We extract a process structure from event logs using process mining.We obtain the rules that guide adaptive learning from these logs by means of decision tree learning.We developed an algorithm to recompile the extracted process structure and rules in IMS Learning Design (IMS LD).The proposed framework facilitates the reuse of units of learning from legacy and proprietary e-learning systems. In this paper a novel approach to reuse units of learning (UoLs) - such as courses, seminars, workshops, and so on - is presented. Virtual learning environments (VLEs) do not usually provide the tools to export in a standardized format the designed UoLs, making thus more challenging their reuse in a different platform. Taking into account that many of these VLEs are legacy or proprietary systems, the implementation of a specific software is usually out of place. However, these systems have in common that they record the events of students and teachers during the learning process. The approach presented in this paper makes use of these logs (i) to extract the learning flow structure using process mining, and (ii) to obtain the underlying rules that control the adaptive learning of students by means of decision tree learning. Finally, (iii) the process structure and the adaptive rules are recompiled in IMS Learning Design (IMS LD) - the de facto educational modeling language standard. The three steps of our approach have been validated with UoLs from different domains.
['Juan Carlos Vidal', 'Borja Vázquez-Barreiros', 'Manuel Lama', 'Manuel Mucientes']
Recompiling learning processes from event logs