Students use the community college in a wide variety of ways to achieve an equally wide variety of ends. Some of these ends align closely with institutional goals, priorities, and performance indicators, and others do not. Consequently a typology of community college students based on their use of the institution has the potential to be of great…

One useful and increasingly popular method of classifying students is known commonly as cluster analysis. The variety of techniques that comprise the cluster analytic family are intended to sort observations (for example, students) within a data set into subsets (clusters) that share similar characteristics and differ in meaningful ways from other…

The development of a typology of community college students is a topic of long-standing and growing interest among educational researchers, policy-makers, administrators, and other stakeholders, but prior work on this topic has been limited in a number of important ways. In this paper, I develop a behavioral typology based on students'…

This explorative data mining project used distance based clustering algorithm to study 3 indicators, called OIndex, of student behavioral data and stabilized at a 6-cluster scenario following an exhaustive explorative study of 4, 5, and 6 cluster scenarios produced by K-Means and TwoStep algorithms. Using principles in data mining, the study…