The purpose of this study is to investigate the viability of a computer-based system for collecting and analyzing data from large-N microgenetic studies of scientific reasoning. Most studies of children’s scientific problem-solving strategies take place in classroom settings with established norms that homogenize student behavior. Small sample sizes and the limited range of settings limit the g...

We examined short-term changes in children’s numerical estimation, the representational changes that gave rise to improved estimates, and the hypothesis that experiences that highlight discrepancies between logarithmic and linear representations of numerical magnitude result in the greatest changes in estimation accuracy.

Both metacognitive and associative models have been proposed to account for children’s strategy discovery and use. Models based on only metacognitive or only associative mechanisms cannot entirely account for the observed mix of variability and constraint revealed by recent microgenetic studies of children’s strategy change. We propose a new approach where metacognitive and associative mechanis...

Several methods for ontology development have been proposed. However, the development of domain ontologies is still carried out in an ad-hoc manner. This paper explores the use of a microgenetic algorithm with a seeding scheme based on hierarchical clustering for ontology class hierarchy construction. The microgenetic algorithm (μGA) is composed of an inner loop and an outer loop. The inner loo...