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 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.

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.

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.

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.

Research in mathematics education and interdisciplinarity is varied and extensive, covering multiple approaches that reflect a growing interest in this type of perspective. The objective of this study is to systematize the findings of research on interdisciplinary mathematics education published between 2019 and 2024. The review was carried out following the guidelines of the PRISMA statement, allowing us to identify 49 articles published in journals indexed in the Web of Science (WOS) and Scopus databases. Subsequently, a content analysis was carried out to identify methodological and theoretical aspects present in the studies reviewed, such as methodology employed, education level of participants, disciplines integrated with mathematics, and types of interdisciplinary tasks proposed. Additionally, four main research themes were identified: (a) understanding of interdisciplinarity; (b) pedagogical strategies for interdisciplinary development in mathematics education; (c) interdisciplinarity for the development of mathematical skills; and (d) professional development of mathematics teachers. The results reveal a sustained increase in the number of publications, which reflects a growing interest in the interdisciplinary approach in mathematics education. Finally, several challenges and opportunities are highlighted for future research, including the need to develop an interdisciplinary teacher training model, the creation of pedagogical strategies that promote greater interconnection between disciplines, and the need to carry out more studies focused on early childhood and primary education in this area.

This study investigated the relationships between conflict management strategies and family functioning among university students from diverse ethnic backgrounds in the multicultural context of Kosovo. A cross-sectional design was used with 362 university students (183 female, 179 male) comprising Kosovo Turks (58.6%), Albanians (23.8%), and Bosnians (17.7%). Data were collected using the Conflict Management Strategy Scale and Family Assessment Device. Path analysis was used to examine relationships between conflict strategies and family functioning dimensions. Students preferred compromising strategies most (M = 3.68) and withdrawing least (M = 2.98). Family functioning was healthy in problem-solving, communication, roles, affective responsiveness, and general functioning (scores < 2.0), but unhealthy in affective involvement (M = 2.29) and behavioral control (M = 2.12). Significant ethnic differences emerged in communication (F(2,144) = 3.158, p = .045, η² = .020) and behavioral control (F(2,149) = 4.109, p = .018, η² = .018), but not in conflict strategies. Path analysis revealed that withdrawing strategies negatively affected family functioning (β = .113-.143), while smoothing strategies had positive effects (β = -.139 to -.220). However, conflict strategies explained only 1.6-4.3% of the variance in family functioning (R² = .016-.043), indicating small effect sizes. While statistically significant relationships exist between conflict management strategies and family functioning, effect sizes are modest. Ethnic variations in these relationships emphasize the importance of cultural considerations for family counseling practices. The findings suggest that conflict management training may have a limited direct impact on family functioning, highlighting the need for comprehensive, culturally sensitive intervention approaches.