Community College Student Engagement Patterns: A Typology Revealed Through Exploratory Cluster Analysis

Authors

Victor B. Sáenz, University of Texas at AustinFollow
Deryl K. Hatch, University of Nebraska–LincolnFollow
Beth E. Bukoski, University of Texas at AustinFollow
Suyun Kim, University of Texas at Austin
Kye-hyoung Lee, University of Texas at Austin
Patrick Valdez, University of Texas at Austin

Document Type

Article

Date of this Version

2011

Citation

Published in Community College Review 39:3 (2011), pp 235–267. doi 10.1177/0091552111416643

Comments

Copyright © 2011 Victor B. Sáenz, Deryl Hatch, Beth E. Bukoski, Suyun Kim, Kye-hyoung Lee, and Patrick Valdez. Published by SAGE Publications. Used by permission.

Abstract

This study employs survey data from the Center for Community College Student Engagement to examine the similarities and differences that exist across student-level domains in terms of student engagement in community colleges. In total, the sample used in the analysis pools data from 663 community colleges and includes more than 320,000 students. Using data-mining techniques to discover a parsimonious number of natural clusters and, in turn, a k-means cluster analysis as a means of revealing a naturally occurring typology of engagement patterns, our findings reveal that support service utilization is the most distinguishing feature of the similarities and dissimilarities across student groups, suggesting areas for further theory development and testing.