TEACHING MANAGEMENT AND FINANCE THROUGH SIMULATION Choosing the Proper Paradigm Marco Remondino, Anna Maria Bruno and Nicola Miglietta e-business L@B, University of Turin, Torino, Italy Keywords: Simulation, Discrete Events, Agent Based, System Dynamics, Knowledge Transfer. Abstract: Compared to analytical modelling, simulation has sometimes a greater expressive and computational power, especially for a behavioural study of an activity, system, organisation and other topics from the Social Sciences, which an analytic study cannot adequately achieve. In this paper simulation is discussed as a support for teaching and knowledge transfer: a model can be built and used to dynamically show and explain a particular phenomenon through direct experiments, though contributing to a “maieutical” way of learning by the students (learning by doing). Also team work is triggered by using simulation models as a educational tool. In particular, three simulation paradigms are described, along with their potential applications and points of strength and weakness. Management and Finance are the focus of the work, but the same considerations may be extended to other social disciplines and sciences. Note: Although the article is the result of a joint research project, the paragraphs are divided among the authors as follows: paragraphs 1 and 5 are jointly written and equally divided among all the authors; paragraph 2 is by Nicola Miglietta; paragraph 3 is by Anna Maria Bruno and Marco Remondino; paragraph 4 is by Marco Remondino. 1 INTRODUCTION This work presents an analysis of modelling and simulation applied to the Social Sciences, as a supporting methodology for teaching purposes. A model is a scaled down representation of a target system in the real world; it wouldn't be useful to create a one-to-one representation of the reality, so it's very important to identify which are the main features of the studied system and bring them in the model (this process is called abstraction). Modelling is applied when prototyping or experimenting with the real system is expensive or impossible, and thus it seems a perfect tool for researching in the social field. In Ostrom (1988), simulation is described as a third way to represent social models, being a powerful alternative to other two symbol systems: the verbal argumentation and the mathematical one. The former, which uses natural language, is a non computable way of modelling though a highly descriptive one; in the latter, while everything can be done with equations, the complexity of differential systems rises exponentially as the complexity of behaviour grows, so that describing complex individual behaviour with equations often becomes an intractable task. Simulation has some advantages over the other two: it can easily be run on a computer, through a program or a particular tool; besides it has a highly descriptive power, since it is usually built using a high level computer language, and, with few efforts, can even represent non-linear relationships, which are tough problems for the mathematical approach. According to Gilbert and Terna (1999), the logic of developing models using computer simulation is not very different from the logic used for the more familiar statistical models. In either case, there is some phenomenon that the researchers want to understand better, that is the target, and so a model is built, through a theoretically motivated process of abstraction. The model can be a set of mathematical equations, a statistical equation, such as a regression equation, or a computer program. The behaviour of the model is then observed, and compared with observations of the real world; this is used as evidence in favour of the validity of the model or its rejection. Computer programs can be used to model either quantitative theories or qualitative ones; simulation has been successfully applied to many fields, and in Social 464 Remondino M., Bruno A. and Miglietta N. (2010). TEACHING MANAGEMENT AND FINANCE THROUGH SIMULATION - Choosing the Proper Paradigm. In Proceedings of the 2nd International Conference on Computer Supported Education, pages 464-468 Copyright c  SciTePress