This mixed-methods study investigates the impact of the Science, Technology, Engineering, Arts, and Mathematics (STEAM) method and fifth-semester student engagement on entrepreneurial competencies in the higher education of the makeup and beauty program at Padang State University. Using a convergent parallel design, data were collected from 117 fifth-semester students through questionnaires, interviews, observations, and portfolio assessments. The data were analyzed using Two-Way ANOVA and thematic analysis. The quantitative results revealed that the STEAM approach significantly outperformed conventional methods. Specifically, 83.33% of students achieved excellent leadership scores (M = 89.00, SD = 2.85), and 78.33% excelled in creativity (M = 87.50, SD = 2.98). High levels of engagement (M = 4.33) across behavioral, emotional, and cognitive dimensions correlated with enhanced competencies (p < .001). Qualitative findings indicated increased motivation, collaborative learning through platforms like TikTok Shop, and heightened mental engagement from diverse resources. The interaction between the STEAM and student engagement further amplified outcomes (F = 3.75, p = .025, R² = 0.454). This study highlights the transformative potential of the STEAM method in developing entrepreneurial competencies, underscoring its applicability in vocational education. Educators should integrate STEAM methodologies and digital platforms into their curricula, while future research should examine the long-term impacts and scalability of these approaches.

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.

This study examines the transformation of higher education through digital solutions, with a specific focus on developing a user-centered digital student handbook prototype for Surin Vocational College in Thailand, with potential scalability nationwide. Utilizing a mixed-methods approach, the research integrates qualitative and quantitative data to design a digital tool that enhances accessibility, usability, and personalization for students. The prototype features key components, including mobile accessibility, real-time updates, interactive notifications, and integration with academic tools, designed to enhance student engagement, career readiness, and academic performance. Data collection involved students, faculty, and experts to ensure a comprehensive understanding of user needs and preferences. The findings indicate that the digital format offers significant advantages over traditional paper-based handbooks, particularly in terms of accessibility, real-time content updates, personalized experiences, and environmental sustainability. However, variability in user feedback suggests areas for further refinement,  emphasizing that there must be continuous improvement. This research offers interesting perspectives on the role of digital solutions in higher education, contributing to the ongoing evolution of learning tools that support academic success, student engagement, and institutional sustainability.

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.

The emergence of artificial intelligence (AI) has transformed higher education, creating both opportunities and challenges in cultivating students’ critical thinking skills. This study integrates quantitative bibliometric analysis and qualitative systematic literature review (SLR) to map global research trends and identify how critical thinking is conceptualized, constructed, and developed in the AI era. Scopus served as the primary data source, limited to publications from 2022 to 2024, retrieved on February 8, 2025. Bibliometric analysis using Biblioshiny R and VOSviewer followed five stages—design, data collection, analysis, visualization, and interpretation—while the SLR employed a deductive thematic approach consistent with PRISMA guidelines. A total of 322 documents were analyzed bibliometrically, and 34 were included in the qualitative synthesis. Results show that Education Sciences and Cogent Education are the most productive journals, whereas Education and Information Technologies have the highest citation impact. Several influential documents and authors have shaped global discussions on AI adoption in higher education and its relationship to critical thinking. Thematic mapping identified five major research clusters: pedagogical integration, ethical and evaluative practices, technical and application-oriented AI models, institutional accountability, and socio-technical systems thinking. Conceptually, critical thinking is understood as a reflective, evaluative, and metacognitive reasoning process grounded in intellectual autonomy and ethical judgment. Across the reviewed literature, strategies for fostering critical thinking converge into three integrated approaches: ethical curriculum integration, pedagogical and assessment redesign, and reflective human–AI collaboration. Collectively, these strategies ensure that AI strengthens rather than replaces human reasoning in higher education.