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Behavior-Based Student Typology: A View from Student Transition from High School to College

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  • Lanlan Mu

    (College of William & Mary)

  • James Cole

    (Indiana University-Bloomington)

Abstract

Several recent studies have successfully identified college student typologies based on individuals’ behaviors. One limitation of past studies has been their reliance on one-time cross-sectional assessments. As a result, we are left to ponder the stability of students’ behavioral types as their academic years move forward. This study used longitudinal student data from high school to college, to investigate the stability of a behavior-based student typology. Guided by findings in behavioral consistency from personality psychology, this study explored the associations of higher education institution’s structure, and supportive elements of the environment and the transition of students’ behavior-based types. The results showed that, in high school and higher education settings, students’ behaviors in a variety of activities classified students into four types. In the higher education setting, about half of the students were of the same behavioral type while the remaining students engaged in changes as compared with their behavior-based types in high school. Students’ background characteristics and institutional environment demonstrated an association related to these shifts.

Suggested Citation

  • Lanlan Mu & James Cole, 2019. "Behavior-Based Student Typology: A View from Student Transition from High School to College," Research in Higher Education, Springer;Association for Institutional Research, vol. 60(8), pages 1171-1194, December.
    • Handle: RePEc:spr:reihed:v:60:y:2019:i:8:d:10.1007_s11162-019-09547-x
    DOI: 10.1007/s11162-019-09547-x
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    References listed on IDEAS

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    1. Thomas G. Greene & C. Nathan Marti & Kay McClenney, 2008. "The Effort—Outcome Gap: Differences for African American and Hispanic Community College Students in Student Engagement and Academic Achievement," The Journal of Higher Education, Taylor & Francis Journals, vol. 79(5), pages 513-539, September.
    2. Nema Dean & Adrian Raftery, 2010. "Latent class analysis variable selection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 11-35, February.
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