Petri net-based engine for adaptive learning
Expert Systems with Applications: An International Journal
A Petri net model for changing units of learning in runtime
Knowledge-Based Systems
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Nowadays a greater number of domains require an improvement in the flexibility of its e-learning systems to so facilitate the adaptation of their course to their user needs. Some adaptive learning systems have been developed in recent years to cover part of these needs, and provide the ability to redirect the student learning flow based on the knowledge base (mainly rules) defined by the teacher. However, these systems, most of them based on the IMS Learning Design specification, have a major restriction: once the course has been published, it can not be changed, regardless that the circumstances in which the course is taught have changed. To remedy this lack, in this paper we present a solution to adapt the structure of units of learning at runtime. This solution extends a proposal for modelling IMS Learning Design through workflows with new capabilities that facilitate the replacement of plays, events and activities on the fly.