Participatory simulation and learning process: Technology matters!

Becu Nicolas, Bommel Pierre, Le Page Christophe, Bousquet François. 2016. Participatory simulation and learning process: Technology matters!. In : Proceedings of the 8th International Congress on Environmental Modelling and Software Vol4.. Sauvage, S. (ed.), Sánchez-Pérez, J.M. (ed.), Rizzoli, A.E. (ed.). Toulouse : Université de Toulouse, Résumé, p. 840. ISBN 978-88-9035-745-9 International Congress on Environmental Modelling and Sofware (iEMSs 2016). 8, Toulouse, France, 10 July 2016/14 July 2016.

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Abstract : Participatory modelling (PM) is an approach under constant renewal due to its close link to available technologies and evolution of learning ha bits of citizens. Since the years 2000 many PM research projects leapt into the breach of hybrid simulation to produce new modes of interaction between PM session's participants. This paper reports on the ad vances of participatory simulation (PS) – the branch of PM that focuses on learning by interacting with a collective simulation – on using different projection t echnologies for participants' in terfaces. The use of two types of technologies is analyzed in this paper: ultra-short throw projector an d distribution of simulation interfaces on several terminals. After a brief history of how these techno logies have been used in PS applications since 2000, we conduct a comparative analysis of 5 differ ent PS applications that use at least one of these technologies (ClimFabiam, Kulayinjana, LittoSIM, NewDistrict, ReHab). These applications have common points. PS participants are located in the same room, simulation is about a socio-ecosystem and includes different roles played by the particip ants, PS session aims at building collectively a scenario on the socio-ecosystem dynamics. Our findin gs are based on ex-post questionnaires and PS facilitators' observations. Ultra -short throw projectors enable to display a simulation interface on a table around which participants stand. This config uration favors both collective exchanges, which produces social learning, and direct human-machin e interactions, which speeds up the loop of experiential learning. Distributed us er interfaces enable to reinforce the asymmetry of the environment in which participants evolve during the simulation. Such configuration favors strategic behaviors by the participants and learning on how to comm unicate and when to interact with others. (Texte intégral)

Classification Agris : U30 - Research methods
C20 - Extension

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