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Comparing Explicit and Implicit Teaching of Multiple Representation Use in Physics Problem Solving.
USF St. Petersburg campus Faculty Publications
  • Patrick B. Kohl
  • David Rosengrant, University of South Florida St. Petersburg
  • Noah D. Finkelstein
SelectedWorks Author Profiles:

David Rosengrant

Document Type
Conference Proceeding
Publication Date
2006
Abstract

There exist both explicit and implicit approaches to teaching students how to solve physics problems involving multiple representations. In the former, students are taught explicit problem-solving approaches, such as lists of steps, and these approaches are emphasized throughout the course. In the latter, good problem-solving strategies are modeled for students by the instructor and homework and exams present problems that require multiple representation use, but students are rarely told explicitly to take a given approach. We report on comparative study of these two approaches; students at Rutgers University receive explicit instruction, while students from the University of Colorado receive implicit instruction. Students in each course solve five common electrostatics problems of varying difficulty. We compare student performances and their use of pictures and free-body diagrams. We also compare the instructional environments, looking at teaching approaches and the frequency of multiple-representation use in lectures and exams. We find that students learning via implicit instruction do slightly better and use multiple representations more often on the shorter problems, but that students learning via explicit instruction are more likely to generate correct free-body diagrams on the hardest problem.

Comments

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Language
en_US
Publisher
American Institute of Physics
Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 4.0
Citation Information
Kohl, P., Rosengrant, D., & Finkelstein, N. (2006). Comparing Explicit and Implicit Teaching of Multiple Representation Use in Physics Problem Solving. 2006 Physics Education Research Conference, Syracuse, NY. AIP Conference Proceedings. doi: 10.1063/1.2508713