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.

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.

This study presents a comprehensive bibliometric and content analysis of research on autism and mathematics learning from 2010 to 2024. A total of 131 peer-reviewed articles were retrieved from the Web of Science (WoS) database using keywords such as autism, mathematics, learning, and intervention. Bibliometric analysis was conducted to quantitatively examine publication trends, leading authors, contributing countries, and co-authorship networks, offering a macroscopic overview of the field’s evolution. Visualisations generated using VOSviewer further illustrated keyword co-occurrence and thematic clustering. Complementing this, content analysis provided a qualitative synthesis of research themes and conceptual progressions across the literature. The findings revealed a clear thematic evolution. Early research (2010–2015) predominantly focused on behavioural interventions, structured instructional approaches, and basic numeracy development. Mid-phase studies (2016–2020) introduced inclusive pedagogies, social-emotional considerations, and differentiated instruction. Recent research (2021–2024) has shifted towards personalised, technology-enhanced instruction, Universal Design for Learning (UDL), and the integration of digital tools in mathematics education. Despite this growth, several gaps remain. Research remains limited in addressing cross-cultural diversity, long-term evaluations of digital interventions, and the adaptation of pedagogies in underrepresented regions. This study emphasises the need for future research to explore culturally responsive frameworks, the sustainability of technology uses, and equity in mathematics education for autistic learners.

This systematic review synthesizes research on the application of Augmented Reality (AR) technology in K–12 special education to evaluate its impact on learning outcomes and identify implementation trends, benefits, and challenges. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, a search of the Scopus, IEEE, Web of Science, and ProQuest databases on 20 March 2024 for English-language peer-reviewed articles published between 2010 and 2024 yielded 16 studies that met the inclusion criteria. The analysis of these studies reveals a growing research interest, particularly after 2019, with a concentration of research in developing nations like Indonesia and Malaysia. The findings consistently show that AR technology interventions, predominantly targeting students with learning disabilities and autism spectrum disorder (ASD) through 3D objects and game-based applications, positively impact academic achievement, motivation, and skill development. Despite these promising outcomes, this review concludes that a significant gap remains between the technology's potential and its current practice, hindered by challenges such as high costs, technical complexity, and a narrow research focus. Therefore, future work should prioritize developing cost-effective, user-friendly AR technology and expanding research to include a wider range of disabilities and educational contexts to ensure equitable and effective access for all students. 

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.

Globalization, digitalization, and evolving national regulations have intensified the need for rigorous quality-assurance systems to secure accreditation in Higher Education Institutions (HEIs). This study asks: What theoretical contributions underpin HEI accreditation, and how have research themes evolved? Employing the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and Bibliometric Analysis via Biblioshiny and Vantage Point, we examined 1,252 documents indexed in Scopus® (781) and Web of Science™ (471) from 2012 to May 2025. Findings delineate three production phases—Foundation Consolidation (2012–2017), Expansion and Diversification (2017–2020), and Sustained Transformation and Innovation (2020–2025)—and three thematic perspectives: (a) Teaching and Learning Quality, (b) Technology and Sustainability as Quality Catalysts, and (c) Governance, Management, and Accountability. Multiple Correspondence Analysis (MCA) identified three Motor Theme clusters—[1] Sustainable Development and Institutional Change, [2] Technological Pedagogy and Student Experience, and [3] Governance and Regulation—led by Spain, the United States, Chile, Colombia, the UK, Australia, and India. Conclusions underscore accreditation’s dual role as a strategic lever for institutional improvement and a competitive mechanism, with emerging focus on competency, e-learning, employability, machine learning, and sustainability. Future research should explore cross-border accreditation dynamics; the impact of AACSB and NAAC standards on business-school curriculum design and program quality; accreditation’s pedagogical effects; and leadership practices for effective implementation.

Information and Communication Technology (ICT) is increasingly developed and widely applied in education. Accordingly, teacher-training schools are continually improving pre-service teachers' ICT capacity. However, studies on ICT integration for pre-service teachers are still scattered. In this article, the author conducts a comprehensive systematic review of studies on ICT integration for pre-service teachers using bibliometric analysis techniques. Data from the Scopus database comprising 415 studies were analyzed using VOSviewer and Biblioshiny. In addition, the research designs used in the 10 most-cited articles were analyzed. The research results show that the first studies in this field appeared in 1997, but the number of publications has increased rapidly since 2018. Australia, Turkey, and Spain are the most influential countries in this field, while scholars from Belgium, Finland, and Singapore are among the most productive authors. The authors tend to publish in sources that are not highly ranked in Scopus. Research topics related to ICT integration of pre-service teachers can be classified into three main trends, including the use of ICT tools in higher education institutions under the impact of COVID-19, ICT integration models for professional development in teacher education, and research assessing the understanding and capacity of ICT integration and digital transformation of pre-service teachers at universities. This study analyzed the research trends on ICT integration of pre-service teachers to closely monitor the rapid development of this research area.

Despite the increasing integration of artificial intelligence (AI) into education, a comprehensive understanding of how scholarly discourse has evolved over time remains limited. Most existing studies focus on technical implementation or short-term pedagogical outcomes, often lacking longitudinal scope or thematic synthesis. This study addresses that gap by offering a 25-year bibliometric analysis of AI-related educational research, mapping its conceptual development, publication trends, and emerging priorities from 2000 to 2025. Using data sourced from Lens.org and processed through Biblioshiny (R-Studio) and VOSviewer, 350 peer-reviewed articles were analyzed based on their thematic focus, keyword evolution, authorship patterns, and citation networks. The novelty of this study lies in its integration of bibliometric mapping with temporal thematic evolution, enabling a detailed understanding of how foundational concepts, such as lifelong learning, AI literacy, and ethics, have transitioned from peripheral concerns to central research themes. Findings show a sharp increase in publication volume after 2018, reflecting the impact of cloud-based AI platforms and the pandemic-induced pivot to remote education. While “artificial intelligence” and “education” remain dominant keywords, emerging themes such as “student well-being,” “digital competency,” and “personalized learning” suggest a shift toward more human-centered and ethically conscious AI applications. The study concludes by identifying persistent gaps related to pedagogical effectiveness, global equity, and critical digital literacy, offering a roadmap for future interdisciplinary research and inclusive educational policy.