Students learning pathways in higher blended education: An analysis of complex networks perspective

The purpose of this study is to introduce a model of the students' learning pathways, as a network that captures the time dimension and sequences of the learning events. Also, the online learning rate that is computed on these learning pathways networks is defined. The results show that the online learning rate of students who passed is greater than students who failed. The results of the person-centred analysis show that only test anxiety influences the number of nodes and arcs of the individual learning pathway network, which was modelled as individual networks. Also, engagement and disengagement affect these networks' features. This supports the conjecture that motivated students do not necessarily review more learning materials. As a consequence, test anxiety, engagement, and disengagement mould the individual learning pathway networks.