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Study Strategies and Exam Grades in CS1

Published: 06 May 2016 Publication History

Abstract

Few have studied the correlations between the type of study strategies appropriated by students in a first-year Computer Science (CS1) class and their success in the course. In this study, CS1 students were surveyed in order to determine their study strategies (deep, surface or disorganized), which were then compared to their final exam grade. Deep study strategies were found to correlate positively with exam grade while both surface and disorganized strategies correlated negatively with exam grade. The scales, largely developed as part of this work, were found to be reliable. Hence, fellow researchers are encouraged to use these scales in future research and further develop the literature regarding study strategies in Computer Science (CS).

References

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R. Choinard, T. Karsenti, and N. Roy. Relations among competence beliefs, utility value, achievement goals, and effort in mathematics. British Journal of Educational Psychology, 77(3):501--517, 2007.
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A. Elliot, H. A. McGregor, and S. Gable. Achievement goals, study strategies, and exam performance: A mediational analysis. Journal of Educational Psychology, 91(3):549--563, 1999.
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Cited By

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  • (2024)Applying CS0/CS1 Student Success Factors and Outcomes to Biggs' 3P Educational ModelProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630781(1168-1174)Online publication date: 7-Mar-2024
  • (2023)Enhancing learning from online video lectures: the impact of embedded learning prompts in an undergraduate physics lessonJournal of Computing in Higher Education10.1007/s12528-023-09379-w36:3(852-874)Online publication date: 12-Jul-2023

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WCCCE '16: Proceedings of the 21st Western Canadian Conference on Computing Education
May 2016
137 pages
ISBN:9781450343558
DOI:10.1145/2910925
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 06 May 2016

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WCCCE '16

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WCCCE '16 Paper Acceptance Rate 26 of 35 submissions, 74%;
Overall Acceptance Rate 78 of 117 submissions, 67%

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View all
  • (2024)Applying CS0/CS1 Student Success Factors and Outcomes to Biggs' 3P Educational ModelProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630781(1168-1174)Online publication date: 7-Mar-2024
  • (2023)Enhancing learning from online video lectures: the impact of embedded learning prompts in an undergraduate physics lessonJournal of Computing in Higher Education10.1007/s12528-023-09379-w36:3(852-874)Online publication date: 12-Jul-2023

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