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