Search Results (263)

This research aimed to evaluate the emotional intelligence of future teachers and its relationship with attitudes towards people with disabilities, sexism, and bullying behaviors. Using a non-experimental design under a quantitative approach, 1004 future teaching subjects were selected by convenience sampling from different Faculties of Education in Spanish universities. The following instruments were applied online: for emotional intelligence, the TMMS-24; for bullying assessment, the Bullying Questionnaire-CAME; the General Scale of Attitudes towards People with Disabilities (2016) and the Ambivalent Sexism Inventory (ASI). Results indicated that both male and female future teachers exhibited low levels of emotional intelligence. A correlation was observed between greater emotional intelligence and more positive attitudes towards people with disabilities, as well as a lower tendency towards sexism. Additionally, a relationship was found between greater emotional attention and a lower tendency to bully from the victim’s perspective. These findings highlight the importance of developing emotional intelligence in future teachers to improve their interactions with students and promote a more inclusive and respectful school environment. Full article

The aim of this article is to identify the effectiveness of a teacher education program based on student perceptions. In this aim, a longitudinal research project was carried out with a sample of 14,229 students at a Spanish university who evaluated their teachers (using a Likert-type scale) after they completed a teacher training program. The CEDA teacher evaluation scale (α = 0.968; ω = 0.968) was used to assess students’ perceptions of the instructor’s role as a facilitator of learning. Complementary qualitative information was also collected, which complemented the quantitative findings. The first conclusion is the positive impact of key variables of the teacher training program: the pedagogical model, educational innovation, and evaluation strategies. Secondly, the students’ perception was slightly better in relation to the pedagogical model, followed by evaluation strategies and finally educational innovation. Thirdly, although students generally rated the teaching of technical subjects more highly than the humanities, the perception of change linked to teacher training was positive for all subjects. Finally, there was a slight difference in students’ perceptions according to the academic course (second, third, or fourth). All of the above should be considered for future teacher training programs. Full article

This study evaluates the effectiveness of the newly restructured 1st Grade Turkish Language Curriculum within the “Century of Türkiye Education Model” using Stufflebeam’s Context, Input, Process, and Product (CIPP) framework. The aim is to examine the program’s contribution to sustainable and inclusive educational practices and to provide implications for similar developing contexts. In the research, a convergent parallel mixed method design was used simultaneously with 112 primary school teachers working in Adana, one of the largest cities in Türkiye, in the 2024–2025 academic year. Quantitative data were obtained through the CIPP Evaluation Scale, analyzed with descriptive statistics, t-tests, and ANOVA, while qualitative data from semi-structured interviews were subjected to content analysis. Results indicated generally positive teacher perceptions, highlighting contextual relevance, cultural alignment, flexible structure, and engaging content as strengths. However, limitations included insufficient adaptation for disadvantaged students, superficiality in some content, infrastructure inequalities, and assessment inadequacies. Process-related strengths included constructivist activities and instructional guidance, though time constraints and classroom incompatibilities were noted. In terms of outcomes, the program was found to enhance language and social skills. Demographic analyses revealed limited differences, mainly by gender, professional experience, and educational background. This study concludes with multidimensional recommendations addressing teacher training, resource equity, assessment diversity, international best practice adaptation, and future longitudinal research. Full article

Teaching is a complex profession that demands simultaneous cognitive and emotional efforts. The present study aims to determine whether teachers’ emotional intelligence moderates the relationship between psychosocial risk factors and burnout. A cross-sectional online survey was conducted among 215 secondary school teachers. Measurement instruments included the Burnout Assessment Tool (BAT-23) to assess burnout dimensions; the Health and Work Survey (INSAT) to evaluate psychosocial risk factors; and the Wong and Law Emotional Intelligence Scale (WLEIS-P) to assess emotional intelligence. A mediation/moderation analysis using the PROCESS macro was conducted to examine whether emotional intelligence mediates/moderates the relationship between psychosocial risk factors and burnout among teachers. The results show that psychosocial risk was a significant positive predictor of burnout (B = 0.313, p = 0.001), indicating that higher perceived risk was associated with higher burnout symptoms. Emotional intelligence did not significantly predict burnout on its own (B = 0.176, p = 0.364), and the interaction term (psychosocial risk × emotional intelligence) was not significant (B = 0.000, p = 0.995), suggesting that emotional intelligence does not moderate the relationship between psychosocial risks and burnout. These findings underscore a more holistic approach to address burnout, centered in intervention strategies that include a deeper analysis of organizational context determinants. Full article

The significance of children’s mathematical competence during the early years is well established; however, the methods for developing such competencies remain less understood. Specifically, there is a need to identify what constitutes high-quality educational environments and effective instruction. Both the study and promotion of high-quality educational environments and teaching, through coaching and other professional development initiatives, necessitate the use of observational instruments that are reliable, efficient, and valid, including content, internal, external, and consequential validity. Moreover, domain-specific measures are essential, as general quality measures often fail to adequately assess curriculum content, scope, or sequence, and they do not reliably predict improvements in children’s learning outcomes. This study employed innovative analytical techniques to evaluate the scoring and interpretation of an existing domain-specific observational measure: the Classroom Observation of Early Mathematics Environment and Teaching (COEMET). We applied non-linear modeling approaches (i.e., Random Forest [RF] and Generalized Additive Models [GAMs]) to investigate and provide a comprehensive overview of the relationships between COEMET’s measures—at both the scale and item levels—of teachers’ practices and children’s mathematical competencies. The study first employed the RF machine learning method to identify the most important COEMET items for prediction, followed by the use of GAMs to depict the non-linear relationships between COEMET predictors and the outcome variable. The analysis revealed that certain teaching practices, as indicated by the COEMET items, exhibited non-linear and even non-monotonic associations with children’s mathematical competencies. Full article

Artificial Intelligence (AI) tools have transformed academic writing and literacy development in higher education. Students can now receive instant feedback on grammar, coherence, style, and argumentation using AI-powered writing assistants, like Grammarly, ChatGPT, and QuillBot. Moreover, these writing assistants can quickly produce completed essays and papers, leaving little else for the student to do aside from reading and perhaps editing the content. Many teachers are concerned that this erodes critical thinking skills and undermines ethical considerations since students are not performing the work themselves. This study addresses this concern by synthesizing and evaluating peer-reviewed literature on the effectiveness of AI in supporting writing pedagogy. Studies were selected based on their relevance and scholarly merit, following the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines to ensure methodological rigor and quality. The findings reveal that although AI tools can be detrimental to the development of writing skills, they can foster self-directed learning and improvement when carefully integrated into coursework. They can facilitate enhanced writing fluency, offer personalized tutoring, and reduce the cognitive load of drafting and revising. This study also compares AI-assisted and traditional writing approaches and discusses best practices for integrating AI tools into curricula while preserving academic integrity and creativity in student writing. Full article

Our study tracks the development of 105 Roma children between 3 and 5 (median age: 51 months), enrolled in an NGO-aided developmental program. Each child undergoes pre- and post-assessment based on the Developmental Assessment of Young Children (DAYC), a standard tool used to track the progress in early childhood development and detect delays. Data are gathered from three sources, teacher, parent/caregiver and specialist, covering four developmental domains and adaptive behavior scale. There are subjective biases; however, in the post-assessment, the teachers’ and parents’ evaluations converge. The test results confirm significant improvement in all areas ($p<0.0001$), with the highest being in cognitive skills $32.2\%$ and the lowest being in physical development $14.4\%$. We also apply machine learning methods to impute missing data and predict the likely future progress for a given student in the program based on the initial input, while also evaluating the influence of environmental factors. Our weighted ensemble regression models are coupled with principal component analysis (PCA) and yield average coefficients of determination $R^2\approx 0.7$ for the features of interest. Also, we perform k-means clustering in the plane cognitive vs. social–emotional progress and consider the classification problem of predicting the group in which a given student would eventually be assigned to, with a weighted $F_1$-score of $0.83$ and a macro-averaged area under the curve (AUC) of $0.94$. This could be useful in practice for the optimized formation of study groups. We explore classification as a means of imputing missing categorical data too, e.g., education, employment or marital status of the parents. Our algorithms provide solutions with the $F_1$-score ranging from $0.92$ to $0.97$ and, respectively, an AUC between $0.99$ and 1. Full article

Emotional education is essential in teacher training processes, but historically it has been neglected in the training system. The purpose of this study was to design and psychometrically validate the EEITT Scale, an instrument that assesses the perception of knowledge acquired about emotional education in student teachers and practicing teachers. A quantitative, descriptive and comparative approach was used with 548 participants, applying confirmatory factor analysis and invariance analysis to evaluate the model. Confirmatory factor analysis showed that the model fit well and had high reliability scores, which backs up the validity and internal consistency of the EEITT for measuring perceptions about emotional education training. Statistically significant differences were identified between groups, with students reporting greater social-emotional learning in the four factors evaluated. Likewise, a negative and significant effect of age on the perception of emotional education training was observed. These findings highlight the importance of emotional education in teacher training and point to the need for educational policies that integrate holistic and continuous approaches throughout the teaching career. Despite its limitations, this instrument provides relevant tools for future research and for guiding the design and improvement of teacher training practices. Full article

The integration of Artificial Intelligence (AI) in education has raised important questions about its role in supporting inclusive practices, particularly in special education. This qualitative-dominant study with quantitative support examines how special education teachers in inclusive primary classrooms in Greece use ChatGPT to design Individualized Education Programs (IEPs) for students with learning disabilities. Six teachers participated, with some employing ChatGPT and others relying on traditional methods. The quality of IEP goals was described using the Revised IEP/IFSP Goals and Objectives Rating Instrument (R-GORI), while in-depth teacher perspectives were explored through thematic analysis. Findings suggest that ChatGPT contributed to clearer goal-setting, generation of diverse instructional resources, and more structured lesson planning. However, teachers emphasized the need for critical oversight, adaptation to real-world classroom conditions, and safeguarding the relational and emotional aspects of teaching. Participants expressed cautious optimism, viewing ChatGPT as a valuable support tool when integrated thoughtfully and ethically. These context-specific, exploratory results offer preliminary guidance for educators, policymakers, and researchers seeking to integrate AI tools into special education. They highlight the importance of targeted professional development, ethical safeguards, and further large-scale research to evaluate the broader applicability of AI-assisted IEP planning. Full article

This mixed-methods study investigated the dispositions and motivations of 118 K-12 teachers in Abu Dhabi regarding lifelong learning. Employing a sequential explanatory design, quantitative data were collected using a validated 40-item Likert scale survey across five domains: Goal setting, Application of knowledge and skills, Self-direction and evaluation, Locating information, and Adaptable learning strategies. Results indicated a moderate overall disposition toward lifelong learning, with the highest motivation observed in Self-direction and evaluation. Significant gender differences favored male teachers across all domains. The recommendations stress the need for developing goal-setting abilities, improving information accessibility, and encouraging adaptive learning strategies through focused professional development programs. Full article

This study investigated the impact of preparing lesson plans and conducting microteaching activities—aligned with the learning outcomes of the mathematics curriculum—on the development of sustainability beliefs among teacher candidates. The rationale behind this research stems from the growing global emphasis on sustainability and the urgent need to embed sustainability literacy into teacher education programs, particularly in disciplines such as mathematics, which are often perceived as abstract and value-neutral. There is a recognized gap in equipping pre-service teachers with the pedagogical skills and conceptual awareness needed to integrate sustainability meaningfully into mathematics instruction. Employing a mixed-methods design, the Sustainability Belief Scale was administered to 45 teacher candidates (22 in the experimental group and 23 in the control group) as both a pre-test and post-test. During the intervention, participants in the experimental group collaboratively designed lesson plans and delivered them through microteaching sessions. Throughout the process, they maintained individual reflective journals. The lesson plans and microteaching performances were evaluated using instructor-developed rubrics. Data were analyzed using both quantitative statistical techniques and qualitative content analysis. The findings indicate that integrating sustainability themes into mathematics education significantly enhances teacher candidates’ sustainability beliefs and informs their pedagogical orientations. This study underscores the importance of structured, practice-based learning experiences—such as sustainability-focused microteaching—as a means to develop the competencies needed for education for sustainable development in mathematics classrooms. Full article

(1) Background: Aimed at improving school children’s motor, social, emotional, and cognitive competence (CC), the effects of physical activity (PA) have been widely investigated. However, investigations into the effects of PA during Physical Education (PE) on children’s CC have only been subject to growing interest among researchers in recent years. To bring it, the present article aims to systematically summarize the PE intervention programs whose effects on school children’s CC have been evaluated through a randomized controlled trial (RCT) design. (2) Methods: This systematic review follows the PRISMA guidelines and has been registered in PROSPERO: CRD420251083924. A systematic literature search was conducted across four electronic databases: PubMed, SCOPUS, Web of Science, and ProQuest Central. The articles were included based on the following inclusion criteria: (i) primary education children, (ii) children practicing PE, (iii) outcomes related to CC, and (iv) articles providing evaluations through RCTs. The quality assessment of all included articles was performed using the PEDro scale. (3) Results: Out of 219 initially identified studies, 25 met the inclusion criteria and were synthesized qualitatively. (4) Conclusions: The main outcomes highlighted that PE has a positive effect on primary school children’s cognitive ability, including attention, creativity, memory, academic performance, and inhibitory control. Thus, elementary school teachers are encouraged to implement these intervention programs to foster children’s CC. However, different types of interventions should be analyzed to highlight their effects on different variables of CC. Full article

This systematic review aims to provide a comprehensive and up-to-date overview of the most effective identification protocols used to detect giftedness in primary school students, intended to be used by teachers, parents, and diagnostic professionals. This review, registered in PROSPERO (CRD420251064093), analyzed studies published between 2019 and 2024 in the PsycINFO, Web of Science, and Scopus databases. It included articles published in English or Spanish and focused on multidisciplinary fields. A total of 17 studies were selected and evaluated for quality using the Newcastle–Ottawa Scale. The findings highlight the effectiveness of using multiple tools in the identification process, grouped into teacher nominations, family nominations, and tools for diagnostic professionals. This multidimensional approach helps reduce false negatives and supports the identification of underrepresented and twice-exceptional students. In conclusion, the identification of giftedness should be grounded in methods that prioritize general cognitive abilities over IQ scores and academic achievements. Full article

Over the past two decades, rising concerns about teacher stress and professional sustainability have fueled the development of instruments assessing teacher resilience. This review aims to map the existing resilience assessment tools specifically designed for educators, evaluating their theoretical frameworks, psychometric soundness, and contextual relevance. Twelve instruments were analyzed through an extensive literature review of peer-reviewed studies published over the past twenty years, including general, preservice, EFL, and teacher-specific scales for special education. Findings reveal a progression from early instruments emphasizing intrapersonal traits to current tools incorporating ecological and contextual dimensions. While several scales demonstrate satisfactory reliability and cross-cultural applicability, many still suffer from conceptual limitations, insufficient cultural adaptation, or marginal psychometric robustness. This review concludes that despite significant advances, future research must prioritize culturally grounded frameworks, broader subgroup validation, and advanced psychometric methodologies to ensure accurate, inclusive, and practical assessments of teacher resilience across diverse educational settings. Full article

Introduction: Burnout syndrome, long described as an “occupational phenomenon”, now affects 15–20% of the general workforce and more than 50% of clinicians, teachers, social-care staff and first responders. Its precise nosological standing remains disputed. We conducted a mechanistic review of electroencephalography (EEG) studies to determine whether burnout is accompanied by reproducible brain-function alterations that justify disease-level classification. Methods: Following PRISMA-adapted guidelines, two independent reviewers searched PubMed/MEDLINE, Scopus, Google Scholar, Cochrane Library and reference lists (January 1980–May 2025) using combinations of “burnout,” “EEG”, “electroencephalography” and “event-related potential.” Only English-language clinical investigations were eligible. Eighteen studies (n = 2194 participants) met the inclusion criteria. Data were synthesised across three domains: resting-state spectra/connectivity, event-related potentials (ERPs) and longitudinal change. Results: Resting EEG consistently showed (i) a 0.4–0.6 Hz slowing of individual-alpha frequency, (ii) 20–35% global alpha-power reduction and (iii) fragmentation of high-alpha (11–13 Hz) fronto-parietal coherence, with stage- and sex-dependent modulation. ERP paradigms revealed a distinctive “alarm-heavy/evaluation-poor” profile; enlarged N2 and ERN components signalled hyper-reactive conflict and error detection, whereas P3b, Pe, reward-P3 and late CNV amplitudes were attenuated by 25–50%, indicating depleted evaluative and preparatory resources. Feedback processing showed intact or heightened FRN but blunted FRP, and affective tasks demonstrated threat-biassed P3a latency shifts alongside dampened VPP/EPN to positive cues. These alterations persisted in longitudinal cohorts yet normalised after recovery, supporting trait-plus-state dynamics. The electrophysiological fingerprint differed from major depression (no frontal-alpha asymmetry, opposite connectivity pattern). Conclusions: Across paradigms, burnout exhibits a coherent neurophysiological signature comparable in magnitude to established psychiatric disorders, refuting its current classification as a non-disease. Objective EEG markers can complement symptom scales for earlier diagnosis, treatment monitoring and public-health surveillance. Recognising burnout as a clinical disorder—and funding prevention and care accordingly—is medically justified and economically imperative. Full article