"Analogy-based reasoning: This term is sometimes used, as a synonym to case-based reasoning, to describe the typical case-based approach... However, it is also often used to characterize methods that solve new problems based on past cases from a different domain, while typical case-based methods focus on indexing and matching strategies for single-domain cases."
– Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Agnar Aamodt & Enric Plaza. AI Communications. IOS Press, Vol. 7: 1, pp. 39-59.
In this summary report I give an account of research conducted over the last two years, showing the suitability and the advantages of applying computational analogy-engines in the analysis and design of analogy-based methods and tools in teaching and education. This overview constitutes the conclusion of the first phase of a multi-stage effort trying to introduce computational models of analogy also to education and the learning sciences, thus opening up these fields to computational tools and methods not only on an instrumental level, but also in analytical, conceptual, and design-oriented studies. I locate the "analogy-engines in the classroom" research program within the bigger schemes of studying human creativity and computational creativity, provide an introduction to the theoretical underpinnings of the endeavor, and revisit three worked out case studies serving as proofs of the feasibility of the overall approach.
We believe that current research in creativity (especially in artificial intelligence and to a great extent psychology) focuses too much on the product and on exceptional (big-C) creativity. In this paper we want to argue that creative thinking and creative behavior result from the continuation of typical human cognitive development and that by looking into the early stages of this development, we can learn more about creativity. Furthermore, we wish to see analogy as a core mechanism in human cognitive development rather than a special skill among many. Some developmental psychology results that support this claim are reviewed. Analogy and metaphor are also seen as central for the creative process. Whereas mainstream research in artificial creativity and computational models of reasoning by analogy stresses the importance of matching the structure between the source and the target domains, we suggest that perceptual similarities play a much more important role, at least when it comes to creative problem solving. We provide some empirical data to support these claims and discuss their consequences.