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.

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.

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.

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.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by persistent challenges in language acquisition, particularly in the lexical and semantic domains. This study examined the effectiveness of an adapted Applied Behavior Analysis (ABA) intervention in improving lexical and semantic language skills among preschool-aged children with ASD. A total of 3- to 6-year-old children participated, divided into experimental and control groups across two specialized centers. The experimental group received an adapted ABA-based program emphasizing discrete trial teaching, functional communication strategies, visual supports, and targeted reinforcement techniques. Pre- and post-intervention assessments were conducted using a structured methodology that evaluated active and passive vocabulary, semantic categorization, and contextual language use. Results from paired t-tests showed statistically significant improvements in the experimental group compared to the control group (p < .05). Despite these gains, generalization of language skills across social contexts remained limited. These findings highlight the value of individualized behavioral interventions and support their inclusion in early childhood programs for children with ASD.

This study examined the impact of reading journals on the development of English as a foreign language (EFL) reading comprehension and engagement, while also analyzing participants' perceptions of the learning process. A mixed-method design was applied to a sample of 80 second-year senior high school students (aged 15–18) with A2 proficiency. Using a quasi-experimental approach, participants were divided into an experimental group that kept journals and a control group that followed traditional instruction. Data were collected through pre- and post-tests, student questionnaires, and thematic analysis of the journals. Results showed significant improvements in reading performance among students in the experimental group. Students also reported better vocabulary retention, improved ability to identify main ideas, and greater confidence. Reflections revealed increased engagement, critical thinking, and autonomy. However, learners faced challenges such as complex grammar, summarization, and time constraints. Overall, the findings suggest that reading journals can be an effective strategy to support EFL reading comprehension and foster deeper interaction with texts.

The current study sought to evaluate the impact of programs used to enhance the self-regulation and social interaction for children with Autism Spectrum Disorders (ASD), as perceived by their families. The descriptive approach was used to collect and analyze data and derive conclusions after developing the study instruments. The study sample consisted of 150 families of children with ASD enrolled in special education centers in Amman, Jordan. The study participants were purposefully selected to respond to the two provided measurement scales. To measure the impact of the intervention programs, the researchers developed the Self-Regulation Behavior Scale and the Social Interaction Scale, ensuring the validity and reliability of both scales. The results of the study indicated that from the families’ perspective, programs for children with ASD had a moderate impact on enhancing self-regulation and a high impact on social interaction. Additionally, the findings of the study revealed statistically significant differences in the degree of improvement in self-regulation and social interaction behaviors related to the child’s gender and the severity of their disorder. However, no statistically significant differences were found related to the child’s age and gender in their level of improvement in self-regulation and social interaction behaviors.

This preliminary study examines how three generative AI tools, ChatGPT-4, Google Gemini, and Microsoft Copilot, support B+ level English as a Foreign Language (EFL) students in opinion essay writing. Conducted at a preparatory school in Türkiye, the study explored student use of the tools for brainstorming, outlining, and feedback across three essay tasks. A mixed methods design combined rubric-based evaluations, surveys, and reflections. Quantitative results showed no significant differences between tools for most criteria, indicating comparable performance in idea generation, essay structuring, and feedback. The only significant effect was in the feedback stage, where ChatGPT-4 scored higher than both Gemini and Copilot for actionability. In the brainstorming stage, a difference in argument relevance was observed across tools, but this was not statistically significant after post-hoc analysis. Qualitative findings revealed task-specific preferences: Gemini was favored for clarity and variety in brainstorming and outlining, ChatGPT-4 for detailed, clear, and actionable feedback, and Copilot for certain organizational strengths. While the tools performed similarly overall, perceptions varied by task and tool, highlighting the value of allowing flexible tool choice in EFL writing instruction.

This article aims to establish a research map of the flipped classroom (FC) model in general education for the period 2014-2024, exploring publication trends, influential authors, organizations, countries, and prominent research topics, while also identifying academic gaps in this field. The study focuses on three main aspects: (1) publication trends and influential authors, organizations, and countries; (2) key research topics and academic gaps; (3) international collaboration networks in FC research. The research employs a bibliometric analysis method, utilizing the Scopus database and the VOSviewer visualization tool, to synthesize information and identify research trends. The results indicate that research on FC in K-12 education increased sharply from 2019, reflecting the impact of digital transformation in education during and after Covid-19. The United States, Hong Kong, and Taiwan are the leading research centers. Authors such as Bergmann, Bishop, and Hew have been highly influential. Prominent research trends include self-regulated learning, learner satisfaction, gamification, and the application of artificial intelligence. The international collaboration network in this field is growing, with strong participation from institutions from Southeast Asia, including Vietnam. The study recommends expanding the scope of analysis beyond Scopus and using qualitative methods and systematic reviews to further evaluate the FC model. The research will provide policymakers, teachers, and researchers with useful evidence for improving programs, enhancing professional development, and promoting digital transformation in general education.

Our study examines the link between adolescents’ skills (mathematics, reading literacy, and physical fitness) and the frequency with which they participate in housework. We utilize a large longitudinal dataset of Hungarian adolescents (N = 37,461), making this, to our knowledge, the first European study on this topic. We use a rich set of background variables and fixed effects estimators to account for time-varying and time-invariant individual characteristics. Contrary to most of the literature we find cognitive skills to have no practically significant relationship with housework frequency. This discrepancy can be attributed to methodological choices (i.e., the use of the fixed effects estimator) or sociocultural differences in housework duties between the regions studied. Investigating heterogeneous effects on cognitive skills, we find girls’ literacy scores to be slightly affected by daily housework (-.02 SD), unlike boys’. The difference is more pronounced for children with highly educated parents and working mothers (-.06 SD). Substantially lower mathematics scores are detected for children who almost never participate in housework and have unemployed mothers (-.19 SD). Children who have chores to do almost every day and whose mothers are on parental leave also show signs of worsened mathematics ability (-.1 SD). Fitness levels of students who rarely engage in housework are significantly lower (-.04 SD), suggesting that some participation in household tasks contributes to physical well-being. This effect is pronounced for children of tertiary-educated parents (-.05 SD). Overall, findings suggest that household chores are cognitively neutral for most adolescents, have small physical-fitness benefits when performed in moderation, and become academically detrimental only at the extremes within specific family contexts.

Text readability assessment stands as a fundamental component of foreign language education because it directly determines students' ability to understand their course materials. The ability of current tools, including ChatGPT, to precisely measure text readability remains uncertain. Readability describes the ease with which readers can understand written material, while vocabulary complexity and sentence structure, along with syllable numbers and sentence length, determine its level. The traditional readability formulas rely on data from native speakers yet fail to address the specific requirements of language learners. The absence of appropriate readability assessment methods for foreign language instruction demonstrates the need for specialized approaches in this field. This research investigates the potential use of ChatGPT to evaluate text readability for foreign language students. The examination included selected textbooks through text analysis with ChatGPT to determine their readability level. The obtained results were evaluated against traditional readability assessment approaches and established formulas. The research aims to establish whether ChatGPT provides an effective method to evaluate educational texts for foreign language instruction. The research evaluates ChatGPT's capabilities beyond technical aspects. The study examines how this technology may influence students' learning experiences and outcomes. The text clarity evaluation capabilities of ChatGPT might lead to innovative approaches for developing educational tools. The implementation of this approach would generate lasting benefits for educational practices in schools. For example, ChatGPT’s readability classifications correlated strongly with Flesch-Kincaid scores (r = .75, p < .01), and its mean readability rating (M = 2.17, SD = 1.00) confirmed its sensitivity to text complexity.

The evaluation of Service-Learning (S-L) projects in online environments has become increasingly relevant in educational research, at the same time as the importance of using mixed methods has risen. However, there are few studies focusing on the evaluation of virtual Service-Learning, as most studies concentrate on face-to-face Service-Learning projects. In this regard, the aim of the present research is to assess three Virtual Service-Learning (vS-L) projects using a blended (quantitative-qualitative) evaluation method, also conducted online. The evaluation was conducted by students from the National University for Distance Learning, who completed a questionnaire asynchronously and participated in synchronous focus groups within their respective groups. Data were arranged in a mixed panel (questionnaire items and focus group verbatim opinions). The questionnaires demonstrated that Service-Learning is an excellent methodology to broaden students’ skills, abilities, and competencies to better face the professional world. The focus group verbatim interventions showed that the construction of indicators improves learning. Overall, the assessment results revealed a high level of student satisfaction. The implementation of our mixed-methods approach is innovative because it is conducted entirely online and utilizes computer technology for processing the gathered information.