Search Results (11,264)

Techno-mathematical fluency (TmF) is the ability to coordinate mathematical knowledge with technological means—digital and non-digital—to solve mathematical problems and express solutions, by recognising affordances, selecting appropriate tools and data, and integrating them with mathematical ideas in iterative cycles of exploration and integration. It goes beyond instrumental tool use to encompass reasoning, modelling, representation, and communication mediated by technologies, and functions as a form of expertise important for both students’ learning and teachers’ professional practice. Full article

This study investigates how teacher-education undergraduates in Greece use, evaluate, and trust Artificial Intelligence (AI) in higher education, with particular attention to the gap between widespread adoption and limited epistemic trust. The topic is important because generative AI is rapidly entering universities, reshaping learning practices, academic integrity, and the legitimacy of knowledge, while learners often rely on systems whose outputs are not easily verifiable. The study focuses on future teachers because they are both current users of AI in higher education and likely future mediators of its use in school settings. Addressing this problem, the study contributes empirical evidence on how AI adoption relates to epistemic authority and institutional legitimacy within teacher education rather than across university students in general. A mixed-methods design was employed using a structured questionnaire completed by 363 teacher-education undergraduates from the University of Patras and the University of Ioannina in Greece; the sample was predominantly women (86.0%) and first-year students (92.6%). Quantitative responses were analyzed statistically, open-ended answers were examined thematically, and factor analysis was used to identify latent attitudinal dimensions. The findings indicate very high AI use in everyday life (92.6%) and study practices (81.3%), but only moderate trust: 1.4% reported complete trust and 12.1% generally trusted AI-generated answers. Six dimensions explained 61.73% of total variance, pointing to a layered attitudinal structure within this teacher-education population, consistent with an adoption–trust paradox and with the need for transparent, verifiable, human-supervised educational AI. The observed verification-based trust calibration may partly reflect an emerging pedagogical orientation toward source checking and responsibility for knowledge mediation, but given the strong concentration of first-year students, this should be interpreted as characteristic of early-stage teacher education rather than of university students more broadly. Full article

The Teachers’ Beliefs and Intentions Questionnaire (TBIQ) assesses educators’ beliefs and intentions regarding the importance of sensitive interactions with young children. Understanding these beliefs is particularly relevant in contemporary educational contexts where teacher–child interactions are viewed as central to children’s learning and development. Despite its use in several countries, there is no validated Spanish version available. This study aimed to translate, culturally adapt, and psychometrically validate a Spanish version of the TBIQ for early childhood education settings in Chile. Following international guidelines for cross-cultural adaptation, the questionnaire was translated into Spanish and administered to early childhood teachers and assistant teachers working in public early childhood education centers. The original two-factor structure (Beliefs and Intentions) was tested using confirmatory factor analyses with robust estimators for ordinal data. Results supported the two-factor model after removing six items with low factor loadings and indicated excellent model fit. Both scales demonstrated high internal consistency. However, measurement invariance across educator roles could not be established, and cross-group comparisons should be interpreted with caution. Despite this limitation, the Spanish version of the TBIQ demonstrates adequate validity and reliability and offers a brief and accessible instrument for research and for the assessment of educators’ beliefs and intentions regarding interaction quality in early childhood education. Full article

Policy learning under delayed reward conditions remains a significant challenge for end-to-end reinforcement learning (RL) agents. The difficulty increases for problems that require long-term planning and the execution of multiple dependent subtasks. As a result, solutions based on a single monolithic policy often suffer from unstable training. One possible solution to this problem could be to delegate the long-term planning to a separate model. This paper presents an implementation comprising two models: a large language model (LLM) for long-term planning and an execution model that solves subtasks. The execution model was trained via distillation from multiple teacher models trained with RL on individual tasks. The results presented in this paper demonstrate the benefits of this approach. By delegating long-term planning to the LLM, the agent can solve more complex problems than end-to-end agents trained with the proximal policy optimization (PPO) algorithm. Full article

Emotional intelligence and teaching self-efficacy are essential competencies for teachers’ professional and personal development. The aim of this study was to evaluate the effectiveness of a psychoeducational intervention to enhance both areas in future teachers. A quasi-experimental design with pretest and posttest measures was implemented, including an experiment. An eight-week program was conducted using active, reflective, and participatory methodologies to promote emotional awareness and confidence in teaching abilities. The OSTES instrument was used to measure teaching self-efficacy, the TMMS-24 to assess perceived emotional intelligence, and the EQ-i to evaluate socioemotional competencies, and. Results revealed significant improvements in the experimental group in emotional attention, clarity, and repair; in instructional strategies, classroom management, and student engagement; as well as in adaptability, interpersonal skills, stress management, and overall emotional intelligence. These effects ranged from moderate to large in magnitude and contrasted with the stable scores in the control group. The findings confirm that psychoeducational interventions focused on emotional competencies can be effective in strengthening emotional intelligence and self-efficacy in pre-service teachers. These outcomes suggest that such programs may contribute to the promotion of well-being and teaching effectiveness during initial teacher education, offering implications for future curricular development in teacher training programs. Full article

This study developed and validated a multidimensional instrument to assess teachers’ perceptions and attitudes toward the reuse of treated sewage effluent (TSE) in agriculture, a key sustainability strategy in water-scarce regions such as Qatar and the wider Gulf Cooperation Council (GCC). Using factor-analytic validation procedures on data from 444 teachers, the study confirms a robust five-factor model comprising Perceived Knowledge and Awareness, Attitudes, Pedagogy, Perceived Limitations, and Sources of Knowledge, demonstrating strong psychometric properties. Beyond validation, the findings provide insight into how educators understand and engage with wastewater reuse as an educational and sustainability issue. While teachers generally demonstrate sound conceptual understanding and positive attitudes toward sustainability, persistent concerns related to health risks, food quality, and cultural acceptability reveal a notable cognitive–behavioral gap. Although respondents express strong support for student-centered pedagogical approaches, including experiential learning and technology-enhanced instruction, implementation is often constrained by limited curricular guidance, time pressures, and insufficient professional development. These findings have important implications for sustainability education policy and teacher preparation in arid contexts pursuing water resilience strategies. Recommendations include integrating TSE-related content across disciplines, expanding experiential professional development opportunities, and strengthening curricular frameworks that support applied sustainability education. The validated instrument offers a transferable model for comparable regions globally, enabling cross-cultural research and evidence-based interventions in sustainability education. Full article

Background: During the early years of the coronavirus disease 2019 (COVID-19) pandemic, many schools found their staff, specifically teachers, adapting their roles to address social and health challenges, such as food insecurity and health literacy. Given the challenges these school-based communities faced, and continue to face, a clear gap was exposed during these early years of the public health crisis: a lack of community-centered professionals who can assist with social health factors impacting health and well-being. Methods: In this descriptive report, we examine the process and implementation of training two teachers to become community-centered professionals, specifically community health workers (CHWs), to serve schools located in socioeconomically challenged neighborhoods of urban regions. We explore their training and how these CHW–teachers prescribed social health interventions across four major domains: (a) access to medical and environmental equipment, (b) mental health challenges, (c) food insecurity, and (d) health literacy. We describe the specific interventions they implemented and the potential economic value and practicality of the overall initiative. Outputs: In less than one year, two teachers were successfully trained as CHWs in and for underserved communities. These CHW–teachers conducted informal surveys based on objectives of health themes that aligned with absenteeism. Both the process and implementation of the CHW training and CHW-led school-based interventions proved cost-effective and practical. Conclusions: Having CHW–teachers in schools is practical, may offer economic value, and is likely to complement additional health initiatives at schools (e.g., school nurses). As a small-scale pilot initiative, further studies should evaluate CHW–teacher impact on school-based goals, such as attendance rates, while this report focuses on early implementation processes. Full article

The rapid institutional and technological transformations of the 2020–2025 period have had a significant impact on teacher professional identity. Drawing on Rosa’s social acceleration thesis and Harvey’s concept of time–space compression, this scoping review examined the dimensions of professional identity emerging in the literature published between 2020 and 2025 among in-service pre-kindergarten through 12th grade (PK-12) teachers, the educational contexts in which these dimensions were addressed, and how they interrelate. Following the PRISMA-ScR guidelines, 45 peer-reviewed articles retrieved from the Scopus and Web of Science databases were analyzed through inductive thematic coding and a dimension–context interaction matrix. Six analytically distinct yet interrelated identity dimensions were identified: Biographical and Personal, Professional and Pedagogical, Emotional and Psychological, Social and Relational, Political and Agentic, and Prospective and Imagined. These dimensions were organized within a dialogical space model distinguishing internal/individual and external/structural domains. The Emotional and Psychological dimension achieved near-universal representation, while the Prospective and Imagined dimension remained the least studied. Six convergence, five divergence, and six gap patterns were identified across seven educational contexts. The findings reveal that, in this period, teacher professional identity is not a fixed attribute carried by the individual but rather a dynamic process continuously negotiated under structural pressures. Full article

Existing adult-report survey measures provide crucial information about children’s executive function (EF) development across contexts, but lack cultural relevance and ecological validity. To address these limitations, we introduce the Executive Function from Observation and Reflection Tool (EFFORT), a publicly available, open-source item bank designed for cross-cultural adaptation that includes 32 parallel items for caregivers and teachers across six EF domains: sustained attention, response inhibition, interference suppression, working memory, cognitive flexibility, and planning/organization. EFFORT additionally includes 10 assessor report items intended for use following a structured, standardized assessment session. This study presents the first validation of the tool within seven countries (Argentina, Australia, Bangladesh, Haiti, South Africa, Sri Lanka, United States) leveraging caregiver, teacher, and assessor observations of 1738 children (aged 3–11 years). Findings revealed acceptable fit for a six-factor structure for caregiver and teacher reports that were not empirically distinct, but yielded highly reliable composites. We further validated a 12-item short form for caregivers and teachers that demonstrated strong unidimensionality, gender invariance, and age-related increases. We demonstrated significant convergence of a short-form caregiver and teacher composite with the assessor-reported measures, as well as convergence of all three adult reports with direct assessments of children’s EF skills. This new tool holds promise to advance the science of how children develop and apply EFs to accomplish everyday goals across different cultural settings and in understudied populations. Full article

Artificial intelligence (AI) tools are increasingly integrated into mathematics education, yet most reviews emphasize achievement rather than how AI shapes mathematical thinking. This scoping review mapped literature published between 2020 and 2026 on AI-supported mathematics learning through three cognition frameworks: APOS (Action–Process–Object–Schema), Sfard’s process–object duality and reification, and Conceptual Image theory. Searches were conducted in Scopus, Web of Science, ERIC, PsycINFO, Education Source, and IEEE Xplore, followed by duplicate removal and Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR)-aligned screening. Twenty-one peer-reviewed studies met inclusion criteria (18 empirical studies plus three theoretically oriented studies). Evidence growth accelerated after 2022, with most studies situated in secondary and higher education. Large language models (LLMs) and Intelligent Tutoring Systems (ITS) were the most frequently investigated modalities. Across studies, AI commonly supported theoretically inferred action-level execution and procedural management (APOS) via adaptive feedback, hinting, and stepwise scaffolding, and it often broadened learners’ conceptual images through multiple representations and generated explanations. However, these interpretations were necessarily cautious, because very few studies directly operationalized theory-linked conceptual mechanisms such as process internalization, object encapsulation, reification, or alignment between conceptual images and formal definitions. In LLM-supported contexts, gains in explanation quality coexisted with risks of procedural outsourcing when students relied on generated solutions without prior reasoning. By contrast, ITS-based environments more often supported tightly structured procedural engagement, suggesting that different AI modalities afford different forms of cognitive support and risk. Overall, AI’s conceptual impact appears to depend less on tool availability and more on instructional orchestration (task design, prompting, and teacher mediation). The findings also suggest that sustainability-related dimensions—particularly learner agency, transparency of AI support, and equitable participation—are closely connected to whether AI use promotes durable conceptual learning rather than superficial performance gains. Future research should operationalize cognitive transitions, assess structural understanding, and report AI-use conditions transparently to support cumulative, theory-driven synthesis. Full article

Background: Despite the availability of safe vaccines, Ethiopia’s human papillomavirus (HPV) vaccine uptake remains suboptimal, particularly among out-of-school girls (OOSGs). This study examines the effect of multi-channel demand generation messages in two districts to determine which interventions most effectively improve uptake. Methods: A convergent mixed-methods design was employed across four districts in the Somali and South Ethiopia regions, with Jigjiga and Derashe serving as intervention sites and Gode and Kolango Zuria as controls. For the quantitative component, 950 sample households were recruited using cluster sampling. The qualitative inquiry involved 27 in-depth interviews (IDIs) and 16 focus group discussions (FGDs) within the intervention sites. Results: A total of 950 caregivers and 1134 girls completed the survey. Awareness was significantly higher among caregivers (AOR: 4.42; 95% CI: (3.06, 6.39)) and girls (AOR: 7.63; 95% CI: (3.49, 16.67)) in intervention sites, as well as among in-school girls (AOR: 13.46; 95% CI: (4.09, 41.90)). The mean vaccination coverage reached 71%, with significantly higher rates in intervention sites (AOR: 4.07; 95% CI: (2.29, 7.23)) and among in-school girls (AOR: 47.16; 95% CI: (20.23, 109.9)). Interpersonal communication—via teachers, peers, community health workers and vehicle-mounted promotion—was more effective in influencing awareness, attitude and uptake. Barriers for OOSGs included limited access to vaccination sites, low campaign awareness, misconceptions and gender-related issues. Conclusions: Appropriate demand generation strategies effectively enhance HPV awareness and vaccine uptake, yet a significant equity gap remains, as only one-third of OOSGs received the vaccine compared with 85% of in-school girls. Targeted interventions are recommended for OOSGs focused on both access to service and context-specific demand creation to address this disparity. Full article

The rapid proliferation of generative artificial intelligence (GenAI) tools has created an urgent need for instruments to evaluate their educational value as teachers, faculty, administrators, and instructional designers consider adopting them. While rubrics exist to assess mobile applications and virtual reality tools, no comparable instrument has been developed specifically for large language models (LLMs) and AI media generators. The authors reviewed existing evaluation rubrics for edtech and GenAI tools, with edtech meaning digital tools that support ethical teaching to improve student learning and GenAI referring to neural networks that simulate human interactions by contextualizing relevant content based on learning needs. Grounded in Waks’ framework, the resulting Edu-GenAI Rubric comprises multiple dimensions organized into five domains: the Instrumental, Technical, Hedonic, Use, and Beneficial values. Dimensions include accuracy, productivity, personalization, citation, user interface, user experience, sharing, storage, and ethical dimensions encompassing data privacy, data transparency, guardrails, fair use, and algorithmic discrimination. The Edu-GenAI Rubric offers decision-makers with a preliminary, theory-informed instrument for evaluating GenAI tools in educational contexts that can be applied to institutional adoption decisions, developer benchmarking, and future research. Full article

This study proposes an innovative instructional approach to promote scientific literacy by integrating the Nature of Science and the Nature of Scientific Inquiry with experimental practice and the history of physics. The aim is to foster a deep understanding of how scientific knowledge is constructed and to promote informed trust in science. Using an explicit and reflective methodology, the intervention combines experimental activities with historical reflection. The core of the learning sequence is the experimental reconstruction of Galileo’s studies on falling bodies, based on the historical manuscript folio 116v, an original document that provides the empirical evidence for the law of falling bodies, illustrating the transition from raw experimental data to mathematical formalization. Through this activity, students engage with key epistemic aspects of scientific practice, including the management of uncertainty—distinguished into statistical/aleatory and structural/epistemic forms—the probabilistic nature of scientific knowledge, the predictive power of models and theories, and the underdetermination of scientific theories. Additional themes addressed include the role of thought experiments, the importance of communicating results for scrutiny and validation, the function of models as mediators between theory and phenomena, and the process of de-idealization. The study also challenges the persistent myth of a single, linear “scientific method,” highlighting instead the theory-laden character of scientific inquiry and the central role of the scientific community. This dimension is explored through the historical comparison between Galileo and Mersenne, which illustrates elements of the scientific ethos and the role of peer review as a mechanism for the correction and refinement of knowledge. The results obtained with pre-service teachers, with whom this instructional sequence was implemented, indicate that this contextualized approach facilitates the overcoming of a view of science as a set of absolute truths. Instead, it promotes a more mature understanding of science as a dynamic, provisional, and self-correcting human enterprise, while equipping future citizens with the critical tools necessary to navigate the challenges of the twenty-first century. Full article

Despite significant advances in AI language models, Modern Standard Arabic (MSA) remains a linguistically complex domain in which apparent fluency often masks deeper grammatical instability. This study investigates recurrent grammatical error patterns in ChatGPT-generated Arabic texts, focusing on how these patterns reflect underlying morpho-syntactic challenges and the constraints of probabilistic language generation. Adopting a qualitative, pattern-oriented analytical framework, the study draws on online focus group discussions with secondary-level Arabic teachers, who served as expert linguistic evaluators. Participants collaboratively examined a set of AI-generated texts to identify and interpret systematic grammatical deviations across five key domains: agreement, inflection and case marking, sentence structure, prepositions and transitivity, and cross-linguistic influence. The findings indicate that grammatical errors in AI-generated Arabic are not random but occur as recurring, structured patterns, particularly in contexts involving long-distance dependencies and morphologically complex constructions. These patterns suggest a reliance on surface-level fluency at the expense of deeper grammatical coherence, reflecting limitations in maintaining consistent morpho-syntactic relationships. This study contributes by identifying and characterizing systematic grammatical patterns in AI-generated MSA as interpreted through expert linguistic judgment, offering a qualitative perspective that complements existing quantitative approaches and advances understanding of how large language models engage with morphologically rich languages. Full article

Inclusive leadership and collective teacher efficacy are key dimensions for understanding school improvement processes in Latin America. To synthesize recent developments in the field, this systematic review—conducted in accordance with the PRISMA protocol—aimed to: (1) compile the quantitative and qualitative evidence on inclusive leadership and collective teacher efficacy from empirical studies carried out in Latin America between 2015 and 2025, and (2) identify current trends and main gaps in the scientific literature, considering the educational reality of the region. Searches conducted in Web of Science, Scopus, and ERIC resulted in the selection of ten studies that met the established methodological criteria. The findings indicate that inclusive leadership promotes structures for participation, professional collaboration, and the creation of positive school climates, while collective teacher efficacy emerges as a shared perception influenced by organizational support, staff cohesion, and opportunities for collaborative work. The reviewed studies primarily focus on teachers working at the primary and secondary education levels. Overall, the evidence outlines a field in consolidation that offers valuable insights into the development of school leadership policies and the strengthening of inclusive educational cultures in Latin America in the future. Full article