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This paper presents an explorative-based computational methodology to aid the analogical retrieval process in design-by-analogy practice. The computational methodology, driven by Nonnegative Matrix Factorization (NMF), iteratively builds a hierarchical repositories of design solutions within which clusters of design analogies can be explored by designers. In the work, the methodology has been applied on a large repository of mechanical design related patents, processed to contain only component-, behavior-, or material-based content, to demonstrate that unique and valuable attribute-based analogical inspiration can be discovered from different representations of patent data. For explorative purposes, the hierarchical repositories have been visualized with a three-dimensional hierarchical structure and two-dimensional bar graph structure, which can be used interchangeably for retrieving analogies. This paper demonstrates that the explorative-based computational methodology provides designers an enhanced control over design repositories, empowering them to retrieve analogical inspiration for design-by-analogy practice.
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Teaching by Analogy: From Theory to Practice
ABSTRACT Analogy is a powerful tool for fostering conceptual understanding and transfer in STEM and other fields. Well‐constructed analogical comparisons focus attention on the causal‐relational structure of STEM concepts, and provide a powerful capability to draw inferences based on a well‐understood source domain that can be applied to a novel target domain. However, analogy must be applied with consideration to students' prior knowledge and cognitive resources. We briefly review theoretical and empirical support for incorporating analogy into education, and recommend five general principles to guide its application so as to maximize the potential benefits. For analogies to be effective, instructors should use well‐understood source analogs and explain correspondences fully; use visuospatial and verbal supports to emphasize shared structure among analogs; discuss the alignment between semantic and formal representations; reduce extraneous cognitive load imposed by analogical comparison; and encourage generation of inferences when students have some proficiency with the material. These principles can be applied flexibly to topics in a wide variety of domains.
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- Award ID(s):
- 1827374
- PAR ID:
- 10450210
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Mind, Brain, and Education
- Volume:
- 15
- Issue:
- 3
- ISSN:
- 1751-2271
- Format(s):
- Medium: X Size: p. 250-263
- Size(s):
- p. 250-263
- Sponsoring Org:
- National Science Foundation
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