In recent years, research efforts on complex systems have contributed to improve our ability in investigating, at different levels of complexity, the emergent behaviour showed by system in the course of its evolution. The study of emergence, an intrinsic property of a large number of complex systems, can be tackled by making use of Cellular Automata (CA): these enable researchers to identify the emergent dynamics of a complex system, whose behaviour is determined by local rules that define the way in which the elementary parts interact with each other. This work presents the results of an experimentation aimed to investigate the efficacy of a methodology which uses the simulation and CA in the learning of emergence. As results, the 93% of the students that which took parts to the experimentation is able to recognize characteristics of complex system.
The use of Cellular Automata in the learning of emergence
PANTANO, Pietro Salvatore;SERVIDIO, Rocco Carmine
2006
Abstract
In recent years, research efforts on complex systems have contributed to improve our ability in investigating, at different levels of complexity, the emergent behaviour showed by system in the course of its evolution. The study of emergence, an intrinsic property of a large number of complex systems, can be tackled by making use of Cellular Automata (CA): these enable researchers to identify the emergent dynamics of a complex system, whose behaviour is determined by local rules that define the way in which the elementary parts interact with each other. This work presents the results of an experimentation aimed to investigate the efficacy of a methodology which uses the simulation and CA in the learning of emergence. As results, the 93% of the students that which took parts to the experimentation is able to recognize characteristics of complex system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
