Date: 16 Nov 2012
Coordinating principles and examples through analogy and self-explanation
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Research on expertise suggests that a critical aspect of expert understanding is knowledge of the relations between domain principles and problem features. We investigated two instructional pathways hypothesized to facilitate students’ learning of these relations when studying worked examples. The first path is through self-explaining how worked examples instantiate domain principles and the second is through analogical comparison of worked examples. We compared both of these pathways to a third instructional path where students read worked examples and solved practice problems. Students in an introductory physics class were randomly assigned to one of three worked example conditions (reading, self-explanation, or analogy) when learning about rotational kinematics and then completed a set of problem solving and conceptual tests that measured near, intermediate, and far transfer. Students in the reading and self-explanation groups performed better than the analogy group on near transfer problems solved during the learning activities. However, this problem solving advantage was short lived as all three groups performed similarly on two intermediate transfer problems given at test. On the far transfer test, the self-explanation and analogy groups performed better than the reading group. These results are consistent with the idea that self-explanation and analogical comparison can facilitate conceptual learning without decrements to problem solving skills relative to a more traditional type of instruction in a classroom setting.
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- Coordinating principles and examples through analogy and self-explanation
European Journal of Psychology of Education
Volume 28, Issue 4 , pp 1237-1263
- Cover Date
- Print ISSN
- Online ISSN
- Springer Netherlands
- Additional Links
- Problem solving
- Knowledge transfer
- Worked examples
- Author Affiliations
- 1. Department of Psychology, Learning Research and Development Center, University of Pittsburgh, 3939 O’Hara Street, Pittsburgh, PA, 15260, USA
- 2. School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
- 3. Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA