摘要：This article describes a microgenetic methodology and presents an overview of the most frequently-used approaches in microgenetic data analysis. The microgenetic method is a methodology in which subjects are repeatedly exposed to learning situations in relatively short-time spans, which allows for the investigation of the process of change in knowledge, abilities and understanding (Granott and Parziale, 2002). The density and intensity of observations, as well as the richness of data (both qualitative and quantitative) gathered in the research, allow access to ongoing processes of learning and insight into how learners construct new knowledge and develop strategies on tasks. Because of the rich data produced on learners' experiences and reactions in the period of change, this method is applicable for examining individual differences in the process of learning and development. However, the complexity of microgenetic methodology is often not complemented with the application of adequate analytic procedures. While the nature and structure of microgenetic data do not adequately correspond with the requirements of standard analytic methods (e.g. ANOVA), the exclusive use of descriptive analysis and graphical representation of data neglects important data on change processes and makes testing of complex research hypotheses impossible. Statistical modeling of microgenetic data is a promising analytic tool, but is still not used widely. This article introduces examples of such modeling, as proposed by Cheshire et al. (2007).
关键词：microgenetic studies; measuring change processes; data analysis
