Modeling of Numerical Learning Environments of New Generation: Theory of Complex Systems

With the emergence of social networks, MOOCs, informal learning via networks and connectivist approaches to learning, the Digital Learning Environment (ENA) analysis is becoming increasingly complex. The models previously used to report on instrumented activity for cognitive purposes now show their limits. The massive aspect of a MOOC for example becomes difficult "representable" in this type of models. Its "open" character is nonetheless difficult to model. Moreover, the evolution of these environments is chaotic and their effects appear unpredictable. But chaotic does not mean hazardous. A complex system is of an unpredictable nature and it is not possible to directly predict, by calculation, the outcome of the processes involved. But it is possible, from a systemic modeling, to develop plausible scenarios on the basis of the analysis of the available data (trace of the activity, heavy trends, emergence phenomena, etc.).  In this book, the authors hypothesize that the paradigm of systemic modeling of complexity appears more than ever as a conceptual framework adapted to the representation of ENA of last generation. They propose approaches and modeling languages ​​that use a whole series of symbolic representations that make it possible to graphically represent the processes involved in a complex system in order to facilitate their analysis.