Mental Models and Transfer of Learning in Computer Programming

Abstract

Learning and transfer of procedural skills was measured as a function of conceptual understanding (subjects’ mental models) induced by conceptual models in the form of computer graphics and animation during computer-based instruction. Three groups of nonprogrammers learned and practiced either code evaluation, code evaluation with the aid of conceptual models, or code generation. Practicing code evaluation with conceptual models was found to facilitate conceptual understanding, learning of code evaluation, and transfer to code generation. A positive relationship was found between the quality of subjects’ mental models and transfer ability, regardless of the experimental condition. The findings suggest that both number of shared productions and level of declarative knowledge are developed during practice and that transfer is a function of both. In practical terms, conceptual methods of instruction fostering appropriate mental models are suggested for cognitive skill learning. The instructional materials demonstrate methods by which computer graphics and animation may stimulate the formation of appropriate mental models.