A study of the impact of student background and preparedness on outcomes in CS I

Morrison, Malcolm H.; Newman, Timothy S.

doi:10.1145/364447.364580

Cited by 25 publications

(14 citation statements)

References 6 publications

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“…This follows results from other studies showing math preparedness as being one of the biggest predictors of success in introductory CS courses [7,8,10]. This result indicates that requiring a certain level of math pre-requisite for CS2 may better prepare students for success in the course.…”

Section: Longitudinal Studysupporting

confidence: 86%

A support program for introductory CS courses that improves student performance and retains students from underrepresented groups

Newhall

Meeden

Danner

et al. 2014

Proceedings of the 45th ACM Technical Symposium on Computer Science Education

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In line with institutions across the United States, the Computer Science Department at Swarthmore College has faced the challenge of maintaining a demographic composition of students that matches the student body as a whole. To combat this trend, our department has made a concerted effort to revamp our introductory course sequence to both attract and retain more women and minority students.The focus of this paper is the changes instituted in our Introduction to Computer Science course (i.e., CS1) intended for both majors and non-majors. In addition to changing the content of the course, we introduced a new student mentoring program that is managed by a full-time coordinator and consists of undergraduate students who have recently completed the course. This paper describes these efforts in detail, including the extension of these changes to our CS2 course and the associated costs required to maintain these efforts. We measure the impact of these changes by tracking student enrollment and performance over 13 academic years. We show that, unlike national trends, enrollment from underrepresented groups has increased dramatically over this time period. Additionally, we show that the student mentoring program has increased both performance and retention of students, particularly from underrepresented groups, at statistically significant levels.

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Section: Longitudinal Studysupporting

confidence: 86%

A support program for introductory CS courses that improves student performance and retains students from underrepresented groups

Newhall

Meeden

Danner

et al. 2014

Proceedings of the 45th ACM Technical Symposium on Computer Science Education

View full text Add to dashboard Cite

show abstract

“…Prior programming experience was collected because of its reliable role in predicting student grade (e.g. [10,15]). On the end-of-term questionnaire, a post-selfefficacy measure was obtained.…”

Section: Methodsmentioning

confidence: 99%

Peer instruction contributes to self-efficacy in CS1

Zingaro

2014

Proceedings of the 45th ACM Technical Symposium on Computer Science Education

106

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Recent work in computing suggests that Peer Instruction (PI) is a valuable interactive learning pedagogy: it lowers fail rates, increases retention, and is enjoyed by students and instructors alike. While these findings are promising, they are somewhat incidental if our goal is to understand whether PI is "better" than lecture in terms of student outcomes. Only one recent study in computing has made such a comparison, finding that PI students outperform traditionallytaught students on a CS0 final exam. That work was conducted in a CS0, where the same instructor taught both courses, and where the only outcome measure was final exam grade. Here, I offer a study that complements their work in two ways. First, I argue for and measure self-efficacy as a valued outcome, in addition to that of final exam grade. Second, I offer an inter-instructor CS1 study, whose biases differ from those of intra-instructor studies. I find evidence that PI significantly increases self-efficacy and suggestively increases exam scores compared to a traditional lecture-based CS1 class. I note validity concerns of such an in-situ study and offer a synthesis of this work with the extant PI literature.

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“…According to many previous studies [4,6,10,12,13], there is a positive correlation between students' previous computer-related background and level of success in computer science. However, these studies usually defined success in computer science by student achievement in academic CS1 courses, or introduction to programming courses, with an emphasis on programming.…”

Section: The Connection Between Students' Computer-related Backgroundmentioning

confidence: 99%

On the achievements of high school students studying computational models

Armoni

Gal‐Ezer

2004

Proceedings of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education

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One of the units in the relatively new high school CS curriculum which is being implemented in Israel is a theoretical unit on computational models. It includes deterministic and nondeterministic finite automata, regular and non-regular languages, closure properties of regular languages, pushdown automata, closure properties of context free languages, Turing machines, the Church-Turing thesis and the halting problem. This paper focuses on part of a study we conducted dealing with the achievements of high school students studying this unit. Specifically, this paper compares the achievements of students on the technical parts of this unit vs. its theoretical parts. We also examine the correlation between achievements of students studying the Computational Models unit, and two other factors: The students' previous computer-related background (not necessarily computer science) and the level on which they studied mathematics.

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A study of the impact of student background and preparedness on outcomes in CS I

Cited by 25 publications

References 6 publications

A support program for introductory CS courses that improves student performance and retains students from underrepresented groups

A support program for introductory CS courses that improves student performance and retains students from underrepresented groups

Peer instruction contributes to self-efficacy in CS1

On the achievements of high school students studying computational models

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