title: A computational model of the emergence of seriation in the young child
Creators: name: Kusel, Iain Henry
Publisher: name: The Open University
Year: 2013

description: The aim of the research is to understand how children’s competence in seriation grows between 5 and 7 years of age, using a computational model as an explanatory method. Seriation is the linear ordering of a set of objects bound by a relation of some sort, such as cubes differing in size by a specific amount being arranged from biggest to smallest in a straight line. Jean Piaget saw the ability to seriate as a prerequisite for the child’s logical thinking and significant for abstract thought more generally. However, the mechanism Piaget proposed to account for seriation’s very specific growth trajectory has theoretical problems, as do existing computational explanations attempting to capture the this growth. As a result, a satisfactory scientific explanation for how seriation competence develops remains to be specified. The research presented here consists of a novel characterisation and computational model of seriation, thus contributing to the scientific literature on seriation. The characterisation comprises a view of the child as a complex biological system that can create flexible, linear representations that inform action, as part of an on-going adaptation to their environment. In order to test this characterisation, it is formalised as a computational model, specifically as a simulated situated, embodied artificial agent which can interact with a simulated task environment. The novel model incorporates a Bayesian ranking mechanism to capture trial and error seriation and a common stimulus interval detection mechanism, also probabilistic in nature, to capture ‘insightful’ seriation. The novelty within the model derives from its coherence with known psychological facts about seriation, and its incorporation of a transitional mechanism, not present in any computational account of seriation to date. The agent is given the opportunity to learn about the object relationships inherent in simulated seriation tasks, a learning process which allows a series of linear forms to emerge in the form of probability distributions. These linear forms allow a transitional mechanism from weak classification ability to robust seriation expertise to be hypothesised in the form of a computational model, a dimension of explanation not adequately specified in Piaget’s account or contemporary computational accounts. The novel computational model presented validates the hypothesis by successfully replicating the errors generated by the 5 year old child within a computerised touch-screen version of the Piagetian arrangement of the seriation task. The computational model also allows a further hypothesis to be formed as to how spontaneous seriation may start to emerge in the older child. It is concluded that the research presented allows an appreciation of how the linear representations that are a necessary precondition for externalised, symbolic thought may start to emerge within the child, a conclusion that has implications for understanding the growth of intelligence in complex species and artificially engineered systems alike.