Modeling Creative Problem-Solving Tasks from a Computational and Neuroeducational Approach

Overview & Synopsis

Creativity is a complex process that has been studied in different fields with a high level of diversity in relation to the types of tasks, contexts, and assessment methodologies. In this study, we focus on ill-defined individual creative problem-solving (CPS) tasks with the objective of creating a computational model based on the regulatory process of CPS, inspired by the neuroscientific knowledge of the related cognitive processes, and artificial cognitive architectures. The model operationalization considers the emergent character of the path engaged by the learner when solving an ill-defined task and the geometrization of this path within a problem space describing the task. Stimulus-based and goal-directed creative behavior are then distinguished on the computational processes underlying creativity. Through a computational and neuroeducational approach, the study introduces a model of creative problem-solving tasks and provides an operational geometric definition of problem-solving tasks, emphasizing the challenges associated with ill-defined problems. We finish discussing creativity as a semantic grounding process with a focus on data representation, as well as symbolic data manipulation using inference and metric space algorithms.