The education of gifted students is often characterized by high expectations, ambitious goals, and significant effort invested in learning. Their experiences of success and failure are shaped by a variety of factors, including personal, family, school, cultural, and social influences. This article examines how gifted students perceive and experience their own successes and failures, as well as how these experiences are perceived and responded to by their peers. Using qualitative methods, the study involved semi-structured interviews with thirty gifted students from seventh to ninth grades across ten elementary schools in Slovenia. The findings indicate that gifted students experience a range of emotions in response to success, from satisfaction to anxiety, while their reactions to failure often involve frustration and self-criticism. Peer responses to their success and failure vary significantly, ranging from supportive encouragement to jealousy and social exclusion. These findings highlight the complex interpersonal dynamics at play within school environments. Understanding and addressing these dynamics is crucial for creating inclusive, supportive, and stimulating learning environments that nurture both the academic and social-emotional well-being of gifted students.

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 addresses global concerns surrounding elementary students' science performance following the COVID-19, as a result of international tests such as Trends in International Mathematics and Science Study (TIMSS) highlight the ongoing challenges that urge the exploration of innovative educational approaches to improve science learning. This research employed gamification-assisted instruction and explored its impact on enhancing the understanding of science concepts and attitudes toward science class among fourth graders. The study adopted a quasi-experimental design and included an experimental group (ExG) that was taught using a gamification strategy and a control group (CoG) that was taught using a traditional method with a sample of 38 female elementary students from a public school in Jordan. Data were gathered using valid and reliable tools: the developed scientific concepts test and the Attitude Towards Science class measures. The ANCOVA analysis revealed that gamification significantly improves the acquisition of scientific concepts (η2=.208) and boosts a positive attitude toward science classes among elementary students (η2=.626). These findings encourage decision-makers to incorporate gamification into science teaching practices and methods.

Children diagnosed with moderate autism spectrum disorder (MASD) exhibit a range of socially unacceptable behaviors, which notably include social withdrawal behavior (SWB); these individuals tend to disengage from various social contexts, consequently impeding their communication and social interaction capabilities. The primary objective of this research was to employ miniatures (diorama) as a methodological approach to construct semi-naturalistic scenarios for children with MASD that authentically represent their quotidian experiences and facilitate interaction, contributing to the alleviation of their SWB. The research sample comprised 21 children with MASD, aged between 6 and 9 years, who were enrolled at the Al-Jabr Institute in Al-Ahsa, Saudi Arabia. A quasi-experimental methodology was adopted to align with the research's inherent characteristics, using a three-group design. The instruments utilized included the Social Withdrawal Behavior Scale (SWBS) alongside a training program devised by the authors. The results showed a significant reduction in SWB among those children to whom the diorama program was applied. Results also indicated the continuation of this effect after the end of the diorama program period for two consecutive months. The outcomes encourage further implementation of the diorama methodology on more extensive samples and across a broader geographic scope within Saudi Arabia, thereby facilitating the generalization of the findings to the entire population of children diagnosed with MASD. Findings also encourage the enhancement of the diorama's role in forthcoming experimental inquiries to ascertain its efficacy in mitigating other socially maladaptive behaviors exhibited by children with MASD.

This research investigated the validity of measurement and causal model of online scam protection behavior (OSPB) among at risk Thai students. The sample comprised 286 high school students from three demonstration schools under the University. Data were analyzed using descriptive statistics, confirmatory factor analysis (CFA), and structural equation modeling (SEM). The factor loadings for all items satisfied the standard criteria with scores ranging from .40 to .80, item-total correlations ranging from .405 to .718, and Cronbach’s alpha coefficients ranging from .773 to .928. The modified model demonstrated a better fit with the empirical data (χ² = 47.62, df = 37, p = .113,  χ²/df = 1.287, RMSEA = .032, SRMR = .028, GFI = .97, CFI = 1.00, NFI = .99). All factors: a) awareness of online risks, b) inhibitory control, c) game-based learning, d) social support, and e) motivation to prevent online scams can predict 81% of OSPB. The motivation to prevent online scams strongly influenced OSPB, with an effect size of .60. Additionally, all factors can predict 88% of the motivation for online scam prevention, suggesting that Protection Motivation Theory (PMT) is a suitable framework for understanding and evaluating Thai students' preventive behaviors in online deception scenarios. This newly developed instrument is highly reliable and can be effectively used by researchers and educators to assess the risk of online fraud victimization among high school students.

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.

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.

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.