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.

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.

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.

In an era where diversity and digitalization significantly influence higher education, understanding and adapting to various learning preferences is crucial. This study comprehensively analyzes 394 scholarly articles from 1984 to 2022 using bibliometric methods, providing a dynamic overview of the research patterns in learning styles within higher education. We identified four stages of development during this period: 1984–1995 (Low-interest), 1996–2005 (Early development), 2006–2018 (Development), and 2019–2022 (Intensification). Our analysis highlights that the United States, the United Kingdom, and Australia were the top three leading publishers of research on learning styles in higher education. The results reveal three main topics of publications: educational technology, learning environments, and subject behaviors. This research not only identifies emerging research topics but also underscores the importance of adapting instructional strategies to diverse learning styles to enhance educational outcomes in higher education.

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 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.

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.

The integration of AI tools in education is reshaping how students view and interact with their learning experiences. As AI usage continues to grow, it becomes increasingly important to understand how students' perceptions of AI technology impact their academic performance and learning behaviours. To investigate these effects, we conducted a correlational study with a sample of 44 students to examine the relationship between students' perceptions of ChatGPT’s utility—focusing on usage frequency, perceived usefulness, accuracy, reliability, and time efficiency—and key academic outcomes, including content mastery, confidence in knowledge, and grade improvement. Additionally, we explored how these perceptions influence student behaviours, such as reliance on ChatGPT, procrastination tendencies, and the potential risk of plagiarism. The canonical correlation analysis revealed a statistically significant relationship between students' perceptions of ChatGPT's utility and their academic outcomes. Students who viewed ChatGPT as reliable and efficient tended to report higher grades, improved understanding of the material, and greater confidence in their knowledge. Furthermore, the bivariate correlation analysis revealed a significant relationship between dependency on ChatGPT and procrastination (r = 0.546, p < .001), indicating that a higher reliance on AI tools may contribute to increased procrastination. No statistically significant association was identified between ChatGPT dependency and the risk of plagiarism. Future research should prioritize the development of strategies that promote the effective use of AI while minimizing the risk of over-reliance. Such efforts can enhance academic integrity and support independent learning. Educators play a critical role in this process by guiding students to balance the advantages of AI with the cultivation of critical thinking skills and adherence to ethical academic practices.

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.

This study examines the factors influencing English language achievement among non-English major undergraduate students in Thailand, with a specific focus on the differences between high-achieving and low-achieving learners. Conducted at Rajamangala University of Technology Lanna, this research adopts a mixed-methods approach, combining quantitative data from questionnaires and qualitative insights from semi-structured interviews. Three primary influencing factors were identified: student-related factors (e.g., motivation and self-regulated learning), teacher-related factors (e.g., pedagogical practices and teacher-student interactions), and environmental factors (e.g., availability of learning resources). Student motivation and self-regulation emerged as the strongest predictors of success, while teacher-related factors unexpectedly showed a negative influence, suggesting a misalignment between teaching strategies and student needs. Environmental factors, though positively perceived, had a less direct impact on outcomes. Practical implications include enhancing intrinsic motivation, adopting tailored teaching strategies to meet diverse learner needs, and strengthening teacher-student relationships to support low-achieving students. Policymakers are encouraged to address resource disparities and develop targeted interventions to enhance English language proficiency among students.

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 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.

: In this study, we present a didactic experience carried out in a public university with 60 students enrolled in the 2nd year of the Primary Education Teaching Degree. This experience consisted of implementing a teaching and learning sequence in which proportionality problems (mathematics content) and pure substances and mixtures (experimental science content) were addressed together in an ecodidactic garden context. This work presents the results obtained through the analysis of the students' responses. Our findings suggest that pre-service teachers have difficulties similar to those of primary and secondary students in the use of measuring instruments and conversion units, as well as in the calculation of proportions in mathematics and conceptual errors at a microscopic and macroscopic level in experimental sciences. This study highlights the need to design and implement strategies to support students in their formative process in relation to the contents of proportion and matter. As an added value in our work, we emphasize the interdisciplinary connection between mathematics and experimental sciences, offering a more real-life perspective of science.

The use of technology in education aims to improve students' problem-solving skills so that they have the skills needed by 21st century society in dealing with various kinds of challenges and problems. This study was carried out aiming to obtain the characteristics of augmented reality-based learning media for mathematics learning in student problem-solving skill, and obtain the results of the average difference in the problem-solving abilities of junior high school students. This research and development (R&D) study, employing the (Analyze, Design, Develop, Implement, and Evaluate) ADDIE model, investigated Augmented Reality (AR)-based learning media for mathematics to enhance junior high school students' problem-solving skills. The aim was to identify characteristics of effective AR media and assess their impact on problem-solving abilities. Quantitative data, collected from student problem-solving tests, were analyzed using a t-test in SPSS. The AR media featured virtual manipulation, virtual measurement tools, and real-world problem exploration. While the experimental group using AR showed a higher average problem-solving score compared to the control group using Problem-Based Learning (PBL), the difference was not statistically significant (t (df) = 0.638, Cohen's d = 0.0876). This lack of significance, despite the higher mean, is likely due to a small sample size and the limited integration timeframe, coupled with pre-existing skill variations. Future research should address these limitations to further explore the potential of AR in mathematics education.

This study aims to evaluate the effectiveness of cooperative learning models in improving critical reading skills. This study uses a meta-analysis study method by analyzing 28 articles extracted from the databases of Scopus, Google Scholar, EBSCO, EmeraldInsight, Science & Direct, SpringerLink, Taylor & Francis, and ProQuest. The meta-analysis allows researchers to combine the results of previous research, providing a more comprehensive picture of how effective a particular approach is in teaching critical reading. The research findings show that cooperative learning models significantly improve essential skills of reading more effectively than traditional ones. This is shown by the effect sizes based on the fixed model, showing the overall standard difference in the mean is 0.784 (95% CI, 0.689 to 0.880) with p-values = 0.00 (<0.05). Using a cooperative learning model, The measure showed positive effect sizes on critical reading learning. Based on these results, it can be concluded that the cooperative learning model effectively improves essential reading skills. However, several factors, such as the quality of the facilitators and the teaching methods, influence the results. The implications of this study show the need for a broader application of cooperative learning models to improve critical reading skills in schools and other educational institutions, with adjustments to the needs and characteristics of students.

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.