| Summary: | 碩士 === 中原大學 === 資訊工程研究所 === 93 === Cognitive psychologists have devoted their efforts to understand the cognitive structure of humans. Because it is not able to be seen, knowledge representation is used to infer the intension of cognitive structures. In order to comprehend students’ understanding and discovery their weakness of domain knowledge, researchers and educators apply network model to represent mental knowledge of students.
Concept mapping and Pathfinder are two of common assessment methodologies. A concept map generated after concept mapping includes concepts and concept relations. Concepts are used to stand for objects while concept relations are used to represent the relationship between two concepts. Although concept map is effective in representing cognitive structure in a structural way, it needs training before students are able to construct the concept map which replies what they think in their minds.
Pathfinder on the other hand is a method which needs less effort in collecting students’ understanding of domain knowledge in knowledge elicitation step. After collecting students’ understanding, a network structure is produced according to Pathfinder algorithm. A numerical value is adopted as evaluation of each network structure. But it is not display more information than a value.
In this thesis, a methodology which integrates the advantages of concept mapping and Pathfinder is proposed. It converts the similarity rating data generated by knowledge elicitation step in Pathfinder into hierarchical concept map. In addition, formal concept analysis is applied to discover the characteristics of different type of students. The real data of twelve concepts of genetics are used in the experiments of this thesis. According to the results, the students can be divided into thirty-four clusters with eight outliers. The errors on the concept pair related to gamete or DNA are happened on most of the students. The experiment results in both of above methods are consistent. In conclusion, the method proposed here provides not only a way to represent cognitive structure but also more detail information of students’ cognitive structures for teachers to provide adaptive instruction.
|
|---|
