A Social Network Analysis Approach to Modeling Learning Interactions in a Social Learning Management System
Date of Award
Doctor of Philosophy in Computer Science
Information Systems & Computer Science
Maria Regina Justina E. Estuar., PhD
Interaction is a result of interplay between two or more entities where in- terplay could be behavior or some other variable being measured. The primary contribution of this research is on the discovery of the learning interaction model and the realization of interaction networks of administrators, faculty members, students, and parents. This study suggests administrators and parents have big contributory roles to extend the e-Learning Interaction Matrix with the addition of administrator-faculty member, faculty member-faculty member, and faculty member to parents channels with their respective formal and informal interac- tions mode. Results showed that network density, which measures 0.029, is less when the principal asserts instructional leadership because of imposed hierarchical structure in the educational environment. Low-density scores indicate more learning interactions because the principal’s involvement cascades to teachers’ participation and then to the involvement of students and parents. Moreover, state switching from initiator to receiver contributes to feedbacking mechanisms useful to guide in student’s learning. The structural stability of the derived so- cial network as supported by low standard error scores of 0.0015 and 0.0074 for the respective betweenness and influence centrality measures.
(2020). A Social Network Analysis Approach to Modeling Learning Interactions in a Social Learning Management System. Ateneo de Manila University.