Prompting Knowledge Construction as an Instructional Support for Principle Learning in Simulations

• In Event: Self-Regulated Learning Across Diverse Contexts and Populations

Abstract

This study examined the incorporation of generative strategies for the guided discovery of physics principles in a simulation. Participants who either paraphrased or predicted and self-explained assignments exhibited improved performance on an achievement test as compared to a control group. Calibration accuracy was also improved for the two generative strategy groups. Test performance was strongly correlated with the thoroughness of generative content and with the quality of self-explanations. Participants who predicted and self-explained reported significantly higher levels of mental effort, decreased levels of confidence, and higher levels of frustration compared to those in other treatments. The improvement in learning by the two generative strategy groups is consistent with the generative model of learning describing the importance of knowledge construction.

Authors

• Jennifer R. Morrison, Johns Hopkins University

• Linda Bol, Old Dominion University

• Steven M. Ross, Johns Hopkins University

• Ginger S. Watson, Old Dominion University