Intra-individual variability as a predictor of learning
Matija Svetina · DOAJ (DOAJ: Directory of Open Access Journals) · 2004
Learning is one of the most important aspects of children's behaviour. A new theory that emerged from evolutionary principles and information-processing models assumes learning to be run by two basic mechanisms: variability and selection. The theory is based on the underlying assumption that intra-individual variability of strategies that children use to solve a problem, is a core mechanism of learning change. This assumption was tested in the case of multiple classification (MC) task. 30 6-year-old children were tested for intelligence, short-term memory, and MC. Procedure followed classical pre-test/learning/post-test scheme. Amount of learning was measured through percentage of correct answers before and after learning sessions, whereas intra-individual variability was assessed through children's explanations of their answers on MC problems. The results yielded intra-individual variability to explain learning changes beyond inter-individual differences in intelligence or short-term memory. Although the results rose some new questions to be considered in further research, the data supported the hypothesis of intra-individual variability as predictor of learning change.