Amartuvshin Deleg

This study examined attitudes toward artificial intelligence (AI) among pre-service primary school teachers in Mongolia and evaluated the psychometric properties of a Mongolian adaptation of the Students’ Attitudes toward Artificial Intelligence (SATAI) scale. A cross-sectional survey yielded an analytic sample of 672 students at a public teacher education university, randomly divided by academic-year strata into exploratory (n = 334) and confirmatory (n = 338) subsamples. Factor-retention criteria disagreed, and the exploratory solution did not match the component grouping of the source adaptation. A model reproducing that structure fitted poorly and yielded an inadmissible solution. Of seven measurement models estimated from polychoric correlations by diagonally weighted least squares, a bifactor model fitted best (CFI = 0.975; TLI = 0.970), although RMSEA remained 0.086; a four-factor model fitted comparably, but its factor correlations (0.86–0.93) failed the Fornell–Larcker criterion for every pair. Omega hierarchical (0.949) and explained common variance (0.876) indicated a dominant source of common variance, while subscale-specific reliability was limited; internal consistency of the total score was high (α = 0.972). Attitudes were moderately positive (M = 3.59, SD = 0.85), with enjoyment and educational relevance endorsed more strongly than everyday application and self-rated competence. Metric and scalar invariance across academic years was supported by change-in-fit criteria, and fourth-year students scored higher than all earlier cohorts. The findings favor cautious use of the total score rather than subscale scores, and they provide a descriptive basis for designing and then evaluating structured, ethically informed AI preparation in teacher education rather than evidence that such provision is effective.

Teacher education plays a crucial role in preparing teachers to teach about climate change and its impacts on nature and society. This study analyzes the pre-service teacher education curricula at the Mongolian National University of Education (MNUE) to determine the current state of integrating climate change education (CCE) into teacher education in Mongolia. This study aims to identify CCE current practices, gaps, and challenges. Terms related to climate change and/or climate change education have been extracted from the learning objectives of the SDG 13 “Climate Action” according to United Nations Educational, Scientific and Cultural Organization and the extent of their occurrence in the syllabi of all courses offered by the MNUE’s undergraduate schools has been analyzed. The analysis has revealed that the terms only appeared in 24 courses, mostly professional education courses, and CCE is not emphasized in the curricula. According to the findings, CCE is found in only two course syllabi, and the extracted terms have not been directly incorporated into any of the five sections of those syllabi. However, the study has identified some good practices that can be built upon to enhance the integration of CCE into teacher education. The findings of the study provide a foundation for further research and development of strategies to mainstream CCE in the teacher education schedule.

Based on the CiteSpace visualization analysis method, this study systematically examines the research status, key issues, and development trends in the field of social-emotional learning (SEL) in China from 2012 to 2024. The study finds that SEL research in China has showen a trend of continuous growth and has gradually expanded to different school-age groups, including primary school students, preschool children, adolescents, and middle school students. The research hotspots mainly focus on topics such as emotional intelligence, school bullying, and teacher-student relationships, reflecting the important role of SEL in improving students’ mental health and promoting positive social behavior. In addition, this study reveals the current situation of cooperation among SEL research teams in China and finds that there is limited cross-regional and cross-institutional academic cooperation. Through quantitative analysis of the evolution of SEL research in China, this study provides a systematic review and offers valuable references for scholars, educational practitioners, and policy makers to promote the localization of SEL in China. In the future, further strengthening academic cooperation, optimizing the SEL curriculum system, and combining successful international experiences will help improve the effectiveness of SEL in China's education system and promote students’ all-round development and social adaptability.

Mathematics is a subject with numerous applications in everyday life but it is often viewed as difficult leading to math anxiety among students. This anxiety can limit students' career options and affect their success. To address this issue, we investigated the factors contributing to math anxiety among university and college students. This study focused on students from the National University of Mongolia (NUM) and the Mongolian State University of Education (MSUE). We used the Mathematics Anxiety Rating Scale questionnaire (A-MARS) developed in 1972 by Richardson and Suinn and conducted various statistical tests including factor analysis, correlation analysis and regression analysis to analyze the data. Our results show that teacher-related factors have a strong negative correlation with math anxiety (β=-0.583) while family-related factors (β=-0.311) and student-related factors (β=-0.133) have weaker correlations. Possible explanations for these findings include inadequate teaching and professional skills, poor communication between students and teachers, heavy task loads and outdated resources. This study highlights the importance of these factors to reduce math anxiety and promote success in mathematics education.