Soft Computing for Learner's Assessment in SoftLearn

One of the most challenging issues in learning analytics is the development of techniques and tools that facilitate the evaluation of the learning activities carried out by learners, i.e., the learning path which was planned for achieving the pedagogical objectives of a course. In this context, the issue is to determine whether learners have undertaken additional learning activities, such as looking for new learning contents or interacting with other learners, in order to better understand the object of study. SofLearn is a process mining-based platform that identifies and highlights all these activities –all the content generated by the learners during the course–, enabling teachers to improve the learning paths as well as the evaluation process for each of the learners. Moreover, SoftLearn has an intuitive graphical interface that has been specifically developed to visualize and evaluate both the learning paths and the data generated during the learning activities, to automatically build natural language reports describing the most relevant facts about them, and to visualize different statistics regarding the learning process of the students.

keywords: Natural language generation, Process Mining, Learning Analytics