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Journal of Science Education and Technology

, Volume 22, Issue 6, pp 899–913 | Cite as

Profiles of Motivated Self-Regulation in College Computer Science Courses: Differences in Major versus Required Non-Major Courses

  • Duane F. Shell
  • Leen-Kiat Soh
Article

Abstract

The goal of the present study was to utilize a profiling approach to understand differences in motivation and strategic self-regulation among post-secondary STEM students in major versus required non-major computer science courses. Participants were 233 students from required introductory computer science courses (194 men; 35 women; 4 unknown) at a large Midwestern state university. Cluster analysis identified five profiles: (1) a strategic profile of a highly motivated by-any-means good strategy user; (2) a knowledge-building profile of an intrinsically motivated autonomous, mastery-oriented student; (3) a surface learning profile of a utility motivated minimally engaged student; (4) an apathetic profile of an amotivational disengaged student; and (5) a learned helpless profile of a motivated but unable to effectively self-regulate student. Among CS majors and students in courses in their major field, the strategic and knowledge-building profiles were the most prevalent. Among non-CS majors and students in required non-major courses, the learned helpless, surface learning, and apathetic profiles were the most prevalent. Students in the strategic and knowledge-building profiles had significantly higher retention of computational thinking knowledge than students in other profiles. Students in the apathetic and surface learning profiles saw little instrumentality of the course for their future academic and career objectives. Findings show that students in STEM fields taking required computer science courses exhibit the same constellation of motivated strategic self-regulation profiles found in other post-secondary and K-12 settings.

Keywords

Student self-regulation Student motivation Discipline-based education Computational thinking Approaches to learning Learning profiles 

Notes

Acknowledgments

This research was supported by a grant from the National Science Foundation (Grant# CNS-0829647).

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Educational Psychology, 114 TEACUniversity of Nebraska-LincolnLincolnUSA
  2. 2.Department of Computer Science and Engineering, 122E AVHUniversity of Nebraska-LincolnLincolnUSA

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