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Partnership Characteristics and Student Performance in an Introductory Computer Science Course

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Software Engineering Division Technical Session 1

Tagged Division

Software Engineering Division

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Paper Authors


Charles Kowalec University of Michigan

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Charles Kowalec is an undergraduate student at the University of Michigan interested in the science of how students learn.

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Andrew Deorio University of Michigan Orcid 16x16

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Andrew DeOrio is a lecturer at the University of Michigan and a consultant for web, machine learning and hardware projects. His research interests are in ensuring the correctness of computer systems, including medical devices, internet of things (IOT) devices, and digital hardware. In addition to teaching software and hardware courses, he teaches Creative Process and works with students on technology-driven creative projects.

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Group work and programming in partnerships have been shown to have a positive effect on student learning in computer science education. As a result, students in introductory computer science courses often work in teams or partnerships. In this paper, we examine the composition of student partnerships on programming projects in an introductory computer science course and its relationship to student performance.

We analyze data from 1,434 students enrolled in an introductory computer science course at a highly ranked public university, collected over one academic year. These data include student group composition, performance on projects and exams, and demographic information. The course is a second-semester "CS2" programming and introductory data structures course, and is part of the core computer science curriculum for majors and minors. Students had the option to work in partnerships or to work alone on projects.

Our results examine several factors influencing the success of a partnership, including difference in cumulative grade point average (GPA), gender balance, and work habits like starting projects early. After controlling for GPA, we observed an association between starting projects early and increased performance on both exams and projects. The impact was greatest among those in the lowest GPA quartile, where an early start made the difference between an average final letter grade of C+ (lowest early-start quartile) and B- (highest early-start quartile).

Kowalec, C., & Deorio, A. (2017, June), Partnership Characteristics and Student Performance in an Introductory Computer Science Course Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28732

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