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.

With the current rate of technological advancements, higher education institutions around the world are increasingly adopting a wide variety of technology-related approaches to instruction. One of the teaching strategies used on digital platforms that has been successfully and widely adopted in higher education institutions is blended learning (BL). The objective of this investigation is to provide a comprehensive examination of the research efforts on BL in the context of higher education (HE) over the past 20 years, including the rise in publications, the most cited scientific journals and sources, and the upcoming research topics. This paper uses bibliometric analysis with a dataset of 651 documents from Scopus data, including 638 authors from 95 countries published in 271 journal sources. The results of the study show that the top three countries for BL research in higher education are the United Kingdom, the United States, and Australia; the authors with the highest citation indexes are D. R. Garrison and B. Means, and the top two publishing sources are Education and Information Technologies and Internet and Higher Education. Based on the analysis, the main trends detected are (a) student participation and environment, (b) educational technology instructional innovation, (c) effective instructional strategies within the parameters of the COVID-19 pandemic, (d) effectiveness of evaluation in BL environments and (e) BL with Massive Open Online Courses (MOOCs) and Learning Management System (LMS) in HE. These findings offer meaningful insights to early career researchers who consult the publications and research lists above, as well as to policy makers who develop suitable BL in HE policies.

The world is looking forward to advancements in artificial intelligence (AI) technology, with significant research underway regarding the application of AI in education. This study analyzed publications on the potential of AI in secondary schools, focusing on its bibliometric aspects. Data from the Scopus database revealed 1,764 publications from 2019 to 2024. The analysis showed a steady annual growth in publications in this area. China and the USA were the leaders in the number of publications. Xiaoyue Wang was the most prolific researcher, having authored 71 AI-related articles. Yueying Li, Xiaoxu Chen, Yanzhu Zhang, and Yi Liu contributed to the field with 56, 55, 53, and 51 articles, respectively. The themes that emerged from 2019 to 2022 are related to media, application, study, institutions, artificial, digital, learning, factors, development, technologies, medical, automated, perception, support, and sustainability. From 2023 to 2024, the topics discussed in AI are related to students, education, perception, algorithms, digital, prediction, networks, challenges, writing, teachers, AI-powered, curriculum, century, integration, technology, and framework. The difference in research in 2019-2022 and 2023-2024 is focusing the theme's focus from the general to the specific. The co-occurrence analysis revealed that prominent keywords appeared in 3 clusters. Cluster 1 is the most popular in recent times. It deals with the application, assessment, and management of AI. Cluster 2 relates to AI relationships and models, while Cluster 3 relates to AI data sources.

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 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.

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.

The higher education system in Vietnam is undergoing a significant shift from training based on university capacity to training based on labor market demands. In a developing economy dominated by small and medium-sized enterprises, it is a big challenge to train graduates to meet changing and very diverse competence requirements. AI and machine learning tools are applied in three stages: (a) processing survey data: Expected learning outcomes (pELOs) are quantified into credit values, with each module's contribution determined using the apriori algorithm and expert methods; (b) Optimizing framework curricula (FC): A genetic algorithm identifies module combinations that meet all pELOs while minimizing redundancy within a specified study duration; (c) Framework curriculum adjustment (FCA): An FCA tool, using genetic algorithms, enables schools to update FC annually and allows learners to personalize their programs. WEKA is used to implement the apriori algorithm (https://www.cs.waikato.ac.nz/ml/weka). The PASCAL language is used to write GA and its associated subroutines. Foreign language bachelor's degree programs at the University of Languages and International Studies Vietnam National University, Hanoi, (ULIS-VNU) were used to test algorithms and procedures. According to the calculations, present FCs have caused overstudy and can be modified for every employment post to reduce the surplus credit values that have accrued. Furthermore, FCA can assist in making the curriculum more flexible so that students can more easily switch out FC modules based on their skills and circumstances while still meeting all of the stated ELOs. Under project number N.21.13, this research piece was finished with assistance from ULIS-VNU.

With the introduction of the new curriculum, primary school Croatian fine arts teachers faced many challenges. The fundamental problem, the lack of school lessons, is highlighted by the challenges of implementing problem and project work and integrating technology into the teaching process. Therefore, it is important to organise activities where pupils use modern tools and media for high-quality educational purposes. The animation was chosen as a fine arts technique that can fulfil these requirements. Qualitative action research was conducted in city Split in the school year 2023/2024. The 5th and 8th grade pupils (125) and their fine arts teachers (3) participated in the research. A total of 75.23% of respondents were positive about the occasional introduction of technology into fine arts classes. After completing the fine arts project, 77.98% of pupils stated that they now have the knowledge and skills to create an animation themselves, while 77% of pupils consider their digital stories to be interesting and original. All three fine arts teachers cite a lack of continuity due to the small number of lessons as a shortcoming. The results point to poor material conditions: overheating of old projectors, low-quality tablets, poor internet connection and lack of power sockets. The research has shown that there are discrepancies between the prescribed theoretical requirements for learning outcomes and the possibilities for their practical realisation. As a result, teachers need to take a keen interest and receive additional training to ensure that the projects designed are in line with the requirements of the curriculum.

This study explores the impact of artificial intelligence (AI) integration on students' educational experiences. It investigates student perceptions of AI across various academic aspects, such as module outlines, learning outcomes, curriculum design, instructional activities, assessments, and feedback mechanisms. It evaluates the impact of AI on students' learning experiences, critical thinking, self-assessment, cognitive development, and academic integrity. This research used a structured survey distributed to 300 students through Microsoft Forms 365, yet the response rate was 29.67%. A structured survey and thematic analysis were employed to gather insights from 89 students. Thematic analysis is a qualitative method for identifying and analysing patterns or themes within data, providing insights into key ideas and trends. The limited response rate may be attributed to learners' cultural backgrounds, as not all students are interested in research or familiar with AI tools. The survey questions are about AI integration in different academic areas. Thematic analysis was used to identify patterns and themes within the data. Benefits such as enhanced critical thinking, timely feedback, and personalised learning experiences are prevalent. AI tools like Turnitin supported academic integrity, and platforms like ChatGPT and Grammarly were particularly valued for their utility in academic tasks. The study acknowledges limitations linked to the small sample size and a focus on undergraduate learners only. The findings suggest that AI can significantly improve educational experiences. AI provides tailored support and promotes ethical practices. This study recommends continued and expanded use of AI technologies in education while addressing potential implementation challenges.

The field of engineering education is constantly evolving to meet the challenges of technological and societal advancements. Continuous research should be conducted to identify the potential match between the skills that employers seek and the ones engineering graduates gain at college. The purpose of this study is to identify areas of agreement and disagreement between the faculty and employers regarding the skills and knowledge that engineering students acquire during their undergraduate education. The study uses an explanatory sequential design method by employing a questionnaire that was developed based on the Engineering Competency Model (ECM) by the Employment and Training Administration of the USA Department of Labor and responded to by 125 volunteer engineering faculty. Additionally, interviews were conducted with 2 industry professionals to gain deeper qualitative insights. The study found that while faculty mainly stated that students acquire personal effectiveness, academic, and workplace competencies in college, employers disagreed with these perceptions, particularly regarding interpersonal skills, integrity, professionalism, writing, and communication. Additionally, the study found a significant mismatch between faculty and employer assessments of industry-wide competencies, with employers expressing concerns about graduates' preparedness in areas like design, business, and sustainability. These findings suggest significant updates and cooperation with industry experts in engineering curricula and their implementation.

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.  

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.

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.

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 presents a comprehensive bibliometric and content analysis of research on autism and mathematics learning from 2010 to 2024. A total of 131 peer-reviewed articles were retrieved from the Web of Science (WoS) database using keywords such as autism, mathematics, learning, and intervention. Bibliometric analysis was conducted to quantitatively examine publication trends, leading authors, contributing countries, and co-authorship networks, offering a macroscopic overview of the field’s evolution. Visualisations generated using VOSviewer further illustrated keyword co-occurrence and thematic clustering. Complementing this, content analysis provided a qualitative synthesis of research themes and conceptual progressions across the literature. The findings revealed a clear thematic evolution. Early research (2010–2015) predominantly focused on behavioural interventions, structured instructional approaches, and basic numeracy development. Mid-phase studies (2016–2020) introduced inclusive pedagogies, social-emotional considerations, and differentiated instruction. Recent research (2021–2024) has shifted towards personalised, technology-enhanced instruction, Universal Design for Learning (UDL), and the integration of digital tools in mathematics education. Despite this growth, several gaps remain. Research remains limited in addressing cross-cultural diversity, long-term evaluations of digital interventions, and the adaptation of pedagogies in underrepresented regions. This study emphasises the need for future research to explore culturally responsive frameworks, the sustainability of technology uses, and equity in mathematics education for autistic learners.