Optimizing Case-Based Instruction in Teacher Education: Generating Versus Modeling Solutions for Improvement Over Time

• In Event: AERA Poster Session 7
  In Poster Session: PBL Activities and Impact (San Diego)

Abstract

The study investigated two instructional approaches, modeling and generative tasks, in conjunction with case-based instruction to determine which instructional approach maximizes the effect of learning from classroom cases. Preservice teachers (N = 40) participated in the study. We conducted two 2 X 3 mixed factorial ANOVA with instructional approaches as a between-groups factor, time as the within-group factor, and learning theories or text interpretation score as our dependent variables. The results of the main effects suggest that both modeling and generative tasks are comparably similar in their effects. However, across time, we found that the generative condition significantly and progressively improved participants’ learning theories and text interpretation scores. Study implications and directions for future studies were discussed.

Authors

• Samuel Aina, Washington State University

• Kira Joy Carbonneau, Washington State University - Pullman

• Sara A. Abercrombie, Northern Arizona University

• Carolyn J. Hushman, University of New Mexico