Learning Analytics to Explore Dropout in Online Entrepreneurship Education

Abstract

The technological disruption of E-Learning offers Entrepreneurship Education (EE) an unprecedented opportunity to leverage the affordances of web 2.0 and to widen the scope of entrepreneurship educational programs. However, in practice, high dropout rates in online courses (near 90%) pose major challenges to EE researchers. In this paper, we use learning analytics to explore the case of dropout during a female-oriented online entrepreneurship educational program. We observed that the evolution of dropouts and learning behavior of the participants in this program is not linear in time. Persistence decays in a two-step process: The first dropout phase reaches approximately 30% before the middle of the program and then stabilizes around that number. A second dropout phase is triggered in the last quarter of the program and it continues declining until the end of the program. This dropout pattern corresponds to the interaction indicators at aggregated level: Before the middle of the program the level of interaction drops together with the number of active users. However, the reduction in the interaction frequency is disproportionate in relation to the fall of number of the active users. After dividing by the percentage of active users the number of interactions still drops before the middle of the program. Using social network analysis (SNA) we show that initial dropouts have a considerable effect on the connectivity of the communication network, this is consistent with the observed decrease in social interactions. We also found significant correlations between entrepreneurial competencies and indicators of learning behavior and persistence, at the individual level. In line with the relevant literature, the most significant feature associated with persistent behavior was found to be the risk-taking orientation. Our findings suppose the first step towards an empirical model of persistence in Entrepreneurship Education online programs providing valuable insights for future research and for developing retention methods in online courses.