Using cluster analysis for data mining in educational research

Data mining is the process of sorting and classification of large Data. This paper introduces cluster analysis as a data mining technique and provide examples of its application in clustering of procrastinators. So introduce the cluster analysis and a variety of approaches, how to choose each step of its implementation in a representative sample presented the sample consists of 200 students of Tehran university (100 boys and 100 girls) that get high score in procrastination on the scale of Solomon and Rothblum (1984) and this sample responded to scale of self regulation by Green and Miller (2004), self-efficacy of Midelton and Midgley (1997), the scale of the failure beliefs Harrington (2005) and irrational beliefs Koopmans et al. (1994). The results indicated that different clusters of procrastinators which with identify groups of procrastinators and the characteristics of each of the groups can be more effective ways to reduce procrastination each group presented.