A comparison of information processing and dynamical systems perspectives on problem solving

Abstract

Abstract This article compares the information processing and dynamical systems perspectives on problem solving. Key theoretical constructs of the information-processing perspective include “searching” a “problem space” by using “heuristics” that produce “incremental” changes such as reaching a “subgoal” to solve a puzzle. Key theoretical constructs of the dynamical-systems perspective include “positive attractors”, “negative attractors”, and “latent attractors” that can cause large “nonincremental” changes in the possibility of a solution through the “emergence” of new ideas and beliefs that can resolve a conflict. The proposed alignment maps dynamical-system constructs to information-processing constructs: state space to problem space, negative attractor to impasse, positive attractor to productive subgoal, latent attractor to implicit cognition, and nonincremental change to insight. The purpose of the mapping is to explore similarities and differences between these constructs. Research from cognitive and social psychology illustrates how using constructs from both perspectives is helpful. The concluding section on Future Directions recommends an agenda based on three objectives: (1) create ontologies to organise current knowledge, (2) conduct research to obtain new knowledge, and (3) provide education to inform students about this knowledge.