Emerging Technologies in Process Management and Educational Quality: A Bibliometric Analysis of Public Institutions

This study provides a bibliometric analysis of research on process management in public educational institutions, examining trends, collaborations, and dominant themes between 2000 and 2023 using data extracted from Scopus. Tools such as VOSviewer and Bibliometrix were employed to visualize research patterns and thematic clusters. Findings show growing research on process optimization, enhancing institutional efficiency, equitable access, and student learning environments in public education. Key challenges identified include the ethical integration of emerging technologies, such as artificial intelligence and blockchain, and the need for localized adaptations in developing countries. The analysis highlights gaps in interdisciplinary approaches and insufficient studies addressing cultural resistance to process changes. Moreover, it underscores the importance of advancing quality assurance practices and leveraging digital transformation to optimize workflows. Future research should prioritize context-specific strategies and evaluate their impact on student performance, organizational adaptability, and equity. This study contributes to the theoretical foundation for process management and provides insights for policymakers and administrators to enhance educational systems through evidence-based practices and technological innovation. Received: 20 March 2025 / Accepted: 19 June 2025 / Published: 05 July 2025

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Publication Details

Journal
Journal of Educational and Social Research
Published
2025-07-05
DOI
https://doi.org/10.36941/jesr-2025-0143
Citations
1
Primary Topic
Advanced Data Processing Techniques
Type
article
Field-Weighted Citation Impact
1.21
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article

Emerging Technologies in Process Management and Educational Quality: A Bibliometric Analysis of Public Institutions

Alex Javier Sánchez Pantaleón, Victor Manuel Valdiviezo Sir, Luis Contreras, Adolfo Cacho Revilla et al.
1 citations
Journal of Educational and Social Research
Advanced Data Processing Techniques
1.21
article

Emerging Technologies in Process Management and Educational Quality: A Bibliometric Analysis of Public Institutions

Alex Javier Sánchez Pantaleón, Victor Manuel Valdiviezo Sir, Luis Contreras, Adolfo Cacho Revilla, Julio Arévalo Reátegui, Rosas Carranza Guevara, Dotila Orosco Vilchez, Karin Araceli Valverde Reyes
article en
1 citations

Abstract

This study provides a bibliometric analysis of research on process management in public educational institutions, examining trends, collaborations, and dominant themes between 2000 and 2023 using data extracted from Scopus. Tools such as VOSviewer and Bibliometrix were employed to visualize research patterns and thematic clusters. Findings show growing research on process optimization, enhancing institutional efficiency, equitable access, and student learning environments in public education. Key challenges identified include the ethical integration of emerging technologies, such as artificial intelligence and blockchain, and the need for localized adaptations in developing countries. The analysis highlights gaps in interdisciplinary approaches and insufficient studies addressing cultural resistance to process changes. Moreover, it underscores the importance of advancing quality assurance practices and leveraging digital transformation to optimize workflows. Future research should prioritize context-specific strategies and evaluate their impact on student performance, organizational adaptability, and equity. This study contributes to the theoretical foundation for process management and provides insights for policymakers and administrators to enhance educational systems through evidence-based practices and technological innovation. Received: 20 March 2025 / Accepted: 19 June 2025 / Published: 05 July 2025

Journal of Educational and Social ResearchVol. 15(4)
Universidad César Vallejo (PE), National University Toribio Rodríguez de Mendoza (PE), Forum Solidaridad Perú (PE), Universidad Nacional Pedro Ruíz Gallo (PE)
Openalex Percentile: Top 19%
Advanced Data Processing Techniques
1.21
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