gap in early childhood STEM education by providing evidence-based insights into how to enhance foundational STEM dispositions and engagement through inquiry-based, technology-integrated instruction. Full article

The integration of Generative Artificial Intelligence (GenAI) tools, such as ChatGPT, into higher education has introduced new opportunities and challenges for students and lecturers alike. This study investigates the psychological, ethical, and institutional factors that shape the adoption of GenAI tools in Saudi Arabian universities, drawing on an extended Technology Acceptance Model (TAM) that incorporates constructs from Self-Determination Theory (SDT) and ethical decision-making. A cross-sectional survey was administered to 578 undergraduate students and 309 university lecturers across three major institutions in Southern Saudi Arabia. Quantitative analysis using Structural Equation Modelling (SmartPLS 4) revealed that perceived usefulness, intrinsic motivation, and ethical trust significantly predicted students’ intention to use GenAI. Perceived ease of use influenced intention both directly and indirectly through usefulness, while institutional support positively shaped perceptions of GenAI’s value. Academic integrity and trust-related concerns emerged as key mediators of motivation, highlighting the ethical tensions in AI-assisted learning. Lecturer data revealed a parallel set of concerns, including fear of overreliance, diminished student effort, and erosion of assessment credibility. Although many faculty members had adapted their assessments in response to GenAI, institutional guidance was often perceived as lacking. Overall, the study offers a validated, context-sensitive model for understanding GenAI adoption in education and emphasises the importance of ethical frameworks, motivation-building, and institutional readiness. These findings offer actionable insights for policy-makers, curriculum designers, and academic leaders seeking to responsibly integrate GenAI into teaching and learning environments. Full article

The benefits of work-integrated learning (WIL) in higher education are well documented. Conversely, the assessment thereof, across disciplines, remains challenging. WIL is embedded in the environmental health (EH) degree at a University of Technology (UoT) in South Africa (SA), with similar challenges. The absence of explicit competency indicators and associated assessment criteria in the current curriculum necessitates an understanding of the full range of professional competencies necessary for achieving environmental health goals. Concomitantly, research relating to EH WIL and its assessment in EH programmes are sparse. The aim of this study is to present a holistic assessment framework for competencies developed due to WIL. Using a qualitative design, data collection occurred through in-depth interviews, document analysis and focus group discussions. Data analysis was guided by the Legitimation Code Theory’s (LCT) Specialization dimension. The results foregrounds competencies beyond mere knowledge integration and technical skill development in WIL. It is thus recommended that current assessment be altered to adopt holistic assessment of EH WIL and include the full range of professional competencies essential for EH practice success. Further research may explore where additional opportunities exist for authentic assessment of the foregrounded competencies, throughout the programme, additional to the WIL assessments. Full article