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.

Since psychological satisfaction is influenced by the interaction between individuals and their environment, it is necessary to create a cooperative climate at the organizational level and strengthen collective innovativeness at the individual level to improve teachers' job satisfaction. Therefore, the study investigated whether collective innovativeness can be mediated by the school climate to enhance teacher job satisfaction. This study extensively examined survey data with a sample of 3,976 teachers in Shanghai through Structural Equation Modeling, obtained from Teaching and Learning International Survey (TALIS). The findings revealed that teachers' collective innovativeness served as a significant mediator between school climate and job satisfaction. Furthermore, higher levels of collective innovativeness among teachers amplified the influence of school climate on their job satisfaction. These findings show that schools should strive to foster a collaborative school climate and provide support for teachers in implementing innovative and collaborative teaching activities with the aim of enhancing their job satisfaction. Above all, efforts are needed to support teachers' active and cooperative practice capabilities in building teacher-student relationships.

Recent research has identified factors influencing the choice of a special education career; however, it has not thoroughly examined their connection with personality traits and identity status. Thus, the present study was designed to explore how different personality traits and identity statuses correlate with the motives and perceptions associated with the choice to teach in special education. The study involved 209 pre-service special education teachers. The NEO-Five Factor Inventory was used to measure the Big 5 personality traits. The Ego Identity Process Questionnaire assessed identity commitment and exploration. The Factors Influencing Teaching Choice Scale was used to evaluate motivations and perceptions about teaching. Regarding the factors that influenced the decision to pursue a career in special education, intrinsic value, shaping children’s future, social equity, making social contributions, working with children, task demands, and job satisfaction were highly rated. Additionally, extraversion, openness to experience, conscientiousness, and identity statuses were identified as positive predictors for certain factors influencing the choice of a teaching career in special education. Finally, the study identified two distinct groups of students: "Identity Achievers" characterized by high positive personality traits, and identity commitment, and "Identity Explorers" characterized by lower positive personality traits and higher identity exploration. Differences were observed between the groups in their motives and perceptions concerning teaching in special education. In conclusion, this study highlights the relationships between personality, identity status, and career decision factors, offering insights into the factors that influence this critical career decision among future special educators. Directions for future research are discussed.

It is unclear how social networks can be utilized in educational settings. An exploratory study was conducted to examine the differences between university students in Mexico and Spain in terms of their perceptions of knowledge and utilization of networks in the university environment. An overall sample of 378 students was collected from two public universities, one in Mexico and one in Spain. This study utilized descriptive statistics as part of a contingency analysis, X² with correction was used for the analysis of differences, Mann-Whitney U for the analysis of independence, Mantel-Haenszel test for association degree, Cramer's V for strength of association, Spearman's correlation coefficient for correlations. According to the results, the use of social networks is clearly related to country of origin, but not to gender. It seems that Instagram is a platform widely used by both Mexican and Spanish students, but it is not used in educational environments. Therefore, the use of social networks in higher education contexts differs by country, as does the knowledge of social bookmarking and the distribution of content to share information and resources.

Emotional empathy, mindfulness, and subjective well-being are essential to understanding human behavior and mental health among students. However, more research is needed to investigate how these constructs interplay within academic contexts. This study explored the hierarchical relationships between emotional empathy, mindfulness, and subjective well-being. The Multidimensional Emotional Empathy Scale (MDEES), The Kentucky Inventory of Mindfulness Skills (KIMS), and the Subjective Well-Being Scale (WeBs) were administered with a sample of postgraduate professional diplomas in teaching students attending Al Ain University in Abu Dhabi campus and Al Ain campus (n = 1545). The results showed that emotional empathy (positive sharing, suffering, feeling for others, and emotional contagion) positively affects physical and eudaimonic well-being. A negative correlation was found between financial and social well-being and other components of emotional empathy, such as emotional attention and responsive crying. Mindfulness significantly improves emotional empathy in components like describing, accepting without judgment, and observing. This study revealed that some components of mindfulness, such as observing and acting with awareness, decrease emotional empathy, such as suffering and feeling for others. Acting with the awareness component in mindfulness decreases positive sharing, responsive crying, and emotional contagion. Future research could explore these relationships further and examine potential cultural differences.

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 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.

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.

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.

Integrating generative artificial intelligence (GenAI) in education has gained significant attention, particularly in flexible learning environments (FLE). This study investigates how students’ voluntary adoption of GenAI influences their perceived usefulness (PU), perceived ease of use (PEU), learning engagement (LE), and student-teacher interaction (STI). This study employed a structural equation modeling (SEM) approach, using data from 480 students across multiple academic levels. The findings confirm that voluntary GenAI adoption significantly enhances PU and PEU, reinforcing established technology acceptance models (TAM). However, PU did not directly impact LE at the latent level—an unexpected finding that underscores students’ engagement’s complex and multidimensional nature in AI-enriched settings. Conversely, PEU positively influenced LE, which in turn significantly predicted STI. These findings suggest that usability, rather than perceived utility alone, drives deeper engagement and interaction in autonomous learning contexts. This research advances existing knowledge of GenAI adoption by proposing a structural model that integrates voluntary use, learner engagement, and teacher presence. Future research should incorporate variables such as digital literacy, self-regulation, and trust and apply longitudinal approaches to better understand the evolving role of GenAI inequitable, human-centered education.

Mindfulness, recognized as a protective factor against learning burnout in higher education, has garnered considerable attention, yet its underlying mechanisms remain underexplored. This study examined the relationship between mindfulness, regulatory emotional self-efficacy, and learning burnout. Data from 461 Chinese university students were collected using a correlational design and cluster sampling method, employing the Five Facet Mindfulness Questionnaire, University Student Learning Burnout Scale, and Regulatory Emotional Self-Efficacy Scale. Hypotheses were tested using partial least squares structural equation modeling. Results showed that Participants exhibited above-average mindfulness (M=3.090), learning burnout (M=3.278), and regulatory emotional self-efficacy (M=3.417). Results revealed that mindfulness is directly and negatively related to learning burnout (β=-0.679, t = 28.657, p < .001). Regulatory emotional self-efficacy (β = -0.357, t = 8.592, p < .001) was significantly and negatively related to learning burnout. Mindfulness was significantly and positively related to regulatory emotional self-efficacy (β = 0.638, t = 24.306, p < .001), and regulatory emotional self-efficacy (R2: from .461 to .537) partially mediated the relationship between mindfulness and learning burnout. Besides, the Importance-Performance Matrix Analysis revealed that managing negative emotions significantly contributes to learning burnout but performs poorly, whereas non-reacting demonstrates both the lowest contribution and performance. Findings suggest that mindfulness indirectly alleviates learning burnout through regulatory emotional self-efficacy, providing evidence-based insights for targeted mindfulness interventions in higher education.

This study investigates how undergraduate art majors at the National University of Art Education in Vietnam perceive the cultural integration into their English curriculum. A quantitative design was employed using a researcher-developed questionnaire administered to 214 students. Data were analysed using descriptive statistics, independent-samples t-tests, and multiple regression. Findings indicated that students valued culturally relevant content, particularly materials connected to both Vietnamese and international art as well as experiential and student-centered instructional strategies. Reported challenges included limited cultural background knowledge, cognitive overload, and reduced confidence when discussing culture in English. Crucially, results from multiple regression revealed that how culture is taught may have a greater impact on students’ experiences than the content itself. Therefore, these findings underscore the importance of aligning instructional approaches with learners’ disciplinary identities and offer implications for culturally responsive curriculum design, professional development, and the implementation of context-specific teaching strategies in English language instruction for art students.