inductive reasoning only applies to some examples of A, for example, 'It often snows in winter. It is winter now. There is a high probability that we'll have snow.' Analogical reasoning relies on given statements and similar consequences from past experiences, e.g., 'A shark in the ocean...
Despite the important role of specific examples for learning and problem solving, little support is given in computer-based learning and teaching environments to help students organize information about examples and problem solving episodes in a way that may enhance generalization and transfer. The main...
Then, problem and model similarities are discussed at conceptual, structural, and functional levels. This is followed by a description of the process for analogical model formulation, which includes feature mapping, transformation, and evaluation. Finally, examples are illustrated and case-based learning...
The first part - cultivate memetic heterogeneity - should be straightforward, but it is worth examining some examples. If you possess only the same baseline memetic population as your peers, then the chances of your mind evolving truly novel creative combinations are substantially diminished. You hav...
However, there is also evidence that although highly-similar examples support problem-solving success, they may interfere with learning, possibly because they allow the problem solution to be genera...Novick, L. (1995). Some determinants of successful analogical transfer in the solution of algebra ...
The recent advent of large language models has reinvigorated debate over whether human cognitive capacities might emerge in such generic models given sufficient training data. Of particular interest is the ability of these models to reason about novel pr
Participants took part in an experiment consisting of four tasks: rating source examples, selecting a source domain, explaining their selection, and designing a bus stop. The results indicate significant differences among participants with respect to their soundness ratings. The results also show ...
Research in analogical problem solving concentrates on the process of similarity recognition, mapping of past cases to current situation, and modification of past cases to suit a given task. An important aspect of this research is the development of representations that accurately capture prior ...
To determine the boundary between transfer learning models and analogical inference models, we take examples in the two most popular domains—computer vision and natural language processing—to compare algorithms, methods, and applications. The literature review presented here is brief, providing a light...
The group receiving two training examples involving training in problem-solving strategies and mapping were more likely than controls to recognize similarity of solutions and to develop similar problem-solving plans.^ Results were interpreted as indicating that training in mapping correspondences is ...