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.

The wide use of the Internet of Things (IoT) in all spheres of life has led to a surge of cyberbullying among learners worldwide. That is why it cannot be denied that underlying factors, manifestations, consequences, and preventive measures of cyberbullying improve the welfare and overall mental development of students. This systematic literature review examines the causes, effects, and preventive measures of cyberbullying based on empirical studies conducted on learners in various situations. The review will focus on existing material published between 2015 and April 2024. For the inclusion and exclusion of literature, the Scopus online database was employed, along with the guidelines of the PRISMA model. Of 1004 studies, 51 were closely reviewed to determine the responses to the objectives of this study. NVIVO-12 was used for both thematic and content analysis in this study. The results show that there are 29 causes, 12 forms, 31 effects, and 41 different preventives for cyberbullying. The results of this study will not only enhance the comprehension of various concerns for parents, guardians, policymakers, educators, and governments but also provide valuable insights to researchers for addressing this issue.

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.

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.

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 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.

The present study examined how empathy (affective and cognitive), basic psychological need satisfaction (autonomy, competence, and relatedness), and demographic factors (gender and academic achievement) jointly predict prosocial behavior during emerging adulthood. Grounded in Self-Determination Theory, this research explored whether relatedness need satisfaction mediates the relationship between empathy and prosocial tendencies. A total of N=889 undergraduate students from a large public university in the southeastern United States completed self-report measures assessing empathy, psychological needs, and prosocial behavior. Path analysis revealed that affective empathy and relatedness satisfaction were significant predictors of prosocial behavior. Relatedness also partially mediated the link between empathy and helping actions. Furthermore, gender and GPA contributed to prosocial outcomes, with female students and those with higher academic achievement reporting greater prosocial tendencies. These findings suggest that fostering emotional engagement and supporting students’ psychological needs—particularly the need for relatedness—may be key mechanisms for promoting prosocial development in educational settings during the critical stage of emerging adulthood.