Finding Learning Paths Using Petri Nets Modeling Applicable to E-Learning Platforms

This work proposes an approach for course modeling using Petri nets. The proposed modeling method can be applied to support development of e-learning platforms (namely learning management systems - LMS) allowing student guidance when considering reaching a specific goal. This goal could be as simple as getting a set of sequential courses (or a degree), or as complex as combining different modules from different courses having different types of dependencies in order to obtain a qualification. Each course is characterized by a set of modules and their relations. Each module is represented by a Petri net model and the module structure representing the course’s dependency relations is translated into another Petri net model. Additional courses or modules can be included into the offer as their associated Petri net models can be easily composed using net addition operation. The contribution of this paper foresees the usage of common Petri nets analysis techniques (such as state space analysis, invariants, trace finding) to constraint student’s options in order to optimize his/her path to reach a degree or a qualification. A simple example considering a scenario with a few courses and modules is used to illustrate the approach.