School dropout intention and reduced academic achievement are two crucial indicators of school dropout risk. Past studies have shown that school performance plays a mediating role in the models explaining dropout intentions. School burnout and test anxiety have been identified as predictors of both academic performance and school dropout. However, their combined effects on the intention to leave school have not yet been investigated. We aimed to address this gap by exploring the predictors of school dropout intention in a sample of 205 French secondary school students. Structural equation modelling analyses have revealed the specific facets of school burnout (devaluation) and test anxiety (cognitive interference) that explained the school dropout intentions and academic performance. Grade Point Average (GPA) was a mediator of the effects of these variables on the intention to drop out of school. The findings highlight the need to acknowledge assessments as a school stress factor that could contribute to health problems and intentions to drop out of school.

The world is looking forward to advancements in artificial intelligence (AI) technology, with significant research underway regarding the application of AI in education. This study analyzed publications on the potential of AI in secondary schools, focusing on its bibliometric aspects. Data from the Scopus database revealed 1,764 publications from 2019 to 2024. The analysis showed a steady annual growth in publications in this area. China and the USA were the leaders in the number of publications. Xiaoyue Wang was the most prolific researcher, having authored 71 AI-related articles. Yueying Li, Xiaoxu Chen, Yanzhu Zhang, and Yi Liu contributed to the field with 56, 55, 53, and 51 articles, respectively. The themes that emerged from 2019 to 2022 are related to media, application, study, institutions, artificial, digital, learning, factors, development, technologies, medical, automated, perception, support, and sustainability. From 2023 to 2024, the topics discussed in AI are related to students, education, perception, algorithms, digital, prediction, networks, challenges, writing, teachers, AI-powered, curriculum, century, integration, technology, and framework. The difference in research in 2019-2022 and 2023-2024 is focusing the theme's focus from the general to the specific. The co-occurrence analysis revealed that prominent keywords appeared in 3 clusters. Cluster 1 is the most popular in recent times. It deals with the application, assessment, and management of AI. Cluster 2 relates to AI relationships and models, while Cluster 3 relates to AI data sources.

Psychological capital (PsyCap) emerges as a pivotal asset for mitigating student burnout in college settings, as it bolsters their learning empowerment and engagement. However, there have been inadequate empirical studies investigating the significance of these resources in promoting engagement and empowerment, ultimately leading to a reduction in students’ burnout within the context of higher education. To bridge this gap, we examined the extent to which PsyCap predicts student burnout through its impacts on academic engagement and learner empowerment. The sample of the study was college students (N = 562) who completed a battery of self-report questionnaires measuring their PsyCap, academic engagement, learner empowerment, and student burnout. We employed hierarchical multiple regression analyses and PROCESS macro to ascertain prediction and serial mediation effects. The results substantiated the hypotheses that PsyCap positively related to learner empowerment and academic engagement while negatively associated with student burnout. Further, students with higher levels of learner empowerment and engagement reported lower levels of burnout in their academic studies. The mediational results also revealed that engagement and learner empowerment acted as significant serial mediators between PsyCap and student burnout. The study’s findings underscore the critical significance of PsyCap within higher education, particularly in nurturing learner empowerment, and engagement, thereby reducing student burnout.

This complex personality trait serves as the main topic of our paper due to the increasing prevalence of perfectionism as well as the rising demands from educational organizations. Our paper can fill a research gap by examining its definitions, models, components, and influencing elements (personality, gender, and immediate environment) in addition to the role of perfectionism in secondary and tertiary education. We assume that perfectionism in higher education is based on its development at secondary school, and it is becoming more intense in time. In 2023 the authors conducted a survey among Hungarian university students to determine the degree to which the participants pursue perfectionism in their professional and personal lives. The questionnaire finally resulted in 550 responses. The findings of our research suggest that women tend to be more perfectionist, but the picture is differently deemed by individuals than by their immediate surroundings. Another noteworthy result revealed that personal perfectionism also depends on the people with whom those who consider themselves perfectionists live. Our SEM model also showed that perfectionism is stronger throughout university studies and that it might be descended from secondary school perfectionism. Personality traits do affect perfectionism at school, which intensifies in higher education after graduating from secondary school.

Successfully solving reality-based tasks requires both mathematical and text comprehension skills. Previous research has shown that mathematical tasks requiring language proficiency have lower solution rates than those that do not, indicating increased difficulty through textual input. Therefore, it is plausible to assume that a lack of text comprehension skills leads to performance problems. Given that different sociodemographic characteristics and cognitive factors can influence task performance, this study aims to determine whether text comprehension mediates the relationship between these factors and competence in solving reality-based tasks. Additionally, it examines the impact of systematic linguistic variation in texts. Using an experimental design, 428 students completed three reality-based tasks (word count: M = 212.4, SD = 19.7) with different linguistic complexities as part of a paper-pencil test. First, students answered questions about the situation-related text comprehension of each text, followed by a mathematical question to measure their competence in solving reality-based tasks. The results indicate that: a) Tasks with texts of lower linguistic complexity have a significantly higher solution rate for both text comprehension (d = 0.189) and mathematical tasks (d = 0.119). b) Cognitive factors are significant predictors of mathematical solutions. c) Text comprehension mediates the relationship between the impact of students’ cultural resources and cognitive factors and their competence to solve reality-based tasks. These findings highlight the importance of linguistic complexity for mathematical outcomes and underscore the need to reinforce text comprehension practice in mathematical education owing to its mediating role.

Augmented reality offers diverse potential applications for STEM education, enabling students to engage directly with virtual elements in real-time and providing them with immersive, natural experiences. This study conducted a bibliometric analysis of articles on this topic on the Scopus database to determine some quantitative information, such as general information about publications, countries, institutions, authors with the most contributions, and key trends in applying augmented reality technology in STEM education. An analysis of 201 studies published from 2005 to 2023 using Biblioshiny software and VOSviewer reveals that the United States leads in the number of studies conducted on this issue. Kryvyi Rih National University, Ukraine, has the most studies. The authors who contributed the most studies with the most citations on this issue are Lindner, C. and Rienow, A. from Ruhr University Bochum, Germany. Two primary research trends emerge, focusing on how Augmented Reality technology is utilized, particularly in STEM fields like Chemistry, which combines learning forms with other learning support tools and media such as mobile applications. Secondly, integrating augmented reality and virtual reality technologies into STEM programs at the university level, design of games, and virtual tools. This study offers important data for researchers looking to explore future applications of augmented reality technology within STEM education.

The rapid advancement of science, engineering, and technology, driven by the Fourth Industrial Revolution, has heightened the demand for a highly skilled workforce in science, technology, engineering, and mathematics (STEM) fields. Integrated STEM education has emerged as a key driver of educational innovation in Vietnam, spanning both general and higher education. The competence of university lecturers in delivering integrated STEM education, a newly recognized pedagogical and professional skill set, is crucial to the success of STEM education at the tertiary level. As with general pedagogical competence, the development of an integrated STEM education competence framework is essential for enhancing this capability among university lecturers. However, there remains a lack of theoretical foundation and best practices tailored to the Vietnamese higher education context. This study aims to develop a framework for integrated STEM education competence specifically for university lecturers through document analysis and survey research. Multivariate statistical techniques, including exploratory factor analysis (EFA), Cronbach’s alpha, and Pearson correlation, were applied to analyze data collected from 205 lecturers across nine public universities in Vietnam. The integrated STEM education competence framework for Vietnamese university lecturers consists of three component competencies and 23 items: designing and implementing integrated STEM education (15 items), assessing integrated STEM learning outcomes (4 items), and demonstrating positive attitudes toward integrated STEM education (4 items). The framework was found to be both reliable and valid, with strong positive correlations among the three component competencies. This study also outlines limitations and provides recommendations for future research.

University dropout is a multidimensional and multicausal problem that affects every university around the world. The aim of this article is to conduct a bibliometric review of the scientific literature on the main factors that influence university dropouts in scientific publications between 2018 and 2022. The methodology is based on systematic searches using the Web of Science (WoS) and Scopus databases. We analysed 417 and 498 articles, respectively, applying inclusion/exclusion criteria. The main factors of university dropout were identified: problems in the academic and social world of students, student stress, health reasons, the role of teachers, and changes in the education system. Among the countries with the highest scientific output, Spain stands out, along with the United States, the United Kingdom, Australia, and China. This would provide a more complete view of the historical evolution and multifactorial causes of this educational phenomenon.

This study aims to develop and validate a green behavior instrument based on local potential using structural equation modeling (SEM) with smart partial least squares (SmartPLS). The instrument consists of 40 statements covering five main indicators: environmental maintenance, waste reduction, saving natural resources, sustainable mobility and consumption, and community education. This study addresses a gap in existing research by creating a context-specific tool for assessing green behavior, incorporating local cultural and ecological factors. While prior studies emphasize global sustainability principles, they often overlook the significance of local practices and values, which are essential for effective environmental education. By integrating local potential, this instrument bridges global sustainability goals with regional contexts, enabling meaningful and practical student engagement. The instrument was validated through content validity testing, exploratory and confirmatory factor analyses, and construct validity and reliability testing using SEM with SmartPLS. The results indicate strong content validity, with content validity index (CVI) values ranging from .80 to .90. After analysis, 34 valid items were retained from the initial 40. This study contributes to the literature by developing an instrument that aligns with global sustainability goals while integrating local cultural practices and ecological contexts. It offers insights into how local knowledge enhances sustainability education, providing a holistic framework for assessing green behavior across diverse regions.

This study examines how work well-being is addressed in Finnish leadership education programs. The data consist of 91 publicly available course descriptions from Finnish leadership education programs in 2023, including those for master’s degrees from universities of applied sciences, traditional university-level leadership programs, and specialist vocational qualifications in leadership and business management. The study uses content analysis to examine the role of work well-being in leadership training. The results indicate that work well-being is often linked to organizational performance and treated as a tool for achieving economic goals, with less emphasis on the inherent value of employee well-being. This instrumental approach is prevalent across the different types of leadership training programs, including those found in the universities of applied sciences, traditional universities, and programs for specialist vocational qualifications in leadership and business management. The study also finds that leadership training programs often emphasize self-leadership and personal development, which can perpetuate a culture of individual responsibility for well-being and may lead to superficial leadership practices. The study concludes that Finnish leadership educators should prioritize holistic approaches to work well-being in leadership training, emphasizing its intrinsic value alongside its role in organizational performance, while researchers could explore methods to integrate and evaluate these balanced perspectives in diverse educational contexts.

This study examines the factors influencing English language achievement among non-English major undergraduate students in Thailand, with a specific focus on the differences between high-achieving and low-achieving learners. Conducted at Rajamangala University of Technology Lanna, this research adopts a mixed-methods approach, combining quantitative data from questionnaires and qualitative insights from semi-structured interviews. Three primary influencing factors were identified: student-related factors (e.g., motivation and self-regulated learning), teacher-related factors (e.g., pedagogical practices and teacher-student interactions), and environmental factors (e.g., availability of learning resources). Student motivation and self-regulation emerged as the strongest predictors of success, while teacher-related factors unexpectedly showed a negative influence, suggesting a misalignment between teaching strategies and student needs. Environmental factors, though positively perceived, had a less direct impact on outcomes. Practical implications include enhancing intrinsic motivation, adopting tailored teaching strategies to meet diverse learner needs, and strengthening teacher-student relationships to support low-achieving students. Policymakers are encouraged to address resource disparities and develop targeted interventions to enhance English language proficiency among students.

Work-based learning (WBL) is an important tool for enhancing students' employability skills in vocational education and training. Many studies have underlined the importance of a variable of WBL, self-efficacy, and vocational identity in developing vocational students' employability skills. Nonetheless, the research is limited and examined separately. Therefore, this study investigates how WBL, self-efficacy, and vocational identity influence employability skills and how self-efficacy moderates between WBL and employability skills. Four hundred and three state university students in Yogyakarta were involved in the data collection. This study used structural equation modeling (SEM) analysis to test its hypothesis. The results of the study revealed that the implementation of WBL did not have a direct effect on employability skills; however, self-efficacy was able to moderate the relationship between WBL and employability skills. However, WBL directly influences vocational identity, which in turn directly influences employability skills, while self-efficacy also directly influences employability skills. This research has important implications for improving learning that can improve students' self-efficacy skills in an effort to build students' employability skills in vocational education and training.

The digital age has sparked interest among educators in utilizing information technology, especially artificial intelligence (AI) chatbots. Due to the constant technological involvement, students must also acquire solid digital skills, especially AI proficiency, for learning and everyday life. However, there are few studies on models applying AI in teaching to develop mathematical abilities for high school students. Therefore, this paper proposes a theoretical framework for incorporating AI chatbots into education, boosting students’ mathematical problem-solving competence. Based on student data analysis, this framework will cover teaching, assessment, feedback, and dynamic learning activity adjustment. The paper then explains the operations of AI chatbots to provide personalized feedback. This process emphasizes the importance of error handling and information security, ensuring safety and efficiency in the learning process. This theoretical model supports the integration of AI chatbots in personalized teaching, specifically for improving mathematical skills.

Research fronts are dynamic, knowledge-driven clusters of scholarly activity that emerge in response to pressing problems and/or groundbreaking discoveries. Clarivate Analytics provided a valuable tool based on Citation Productivity and Trajectory (CPT) indicator, which successfully identified particularly hot research fronts on a global scale. To enhance the accuracy and comprehensiveness of identifying both active and emerging research trends, this study develops an extended Clarivate formulation incorporating a novel Impact Factor (IF) metric. The refined approach incorporates growth rates, publication productivity, and the average publication gap between published and citing publications. This method is applied to exploring key research fronts in the digital education ecosystem using bibliometric data from the Scopus database in the period of 2019-2023. The results reveal that artificial intelligence and online learning are the most prominent and influential fields, with virtual reality, blockchain, hybrid learning, and digital literacy representing fast-growing areas. By analyzing both quantitative and qualitative aspects, this work informs key stakeholders about the evolving priorities and trends in the digital educational landscape.

This study investigates the ideological orientations of teachers and the potential transformation of these orientations over 14 weeks, focusing specifically on their conceptualizations of educational ideologies within conservative and liberal frameworks. The research employs an inventory-based assessment to capture participants’ ideological stances. Initial findings revealed participants’ tendency to associate ideological labels with political dualities, reflecting simplified views on educational ideologies. Throughout the study’s second phase, participants engaged in critical reading assignments and reflective discussions designed to expand their awareness and understanding of various educational ideological paradigms. Findings indicate a notable shift in ideological positioning, primarily driven by exposure to foundational texts and structured reflection sessions. In the final phase, participants re-took the initial inventory, allowing for a direct comparison of ideological stances. The comparative analysis demonstrated subtle yet significant shifts, particularly regarding participants’ views on the interrelations between educational ideology, social equity, and the intellectual demands of modern pedagogy. This study underscores the transformative potential of immersive engagement with diverse ideological perspectives, highlighting the need for professional development models that prioritize reflective dialogue and critical exploration of ideological content.

With the introduction of the new curriculum, primary school Croatian fine arts teachers faced many challenges. The fundamental problem, the lack of school lessons, is highlighted by the challenges of implementing problem and project work and integrating technology into the teaching process. Therefore, it is important to organise activities where pupils use modern tools and media for high-quality educational purposes. The animation was chosen as a fine arts technique that can fulfil these requirements. Qualitative action research was conducted in city Split in the school year 2023/2024. The 5th and 8th grade pupils (125) and their fine arts teachers (3) participated in the research. A total of 75.23% of respondents were positive about the occasional introduction of technology into fine arts classes. After completing the fine arts project, 77.98% of pupils stated that they now have the knowledge and skills to create an animation themselves, while 77% of pupils consider their digital stories to be interesting and original. All three fine arts teachers cite a lack of continuity due to the small number of lessons as a shortcoming. The results point to poor material conditions: overheating of old projectors, low-quality tablets, poor internet connection and lack of power sockets. The research has shown that there are discrepancies between the prescribed theoretical requirements for learning outcomes and the possibilities for their practical realisation. As a result, teachers need to take a keen interest and receive additional training to ensure that the projects designed are in line with the requirements of the curriculum.

This study explores the impact of artificial intelligence (AI) integration on students' educational experiences. It investigates student perceptions of AI across various academic aspects, such as module outlines, learning outcomes, curriculum design, instructional activities, assessments, and feedback mechanisms. It evaluates the impact of AI on students' learning experiences, critical thinking, self-assessment, cognitive development, and academic integrity. This research used a structured survey distributed to 300 students through Microsoft Forms 365, yet the response rate was 29.67%. A structured survey and thematic analysis were employed to gather insights from 89 students. Thematic analysis is a qualitative method for identifying and analysing patterns or themes within data, providing insights into key ideas and trends. The limited response rate may be attributed to learners' cultural backgrounds, as not all students are interested in research or familiar with AI tools. The survey questions are about AI integration in different academic areas. Thematic analysis was used to identify patterns and themes within the data. Benefits such as enhanced critical thinking, timely feedback, and personalised learning experiences are prevalent. AI tools like Turnitin supported academic integrity, and platforms like ChatGPT and Grammarly were particularly valued for their utility in academic tasks. The study acknowledges limitations linked to the small sample size and a focus on undergraduate learners only. The findings suggest that AI can significantly improve educational experiences. AI provides tailored support and promotes ethical practices. This study recommends continued and expanded use of AI technologies in education while addressing potential implementation challenges.

Integrated learning has emerged as an approach to developing critical thinking and creativity skills. This meta-analysis synthesizes the effects of integrated learning on critical thinking and creativity, drawing from experimental studies published over the past decade. This study addresses the research question: What are the impacts and factors influencing integrated learning on students' critical thinking skills and creativity compared to conventional learning over the past decade? In the database, 403 articles were obtained, which were then supplemented by seven articles from manual searches, so that there were a total of 410 articles. After a strict inclusion process, 8 articles were selected for analysis. The inter-rater reliability test using Cohen's Kappa coefficient produced a value of 0.78, which indicates a substantial level of agreement. The analysis includes data from 497 participants for critical thinking and 266 for creativity. Heterogeneity in critical thinking skill data was 96%, and in creative skills, it was 86%; then, a subgroup analysis of education level was carried out to find out where the high heterogeneity was. The results show a significant positive effect of integrated learning, with an SMD of 1.48 (p = .004) for critical thinking and 1.60 (p = .0001) for creativity. Funnel plots and Egger's regression tests indicate no risk of publication bias. In addition, this study also synthesized the causal factors of how integrated learning affects critical thinking skills and creativity. Further research is recommended to explore its long-term impact and implementation strategies in various educational settings.  

The use of technology in education aims to improve students' problem-solving skills so that they have the skills needed by 21st century society in dealing with various kinds of challenges and problems. This study was carried out aiming to obtain the characteristics of augmented reality-based learning media for mathematics learning in student problem-solving skill, and obtain the results of the average difference in the problem-solving abilities of junior high school students. This research and development (R&D) study, employing the (Analyze, Design, Develop, Implement, and Evaluate) ADDIE model, investigated Augmented Reality (AR)-based learning media for mathematics to enhance junior high school students' problem-solving skills. The aim was to identify characteristics of effective AR media and assess their impact on problem-solving abilities. Quantitative data, collected from student problem-solving tests, were analyzed using a t-test in SPSS. The AR media featured virtual manipulation, virtual measurement tools, and real-world problem exploration. While the experimental group using AR showed a higher average problem-solving score compared to the control group using Problem-Based Learning (PBL), the difference was not statistically significant (t (df) = 0.638, Cohen's d = 0.0876). This lack of significance, despite the higher mean, is likely due to a small sample size and the limited integration timeframe, coupled with pre-existing skill variations. Future research should address these limitations to further explore the potential of AR in mathematics education.

This research investigated the validity of measurement and causal model of online scam protection behavior (OSPB) among at risk Thai students. The sample comprised 286 high school students from three demonstration schools under the University. Data were analyzed using descriptive statistics, confirmatory factor analysis (CFA), and structural equation modeling (SEM). The factor loadings for all items satisfied the standard criteria with scores ranging from .40 to .80, item-total correlations ranging from .405 to .718, and Cronbach’s alpha coefficients ranging from .773 to .928. The modified model demonstrated a better fit with the empirical data (χ² = 47.62, df = 37, p = .113,  χ²/df = 1.287, RMSEA = .032, SRMR = .028, GFI = .97, CFI = 1.00, NFI = .99). All factors: a) awareness of online risks, b) inhibitory control, c) game-based learning, d) social support, and e) motivation to prevent online scams can predict 81% of OSPB. The motivation to prevent online scams strongly influenced OSPB, with an effect size of .60. Additionally, all factors can predict 88% of the motivation for online scam prevention, suggesting that Protection Motivation Theory (PMT) is a suitable framework for understanding and evaluating Thai students' preventive behaviors in online deception scenarios. This newly developed instrument is highly reliable and can be effectively used by researchers and educators to assess the risk of online fraud victimization among high school students.