Improving students' learning and achievement in CS classrooms through computational creativity exercises that integrate computational and creative thinking

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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. Referenc-ing Epstein's Generativity Theory, we designed and deployed Computational Creativity Exercises (CCEs) with linkages to con-cepts in computer science and computational thinking. Prior stud-ies with earlier versions of the CCEs in CS1 courses found that completing more CCEs led to higher grades and increased learn-ing of computational thinking principles. In this study, we ex-Tended 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 think-ing/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 mer-ger 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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APA

Shell, D. F., Flanigan, A. E., Peteranetz, M. S., Soh, L. K., & Ingraham, E. (2017). Improving students’ learning and achievement in CS classrooms through computational creativity exercises that integrate computational and creative thinking. In Proceedings of the Conference on Integrating Technology into Computer Science Education, ITiCSE (pp. 543–548). Association for Computing Machinery. https://doi.org/10.1145/3017680.3017718

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