AN EPIDEMIOLOGICAL MODEL OF KNOWLEDGE DIFFUSION IN VIRTUAL LEARNING NETWORKS: AN APPLICATION TO LEARNING STATISTICS IN MEDICINE

Abstract

ABSTRACT Some authors claim that the genetic metaphor can be used for describing intergenerational cultural transmission. In analogy with genes, memes can be conceived as cultural units that can be transmitted from one generation to another. A variant of this metaphor conceives cultural transmission as a sort of contagion within a social network of individuals.In this respect, distance learning networks provide a valuable tool for analyzing the spreading of information in virtual communities. In this article, the time evolution of the student's applications to an interactive distance learning platform was analysed. The platform DVLN was developed at the University of Naples and allows tracking all the students' interactions with the system. The diffusion of the innovation among the students of the Course of Medical Statistics was modelled by means of a system of differential Equations where the diffusion of the innovation adoption depends on the contact rate between two types of students: the innovators and the potential imitators. Furthermore, by means of k-means cluster analysis of the interactions of the students with the system, three learning styles, i.e. lurkers, socializers, utilitarists, were found. An attempt to explain the macroscopic spreading of innovation adoption on the basis of individual microscopic decisions to accept or refute the innovation was carried out. The authors claim that the representation of the learning process as a temporal dynamics of a network of cognitive agents opens new perspectives to the scientific analysis of the learning process in human groups.