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.

The education of gifted students is often characterized by high expectations, ambitious goals, and significant effort invested in learning. Their experiences of success and failure are shaped by a variety of factors, including personal, family, school, cultural, and social influences. This article examines how gifted students perceive and experience their own successes and failures, as well as how these experiences are perceived and responded to by their peers. Using qualitative methods, the study involved semi-structured interviews with thirty gifted students from seventh to ninth grades across ten elementary schools in Slovenia. The findings indicate that gifted students experience a range of emotions in response to success, from satisfaction to anxiety, while their reactions to failure often involve frustration and self-criticism. Peer responses to their success and failure vary significantly, ranging from supportive encouragement to jealousy and social exclusion. These findings highlight the complex interpersonal dynamics at play within school environments. Understanding and addressing these dynamics is crucial for creating inclusive, supportive, and stimulating learning environments that nurture both the academic and social-emotional well-being of gifted students.

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 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.

This article provides a comprehensive guide to conducting and documenting systematic reviews (SRs) in educational research. While SRs are increasingly recognized for their value in synthesizing and evaluating literature on specific research questions or topics, there remains a notable scarcity of research-based papers that guide their development within the field of education. Systematic reviews, distinguished from traditional literature reviews by their standardized processes—including systematic searching, selection, and critical appraisal of relevant studies—offer a more accurate and comprehensive understanding of the research landscape by integrating findings from multiple sources. This paper underscores the importance of adhering to established methodologies and guidelines to ensure the quality and reliability of SRs. Essential elements discussed include defining research questions, developing search strategies, applying inclusion and exclusion criteria, and synthesizing results. The paper also highlights the role of frameworks such as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in enhancing transparency and methodological rigor. By following this structured approach, researchers can produce systematic reviews that provide valuable insights into educational practices and policies, thereby supporting evidence-based decision-making and advancing the field of 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.

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.

In recent years, particularly over the last 10–15 years, the scientific value of oral history in relation to historical and social knowledge has been increasingly recognized. Since the 1980s, oral history researchers have pioneered new approaches to interpreting human experience, highlighting oral biographical narratives and recounted experiences as valuable material for social research. According to Tsiolis, the biographical narrative approach has become an established scientific methodology for studying how social actors interact with their environment and respond to social changes, as these are reflected through their subjectivity. Based on the above, this study involved four academic lecturers who narrated their academic and professional journeys, the factors that influenced them, the challenges they faced, and the positive impact of their engagement with teaching in the context of Greek higher education. The research employed the methodology of narrative biography, allowing the participants to recount their academic trajectories spontaneously, recalling personal experiences and memories. Through these narratives, qualitative data emerged, which were analyzed and coded into common themes, leading to conclusions about the conditions, aspirations, and disappointments experienced by academics in higher education institutions. The paper concludes some limitations of the current study and offers suggestions for future research.

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.