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.

Given curiosity’s fundamental role in motivation and learning and considering the widespread use of digital stories as educational tools from the preschool age, we pursued measuring preschoolers’ curiosity when interacting with digital stories. Using 129 toddlers and preschoolers as a sample, three groups (one for each class) were given different versions of the same digital story to listen to: interactive, non-interactive, and animated. Toddlers' verbal and nonverbal behaviors were utilized to quantify curiosity as a condition brought on by the app. The participants' verbal and nonverbal behaviors were recorded during the digital reading aloud. Every child's data was encoded at one-minute intervals to examine concurrent behavior, and the results were then compiled. The findings show that interactive presentation formats encourage more touching and language use but less noise production and that interaction and the creative use of hot spots in digital illustrations are key elements in piquing viewers' curiosity while contributing to the strengthening of the engagement to the activity and the cultivation of critical thinking, creativity, and imagination.

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.

This research aims to systematically review the integration of artificial intelligence (AI) in English language teaching and learning. It specifically seeks to analyze the current literature to identify how AI could be utilized in English language classrooms, the specific tools and pedagogical approaches employed, and the challenges faced by educators. Using the PRISMA-guided Systematic Literature Review (SLR) methodology, articles were selected from Scopus, Science Direct, and ERIC, and then analyzed thematically with NVivo software. Findings reveal that AI enhances English teaching through tools like grammar checkers, chatbots, and language learning apps, with writing assistance being the most common application (54.55% of studies). Despite its benefits, challenges such as academic dishonesty, over-reliance on AI (27.27% of studies), linguistic issues, and technical problems remain significant. The study emphasizes the need for ethical considerations and teacher training to maximize AI’s potential. It also highlights societal concerns, including the digital divide, underscoring the importance of equitable access to AI-powered education for learners of all socioeconomic backgrounds.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.

In recent years, particularly over the last 10–15 years, the scientific value of oral history in relation to historical and social knowledge has been increasingly recognized. Since the 1980s, oral history researchers have pioneered new approaches to interpreting human experience, highlighting oral biographical narratives and recounted experiences as valuable material for social research. According to Tsiolis, the biographical narrative approach has become an established scientific methodology for studying how social actors interact with their environment and respond to social changes, as these are reflected through their subjectivity. Based on the above, this study involved four academic lecturers who narrated their academic and professional journeys, the factors that influenced them, the challenges they faced, and the positive impact of their engagement with teaching in the context of Greek higher education. The research employed the methodology of narrative biography, allowing the participants to recount their academic trajectories spontaneously, recalling personal experiences and memories. Through these narratives, qualitative data emerged, which were analyzed and coded into common themes, leading to conclusions about the conditions, aspirations, and disappointments experienced by academics in higher education institutions. The paper concludes some limitations of the current study and offers suggestions for future research.

This study aims to develop a competency framework for teaching natural science under the blended learning (BL) model for Natural Science education students at Thai Nguyen University of Education. Recognizing the increasing importance of BL in the context of modern education and the challenges teachers face during implementation, the modified Delphi method was employed to collect expert opinions, involving three rounds of surveys with 50 participants, including university lecturers and secondary school educational administrators. The research identifies seven core competency groups, including specialized knowledge, lesson design and evaluation competencies, classroom organization and management, student assessment and feedback, information technology competencies, experiment and simulation utilization in teaching, and basic knowledge of BL. The findings highlight the necessity of blending traditional teaching methods with modern technology to effectively implement the BL model, enhancing both the teaching process and students' learning outcomes. This framework is expected to serve as a crucial basis for teacher training universities to adjust their curricula and support educational administrators in fostering and enhancing the capacity of natural science teachers at the secondary level. This competency framework aims to support the professional development of Natural Science teachers and education students, ensuring their preparedness for the evolving demands of modern education. Furthermore, the study provides insights into the skills and knowledge that teachers need to acquire to adapt to the continuously evolving educational environment.