Potential Abstract:
Abstract: This study explores the role of categorical representation in educational technologies through the lens of social network analysis. Drawing on deconstructionist theory, the research examines how different categories are constructed and reinforced within digital learning environments. The study utilizes social network analysis techniques to uncover patterns of categorical representation and to investigate how these representations influence student learning outcomes and educational experiences. By analyzing the connectivity and relationships between different categories within educational technologies, the research aims to shed light on the underlying structures and power dynamics that shape students’ interactions with digital tools. The findings from this study have important implications for educators, curriculum designers, and policymakers seeking to create more inclusive and equitable learning environments that challenge traditional categorical norms and promote diversity and representation.
Potential References:
- Using three social network analysis approaches to understand computer-supported collaborative learning
- Social network analysis of a gamified e-learning course: Small-world phenomenon and network metrics as predictors of academic performance
- Social network analysis and education: Theory, methods & applications
- Analyzing social construction of knowledge online by employing interaction analysis, learning analytics, and social network analysis
- Why (and how) do teachers engage in social networks? An exploratory study of professional use of F acebook and its implications for lifelong learning
