Research on Epistemic Networks of Teacher and Learners in a cMOOC Course

Abstract

As a type of MOOC based on Connectivism, cMOOCs raise a special model of teaching, tutoring, and learning. Hence, compared with the xMOOCs, cMOOCs would need particular approaches to better evaluate the teaching and learning of the connectivist teacher and learners. This study aims to explore a new way to evaluate a cMOOC course by analyzing and comparing the epistemic networks of the teacher and learners, including comparing their epistemic network structure and their development trajectory. Based on a cMOOC course offered by Beijing Normal University in the spring of 2019, 1068 pieces of interactive text data of learners and 40 pieces of interactive text data of the teacher were collected. Methods of Epistemic Network Analysis (ENA), Cluster Analysis, and Content Analysis were used. The study found that there were some differences in the cognitive structure between the teacher and learners in the whole learning process, but no statistically significant difference. Learners' cognition was hysteretic and autonomous. Teachers should also play tutoring and facilitating roles on learners especially in the middle phase of the course. cMOOC was found to be feasible and effective to use ENA to evaluate connectivist learning.