During the implementation of the inclusive education policy in several countries in Association of Southeast Asian Nations (ASEAN), the psychological health of special education teachers should be considered as a key success factor. This study explored special education teachers’ perceived work stress (PWS), bio-psychological burn-out symptoms (BPS), and transformational teaching (TFT) in inclusive education in Indonesia and Thailand. There were 177 Indonesian and 199 Thai teachers completing a series of questionnaires that included BPS, PWS, and TFT. The results showed that BPS and PWS were high, whereas BPS and TFT were significantly different across nations. No gender differences were found among both Indonesian and Thai teachers. Moreover, TFT could be significantly predicted by positive age and negative work stress, which explained 8% of the variance among Indonesian teachers (R2 = .08, F(4, 172) = 4.18, p < .01) and by positive age and negative burnout symptoms, which explained 6% of the variance among Thai teachers (R2 = .06, F(4, 186) = 3.18, p < .05). Furthermore, inclusive education policymakers and stakeholders should be aware of psychological health improvement including burnout symptoms and work stress, which negatively invade the role of TFT among special education teachers in both countries.

The ability to think creatively has a vital role in the development of preschool children. This research provides a comprehensive review of innovative approaches and strategies for developing creative thinking in preschool children based on current trends and methodologies used in educational settings. This research shows three significant areas: (a) creative thinking skills in preschool children, (b) factors influencing creative thinking skills in depth, and (c) innovative strategies and approaches to stimulate creative thinking abilities in preschool children. This research uses a literature study method assisted by the publish perish application to find reference sources related to creative thinking abilities in preschool children. Studies show that creative thinking abilities in preschool children enable them to find innovative solutions, help them adapt to challenges, foster self-confidence and courage, and enrich their experience and knowledge of the world around them. Meanwhile, preschool children's creative thinking abilities are influenced by collaboration from the external environment (parents, teachers, and society); providing support and examples for children to develop and stimulate their creative thinking skills is very important.

This article investigates artificial intelligence (AI) implementation in higher education (HE) from experts' perspectives. It emphasises the view of AI's involvement in administrative activities in higher education, experts' opinions concerning the influence of the incorporation of AI on learning and teaching, and experts' views on applying AI specifically to assessment, academic integrity, and ethical considerations. The study used a qualitative method based on an unstructured qualitative interview with open-ended questions. The participants were thirteen individuals currently involved with higher education institutions and had various talents related to AI and education. Findings stress that implementing AI technology in administrative roles within higher education institutions is essential since it cuts costs, addresses problems efficiently and effectively, and saves time. The findings also revealed that AI plays a vital role in learning and teaching by speeding up the learning process, engaging learners and tutors, and personalising learning depending on the learner's needs within an entirely intelligent environment. AI can produce an accurate, objective, and suitable level of assessment. AI aids students in developing a stronger sense of integrity in their academic work by guiding them through AI-powered applications. AI must adhere to ethical laws and policies, ensuring its potential negative aspects are not overlooked or left unchecked.

eTwinning is a community of European schools that promotes networking and transnational collaboration projects. Therefore, as part of the Initial Teacher Education (ITE) initiative, we decided to explore how the research projects on scientific topics familiarize pre-service primary school teachers with eTwinning. 251 pre-service primary school teachers from Spain, Iceland, and Slovenia designed and carried out joint research projects on scientific topics. The aim was to gain insight into their self-assessment of their knowledge of the platform, the limitations of working with it, and their responses. An electronic questionnaire was used as the main instrument for data collection. It turned out that the pre-service teachers enjoyed this international collaboration, but also found it challenging. By the end of the projects, they were familiar with the eTwinning platform, although the least engaged prospective teachers recognized that they needed strong support and considered the platform a non-intuitive environment. Overall, they were willing to use the platform with pupils in the future, which is in line with the aim of the ITE initiative.

This comprehensive systematic review delves into the increasing prevalence of integrating chatbots into language education. The general objective is to assess the current landscape of knowledge regarding chatbot utilisation and its influence on three crucial elements: students' skills, attitudes, and emotions. Additionally, the review seeks to scrutinise the advantages linked to incorporating chatbots in foreign language teaching, exploring their potential benefits while considering limitations and potential negative impacts on specific skills or user experiences. Consequently, this research offers valuable insights into the application of chatbots in foreign language education, shedding light on their potential advantages and areas that warrant further exploration and enhancement. The integration of chatbots in language learning, despite certain limitations, generally yields positive outcomes and enhances educational results in students' skills. Its characteristics can also influence a language learner's attitude, impacting factors such as motivation, interest, autonomy in learning, and engagement or even their sense of fun. Additionally, chatbots prove to be helpful in creating emotionally positive learning environments and can contribute to boosting students' self-esteem and self-confidence.

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.

The concept of technological pedagogical content knowledge (TPACK) is presented as a framework that guides how to effectively integrate technologies in the educational environment. Through this model, we investigate the ethical implications related to the use of digital tools in teaching, and we outline the necessary knowledge that educators should have to address these issues of ethics and technology in the classroom. We assess the professional, ethical knowledge of pre-service teachers regarding their use of technologies using a descriptive and exploratory mixed-methods approach. The data for this research come from a Likert-scale questionnaire administered to 616 teacher-training students in Spain, as well as from personal interviews with 411 of them. From these data, we identify four of the eight dimensions of ethical knowledge: professional, ethical knowledge, ethics in the use of technologies, pedagogy for their integration in the classroom, and the use of content specific to the disciplines of pre-service teachers. The results obtained indicate that the preparation of educators with professional, ethical knowledge in training is insufficient, which highlights the need to address this issue in the post-pandemic context of the 21st century. Among the difficulties detected, it should be noted that this study is limited to a European university and a sample chosen for convenience, so it would be advisable to extend the study to other European universities.

The integration of AI tools in education is reshaping how students view and interact with their learning experiences. As AI usage continues to grow, it becomes increasingly important to understand how students' perceptions of AI technology impact their academic performance and learning behaviours. To investigate these effects, we conducted a correlational study with a sample of 44 students to examine the relationship between students' perceptions of ChatGPT’s utility—focusing on usage frequency, perceived usefulness, accuracy, reliability, and time efficiency—and key academic outcomes, including content mastery, confidence in knowledge, and grade improvement. Additionally, we explored how these perceptions influence student behaviours, such as reliance on ChatGPT, procrastination tendencies, and the potential risk of plagiarism. The canonical correlation analysis revealed a statistically significant relationship between students' perceptions of ChatGPT's utility and their academic outcomes. Students who viewed ChatGPT as reliable and efficient tended to report higher grades, improved understanding of the material, and greater confidence in their knowledge. Furthermore, the bivariate correlation analysis revealed a significant relationship between dependency on ChatGPT and procrastination (r = 0.546, p < .001), indicating that a higher reliance on AI tools may contribute to increased procrastination. No statistically significant association was identified between ChatGPT dependency and the risk of plagiarism. Future research should prioritize the development of strategies that promote the effective use of AI while minimizing the risk of over-reliance. Such efforts can enhance academic integrity and support independent learning. Educators play a critical role in this process by guiding students to balance the advantages of AI with the cultivation of critical thinking skills and adherence to ethical academic practices.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

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 examines the research trends of Design Thinking (DT) in education during the period 2014–2024 through a systematic literature review. This study aims to analyze annual publication patterns, implementation across educational levels, research methodologies, authorship distribution, geographical spread, journal type distribution, and key themes from highly-cited publications in DT education research. The results show a significant increase in publications, especially in 2023–2024, reflecting growing academic interest in DT as an innovative approach to developing 21st-century skills. Qualitative research methods dominate, with most studies involving collaborative authorship. DT application was initially focused on higher education but expanded in secondary education while remaining limited in primary education. Asia leads in research contribution, while Africa shows lower output. Publications are distributed across educational, design-focused, and interdisciplinary journals. These findings underscore the importance of cross-disciplinary and global collaboration to accelerate DT adoption equitably. This study recommends strengthening educator training, developing holistic evaluation methods, and expanding quantitative research for more inclusive DT implementation.

This article aims to answer the research question: How do 5th grade students experience the use of artificial intelligence (AI) tools to create a comic strip describing the survival struggle between the Myna and the Lesser Kestrel? This study utilized a case-study approach to examine the advantages and challenges experienced by 5th grade students using AI tools to create a comic strip about the Lesser Kestrel's survival struggle. Data were collected through qualitative methods, including student reflections, drawings, and analyses of the comic strips they created. Additionally, a questionnaire was used to assess students' attitudes towards the four components of 21st century skills: Creativity, critical thinking, collaboration, and communication. The study indicates that the development of 21st century skills among students requires a collaborative effort involving both parents and teachers. It is not sufficient to rely solely on technological tools; there must be intermediary processes and support from teachers, who are obliged to adjust their teaching methods. Additionally, a teaching approach that supports the creation of a future citizen with a humanistic outlook and awareness of the complexity of life, is essential. This approach develops students' environmental citizenship, which is also an important 21st century skill. This involves integrating ethical, inclusive, and holistic perspectives to address complex problems, such as the survival struggle between the Lesser Kestrel and Myna.

The higher education system in Vietnam is undergoing a significant shift from training based on university capacity to training based on labor market demands. In a developing economy dominated by small and medium-sized enterprises, it is a big challenge to train graduates to meet changing and very diverse competence requirements. AI and machine learning tools are applied in three stages: (a) processing survey data: Expected learning outcomes (pELOs) are quantified into credit values, with each module's contribution determined using the apriori algorithm and expert methods; (b) Optimizing framework curricula (FC): A genetic algorithm identifies module combinations that meet all pELOs while minimizing redundancy within a specified study duration; (c) Framework curriculum adjustment (FCA): An FCA tool, using genetic algorithms, enables schools to update FC annually and allows learners to personalize their programs. WEKA is used to implement the apriori algorithm (https://www.cs.waikato.ac.nz/ml/weka). The PASCAL language is used to write GA and its associated subroutines. Foreign language bachelor's degree programs at the University of Languages and International Studies Vietnam National University, Hanoi, (ULIS-VNU) were used to test algorithms and procedures. According to the calculations, present FCs have caused overstudy and can be modified for every employment post to reduce the surplus credit values that have accrued. Furthermore, FCA can assist in making the curriculum more flexible so that students can more easily switch out FC modules based on their skills and circumstances while still meeting all of the stated ELOs. Under project number N.21.13, this research piece was finished with assistance from ULIS-VNU.

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.