Purpose Universities worldwide are under increasing pressure to embed sustainability across curricula, yet language programs remain largely peripheral in institutional sustainability strategies. Existing frameworks – such as UNESCO’s Education for Sustainable Development guidelines and Wiek et al.’s model of key competencies – outline what students should know and do, but they offer limited direction on how psychological factors shape the uptake of these competencies. This paper aims to address this gap by positioning self-efficacy as a central mechanism influencing student learning outcomes in sustainability-integrated language education. Design/methodology/approach This conceptual paper proposes a model for embedding sustainability competencies into language curricula while integrating self-efficacy theory. Drawing on sustainability education, competency-based curriculum design and socio-cognitive theory, it synthesizes prior scholarship to link sustainability competencies, curriculum features and student learning outcomes in language-learning contexts. Findings The proposed model shows how systems thinking, anticipatory reasoning, strategic action and interpersonal competence can be cultivated through language-based tasks. It argues that authentic problem scenarios, reflective activities, dialogic tasks and formative feedback can strengthen students’ sustainability-related self-efficacy and, in turn, support both linguistic development and sustainability competency outcomes. Research limitations/implications The paper offers design principles for higher education institutions and language programs seeking to integrate sustainability across disciplines, including guidance on competency-aligned task design, scaffolding and feedback practices that support student confidence and engagement. It also outlines a research agenda to empirically examine the proposed relationships. Originality/value The contribution reframes language curricula as strategic sites for sustainability learning and introduces self-efficacy as a missing psychological dimension in sustainability-oriented language pedagogy, offering a theoretically grounded model that connects competencies, curriculum design and learner outcomes.

This article examines how virtual mobility and collaborative international projects are becoming essential strategies for the internationalization of higher education, enabling students from diverse backgrounds to participate in global experiences without physical or geographical barriers. These modalities, including COIL programs and hybrid experiences, foster intercultural competencies, effective communication, critical thinking, and remote collaboration, while promoting inclusion, equity, and academic diversity. The research was based on a literature review, document analysis, and case studies, identifying best practices, emerging trends, and challenges related to the digital divide, curriculum adaptation, and faculty preparation. The findings show that structured pedagogical design, adequate technological infrastructure, and strategic institutional collaboration are fundamental to maximizing the impact of these experiences, strengthening international partnerships, and offering meaningful and sustainable learning. In short, virtual mobility and collaborative projects are transforming contemporary higher education, contributing to the development of globally competent professionals prepared to thrive in multicultural and digital environments.

Power-Optimized AI-Enhanced Telepresence Robots: A Validated Multi-Modal Framework for Sustainable Remote Learning in Higher Education

The high accuracy achieved by deep learning techniques has made them indispensable in computer vision applications. However, their substantial memory demands and high computational complexity limit their deployment in resource-constrained environments. To address this challenge, this study introduces a Feature Enhancement Module (FEM) as part of a unified hybrid compression framework that combines mixed-precision quantization and structured pruning to improve model efficiency. Experimental results on the Tiny ImageNet dataset using ResNet50 and MobileNetV3 architectures demonstrate the strong adaptability and scalability of the proposed approach. Compared with state-of-the-art compression methods, the proposed FEM-based framework achieves up to 6% improvement in Top-1 accuracy, while reducing memory usage by 32.26% and improving inference speed by 66%. Furthermore, the ablation study demonstrates that incorporating the FEM module leads to up to 24% improvement over the baseline model, highlighting its effectiveness. The results further show that FEM effectively preserves inter-channel feature representation stability even under aggressive compression, making it well suited for real-time processing and practical Artificial Intelligence (AI) applications. By maintaining semantic richness while significantly reducing computational cost, the proposed method bridges the gap between high-performance deep models and lightweight, deployable solutions. Overall, the FEM-based hybrid compression framework establishes a scalable and architecture-independent foundation for sustainable deep learning in resource-limited environments.

Instructor clarity is a central component of instructional communication and has been consistently associated with positive academic outcomes; however, less evidence exists regarding the mechanisms through which it influences student interest in higher education contexts. From a sustainability perspective, understanding these mechanisms is essential for promoting inclusive, equitable, and high-quality learning environments in line with global educational goals. This study fills a gap in the literature by examining, through multivariate models, the relationship between instructor clarity and student interest as mediated by academic satisfaction and state motivation, within the framework of the Rhetorical/Relational Goals Theory in the Spanish higher education context. A quantitative, cross-sectional, ex post facto research design was employed using a survey method. A non-probabilistic convenience sampling approach was used. A total of 258 undergraduate students from the University of Extremadura enrolled in the Bachelor’s Degree in Early Childhood Education and the Bachelor’s Degree in Primary Education participated in the study. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), including an assessment of the model’s predictive capability. The results indicated that instructor clarity was positively associated with academic satisfaction, state motivation, and student interest, with the first two variables acting as complementary mediators in these relationships. Among the predictors, state motivation emerged as the strongest determinant of student interest, whereas the direct effect of instructor clarity was comparatively weaker, highlighting the relevance of indirect pathways. The model demonstrated high predictive power and strong predictive validity with respect to student interest. Overall, the findings indicate that instructor clarity influences student interest primarily through its indirect effects on academic satisfaction and state motivation, emphasizing the importance of fostering motivational processes as key mechanisms linking teaching practices with students’ learning outcomes in higher education. Finally, it should be noted that the findings are directly aligned with Sustainable Development Goal (SDG) 4, contributing to Target 4.3 by enhancing the effectiveness and equity of teaching in higher education, as well as supporting the development of sustainable learning environments that foster long-term student engagement and academic persistence.

The widespread use of innovative pedagogies at all educational levels, from early childhood to higher education, has signaled a significant change in educational practice in the twenty-first century. Emerging pedagogical strategies such as gamification, play-based learning, flipped classrooms, blended and hybrid models, and AI-driven adaptive systems are all thoroughly analyzed in this review. The reviewed literature also reveals enduring structural challenges, including gaps in teacher preparation, digital inequities, curriculum misalignment, exclusion of marginalized learners, and ethical concerns regarding student data, even though these approaches have raised opportunities for personalized learning, learner engagement, and skill development. This review incorporates details about health-related consequences that are frequently only briefly discussed in pedagogical research, in addition to instructional results. Screen fatigue, cognitive overload in younger pupils, psychological anguish, digital burnout, and social isolation are among the reported results the effect both students and teachers. The review shows that the health effects of innovative pedagogies differ significantly by educational level and instructional design by combining evidence from various foreign contexts and developmental stages. The paper stresses how important it is to match technology advancement with human-centered teaching methods and design concepts that prioritize health. In order to promote fair, sustainable, and health-promoting learning environments across the educational lifecycle, it ends with specific suggestions for educators, educational technology developers, legislators, and medical professionals.

Urban forests are strategic components of urban green space systems because they provide ecological, recreational, and educational functions that collectively support sustainable urban environmental quality. This study aims to formulate an ideal model of an urban forest concept as a sustainable educational tourism site based on empirical findings derived from visitor perceptions and the ecological conditions of the Pekanbaru Urban Forest. The research employed a simple mixed-method approach dominated by descriptive quantitative analysis involving 96 respondents, complemented by ecological observations and in-depth interviews with site managers. The results indicate that cleanliness and comfort received positive assessments (scores 4.21 and 4.12), whereas environmental education facilities (3.88), educational activities (3.45), and promotional efforts (3.22) fell within the moderate to low categories. These findings highlight a significant gap between the ecological potential of the area and the development of its educational functions. A synthesis of empirical data and theoretical insights produced six components of the ideal urban forest concept: (1) adaptive ecology, (2) environmental education facilities, (3) interpretive trails, (4) sustainable educational tourism programs, (5) inclusive accessibility, and (6) collaborative governance. Policy analysis further demonstrates that strengthening the educational function aligns with the mandates of Law No. 26/2007 on Spatial Planning, SDG 11.7 targets regarding inclusive green spaces, and the Pekanbaru Strategic Environmental Assessment (KLHS) emphasizing the enhancement of environmental quality. This study concludes that the integration of ecological planning, educational development, and collaborative governance forms the essential foundation for positioning urban forests as centers of sustainable environmental learning

Self-directed learning (SDL) has become a central pedagogical expectation in secondary and post-secondary education, particularly within boarding school contexts that emphasise independence, self-management and autonomous learning routines. However, students with elevated autistic traits often encounter persistent challenges in engaging with self-directed learning environments, despite demonstrating adequate cognitive ability and academic potential. In boarding schools, difficulties in independent learning are frequently interpreted as low motivation, poor discipline or lack of effort, resulting in interventions that prioritise compliance and behavioural monitoring rather than the underlying regulatory processes shaping learning preferences. This paper is conceptual and does not report primary data. Drawing on contemporary literature related to autistic traits, psychological regulation and learning autonomy, this conceptual review synthesises evidence to examine how autistic traits influence students’ preferences for self-directed learning through the mediating role of psychological regulation. Evidence across five interrelated strands which (a) autistic traits in non-clinical student populations, (b) psychological regulation demands in boarding school environments, (c) self-directed learning characteristics and expectations, (d) institutional and contextual influences in residential schooling and (e) psychological regulation as a mediating mechanism suggests that difficulties with emotional, cognitive and behavioural regulation significantly constrain students’ readiness to engage in self-directed learning. Across studies, psychological dysregulation manifested through heightened stress, anxiety, cognitive overload and reduced self-management capacity emerges as a key mechanism shaping students’ learning preferences. Rather than reflecting an aversion to autonomy, lower preference for self-directed learning among students with autistic traits may represent adaptive responses to regulatory demands that exceed individual coping thresholds. Building on this synthesis, the paper proposes an integrated conceptual framework positioning psychological regulation as a central pathway linking autistic traits to self-directed learning preferences in boarding school contexts. This reframing highlights the need for learning environments that align autonomy expectations with students’ regulatory capacities to support sustainable, inclusive and self-directed learning outcomes.

With the rapid integration of artificial intelligence (AI) tools into academic English learning, understanding how learners’ AI-related competencies influence their motivational and emotional experiences has become increasingly important. Drawing on frameworks of technology enhanced learning and foreign language emotions, this study examines the relationship between AI literacy and foreign language boredom in AI-assisted academic English learning, with a particular focus on the roles of learner engagement and task value. Survey data were collected from 392 postgraduate students and analyzed using Exploratory Factor Analysis and Structural Equation Modeling. The results indicated that AI literacy played a foundational role by positively associating with both learning engagement and perceived task value. Learning engagement was found to reduce levels of foreign language boredom and academic pressure, whereas academic pressure emerged as a strong positive predictor of foreign language boredom. Interestingly, perceived task value showed a positive association with boredom, suggesting that highly valued academic English tasks may simultaneously evoke emotional fatigue in high demand learning environments. There is no moderating effect of perceived task value on the relationship between engagement and boredom. Overall, the findings highlight the complex interplay between AI-related competencies, motivational processes, and emotional experiences in AI-assisted foreign language learning. The study underscores the importance of fostering AI literacy and sustained learning engagement while also addressing academic pressure to promote emotionally sustainable AI-supported language learning environments.

The concept of quality education has undergone a profound and multidimensional transformation in the 21st century, shifting from a narrow emphasis on access, enrolment, and participation to a more comprehensive and dynamic framework encompassing equity, inclusivity, relevance, sustainability, and measurable learning outcomes. Situated within the global policy architecture of Sustainable Development Goal 4 (SDG 4), which advocates for inclusive and equitable quality education and lifelong learning opportunities for all, this paper critically interrogates the evolving paradigms that define and shape quality education in contemporary contexts. Adopting a qualitative, descriptive-analytical methodology, the study draws upon an extensive review of international policy documents, global education reports, and peer-reviewed scholarly literature to identify and synthesize key emerging trends. These include the rapid digital transformation of education systems and the integration of educational technologies, the growing prominence of competency-based and outcome-oriented learning frameworks, the expansion of inclusive and equity-driven pedagogical practices, the intensification of globalization and internationalization in education, and the increasing reliance on data-driven governance and accountability mechanisms. The paper further problematizes the uneven and asymmetrical realization of these trends across different socio-economic and geopolitical contexts by examining persistent structural challenges such as widening inequalities in access and outcomes, the digital divide, resource constraints, disparities in teacher capacity and professional development, and the enduring gap between policy formulation and effective implementation. It critically argues that quality education can no longer be understood as a static or universal construct; rather, it must be reconceptualised as a context-sensitive, adaptive, and transformative process that integrates cognitive, social, emotional, ethical, and sustainable dimensions of learning. By foregrounding the interconnections between global policy frameworks and localized educational realities, the study contributes to the ongoing discourse on redefining quality in education in an era marked by rapid technological change, socio-economic uncertainty, and global interdependence. The paper concludes by proposing a set of forward-looking policy recommendations that emphasize systemic reform, inclusive innovation, strengthened public investment, and the development of resilient and future-ready education systems capable of addressing the diverse needs of learners in the 21st century.

The global imperative for digital transformation presents a complex challenge for Nigeria's higher education sector, a system grappling with immense demographic pressure and chronic resource constraints. This article provides a systemic analysis of this transformation, structured around its economic implications, managerial challenges, and societal shifts. Employing a qualitative research methodology based on a systematic review of academic literature, policy documents, and institutional reports, the study examined the multidimensional nature of this transition. The economic analysis reveals a critical tension between the high capital expenditure required for digital infrastructure and the precarious funding models of public universities, while also exploring nascent opportunities for revenue diversification. The managerial dimension uncovers significant challenges in strategic planning, change management, human capital development, and quality assurance, which collectively impede effective implementation. Societally, the research highlights the profound risk of the digital divide exacerbating existing inequalities, alongside fundamental shifts in pedagogical roles and the cultural value of the traditional university experience. The analysis is framed by an integrated theoretical model combining the Resource-Based View (RBV), the Technology Acceptance Model (TAM), and Actor-Network Theory (ANT). This framework facilitates a robust discussion, revealing that technological adoption is not a simple input but a complex process of network alignment. The study concludes that successful digital transformation in Nigerian higher education requires a holistic, strategically managed, and equity-focused approach. It offers targeted, multi-level recommendations for policymakers, university administrators, and other stakeholders to cultivate a sustainable and inclusive digital learning ecosystem capable of meeting Nigeria's 21st-century developmental goals.

Purpose: This qualitative study investigates how poverty impacts the implementation of play-based pedagogy (PBP) in Early Childhood Education (ECE) centres in Mutare Rural, Zimbabwe. While PBP is globally recommended as a developmentally appropriate practice, its feasibility in low-resource, rural contexts remains critically under-researched. This study addresses this gap by examining the specific barriers poverty creates, the adaptive strategies educators employ and how socio-economic deprivation shapes the nature of children's learning. Methodology: Data were collected through semi-structured interviews with 5 ECE educators, focus group discussions with 20 caregivers and systematic observations across ten purposively selected ECE centres. Thematic analysis revealed that poverty fundamentally reconfigures PBP from a child-centred, exploratory ideal into a practice of 'survivalist adaptation Results: Key findings show that severe material scarcity and infrastructur al deficits create 'pedagogical deserts,' while chronic child hunger directly impairs the cognitive energy necessary for engagement. In response, ECE educators engage in exhausting, unsupported labour, improvising with local materials and indigenous games in a process of 'innovation by desperation.' Conclusions: The study concludes that poverty does not merely weaken PBP but actively produces an alternative, constrained pedagogy. It argues for an integrated policy response that combines material support, context-specific teacher training in low-resource PBP and the formal curricular integration of indigenous play practices to foster sustainable and equitable early learning.

ABSTRACT Non-profit organisations (NPOs) in Mexico have historically lacked strategic emphasis on knowledge management. However, the loss of government funding has pushed many to adopt new administrative and learning strategies to remain viable. This qualitative case study examines how 10 women-focussed NPOs, previously funded by the National Institute for Women (INMUJERES), have developed organisational cultures that foster knowledge sharing and learning. Based on interviews and MAXQDA-assisted analysis, the study finds that organisations with adhocracy cultures (e.g. National Women’s Civic Alliance, Gaviota Safe Haven) exhibited more structured learning processes linked to strategic planning and resource mobilisation. Those with clan cultures (e.g. Mountain House Support Center, Life Achievement Initiative) fostered informal learning through collaboration and mentoring. The findings underscore the importance of leadership style, human capital, and cultural alignment in embedding sustainable organisational learning practices in resource-constrained environments.

This study aims to describe the use of digital folklore media "Asal-Usul Surabaya" as an Indonesian learning medium for instilling values in elementary schools. This research uses a qualitative approach with a case study type. Data were collected through in-depth interviews using semi-structured interview guidelines, participant observation with observation sheets and field notes, and documentation studies. The data is analyzed interactively which includes the stages of data reduction, data presentation, and conclusion/verification. The results of the study show that: (1) Media implementation requires pedagogical adaptation of teachers and is supported by visionary school policies; (2) Media succeeds in increasing student engagement in a multimodal manner and functions as a common ground for learning; (3) Narrative understanding and internalization of students' character values increases, although there are technical and cognitive constraints that require improvement of media design. The discussion linked the findings to TPACK theory, cognitive theory of multimedia learning, and multimodal literacy, which confirmed that success is determined by the synergy between school policies, teachers' pedagogical competence, and inclusive media design principles. Digital folklore is an effective learning medium for elementary Indonesian. Its effectiveness is multifactorial, depending on the school's policy support, the teacher's ability to design and mediate learning, and the quality of the media design itself that takes into account the technical and cognitive aspects of the students. This study recommends a holistic approach in adopting similar media to ensure sustainability and optimal learning impact.

<span>The global pandemic was a great challenge to delivering education in Nigerian schools. This undoubtedly came with a sudden shift to remote learning when teachers and students alike had to adapt to emergency remote education. Although, the prediction of international organizations on the effect of school closure during pandemic perhaps stimulated the emergent of remote teaching and learning (RTL) globally and particularly, in Nigeria. However, it was observed that the innovation and reformation has provided opportunities for transformation through borderless learning which is actually apt for situations like the COVID-19 pandemic. This article therefore, utilized naturalistic observation strategy to explore the impact of this shift on sustainable teaching and learning in schools in Ekiti State, Nigeria. It discusses the concept of emergency remote education as it relates to Nigerian education system. More importantly, it exposed the technology usage in classroom practices in Ekiti State, Nigeria vis a vis, the experiences of teachers and students in emergency remote education, highlighting the platforms employed, successes recorded and challenges encountered in the process. It was concluded that stake holders in Nigerian education system have been navigating unexplored territory to ensure continuous learning. Recommendations were made on how to improve the practice of remote education in Nigeria.</span>

This study examines the impact of digital stressors (technostress, digital fatigue, AI dependency) on digital burnout and Sustainable Development Goal (SDG) achievement among Chinese and international EFL learners, investigating the mediating roles of foreign language anxiety and the moderating effect of technology self-efficacy. Using a cross-sectional survey design with n = 545 university students, we employed structural equation modeling (SEM) and multigroup analysis (MGA) to test the hypothesized relationships. The findings confirm a significant sequential pathway where digital stressors increase foreign language anxiety, which subsequently exacerbates digital burnout, ultimately impairing SDG achievement. Crucially, technology self-efficacy served as a vital buffer, significantly weakening the negative impact of burnout on learning outcomes. Multigroup analysis revealed these effects were significantly stronger for international students, who also demonstrated higher vulnerability to digital stressors but benefited more from self-efficacy. The study's novelty lies in its integrated model that uncovers the psychological mechanisms translating digital challenges into educational outcomes, while highlighting crucial cross-cultural variations. These findings offer imperative implications for developing tailored pedagogical interventions that leverage self-efficacy training and differentiated support systems to foster more equitable and sustainable digital learning ecosystems for diverse student populations.

Smart windows for sustainable learning: a multi-climate assessment of adaptive glazing technologies

ABSTRACT Metaverse is rapidly evolving as a digital ecosystem combining immersive virtual and augmented reality with persistent social spaces. While not originally designed for education, the metaverse holds potential for higher education by offering possibilities for embodied learning, rich interaction and authentic practice. Yet, the psychological demands of engaging with educational content in such environments remain underexplored. One potential drawback is technostress, which is the stress from adapting to complex digital systems. If neglected, technostress may largely hinder learning. In addition, it is vital to explore the coping responses that higher education learners use to mitigate technostress. This mixed-methods study investigates how higher education students experience technostress in the Metaverse, identifying main technostressors and learners’ coping strategies. Survey data from 78 Finnish university students and follow-up interviews with 31 participants revealed that technostress is multidimensional, spanning cognitive, emotional, physical and social dimensions. The findings show a significant difference in technostress between male and female participants. In addition, the study advances technostress theory by conceptualising it as both cognitive and embodied. This study offers practical recommendations for developers, educators and policymakers seeking to design inclusive and psychologically sustainable learning in the metaverse. They highlight the need for gender-responsive design and user-centred improvements***.

Language learning anxiety poses a significant challenge for English Language Teaching (ELT) in Indonesian education; however, traditional methods frequently neglect its neurophysiological foundations. Therefore, it is imperative to investigate learning anxiety through EEG-based brainwave monitoring. This review study examines how EEG assessments identify specific brainwave types, brain regions, and treatments for learning anxiety. A systematic literature review (SLR) approach adhered to PRISMA guidelines. The flow diagram results indicate that out of 250 articles identified from Scopus-indexed journals, 140 passed the initial screening stage, 90 were selected for further review, and only 30 met the inclusion criteria. These articles were categorized into three main themes: brainwave types, brain regions, and EEG treatment for anxiety. The findings indicated that EEG studies consistently and accurately detect learning anxiety through increased beta wave activity and decreased alpha and theta wave activity, particularly in the prefrontal cortex, which is linked to cognitive stress and emotional regulation dysfunction. Additionally, significant brain activation was observed in the frontal, prefrontal, parietal, and temporal regions, as well as in the limbic system. EEG-based interventions, such as neurofeedback and vagus nerve stimulation, were also found to be effective in reducing anxiety through non-pharmacological means. However, current research is still limited to experimental studies conducted in laboratory settings, which do not fully capture the dynamic nature of learning anxiety in real classroom contexts for better input of teaching strategies. The study implies that English language teaching should incorporate neuroscience-informed, anxiety-reducing strategies, providing practical insights for teachers to adapt instructional techniques and improve learning outcomes.

This study investigated the impact of prompt engineering competence, knowledge management, and task-individual-technology fit on the continued intention to use artificial intelligence (AI), as well as their implications for educational sustainability. Data from 437 undergraduate students who use AI tools for academic purposes were analyzed using PLS-SEM. The results indicated that prompt engineering competence significantly predicts knowledge acquisition and knowledge application, which, in turn, significantly predict both task-technology fit (TTF) and individual-technology fit (ITF). Furthermore, TTF and ITF were found to have significant impacts on the continuous intention, which, in turn, positively predicts educational sustainability through generative AI. The results of the multi-group analysis revealed that the hypotheses were supported in both the female and male samples and that the model maintained a consistent and robust structure across genders. Overall, the findings provide substantial evidence on how generative AI supports sustainable learning in education by developing prompt engineering skills, promoting effective knowledge management practices, and ensuring technology alignment.