Search Results (1,665)

This study explores how pre-service early childhood educators imagine and anticipate their upcoming practicum experience before entering the classroom, focusing on how schooling is both remembered and reimagined in advance of practice. Drawing on qualitative data from open-ended prompts in a Google Forms survey with undergraduate teacher education students, the study examines expectations regarding childhood, schooling, the teacher’s role, and practicum challenges. Using thematic analysis, the findings reveal persistent tensions in how participants conceptualize teaching and learning. While students frequently articulate child-centred and democratic ideals—emphasizing care, participation, and experiential learning—their responses simultaneously reproduce elements of the schoolized mind, through which schooling is imagined as structured by control, transmission, evaluation, and teacher authority. Practicum is anticipated both as a learning opportunity and as a moment of exposure requiring competence, classroom management, and error avoidance. The findings suggest that pre-service teachers approach practicum through already sedimented and socially shaped imaginaries of schooling. These anticipatory frameworks highlight the need for teacher education to critically engage with how schooling is imagined, better shaping future pedagogical practice. Full article

Brain–Computer Interfaces (BCIs) have increasingly been explored as tools for monitoring and modulating cognitive processes relevant to learning. However, their application to learning disorders, and especially to mathematical learning difficulties such as dyscalculia and ageometria, remains conceptually promising but empirically underdeveloped. The present study offers a scoping review with structured narrative synthesis of recent empirical research on BCI-based interventions in learning disorder populations, with particular attention paid to their possible translational relevance for mathematical learning. Following PRISMA-ScR principles and a Population–Concept–Context framework, studies published between 2020 and 2025 were identified through database searches in Scopus, IEEE Xplore, and PubMed. A total of 30 studies met the inclusion criteria. All eligible studies focused on Attention-Deficit/Hyperactivity Disorder (ADHD), while no eligible BCI intervention studies were found for dyscalculia or ageometria. The reviewed literature was dominated by EEG-based neurofeedback interventions. To move beyond descriptive summary, the included studies were organized using a structured analytical framework based on intervention modality, primary cognitive target, methodological robustness, and translational proximity to mathematical learning disorders. Across the evidence base, the most consistent findings concerned attention regulation and executive function outcomes, whereas academic and mathematics-related outcomes were sparse and methodologically less developed. Although several studies suggested improvements in domain-general cognitive mechanisms relevant to mathematical learning, the absence of direct evidence in dyscalculia and ageometria prevents confirmatory conclusions. The review therefore identifies both the promise and the limits of current BCI applications in learning disorder contexts and argues that future research should prioritize theory-driven, disorder-specific trials targeting numeracy, visuospatial reasoning, and executive processes in mathematical learning disabilities. Although current findings suggest promising cognitive and educational potential, these technologies are not yet ready for routine implementation in standard classroom environments without further validation, teacher training, ethical safeguards, and cost-effective deployment models. Full article

Farm-to-school initiatives, including school gardens, are an increasingly popular strategy to increase student access to healthy produce and nutrition education opportunities. While studies show school garden programs and garden-enhanced nutrition education can positively impact student consumption of fruits and vegetables, there is a gap in evaluation tools that can be used by practitioners across varied school sites, grades, and communities, to assess outcomes of their garden programs. This effort piloted the Student Garden Retrospective Survey (SGR) for grades 4+ in four classrooms in two counties in California. The instrument included items to measure program exposure, garden skill experiences, changes in students’ behaviors, preferences, and attitudes, as well as their perceptions of the program. Student and teacher feedback on the evaluation tool was gathered to determine if students understood the questions being asked, were able to complete the survey, and whether the evaluation questions were pertinent to their school gardening experiences. The results demonstrate that the SGR is suitable for evaluating school garden and garden-enhanced nutrition education programming. In the future, the evaluation tool can be used by practitioners to iteratively improve garden-based education to enhance students’ nutrition and health outcomes. Full article

Despite the existence of several systematic reviews and meta-analyses on co-teaching, research that includes student voice through students’ views and experiences is rare. This systematic review of 63 published and unpublished studies synthesises the experiences and views of students with and without disabilities when co-taught by a general and a special educator. Data were extracted from seven databases in July 2025. We used an assimilated approach to synthesise findings from qualitative, quantitative and mixed-methods studies through reflexive thematic analysis. Findings show that most students with and without disabilities perceive co-teaching as having positive academic, social, and affective impacts, with many preferring varied co-teaching models. Students valued support from special educators for all learners, but some reported frustration and limited academic benefits when collaboration between co-teachers was weak. Their voice calls for reconsidering co-teaching as an inclusive approach through changes in model implementation and co-teachers’ role delivery. Recommendations for future research include examining the distinct voices of students with and without disabilities and increasing their involvement as primary stakeholders in co-teaching research. Recommendations for policy and practice, particularly regarding students’ academic, social, and affective outcomes, highlight the importance of student engagement through participatory activities in promoting the inclusive orientation of co-teaching. Full article

Against the backdrop of uneven educational development and structural constraints in rural Mainland China, teacher agency is critical for driving professional growth and instructional improvement. Rural educators face distinct challenges—limited resources, isolated work contexts, and systemic pressures—that shape their capacity to enact change. While scholarship has documented the roles of contextual resources and individual beliefs in shaping teacher agency, less is known about the mediating mechanisms linking job resources and self-efficacy to agency within China’s rural educational landscape. This study examines how perceived job resources (teaching resources, administrative support, colleague support, parental support) and teaching self-efficacy collectively shape rural teachers’ agency, to inform policy and practice for strengthening their professional capacity. Drawing on a quantitative survey of 625 rural teachers, we employ a two-stage analytical approach: first, descriptive statistics, t-tests, ANOVA, and Pearson correlations to map baseline variable relationships; second, Hayes’ PROCESS macro (Model 4) with bootstrapping to test the mediating role of teaching self-efficacy between job resources and teacher agency. Findings reveal the following: (1) Rural teachers report moderate agency (M = 3.53/5), indicating room for growth; (2) All four job resource dimensions significantly and positively predict agency (β = 0.099–0.163); (3) Teaching self-efficacy is a robust predictor of agency (β = 0.785–0.822, p < 0.001) after controlling for resources; (4) Self-efficacy partially mediates the links between each job resource and agency, with indirect effects ranging from 0.269 (teaching resources) to 0.451 (colleague support), highlighting its central role in translating contextual resources into agentic action. We conclude that fostering rural teacher agency requires a holistic approach addressing both external job resources and internal self-efficacy. Policymakers and administrators should prioritize investments in teaching resources, collaborative support structures, and professional development to build educators’ confidence and competence. Limitations include self-report bias, cross-sectional design constraints on causal inference, and limited generalizability. Future research should use longitudinal designs and broader samples to deepen understandings of agency in structurally constrained educational settings. Full article

Among the basic principles in providing special education services is educational equity for students with disabilities, including those with intellectual disability (ID). The purpose of this study was to examine special education teachers’ perceptions toward the international concept of inclusive education for students with ID in Saudi Arabia. It also aimed to determine their perceptions of the impact of the international concept of inclusive education on students’ community integration. Over three months, the researchers conducted semi-structured interviews with 14 special education teachers who were teaching students with ID in Saudi Arabia. Six themes emerged from the participants’ responses including their understanding of: (a) the international concept of inclusive education, (b) the appropriate placement for students with ID, (c) how the international concept of inclusive education supports a students’ community integration, (d) the role and impact of curriculum modification, (e) strategies related to the international concept of inclusive education, and (f) challenges for the implementation of the international concept of inclusive education A discussion of the findings, limitations of this study, and the implications for future research were provided. Full article

Generative Artificial Intelligence (GenAI) is transforming higher education in terms of pedagogy, student involvement, and academic management. This systematic literature review examines 30 peer-reviewed articles published from 2019 to 2025, adhering to PRISMA 2020 and Kitchenham’s methodologies. Descriptive and thematic analyses highlight five opportunities: (a) tailored and adaptive education; (b) deliberate fostering of critical thinking; (c) enhanced accessibility for varied learners; (d) teaching innovation via multimodal content development and feedback; and (e) collaborative methods that regard AI as a co-teacher. Four ongoing challenge categories also surface: (a) risks to academic integrity; (b) excessive dependence on GenAI that may hinder learner independence; (c) inconsistent faculty preparedness and change-management abilities; and (d) differences in infrastructure and policy both regionally and globally. Intersecting ethical issues, such as data privacy, algorithmic bias, transparency, and accountability, highlight the necessity for governance that aligns with institutional risk and reflects societal values. Analyzing the recent literature, this systematic review offers four contributions: (a) a recommendation model for responsible GenAI implementation in higher education institutions; (b) a framework for sustainable integration of GenAI; (c) a highlight of the future research recommendations; and (d) an integrated policy and pedagogical recommendations roadmap. These models emphasize the integration of AI literacy, ethical considerations, and critical thinking goals into educational programs. The review advocates for a strategic, stakeholder-focused approach to implementation that enhances rather than replaces human instruction, thus connecting GenAI’s educational potential with ethical, context-aware avenues for institutional transformation. Full article

Objectives: Cardiovascular diseases (CVDs) represent the main global burden of morbidity and mortality, with an accelerated epidemiological transition in regions such as Latin America. The university environment constitutes a period of critical vulnerability due to increased sedentary lifestyles and cardiometabolic risk factors. The objective of this study was to evaluate the cardiovascular risk profile in a university community in the central Andean region of Colombia using anthropometric, haemodynamic and biochemical indicators. Methods: A cross-sectional, observational, and analytical study was conducted on a sample of n = 143 participants (students, teachers, and administrators) aged between 18 and 80 years. Haemodynamic parameters (SBP, DBP, MAP), anthropometric parameters (BMI, % body fat, waist-to-height ratio [WC/W]) and lipid profile were evaluated. Statistical analysis included multiple linear regression models to determine predictors of systolic blood pressure (SBP). Results: Significantly higher levels of SBP were found in the older age groups compared with the younger age groups, reaching stage 1 hypertension levels in the sixth decade. The biochemical profile revealed metabolic deterioration with an atherogenic index (TC/HDL) consistently above the clinical threshold (>4.5) in all groups. The regression model BMI was identified as the statistical predictor with the strongest association with SBP variability in the sample (β = 1.18), followed by age (β = 0.28). A marked sexual dimorphism was observed, with men presenting early haemodynamic risk, while women experienced an accelerated post-menopausal tension and metabolic crisis. Conclusions: The university community presents latent cardiometabolic vulnerability closely linked to modifiable anthropometric factors. These findings underscore the urgency of implementing institutional preventive health policies and weight control intervention programmes to mitigate the future burden of chronic diseases on campus. Full article

Teacher attrition, particularly in early career stages, undermines sustainable education. Developing teachers’ sense of agency and well-being is therefore critical, especially for second-career teachers who bring valuable prior knowledge and professional experience. This study explored how narrative pedagogy combined with agency-focused instruction supports second-career students’ professional development. Using qualitative methodology, we analyzed reflective compositions written by 12 special education students in a year-long course. Three main themes emerged: First, narrative approaches enabled students to develop their personal and professional identities. Second, participants experienced the approach as creating relational safety, a psychologically secure environment supporting authentic sharing and collaborative learning. Third, participants envisioned implementing agency processes with their future students while acknowledging systemic challenges. These insights underscore the potential contribution of incorporating narrative and agency-based approaches into teacher education. Such approaches may strengthen resilience and well-being as students transition into practice, thereby supporting reduced attrition and advancement of sustainable education goals. Full article

The rapid development of intelligent learning guidance systems has created a favorable environment for personalized learning. By accurately predicting students’ future performance, education can be tailored and teaching strategies optimized. However, traditional prediction algorithms seldom account for highly imbalanced datasets in basic education, overlook temporal factors, and lack further interpretability of the prediction results. To address these shortcomings, we propose Temporal Variational Autoencoder-Generative Adversarial Network (TVAE-GAN), a temporal variational autoencoder-generative adversarial network model aimed at providing early warnings for high-risk students in basic education, with in-depth interpretability analysis of the prediction results to suit the unique context of basic education. TVAE-GAN extracts features from real samples and introduces a Long Short-Term Memory (LSTM) network to capture dynamic features in time series, helping the model better understand temporal dependencies in the data, remember the sequential causal information of students’ online learning, and achieve better data generation performance. Using these features, the generative model generates new samples, and the discriminator model evaluates their quality, producing outputs that closely resemble real samples through training. The effectiveness of the TVAE-GAN model is validated on a collected online basic education dataset while also advancing the timing of interventions in predictions. The performance differences between the proposed method and classic resampling methods, as well as their impact in the educational field, are analyzed, highlighting that misclassification increases teacher workload and affects students’ emotions. Key influencing factors are identified using a decision-tree surrogate model, providing teachers with multidimensional references for academic assessment. Full article

Background/Objectives: Mental fatigue in adolescents is a growing concern in educational contexts, positioning physical education (PE) teachers as key agents in designing effective mitigation strategies. This study examined the perceptions of Spanish high school PE teachers regarding the causes, consequences, and potential countermeasures for students’ mental fatigue. Methods: A total of 116 in-service teachers (81 males and 35 females; mean teaching experience 7.8 ± 5.3 years) from 12 autonomous communities throughout Spain completed a comprehensive 34-item electronic questionnaire. The instrument assessed the perceived existence, etiology, and outcomes of mental fatigue through multiple-choice, dichotomous (yes/no), and five-point Likert scale questions, with particular attention given to the role of physical activity (PA) in symptom alleviation. A quantitative frequency analysis was conducted to examine the data. Results: The main findings reveal a strong consensus among the teachers (77.6% to 87.9%) on the prevalence of mental fatigue, with its primary causes attributed to academic pressure and sedentarism. The consequences were identified as increased irritability and reduced cognitive performance. The teachers overwhelmingly endorsed moderate intensity PA as the most effective countermeasure. However, a significant gap was identified between this theoretical awareness and the systematic implementation of targeted strategies within schools. Conclusions: These results underscore the critical need for professional development programs and structural support to translate teacher knowledge into practical intervention, suggesting important directions for future research. Full article

The increasing integration of Generative AI (GenAI) into higher education, particularly in the domain of language teaching, presents both opportunities and challenges. While AI-powered tools such as ChatGPT-5 can support language learning by generating personalised content which enables real-time interaction and feedback, they also risk perpetuating biases embedded in training data. These biases can appear in linguistic, cultural or socio-political forms, reinforcing stereotypes and influencing language norms. Therefore, equipping students and educators with strategies to critically assess AI outputs is essential for ethical and responsible AI use in language education. While recent research highlights the risks of algorithmic bias, less attention has been given to the perceptions and attitudes of pre-service teachers, whose future practice will shape classroom uses of these technologies. This exploratory pilot study adopts a survey-based approach to examine pre-service teachers’ baseline awareness of bias in artificial intelligence, with particular attention to linguistic and cultural dimensions Data were collected through an online questionnaire administered to 65 undergraduate students enrolled in Primary Education degree programmes. The study documents baseline perceptions prior to any instructional intervention and provides preliminary empirical evidence to inform the future design of pedagogical strategies aimed at developing critical AI literacy in teacher education. Full article

The practice of employing education students as unqualified teachers in schools has grown over the last three years as the teacher shortage across Australia and the world worsens. This study uses a Bacchian approach to critically analyse the “problem” of pre-service teachers (PST) undertaking teaching roles as unqualified personnel whilst concurrently completing their teaching degrees through the lens of university lecturers working within the Initial Teacher Education (ITE) space. Qualitative semi-structured interviews were conducted with eleven university lecturers. A Bacchian analysis of the discourse arising from these interviews was conducted and followed two distinct groupings, those being between the student and employer, and the student and the university. The silences within these discourses were found to be the voices of the university lecturers working within the ITE programmes since they were not given a seat at the negotiation table between schools and registering bodies, prior to the student undertaking a teaching contract. These findings demonstrate the need for strategies that engender greater awareness of and support for, PST working in the school system, where all stakeholders are actively involved in the implementation of a holistic, purposeful and accountable approach to addressing the teacher shortage in sustainable, future focused endeavours. Full article

Artificial intelligence (AI) can help students accelerate assignment completion, but it may also foster cognitive outsourcing and learning detached from authentic contexts. This paper presents E3-HOT, a conceptual framework that leverages embodied intelligence to sustain learners’ cognitive agency and higher-order thinking for sustainable learning, aligned with SDG 4 (Sustainable Development Goal 4) and its emphasis on inclusive and equitable quality education and lifelong learning. Using an iterative conceptual synthesis, we distill three embodied pathways—situational embedding, embodied participation, and cognitive creation—and translate them into a practical system design with a three-module E3 core. It includes a virtual–real integrated learning environment for rich scenarios, embodied interaction for action and sensing, and an intelligent core that provides bounded and teacher-controlled support. To facilitate equitable adoption across resource-diverse settings, we specify multi-fidelity enactment options and an auditable set of evidence artifacts for subsequent expert review and future validation studies. We further provide an illustrative university human–AI design project that outlines a week-by-week workflow and corresponding evidence plan, presented as a worked example rather than a report of an implemented study. E3-HOT offers a traceable design-and-evidence blueprint without claiming measured learning gains. Full article

The accelerated expansion of artificial intelligence (AI) is reshaping economic systems, labour markets and democratic life, giving rise to hybrid human–AI societies. In this context, education becomes a strategic arena for enabling sustainable and socially just transitions within the Fourth Industrial Revolution. This article examines how digital competence can be reconceptualized to prepare future citizens and educators for these emerging societal configurations, with particular attention to the Ibero-American context. A conceptual framework is proposed that integrates algorithmic literacy, critical data awareness, AI ethics, human–AI collaboration skills, and civic and socio-emotional capacities as core dimensions of “next-decade” digital competence. Methodologically, the study combines three complementary approaches: (a) a structured review of interdisciplinary literature on AI, digital competence and sustainability; (b) an analysis of international and regional policy documents and competence frameworks relevant to Ibero-America; and (c) selected empirical insights drawn from the first author’s doctoral research on digital competence and AI use in teacher education. The findings reveal significant tensions between rapid AI adoption and persistent structural inequalities in the Global South, while identifying key leverage points for aligning teacher education, public policy and institutional strategies with the Sustainable Development Goals. The proposed framework aims to support policymakers, universities and international organizations in fostering inclusive and sustainable AI-driven social change while mitigating new forms of exclusion and dependency. Full article