Relationship between evaluation methods and learning outcome in Massive Open Online Courses (MOOC)

The present paper analyzes some examples of how the evaluation tools have been adapted to the environment of MOOC and lead to some interesting examples with respect to the redefinition of the learning experience and the learning outcomes. The starting point is twofold: 1) the analysis of the evaluation models implemented in MOOCs, grounded on peer review and data analysis supported by specific software and 2) a review of the effectiveness of the different methodologies with respect to the implementation of the evaluation models in the specific context of a MOOC. The results demonstrate two main approaches. On the one hand, “peer evaluation”-based approaches, supported by technological tools, have emerged with the aim to encourage participation and limit in part the negative effects of the automatic procedures applied to the learning context. On the other hand, approaches focused on data analysis, especially those exploiting methodologies of sentiment analysis, do not seem to be a reliable indicator of success of the students in MOOC, although they offer more information about the learning experience in itself.