The objective of SoftLearn is the application of soft computing techniques, specifically evolutionary algorithms and fuzzy rules and, also the hybridization of these techniques with those frequently used on process mining, to extract complete, precise, adaptive and hierarchic workflows that model teaching units in e-learning. Moreover, we will propose algorithms for the analysis and evaluation of those workflows and, also, to recommend users for the educational activities.
The SoftLearn project is in line with the orchestrating learning challenge and is intended to contribute in this research topic with tools that let the teachers understand and evaluate the workflow of the activities done in a course. Thus, just using the event logs of the activities undertaken by students through an e-learning platform, SoftLearn will automatically determine the coordination of the activities of the course (flow), who and in which conditions have executed the activities (roles), and what teaching resources have been used in each activity.