Search Results (88)

The rapid development of generative artificial intelligence (GenAI) is transforming both the health sector and health profession education, although AI-based systems have existed in these sectors for decades. GenAI-integrated virtual agents and simulations now play novel and critical roles in simulation-based education and are potential solutions to enhance the adaptability of health profession education. This systematic review was conducted using the PRISMA guidelines and explores how GenAI-integrated virtual agents and simulations are being applied in health profession education, with a particular focus on their educational impact, technical features and functionalities, and current limitations. This review aims to synthesize the pedagogical value and technological design of GenAI-integrated simulations and to inform health professionals and educators about the effective use, impact, and challenges of GenAI in health education simulations. A total of 16 papers were reviewed. Results show that GenAI-integrated virtual agents and simulations have potential to enhance clinical communication, diagnostic accuracy, multilingual interactions, and learner confidence for health profession education. Related theoretical, technological, and educational implications of generative AI-integrated virtual agents and simulations are discussed to inform future design and application. Limitations include insufficient educational effectiveness, response accuracy issues, and unresolved ethical and privacy concerns. Future studies should focus on long-term efficacy, ethical considerations, and optimizing AI–human collaboration in various health profession education contexts. Full article

Engineering education prepares graduates to face complex environmental and societal challenges. This involves the intersection of sustainability and innovation. Integrating these agendas is therefore necessary, and this involves identifying specific elements that have not yet been explored. To examine this relationship, a systematic literature review was conducted using an adapted PRISMA 2020 approach appropriate for a bibliometric and thematic systematic review, through four research questions related to knowledge production, pedagogical methods, innovation outcomes, and reported results. The PRISMA phases were adopted using the SCOPUS and ERIC databases. This yielded three clusters: innovation, sustainability, and engineering education. Student-centered pedagogies have also been identified as an explored opportunity to enhance innovation skills aligned with sustainability objectives. However, this incorporation involves many elements to explore, including the connection between innovation outcomes and sustainability impact. This context involves both development and the relationships among individuals, institutions, and ecosystems. This requires managing diverse visions, languages, and cultures, which highlights several challenges: long-term impacts, mindset development, contextual influences, pedagogical strategies, research–practice alignment, stakeholder communication, and faculty preparation. Overall, the findings show progress but reveal challenges across approaches and contexts. This is because sustainability-driven innovation in engineering education requires coordinated curricular, institutional, and ecosystem-oriented strategies to support learning and strengthen contributions to sustainable futures. Full article

In today’s educational context, Game-Based Learning (GBL) has emerged as a promising methodology for promoting active learning in an engaging and motivating way. This study aims to analyze the impact of a video game-based intervention on the development of students’ cognitive skills, focusing on the levels of Bloom’s taxonomy, as well as to explore students’ perceptions of this methodology. Accordingly, an intervention was conducted with 52 students in the Early Childhood Education Degree Program, integrating video games designed for this study for pedagogical purposes. An approach combining two quantitative instruments was employed: knowledge assessment tests and a student perception questionnaire. The results show a significant improvement in students’ higher-order cognitive skills, particularly in the dimensions of applying, analyzing, and evaluating. Furthermore, students demonstrated a positive attitude toward the use of video games as a learning tool. Therefore, this study confirms that the integration of GBL methodology at the university level can effectively contribute to the development of higher-order cognitive skills among teachers in initial training. However, further research is recommended to examine its long-term impact and its effectiveness across different levels of education. Full article

Digital games are becoming increasingly important as promising tools to foster Education for Sustainable Development (ESD), aiming to combine engagement, systems thinking, and transformative learning. This narrative review synthesizes evidence from 40 studies on serious games, game-based learning, and gamification to assess both the potential and limitations of digital games in ESD contexts. This review thus contributes to the field by integrating theoretical frameworks, empirical evidence, and design principles to provide a coherent understanding of how digital games support ESD learning processes. The findings reveal positive effects on cognitive and motivational outcomes, particularly regarding knowledge acquisition, systems understanding, and learner engagement. In addition, digital games can foster social learning processes such as collaboration, participation, and perspective-taking. These effects are grounded in established theoretical frameworks, including self-determination theory, flow theory, and experiential learning, and are supported by design features such as adaptive feedback, meaningful narratives, social interaction, and authentic decision-making. Across the reviewed studies, cognitive outcomes are most consistently documented, while evidence for long-term behavioral change and real-world transfer remains limited. This reflects both structural challenges of ESD and methodological constraints, including difficulties in measuring behavior, short-term study designs, and heterogeneous implementations. Overall, digital games can support key ESD competencies by enabling learners to engage with complex socio-ecological systems and multi-perspectivity. Their effectiveness and educational value depend less on gameplay itself than on four overarching design principles: encouraging the exploration of systems, linking experience and reflection, balancing between autonomy and guidance, and embedding within broader social and pedagogical processes. Full article

Within a global landscape characterised by increasing fragmentation, community empowerment requires interdisciplinary, evidence-based and validated methodology for assuring collaborative and transformative action. This research addresses the need for equity and inclusion in underserved rural areas by investigating the CleanAir@Schools initiative in Romania. The study employed a human-centred, multi-stakeholder methodology, utilising exploratory workshops with educators and pilot implementations to develop a learning framework on Sustainability Education, in which students used passive sensors to measure local air quality. Results indicate that the project successfully mobilised entire school communities, catalysing a pedagogical shift from passive reception to active, inquiry-based environmental education. Furthermore, the strategic use of both digital and analogue technologies ensured accessibility for communities facing digital divides. The research concludes that participatory design acts as a catalyst for long-term community empowerment and social transformation by addressing localised challenges through inclusive, restorative practices. By intentionally centring society’s margins, design research fosters regeneration and care, serving as an essential resource for social innovators and policymakers. Full article

Engineering education is increasingly shifting toward data-driven and creativity-centred pedagogies that foster innovation, communication, ethical awareness, and teamwork. However, traditional Problem-Based Learning and Design Thinking approaches rely heavily on subjective evaluation and lack scalable mechanisms for monitoring learning progression and creativity development. These pedagogical limitations highlight the need for data-driven approaches that can support iterative learning processes, continuous feedback, and objective evaluation of creativity and performance. This study proposes a Generative Artificial Intelligence (GenAI)-driven predictive analytics framework for modelling student performance and creativity in engineering design systems. The framework integrates deep learning architectures, including Long Short-Term Memory (LSTM) networks and Transformer-based multimodal fusion, to analyze temporal and heterogeneous learning data. The novel Creativity Index (CI) is introduced to quantify design innovation by combining novelty and feasibility metrics derived from AI-assisted interactions and project milestones. The model was evaluated on a longitudinal dataset comprising 450 students across 10 semesters (~5400 time-series observations). Experimental results demonstrate strong predictive performance, achieving 89% classification accuracy and RMSE of 3.8. Comparative analysis shows significant improvements in engineering design (+15%), communication (+16%), ethical awareness (+17%), and teamwork (+16%) (p < 0.01). The proposed framework enables real-time feedback, early risk detection, and adaptive learning optimization. These findings highlight the potential of integrating generative AI and predictive analytics to develop scalable, data-driven intelligent learning systems. Full article

This systematic review comprehensively explores the integration of Extended Reality (XR) technologies, comprising Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), into New Zealand’s STEM education framework. In alignment with PRISMA 2020 guidelines, we systematically analyzed 127 peer-reviewed studies from the Web of Science (n = 48), Scopus (n = 57), and Dimensions (n = 22) and incorporated 15 grey literature sources, resulting in 142 studies included in the review. Our meta-analysis found substantial improvements in student conceptual understanding from XR-enhanced STEM modules. Specifically, we observed an average increase of 23.4% when compared to traditional instructional methods (95 percent Confidence Interval: 18.7 to 28.1 percent, p < 0.001). These gains were especially prominent in interactive learning environments where immersive XR applications supported deeper engagement and the visualization of abstract STEM concepts. The qualitative synthesis highlighted several key barriers that limit effective XR integration. These include technological infrastructure gaps reported in 68 percent of reviewed studies, a critical need for educator training cited by 82 percent of studies, and curriculum alignment issues present in 57 percent of cases. Methodological quality was assessed using the Mixed Methods Appraisal Tool (MMAT) 2018, and the qualitative component employed a deductive thematic coding approach with inter-coder reliability verification. Successful institutional implementations were also identified. At Auckland University of Technology, XR-supported courses produced a 67 percent increase in student engagement, while Wellington High School achieved a 41 percent reduction in STEM achievement gaps through targeted XR interventions. Based on the evidence, we propose a four-phase implementation framework that addresses the technological, pedagogical, and policy requirements for sustainable XR adoption. These findings highlight the role of immersive technologies in supporting human-centered digital transformation and future skills development in the transition to Industry 5.0. The review contributes evidence-based insights that support the transition from technology-driven approaches associated with Industry 4.0 to the human-centered, socially oriented priorities of Industry 5.0. It also identifies critical research gaps, particularly in long-term learning outcomes and the integration of Mātauranga Māori within XR-enabled STEM environments. Full article

Artificial intelligence has been considered as a transformative element capable of reshaping STEM education into equitable, resource-efficient, and scalable learning environments. However, realizing this potential requires striking a careful balance between technological innovation, pedagogical considerations, and ethical concerns. This study sought to examine the implementation of artificial intelligence (AI) tools by STEM university faculty members in Saudi Arabia to promote Sustainable Development Goal 4 (quality education). While doing so, the study attempted to explore how Saudi STEM university faculty members integrated AI tools in their instructional practices and analyze their perceptions towards these tools. To achieve these goals, the study employed an explanatory sequential mixed-methods design. In the first phase of data collection, a close-ended questionnaire was applied to a random sample of (324) STEM university faculty members. The second phase involved gathering qualitative data using a semi-structured interview administered to 12 purposively selected experts. Key quantitative findings revealed an overall AI integration at a medium level with a mean of (2.71) and standard deviation of (0.36) across three instructional practices, namely planning, implementation, and assessment. The highest integration level was in assessment (M = 2.93, medium) while the lowest was in planning (M = 2.61, medium). The results also revealed that the participants’ perceptions towards integrating AI tools were highly positive (M = 4.00, high), albeit with some concerns regarding the effect of excessive and unguided use of AI tools on students’ higher-order thinking skills, particularly the risk of AI functioning merely as an information delivery mechanism rather than serving its more pedagogically valuable role as a brainstorming scaffold. Furthermore, the study unveiled a number of barriers to integrating AI tools, including the weakness of digital infrastructure, lack of professional development, the limited credibility of AI-generated content, and ethical concerns related to academic integrity and copyrights. The research suggests the establishment of a sustainable digital environment by improving the infrastructure, providing specific training in accordance with the principles of sustainability, and implementing policies that promote equitable, transparent, and responsible integration of AI. These strategies can coordinate the growth of technology with the larger needs of the quality of education, inclusion, and sustainability of STEM education in the long term. Full article

Massive Open Online Courses (MOOCs) serve as catalysts for sustainable education by democratizing access to lifelong learning. While this potentially positions them as a key driver of the United Nations Sustainable Development Goal 4 (SDG 4), their long-term impact depends heavily on the implementation of inclusive design and ethical governance. This study evaluates the social sustainability of the AKADEMA platform—defined through equity of access, institutional trust, and long-term learner retention—using Badrul Khan’s e-learning framework. Employing a multi-layered mixed-methods design, the study triangulates subjective user perceptions—gathered via quantitative surveys (N = 209; a convenience sample of 6140 contacted users) and qualitative insights (n = 122)—with objective structural evidence from a technical accessibility audit. Although the results indicate high satisfaction with pedagogical quality, the findings reveal specific structural nuances regarding platform inclusivity and user diversity. Specifically, data triangulation highlights a notable ‘privacy awareness gap’—where working professionals demonstrate higher sensitivity regarding data governance than learners—alongside structural barriers hindering ‘Universal Design’ for learners with disabilities. Consequently, to strengthen the sustainability of open education models, future strategies should emphasize digital equity and institutional trust, ensuring that technical environments align with the promise of inclusive quality education. Full article

Education for Sustainable Development (ESD) can support and strengthen responses to the environmental challenges faced today. However, the sustainability knowledge–action gap remains mostly unbridged. This article examines communication as a lever for learning and behavior change in sustainability education and compares the use of communication in conventional delivery and a narrative, dialogic and affective communication mode in secondary, university and community-based learning settings in a mixed-methods experimental study. Quantitative measures (pre-, post-, follow-up) included knowledge, systems thinking, emotional engagement, motivation and self-reported sustainable behaviors. Qualitative data, including interviews, observations and action research projects, were also collected to gain deeper insights into learner engagement with knowledge, systems thinking, emotional engagement and motivation. Results suggest that participants in the catalytic communication condition felt more cognitively and emotionally engaged than the control condition, and displayed more long-term pro-environmental behavior. Mediation analysis suggests that the increase in pro-environmental behavior may be driven by an increase in feelings of empathy and hope associated with the learning experience. This supports the understanding that tailored communication can help to reduce the knowledge–action gap in ESD and provides additional insights into the usefulness of cognitive, affective and behavioral dimensions of sustainability-oriented pedagogical approaches. Full article

This paper examines students’ perceptions of factors influencing normative support for the integration of AI Chatbots in universities, providing an empirical basis for developing institutional policies and implementation strategies in higher education. Framed within the sustainability perspective, the study examines how ethical, cognitive, and perceptual factors shape the long-term adoption of AI technologies in academic environments. Our study employs a structural model comprising 10 constructs, 46 items, and 9 hypotheses, tested on a sample of 408 economics students from Timisoara. The research identifies AI literacy as the most influential factor in the formal integration of these technologies in universities. The following factors have a direct impact: teacher perception, student perception, and cognitive risks (reliance on AI Chatbots and avoidance of intellectual effort). Use for personalized learning is a factor with a significant direct effect on positive perceptions and intentions to use AI Chatbots among students. Academic integrity risks, as well as limitations on accuracy and reliability, have no significant impact. AI Chatbots represent an essential opportunity to transform higher education. However, their positive impact is realized only through responsible formal integration, grounded in ethical policies, adequate digital education, and the adaptation of pedagogical practices. Universities must regard AI as a strategic ally for teachers and students, while keeping human interaction, critical thinking, and academic integrity at the centre of the educational process. The study argues that students’ perceptions are that universities must approach AI Integration as a strategic component of sustainable educational ecosystems, aligning innovation with long-term academic integrity and the objectives of sustainable development, particularly Sustainable Development Goal 4 (Quality Education). Full article

This study investigates the pedagogical value of integrating AI-supported feedback with Error Analysis in university-level English as a Foreign Language (EFL) writing instruction, where English is the target language (TL). Adopting a comparative, corpus-based design, the research examines whether AI-mediated feedback can complement traditional teacher-led Error Analysis in reducing recurrent errors, improving grammatical accuracy, and supporting revision practices among Spanish L1 learners of English at the B2 (CEFR) level. Seventy participants completed two writing tasks over a twelve-week period, generating a learner corpus that was randomly assigned to two groups: AI-assisted feedback and teacher-mediated feedback. Quantitative Error Analysis and learner-perception surveys were conducted to assess both linguistic outcomes and attitudinal responses. Results indicate that students receiving AI-assisted feedback demonstrated lower rates of error repetition (25%) compared to those receiving teacher-based correction (40%), particularly in subject–verb agreement, preposition use, tense selection, and L1-induced lexical transfer in L2 English writing. Survey findings further reveal higher perceived levels of clarity, usefulness, and immediacy for AI-generated feedback, although participants continued to value teacher input for higher-order writing concerns. Overall, the findings suggest that AI-supported Error Analysis can contribute to short-term error reduction and foster learner autonomy. This study highlights the potential of blended and mixed feedback models within a focused pedagogical context and underscores the need for longitudinal research examining long-term retention, pragmatic development, and cross-context generalizability. Full article

Engineering education is increasingly shaped by two converging developments: accelerating sustainability transitions and rapid advances in artificial intelligence (AI). However, in many application-oriented undergraduate programs, sustainability learning remains fragmented, methodologically limited, and weakly connected to authentic engineering decision-making. To address this gap, this study proposes AI-SEE (Artificial Intelligence-Integrated Sustainable Engineering Education), a pedagogical framework that integrates AI across the curriculum as both a cognitive scaffold and a resource for system-level analysis. Emphasizing human–AI collaboration, AI-SEE is designed to be feasible and scalable within application-oriented higher education contexts. The framework comprises four interrelated pillars: intelligence-driven, green-empowered, responsibility-leading, and practice-integrated. Drawing on an empirical case from transportation-related programs at Nantong University, the study employs a qualitative comparative design and conducts semi-structured interviews with 144 undergraduates at the end of their eighth semester (control group n = 70; pilot group n = 74). Interview data were analyzed using thematic analysis informed by constructivist grounded theory and the Gioia coding approach. The findings suggest that participation in AI-SEE is associated with differentiated patterns of sustainability consciousness. At the knowledge level, students reported more systematic and interdisciplinary understandings that extended beyond environmentally reductionist perspectives to include life-cycle thinking, social equity, and long-term considerations. At the attitudinal level, students described enhanced ethical reflexivity and evolving professional self-concepts, shifting from a focus on technical execution toward broader value-oriented roles. At the behavioral level, students reported more extensive knowledge-to-action translation across personal, academic, and career-related domains. Overall, AI-SEE provides a transferable pedagogical pathway for integrating AI into engineering education to support the development of sustainability consciousness in higher education. Full article

International trade policy constitutes a challenging subject for undergraduate students, as it requires the integration of historical, institutional, and quantitative perspectives. This study presents a digital learning framework designed to support the teaching of Ecuador’s trade policy trajectory between 1979 and 2024 through the use of open macroeconomic datasets, interactive visualizations, and guided data-analysis tasks. The framework combines historical interpretation with structured digital inquiry, allowing students to explore policy cycles, export composition, and institutional shifts using empirical evidence. A small-scale classroom implementation with economics and social science students (n = 48) indicates that the proposed approach supports students’ ability to recognize long-term economic trends and to relate policy decisions to broader development patterns. Rather than offering causal claims, the study provides exploratory evidence of how data-driven digital environments can enhance analytical engagement in policy-oriented courses. The framework is intended as a transferable pedagogical model for contexts where economic history, public policy, and digital learning intersect. Full article

The COVID-19 pandemic accelerated the global educational evolution towards hybrid education. However, little was investigated on the long-term sustainability of this shift within specific pedagogical domains, such as hybrid classroom management, in emerging economies. This paper assesses the sustainability of this shift by evaluating the hybrid classroom management experiences of Liberian junior and high school teachers. Employing a Hermeneutic Phenomenological Design (HPD), data were collected through 26 interviews and analyzed using a reflexive thematic analysis (RTA). The findings revealed crucial barriers to sustainability, including inadequate digital infrastructure, a lack of structured official digital programs in schools for implementation, and insufficient professional development. To address these gaps, the study proposes a targeted, actionable policy roadmap for the Ministry of Education and stakeholders, including the establishment of a territorial Certificate of Digital Competence (CDC), Green Classrooms Infrastructure Grant for energy supply, and a negotiation of National E-data. This study provides policymakers in Liberia and other developing nations with useful information about the current situation. By providing a baseline for policy intervention, this study advances the discussion on achieving Sustainable Development Goal (SDG4) for quality education within emerging economies settings. Full article