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Improving Students' Learning and Achievement in CS Classrooms through Computational Creativity Exercises that Integrate Computational and Creative Thinking

Published:08 March 2017Publication History

ABSTRACT

Our research is based on an innovative approach that integrates computational thinking and creative thinking in computer science courses to improve student learning and performance. Referencing Epstein's Generativity Theory, we designed and deployed Computational Creativity Exercises (CCEs) with linkages to concepts in computer science and computational thinking. Prior studies with earlier versions of the CCEs in CS1 courses found that completing more CCEs led to higher grades and increased learning of computational thinking principles. In this study, we extended the examination of CCEs to by deploying revised CCEs across two lower division (freshmen, sophomore) and three upper division (junior, senior) CS courses. We found a linear "dosage effect" of increasingly higher grades and computational thinking/CS knowledge test scores with completion of each additional CCE. This dosage effect was consistent across lower and upper division courses. Findings supported our contention that the merger of computational and creative thinking can be realized in computational creativity exercises that can be implemented and lead to increased student learning across courses from freshmen to senior level. The effect of the CCEs on learning was independent of student general academic achievement and individual student motivation. If students do the CCEs, they appear to benefit, whether or not they are self-aware of the benefit or personally motivated to do them. Issues in implementation are discussed.

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          cover image ACM Conferences
          SIGCSE '17: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education
          March 2017
          838 pages
          ISBN:9781450346986
          DOI:10.1145/3017680

          Copyright © 2017 ACM

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          Publication History

          • Published: 8 March 2017

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          SIGCSE '17 Paper Acceptance Rate105of348submissions,30%Overall Acceptance Rate1,595of4,542submissions,35%

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