Semantic Network Analysis of Web Based Learning in Digital Health and Medical Education: A Scientometric Study with Mixed Methods and Systematic Mapping.
Abstract
Objectives: To examine the semantic and structural organization of web based learning at the intersection of digital health and medical education and to identify core, thematic, and bridging concepts within the knowledge network. Methods: A scientometric mixed methods design was applied to 1,123 peer reviewed articles indexed in the Web of Science Core Collection from 2016 to 2025. Bibliographic records were normalized and analyzed using co occurrence and thematic network analysis in VOSviewer and centrality analysis in UCINET and NetDraw. Temporal mapping and systematic semantic interpretation were used to examine convergence, thematic organization, and strategic conceptual positions. Results: The knowledge structure showed a strong educational backbone centered on e learning, education, and medical education, with learning analytics, digital literacy, artificial intelligence, machine learning, telemedicine, and digital health increasingly connected within the same conceptual environment. Thematic analysis indicated three interconnected domains comprising educational and pedagogical, technological and informatics, and clinical and digital health concepts. Closeness and betweenness centrality further distinguished structurally accessible core concepts from potential interdisciplinary bridging concepts. Conclusion: Web based learning has developed from a primarily instructional mechanism into an interconnected digital learning ecosystem linking medical education, intelligent technologies, informatics, and healthcare applications. The findings highlight the importance of understanding both conceptual prominence and structural position when examining the evolution of digital health education.
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