Integrated learning has emerged as an approach to developing critical thinking and creativity skills. This meta-analysis synthesizes the effects of integrated learning on critical thinking and creativity, drawing from experimental studies published over the past decade. This study addresses the research question: What are the impacts and factors influencing integrated learning on students' critical thinking skills and creativity compared to conventional learning over the past decade? In the database, 403 articles were obtained, which were then supplemented by seven articles from manual searches, so that there were a total of 410 articles. After a strict inclusion process, 8 articles were selected for analysis. The inter-rater reliability test using Cohen's Kappa coefficient produced a value of 0.78, which indicates a substantial level of agreement. The analysis includes data from 497 participants for critical thinking and 266 for creativity. Heterogeneity in critical thinking skill data was 96%, and in creative skills, it was 86%; then, a subgroup analysis of education level was carried out to find out where the high heterogeneity was. The results show a significant positive effect of integrated learning, with an SMD of 1.48 (p = .004) for critical thinking and 1.60 (p = .0001) for creativity. Funnel plots and Egger's regression tests indicate no risk of publication bias. In addition, this study also synthesized the causal factors of how integrated learning affects critical thinking skills and creativity. Further research is recommended to explore its long-term impact and implementation strategies in various educational settings.  

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 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.

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.

The aim of this research was to assess changes in secondary school students’ grades longitudinally, including the semester before the COVID-19 pandemic, the period of distance learning, and two semesters when students had returned to face-to-face learning. In this longitudinal study, n=263 Latvian students’ grades from the period of six semesters (autumn 2019 to spring 2022) were collected and analyzed for seven study subjects (mathematics, English, Latvian, biology, chemistry, physics, and literature), using Friedman’s ANOVA, and Wilcoxon test for comparison. Results show that grades increased for several study subjects during the beginning of the distance learning period (e.g., mathematics and Latvian). However, this initial increase diminished after students had returned to schools to study in-person, especially for the subjects of mathematics and Latvian (native language). Decreases in students’ grades after returning to face-to-face studies indicate possible accumulated negative long-term effects of distance learning. The dynamics of the grades differ in various study subjects (e.g., relative stability in chemistry, decrease in mathematics, Latvian, biology), thus justifying the approach to analyze each study subject or study field separately. This study gives insight into longitudinal changes in students’ academic achievement, following the same students throughout their whole secondary school period from 10th to 12th grade during the pandemic.

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.

The COVID-19 pandemic has significantly changed the global educational landscape, prompting a need to explore emerging literature on home learning, literacy development, and parental involvement. This study aims to contribute to Sustainable Development Goals (SDG) 4: Quality Education, and SDG 10: Reduced Inequalities, by examining these aspects in the context of the pandemic and beyond through a bibliometric analysis. The analysis depicts 416 publications from the Web of Science Database between 2014–2023. The study utilized co-citation and co-word analysis techniques to identify key research clusters and trends related to home learning and literacy development. The analysis revealed that parental involvement can help mitigate learning loss, supporting SDG targets for equitable and inclusive education. Key research clusters identified include the influence of socio-economic status on literacy outcomes, continuity of literacy practices, and the long-term effects of traditional versus digital home learning environments. The findings highlighted a consensus on the importance of a supportive home literacy environment for reading skills and overall academic success. The need for intervention programs targeting low-income groups to ensure equitable access to learning resources, aligning with SDG 10, was also identified through the study. The findings have practical implications for enhancing the home literacy environment, increasing parental involvement, and supporting early literacy interventions, providing valuable insights for education stakeholders, policymakers, and researchers in the post-pandemic era.

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.

The proliferating field of writing education increasingly intersects with technological innovations, particularly generative artificial intelligence (GenAI) resources. Despite extensive research on automated writing evaluation systems, no empirical investigation has been reported so far on GenAI’s potential in cultivating intermedial writing skills within first language contexts. The present study explored the impact of ChatGPT as a writing assistant on university literature students’ intermedial writing proficiency. Employing a quasi-experimental design with a non-equivalent control group, researchers examined 52 undergraduate students’ essay writings over a 12-week intervention. Participants in the treatment group harnessed the conversational agent for iterative essay refinement, while the reference group followed traditional writing processes. Utilizing a comprehensive four-dimensional assessment rubric, researchers analyzed essays in terms of relevance, integration, specificity, and balance of intermedial references. Quantitative analyses revealed significant improvements in the AI-assisted group, particularly in relevance and insight facets. The findings add to the research on technology-empowered writing learning.

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 aim of this study is to investigate how postgraduate English as a Foreign Language (EFL) students perceive the impact of the Postgraduate Professional Diploma in Teaching program on promoting effective education for sustainable development (ESD). The study employed a descriptive approach, involving 228 participants. The study employed a 28-item questionnaire, and the data were analyzed using IBM SPSS Statistics software. The findings suggest that participants believe the program employs strategic actions and policies to achieve its long-term development goals for effective English teaching. The results also showed that participants place a high value on the program because it encourages innovative efforts to enhance the quality of learning, provides them with a range of assessment tools to help teach English effectively in the long term, and offers students opportunities to practice feedback techniques that enhance learning in the classroom. Furthermore, because participants were exposed to a pre-service training program in an effective manner, the results demonstrated statistically significant differences among participants regarding the program's impact on promoting effective ESD based on the study's variables. According to the study, it is also necessary to incorporate sustainable development concerns into English instruction and provide participants with information about the benefits of sustainable development.

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.