Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.

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.

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.

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.

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.

This study examines the impact of Project-Based Learning (PjBL) on developing metacognitive skills among preservice science teachers (PSTs) in Northeast Thailand. A sample of 143 PSTs, including first-year students in General Biology 1, second-year students in General Physics 1, and third-year students in Basic Organic Chemistry, participated in an 18-week programme. The study aimed to assess changes in metacognitive skills before and after PjBL implementation, evaluate differences among academic years, and identify predictors of skill development. The methodology included a six-hour orientation workshop and a collaborative, project-based curriculum. Descriptive and inferential statistics were employed, with the item-objective congruence index (IOC) for content validity, paired samples t-tests for pre- and post-intervention comparisons, and Analysis of Variance (ANOVA) to examine differences across academic years. Multiple regression analysis was used to identify significant predictors of metacognitive skill development. Results showed significant improvements in metacognitive skills post-PjBL, with substantial enhancements across all subjects. ANOVA indicated significant differences among academic years, with third-year students demonstrating the highest metacognitive skill levels. Multiple regression analysis identified participation in PjBL and academic level as significant predictors of metacognitive skill development. These findings highlight the effectiveness of PjBL in enhancing metacognitive skills and underscore the importance of active learning and reflective practices in teacher education programmes. This study provides valuable insights into the impact of PjBL on PSTs' professional growth and instructional efficacy, preparing them for modern classroom challenges.

This umbrella review aimed to synthesize variables that explain dropout among students in preschool, primary, secondary, and high school education. The study focused on peer-reviewed articles indexed in SCOPUS, Web of Science, and ERIC, identifying five systematic reviews that provided comprehensive insights. Key findings revealed individual factors, such as insufficient parental support, emotional and behavioral challenges, and substance use, play significant roles in influencing student dropout. Socioeconomic factors, including poverty, financial constraints, and social inequalities, were also identified as critical contributors. Additionally, institutional elements such as inadequate school infrastructure, insufficient teacher training, and a lack of culturally relevant resources emerged as barriers to student retention. This review highlights research gaps in political-legislative, sociocultural, and family determinants, longitudinal analyses, dropout interventions’ long-term effectiveness, and marginalized populations’ representation, limiting a comprehensive understanding of student dropout and effective policy development. Recommendations include targeted policies and interventions that foster inclusive and supportive educational environments, reduce inequities, and improve access to resources to minimize dropout rates among students in preschool, primary, secondary, and high school education.

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 analyzes trends, collaborations, and research developments on augmented reality (AR) in mathematics education using a bibliometric approach. Data were collected from the Scopus database on July 31, 2024, identifying 542 documents published between 2015 and 2024. After screening, 194 journal articles were selected for analysis. Using VOSviewer, the study produced visualizations related to document types, publication trends, journal sources, research subjects, institutions, countries, keywords, and author collaborations. The results show that 88.7% of the documents are journal articles, indicating that this topic is predominantly published in scholarly journals. Publication trends reveal significant growth since 2016, peaking in 2024, reflecting increasing global interest. Education Sciences and IEEE Access are among the top journal sources. Subject-wise, social sciences and computer science are the main disciplines exploring AR in mathematics education. Chitkara University (India) and Johannes Kepler University Linz (Austria) are leading institutions, while the United States, Malaysia, and Spain contribute the most publications. Keyword analysis shows rapid growth in research using terms such as "augmented reality" and "mathematics education," emphasizing the role of immersive technology in enhancing student engagement and conceptual understanding through visual and interactive learning. Influential authors like Lavicza, Mantri, and Haas highlight the importance of global collaboration. Based on a thematic analysis of the most-cited articles, this study proposes the AI Mathematical Education Impact and Outcome Framework. In conclusion, although research on AR in mathematics education has significantly advanced, further studies are needed to evaluate its effectiveness across varied educational contexts.

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.

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 present study examined how empathy (affective and cognitive), basic psychological need satisfaction (autonomy, competence, and relatedness), and demographic factors (gender and academic achievement) jointly predict prosocial behavior during emerging adulthood. Grounded in Self-Determination Theory, this research explored whether relatedness need satisfaction mediates the relationship between empathy and prosocial tendencies. A total of N=889 undergraduate students from a large public university in the southeastern United States completed self-report measures assessing empathy, psychological needs, and prosocial behavior. Path analysis revealed that affective empathy and relatedness satisfaction were significant predictors of prosocial behavior. Relatedness also partially mediated the link between empathy and helping actions. Furthermore, gender and GPA contributed to prosocial outcomes, with female students and those with higher academic achievement reporting greater prosocial tendencies. These findings suggest that fostering emotional engagement and supporting students’ psychological needs—particularly the need for relatedness—may be key mechanisms for promoting prosocial development in educational settings during the critical stage of emerging adulthood.