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Teaching entering students to think like computer scientists

Published: 23 February 2005 Publication History

Abstract

This paper describes a new course developed at University of Maine to help students better understand the discipline of computer science and to aid us in recruiting and retaining majors. The course verview of computer science, but also, through focusing on particular topics at an advanced level, begins to teach students how computer scientists think about problems. The course has been taught in Fall 2002, 2003 and 2004. This paper describes the course and discusses our results from the first two years.

References

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T. P. Murtagh. Teaching breadth-first depth-first. SIGSCE Bulletin, 33(3):37--40, 2001.
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J. Prey and K. Treu. What do you say? Open letters to women considering a computer science major. Inroads (The SIGCSE Bulletin), 34(2):18--20, 2002.
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A. B. Tucker, C. F. Kelemen, and K. B. Bruce. Our curriculum has become math-phobic. In The Proceedings of the Thirty-Second SIGSCE Technical Symposium on Computer Science Education, pages 243--247, New York, NY, 2001. Association for Computing Machinery, Inc.
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E. Turner, R. Turner, and T. Wheeler. A rigorous introduction to computer science without programming. Technical Report UMCS--TR--2004--1, Department of Computer Science, University of Maine, 5752 Neville Hall, Orono, ME 04469, 2004.
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E. H. Turner, C. Emerton, R. Ray, and C. Logan. A rigorous introduction to computer science without programming: Three women's perspectives. Technical Report UMCS--TR--2004--2, Department of Computer Science, University of Maine, 5752 Neville Hall, Orono, ME 04469, 2004.
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A. Pearl, M. E. Pollack, E. Riskin, B. Thomas, E. Wolf, and A. Wu. Becoming a computer scientist. Communications of the ACM, 33(11):47--57, 1990.
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L. J. Barker, K. Garvin-Doxas, and M. Jaskson. Defensive climate in the computer science classroom. In The Proceedings of the Thirty-Third SIGSCE Technical Symposium on Computer Science Education, pages 43--47, New York, NY, 2002. Association for Computing Machinery, Inc.
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Cited By

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  • (2013)Mining for MarksProceedings of the First International Conference on Mining Intelligence and Knowledge Exploration - Volume 828410.5555/2696704.2696758(541-552)Online publication date: 18-Dec-2013
  • (2013)Mining for Marks: A Comparison of Classification Algorithms when Predicting Academic Performance to Identify “Students at Risk”Mining Intelligence and Knowledge Exploration10.1007/978-3-319-03844-5_54(541-552)Online publication date: 2013
  • (2008)A typology of CS students' preconditions for learningProceedings of the 8th International Conference on Computing Education Research10.1145/1595356.1595366(62-71)Online publication date: 13-Nov-2008
  • Show More Cited By

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Published In

cover image ACM Conferences
SIGCSE '05: Proceedings of the 36th SIGCSE technical symposium on Computer science education
February 2005
610 pages
ISBN:1581139977
DOI:10.1145/1047344
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: 23 February 2005

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Author Tags

  1. gender issues
  2. introductory computer science

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SIGCSE05
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SIGCSE05: Technical Symposium on Computer Science Education
February 23 - 27, 2005
Missouri, St. Louis, USA

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Overall Acceptance Rate 1,787 of 5,146 submissions, 35%

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SIGCSE TS 2025
The 56th ACM Technical Symposium on Computer Science Education
February 26 - March 1, 2025
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Cited By

View all
  • (2013)Mining for MarksProceedings of the First International Conference on Mining Intelligence and Knowledge Exploration - Volume 828410.5555/2696704.2696758(541-552)Online publication date: 18-Dec-2013
  • (2013)Mining for Marks: A Comparison of Classification Algorithms when Predicting Academic Performance to Identify “Students at Risk”Mining Intelligence and Knowledge Exploration10.1007/978-3-319-03844-5_54(541-552)Online publication date: 2013
  • (2008)A typology of CS students' preconditions for learningProceedings of the 8th International Conference on Computing Education Research10.1145/1595356.1595366(62-71)Online publication date: 13-Nov-2008
  • (2007)Computer science in contextProceedings of the Seventh Baltic Sea Conference on Computing Education Research - Volume 8810.5555/2449323.2449331(65-76)Online publication date: 15-Nov-2007
  • (2007)Attitudes towards computer science-computing experiences as a starting point and barrier to computer scienceProceedings of the third international workshop on Computing education research10.1145/1288580.1288585(27-38)Online publication date: 15-Sep-2007
  • (2007)Retaining majors through the introductory sequenceACM SIGCSE Bulletin10.1145/1227504.122732139:1(24-28)Online publication date: 7-Mar-2007
  • (2007)Retaining majors through the introductory sequenceProceedings of the 38th SIGCSE technical symposium on Computer science education10.1145/1227310.1227321(24-28)Online publication date: 7-Mar-2007
  • (2007)Preliminary results of a longitudinal study of computer science student trends, behaviors and preferencesJournal of Computing Sciences in Colleges10.5555/1231091.123109722:6(18-27)Online publication date: 1-Jun-2007

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