Kovanović, V., Joksimović, S., Katerinopoulos, P., Michail, C., Siemens, G., & Gašević, D.
Proceedings of the Seventh International Conference on Learning Analytics and Knowledge (LAK'17), March 13-17, 2017, Vancouver, Canada, Pages 1–5, ACM, New York, NY, USA.
Publication year: 2017


In 2011, the phenomenon of MOOCs had swept the world of education and put online education in the focus of the public discourse around the world. Although researchers were excited with the vast amounts of MOOC data being collected, the benefits of this data did not stand to the expectations due to several challenges. The analyses of MOOC data are very time-consuming and labor-intensive, and require a highly advanced set of technical skills, often not available to the education researchers. Because of this MOOC data analyses are rarely done before the courses end, limiting the potential of data to impact the student learning outcomes and experience.

In this paper we introduce MOOCito (MOOC intervention tool), a user-friendly software platform for the analysis of MOOC data, that focuses on conducting data-informed instructional interventions and course experimentations. We cover important design principles behind MOOCito and provide an overview of the trends in MOOC research leading to its development. Although a work-in-progress, in this paper, we outline the prototype of MOOCito and the results of a user evaluation study that focused on system’s perceived usability and ease-of-use. The results of the study are discussed, as well as their practical implications.


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