A quantitative analysis of educational data through the comparison between hierarchical and not-hierarchical clustering

Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science Education. Moreover, in the field of Science Education, a comparison between two different Clustering methods is not discussed in the literature. In this paper two different Cluster Analysis methods are described and the variables and parameters involved are discussed in order to clarify the information that they can supply. The clustering results obtained by using the two methods are compared and showed a good coherence between them. The results are interpreted and compared with the literature. More detail about the relationship between different student conceptions of modeling in physics was obtained.