The Microgenetic Research Of Representational Level's Change In Physical Problem

Content:The research mainly focuses on in the context of practice and representational redescription the change process of cognitive and problem solving strategy used by children. It is well based on representational redescription theory and Karmiloff-Smith's other related cognitive development theories which have gain much recognitive in cognitive development domain. In the general discussion part, the ink was first put to explain the micro-construction and organization of schema. At the methodological level, the characteristics and implications of the microgenetic method were analyzed and evaluated. The research is developed by the aspects as followed. The results showed that:Firstly, we have analyzed Karmiloff-Smith's representational redescription theory and other related cognitive development theories and summarized these literatures. Secondly, a microgenetic method was used to obtain the detailed data about the qualitative and quantitative aspects of change, such as the path, rate, breadth, source and variability of change.In each of the testing sessions the data of solution time, accuracy and verbal report about strategies for solving"collision"physics problems were collected from 34 children.1,The path of the change of representation were not completely consistent with Karmiloff-Smith's hypothesis that the paths of development.2,The qualitative of cognitive change in knowledge construction is various.3,Karmiloff-Smith's representational redescription theory was modified, and I made a specific one.4,The evolution process of problem solving was a constructive one, but it might be affected by knowledge presented by formal or informal instruction. What should be noted was that the patterns of exercise had effect on the acquisition of right strategy. The blocked problems led to higher levels of activation and discovery of the right strategy.5,The mirogenetic method can be used to explain cognitive development. And the method also be used in wider domain. We should make it relate to the character of special domain knowledge to explain knowledge construction. Furthermore, we can use the method within experiment,talking,data collection and so on.Finally, in this study, a relational-representational complexity model was propsed, within which the relational complexities were categorized into horizontal and hierarchical complexity and were deemed as the key determinant for the problem difficulty. So the representational complexity of a problem can be indexed by representational spread and depth. Furthermore, it provided a new direction and dimension for problem-solving difficulty analysis.