Using network science to study children’s conceptual development
Concepts are mental representations that organize experience. They are the building blocks of ideas (e.g.,  the thought “birds are animals” requires the knowledge of both the concepts “birds” and the concept “animal”). They enable inductive reasoning and predictive inferences which guide behavior and explanation.  Some concepts are already present in infancy. These early concepts are richer than previously thought. However, much of the abstract and sophisticated concepts that make human cognition so special (e.g., scientific concepts) are not present at birth. Thus one of the most exciting challenges in psychology is to understand how abstract concepts develop. Much of the abstract concepts that form the basis of our ability to organize the world and make inferences (e.g. “animal”,  “artefact”,  “alive beings”)  have non-observable shared properties (e.g., a cat and a flower are perceptually quite different, but both belong to the concept alive beings). Thus, the refinement of abstract concepts requires access to cultural cues, mostly via language, which provide information beyond what can be obtained through the senses.,,  The goal of this project is to explore how  children’s conceptual development can benefit form the language they hear around them. To capture the complexity of the linguistic input as well as the children developing conceptual knowledge, I use  methods from the growing field of dynamic networks. I will carry out my research at the Institute of Complex Systems, Paris Île-de-France (ISC-PIF). I will also use the model to provide insights about how scientific concepts can be taught efficiently at school. To this end, I will collaborate with experts in science education at the secondment foundation La Main à La pâte (LAMAP), which is the leading French NGO in developing and  promoting best practices in science education.