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Evaluation of native and transfer students' success in a computer science course

Authors:

Helen Catanese,

Carl Hauser,

Assefaw H. GebremedhinAuthors Info & Claims

ACM Inroads, Volume 9, Issue 2

Pages 53 - 57

https://doi.org/10.1145/3204471

Published: 27 April 2018 Publication History

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Abstract

This study is motivated by a practical question faced by a computer science curriculum committee at a major research university. And that question is, are students who transfer credits for the first two courses into the computer science program at a disadvantage in their likelihood for success in the third course compared to students who took all three courses locally at the university? A retrospective longitudinal study using data from 2012 to 2016 revealed that transfer students succeeded in the third course in just about the same way as native students. The study also suggests interesting ideas for future exploration and avenues for further inquiries on broader topics.

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Cited By

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Wu P(2024)Realization of Computer Course Scheduling Algorithm in Higher Vocational Colleges Based on MLApplication of Big Data, Blockchain, and Internet of Things for Education Informatization10.1007/978-3-031-63139-9_45(427-435)Online publication date: 1-Jul-2024
https://doi.org/10.1007/978-3-031-63139-9_45
Ellis MHooshangi SDoyle MStephenson BDorn BSoh LBattestilli L(2023)Replication and Expansion Study on Factors Influencing Student Performance in CS2Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569867(896-902)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569867
Hooshangi SEllis MEdwards SMerkle LDoyle MSheard JSoh LDorn B(2022)Factors Influencing Student Performance and Persistence in CS2Proceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499272(286-292)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499272

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Published In

ACM Inroads Volume 9, Issue 2

June 2018

75 pages

ISSN:2153-2184

EISSN:2153-2192

DOI:10.1145/3211407

Editor:
John Impagliazzo
Emeritus, Hofstra University

Issue’s Table of Contents

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

Publication History

Published: 27 April 2018

Published in INROADS Volume 9, Issue 2

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Wu P(2024)Realization of Computer Course Scheduling Algorithm in Higher Vocational Colleges Based on MLApplication of Big Data, Blockchain, and Internet of Things for Education Informatization10.1007/978-3-031-63139-9_45(427-435)Online publication date: 1-Jul-2024
https://doi.org/10.1007/978-3-031-63139-9_45
Ellis MHooshangi SDoyle MStephenson BDorn BSoh LBattestilli L(2023)Replication and Expansion Study on Factors Influencing Student Performance in CS2Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569867(896-902)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569867
Hooshangi SEllis MEdwards SMerkle LDoyle MSheard JSoh LDorn B(2022)Factors Influencing Student Performance and Persistence in CS2Proceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499272(286-292)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499272

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Experiences of Computer Science Transfer Students

Contributing to success in an introductory computer science course: a study of twelve factors

A nontraditional computer graphics course for computer science students

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