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.

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 study aimed to optimize critical thinking by empowering reflective and impulsive students' collaboration, communication, and information literacy skills through information literacy-oriented e-books in STEM-integrated problem-based learning (PBL). The research method used was a descriptive explorative approach. The study subjects consisted of five reflective students and five impulsive students. The measurement of cognitive style used the Matching Familiar Figure Test (MFFT) instrument. Collaboration skills were assessed through observation sheets, critical thinking and communication skills were assessed through student worksheets based on problem-solving tasks, and information literacy was assessed through a questionnaire. The study found that reflective students excelled in critical thinking and information literacy, while impulsive students demonstrated superior collaboration skills. As for communication skills, reflective and impulsive students have different advantages for each indicator of communication skills. This study can conclude that implementing information literacy-oriented e-books through STEM-integrated PBL can optimize reflective and impulsive students' critical thinking, collaboration, communication, and information literacy skills. The implication of this study is the importance of integrating 21st century skills holistically in learning practices, especially in the digital era, to prepare the younger generation to face the challenges of the 21st century.

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 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.

Critical thinking is highly valued as an integral skill for promoting students’ development, and problem-based learning (PBL) is widely used as an essential method to facilitate the development of critical thinking. However, since individual studies cannot determine the precise overall effect size of PBL on the development of critical thinking, it is difficult to systematically analyze the various influencing factors that hinder PBL from achieving sufficient effectiveness. Therefore, this study adopts a meta-analysis method to examine PBL in depth, aiming to clarify the crucial methods and elements of applying PBL to enhance critical thinking and address the shortcomings of existing studies. This study investigates two primary questions: first, the efficacy of PBL in enhancing critical thinking skills in comparison to traditional pedagogical approaches, and second, the influence of moderating variables on the effectiveness of PBL. To address these questions, a total of 25 studies were selected for meta-analysis. The findings revealed an overall effect size of 1.081 under the random-effects model, with a confidence interval of [0.874, 1.288] and p < .05, indicating that PBL significantly outperforms traditional methods. The analysis demonstrated that the effectiveness of PBL is not significantly influenced by learning stage, sample size, or measurement tools, thereby broadening the applicability of PBL and challenging preconceived limitations associated with its implementation. However, the results also indicated that PBL effectiveness is moderated by teaching methods and subject types, which offers critical insights for educators seeking to adapt their instructional strategies when employing PBL.

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.

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.

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.