Social network analysis in virtual educational environments: Implications for collaborative learning and academic community development

Abstract

This paper investigates the impact of Social Network Analysis (SNA) in optimizing virtual education, focusing on enhancing collaborative learning, strengthening virtual academic communities, and identifying challenges for educational innovation. Through SNA, patterns of interaction and collaboration are uncovered that inform the design of inclusive and dynamic educational practices. A theoretical review combining the benefits of bibliometric studies and documentary analysis was conducted. It highlights how ARS facilitates the identification of effective collaborative patterns and barriers to equal participation, promoting strategies for more meaningful collaboration. In addition, the role of ARS in consolidating academic communities by promoting cohesion, mutual support, and active engagement, crucial for student success and well-being, is discussed. Challenges such as forming subgroups and dependence on certain information nodes are analyzed, viewing them as opportunities to innovate in educational design and promote more equitable participation and knowledge construction. This analysis underscores the importance of ARS for developing more effective, equitable, and collaborative virtual learning environments aligned with the values of our digital society.