FTS-SOCI: An agent-based framework for simulating teaching strategies with evolutions of sociograms

Teaching strategies have been proven to influence the academic performance of students, as well as group sociometrics have been proven to be directly related to group performance. Although in the literature there are examples of teaching strategies and the resulting sociograms, there is not any detailed technique, tool or simulator that predicts the influence of a new teaching strategy on group sociometrics. The current work is aimed at covering this gap in the literature, by providing a framework for programming teaching strategies to simulate their influence on group sociometrics. In particular, this framework is called FTS-SOCI (Framework for simulating Teaching Strategies with evolutions of SOCIograms). This framework includes an agent-based simulator that simulates the evolution of sociograms taking five models of the literature into account. In this framework, students and teacher are modelled as agents, and the teacher agent can have any teaching strategy defined by the user. In order to test the current approach, this work simulates existing teaching strategies in (1) nursing education and (2) sport lessons. The resulting sociograms of FTS-SOCI for these strategies have been compared with the corresponding real sociograms reported in the literature. This works shows that the group sociometric values provided by FTS-SOCI are quite similar to the real cases. For instance, the mean squared error of the group cohesion sociometric (i.e. IAg metric) is only 0.00024 and 0.00068 respectively for the teaching strategies of both fields.