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.

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.

Augmented reality technologies can create unique interactive learning environments for students with special educational needs that enrich the learning process and provide immediate feedback. This research analyzed the use of augmented reality in teaching digital literacy courses for primary school children with special educational needs. The study involved a quasi-experiment with participants using a mobile augmented reality application to assess its impacts on learning outcomes. The results showed the positive effects of augmented reality on student achievement. The results highlight the potential of augmented reality in inclusive education. In addition, the findings emphasize the importance of further research and development in this area and an increased use of augmented reality to improve the educational experience of students with disabilities. In light of the results, we conclude with recommendations for integrating augmented reality into educational programs and improving educational practices.

Augmented reality offers diverse potential applications for STEM education, enabling students to engage directly with virtual elements in real-time and providing them with immersive, natural experiences. This study conducted a bibliometric analysis of articles on this topic on the Scopus database to determine some quantitative information, such as general information about publications, countries, institutions, authors with the most contributions, and key trends in applying augmented reality technology in STEM education. An analysis of 201 studies published from 2005 to 2023 using Biblioshiny software and VOSviewer reveals that the United States leads in the number of studies conducted on this issue. Kryvyi Rih National University, Ukraine, has the most studies. The authors who contributed the most studies with the most citations on this issue are Lindner, C. and Rienow, A. from Ruhr University Bochum, Germany. Two primary research trends emerge, focusing on how Augmented Reality technology is utilized, particularly in STEM fields like Chemistry, which combines learning forms with other learning support tools and media such as mobile applications. Secondly, integrating augmented reality and virtual reality technologies into STEM programs at the university level, design of games, and virtual tools. This study offers important data for researchers looking to explore future applications of augmented reality technology within STEM education.

Considering the importance of the results of national and international standardized tests, which are a benchmark for measuring educational quality, the objective of this research was to model strategies to improve the results of the evaluations, specifically the Saber 11 standardized tests. These tests are applied to students who finish their Vocational Education and Training (VET) in Bogotá, Colombia. To achieve this objective, we employed the Systems Dynamics methodology for a comprehensive analysis, which is a tool that allows for the analysis and projecting of the behavior of different systems, in which anticipation by means of modeling results over time is required. The modeling was conducted in two stages: First, a causal loop diagram and a stock-and-flow diagram that linked 45 variables were designed, showing the underlying physical structure of the system. Then, five groups of alternative simulations were conducted over a time frame of six years: Reference mode, student self-efficacy rate, management rate, teaching competencies rate, and educational policy. An increase in results was observed in each scenario. The combined activity of educational stakeholders is a notably effective strategy to achieve significant improvements. The data used for these simulations came from a six-year period of standardized test results in Bogotá. This period was selected to capture both recent trends and long-term outcomes, ensuring that the model reflects current educational conditions while allowing for meaningful trend analysis.

The sense of belonging is a human need that educational systems must foster to achieve student success. In the school setting, this feeling strengthens the bond between members of the institution and motivates families to become more involved with the school, improving the overall school climate. Teachers play a crucial role in promoting this sense of belonging by influencing the connection between families and the educational community. This study aims to understand how teachers from different contexts, one Colombian and the other Spanish, promote families' sense of belonging to the school. To this end, an evaluative, comparative, quantitative, and non-experimental study was conducted using a validated questionnaire applied to a significant sample in both contexts. The results show that, for teachers in both contexts, it is very important for families to feel satisfied with the education their children receive, which is why they strive to build trust in the teaching staff. The sense of belonging is more strongly promoted by teachers in charter schools and those with more years of experience in schools in the Spanish context. In the Colombian context, women are the ones who most actively promote it, thereby perpetuating gender roles. There is a need to provide specific training for teachers to help them develop this capacity in families, as well as to conduct further research to explore the differences that may influence the promotion of a sense of belonging.

The rapid advancement of science, engineering, and technology, driven by the Fourth Industrial Revolution, has heightened the demand for a highly skilled workforce in science, technology, engineering, and mathematics (STEM) fields. Integrated STEM education has emerged as a key driver of educational innovation in Vietnam, spanning both general and higher education. The competence of university lecturers in delivering integrated STEM education, a newly recognized pedagogical and professional skill set, is crucial to the success of STEM education at the tertiary level. As with general pedagogical competence, the development of an integrated STEM education competence framework is essential for enhancing this capability among university lecturers. However, there remains a lack of theoretical foundation and best practices tailored to the Vietnamese higher education context. This study aims to develop a framework for integrated STEM education competence specifically for university lecturers through document analysis and survey research. Multivariate statistical techniques, including exploratory factor analysis (EFA), Cronbach’s alpha, and Pearson correlation, were applied to analyze data collected from 205 lecturers across nine public universities in Vietnam. The integrated STEM education competence framework for Vietnamese university lecturers consists of three component competencies and 23 items: designing and implementing integrated STEM education (15 items), assessing integrated STEM learning outcomes (4 items), and demonstrating positive attitudes toward integrated STEM education (4 items). The framework was found to be both reliable and valid, with strong positive correlations among the three component competencies. This study also outlines limitations and provides recommendations for future research.

University dropout is a multidimensional and multicausal problem that affects every university around the world. The aim of this article is to conduct a bibliometric review of the scientific literature on the main factors that influence university dropouts in scientific publications between 2018 and 2022. The methodology is based on systematic searches using the Web of Science (WoS) and Scopus databases. We analysed 417 and 498 articles, respectively, applying inclusion/exclusion criteria. The main factors of university dropout were identified: problems in the academic and social world of students, student stress, health reasons, the role of teachers, and changes in the education system. Among the countries with the highest scientific output, Spain stands out, along with the United States, the United Kingdom, Australia, and China. This would provide a more complete view of the historical evolution and multifactorial causes of this educational phenomenon.

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 evaluates the impact of an educational intervention strategy – Project-Based Learning (PBL) – designed to enhance university students' knowledge of the Sustainable Development Goals (SDGs), their integration into academic curricula, and their relevance for future professional and personal applications. The research is motivated by the recognised importance of the SDGs in education and the current limited integration and understanding within higher education settings. The study applied a pre-test and post-test experimental design used, involving 199 first-year students from the University of Cordoba (Spain), enrolled in Primary and Early Childhood Education programmes. The intervention comprised PBL activities aimed at increasing knowledge and perceptions of the SDGs. Data were collected using a questionnaire assessing three dimensions: knowledge of the SDGs, the importance of their inclusion in the curriculum, and the perceived relevance of applying SDG principles in professional and personal contexts. The findings indicate that the intervention strategy effectively improved, albeit partially, students' understanding and perception of the SDGs. There was a significant improvement in students' knowledge. However, regarding the perceived importance of integrating the SDGs into their curriculum and the relevance of the SDGs for their future professional and personal lives, no effects were observed. These results underscore the partial efficacy of PBL in promoting sustainability competences and global citizenship among students, suggesting the need to explore other pedagogical methodologies for greater effectiveness. The study advocates the integration of SDGs into higher education curricula to better prepare students for future challenges, emphasising the need for further research to explore the long-term impacts and broader applicability of such educational intervention.

Sensory integration (SI)-based intervention programs aim to improve the motor performance of children with moderate autism spectrum disorder (MASD), which may contribute to the development of their gross and fine motor skills. This study aimed to explore the effectiveness of a SI-based training program in developing gross and fine motor skills in 70 children with MASD aged 6–9 years (M = 7.11, SD ± 1.19) and selected intentionally from a daycare center in Al-Ahsa in Saudi Arabia. The study used the quasi-experimental approach and followed the experimental design with two groups, which were randomly distributed and examined for equivalence. The study also used the Gross Motor Skills Scale (GMSS), the Fine Motor Skills Scale (FMSS), and the training program based on SI. The study found that the experimental group had significantly higher post-test scores in the GMSS and the FMSS than the control group, with these differences being statistically significant. However, no significant difference was observed between the post-test scores and the follow-up test scores within the experimental group, indicating stability in their performance over time. This indicates the effectiveness of the training program used in developing the targeted skills and the continuation of the training effect after the program’s application period. The study suggests that children should use SI-based training programs to enhance their motor skills.

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 paper presents the results of an action research conducted in a kindergarten in Sarajevo Canton. The participants were four female kindergarten educators who collaborated with two university professors who took the role of research leaders and moderators of reflective meetings. The action research was conceived as a model of professional development for preschool teachers in the Reggio pedagogy field, aiming to develop the skill of documenting pedagogical observation and the competence of implementing reflective practice (RP below the text) based on the Reggio principles. Data were collected on two levels: the educators documented their educational practice (photos, transcripts, videos, etc.), which was the basic material for analysis at collaborative reflective meetings, and all of it was documented by the research leaders. The data were analyzed simultaneously during the research (to decide on further action) and finally at the end of the research. The results of the research indicate that the action research raised awareness of the elements of traditional educational practice and developed the skills of pedagogical documentation management and the skill of implementing RP. Considering the limited time period for the realization of the research (14 months), significant but not optimal results were achieved, and there is still room for further progress in terms of improving the skills of keeping records and the capacity of RP implementation. It is necessary to systematically provide support for the professional development of educators through the development of reflective learning communities in kindergartens instead of the one-off and lecture-based forms that are offered.

Research fronts are dynamic, knowledge-driven clusters of scholarly activity that emerge in response to pressing problems and/or groundbreaking discoveries. Clarivate Analytics provided a valuable tool based on Citation Productivity and Trajectory (CPT) indicator, which successfully identified particularly hot research fronts on a global scale. To enhance the accuracy and comprehensiveness of identifying both active and emerging research trends, this study develops an extended Clarivate formulation incorporating a novel Impact Factor (IF) metric. The refined approach incorporates growth rates, publication productivity, and the average publication gap between published and citing publications. This method is applied to exploring key research fronts in the digital education ecosystem using bibliometric data from the Scopus database in the period of 2019-2023. The results reveal that artificial intelligence and online learning are the most prominent and influential fields, with virtual reality, blockchain, hybrid learning, and digital literacy representing fast-growing areas. By analyzing both quantitative and qualitative aspects, this work informs key stakeholders about the evolving priorities and trends in the digital educational landscape.

This study investigates the ideological orientations of teachers and the potential transformation of these orientations over 14 weeks, focusing specifically on their conceptualizations of educational ideologies within conservative and liberal frameworks. The research employs an inventory-based assessment to capture participants’ ideological stances. Initial findings revealed participants’ tendency to associate ideological labels with political dualities, reflecting simplified views on educational ideologies. Throughout the study’s second phase, participants engaged in critical reading assignments and reflective discussions designed to expand their awareness and understanding of various educational ideological paradigms. Findings indicate a notable shift in ideological positioning, primarily driven by exposure to foundational texts and structured reflection sessions. In the final phase, participants re-took the initial inventory, allowing for a direct comparison of ideological stances. The comparative analysis demonstrated subtle yet significant shifts, particularly regarding participants’ views on the interrelations between educational ideology, social equity, and the intellectual demands of modern pedagogy. This study underscores the transformative potential of immersive engagement with diverse ideological perspectives, highlighting the need for professional development models that prioritize reflective dialogue and critical exploration of ideological content.

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.

This article deals with the European Union's educational policies during the Covid-19 pandemic when several cracks and vulnerabilities in its Member States' education systems were exposed across the European Union (EU). In this sense, and with this exceptional period as a reference, we propose to research whether the Community's educational policies reflect a reinforcement of the commitment to education as one of the pillars of European integration. Other studies have not yet addressed the possible impact of this exceptional period on the design of European educational policies as integration mechanisms. Namely, whether there would be a pause in the integration process or, on the contrary, its strengthening and, if so, in what respect. For this research objective, several documents from the most important European institutions were examined. Its results allow us to verify the intention to renew education as an essential element of European integration and as an instrument to promote the EU as an economically stable and socially integrated community.

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.