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Identifying student misconceptions of programming

Published: 10 March 2010 Publication History

Abstract

Computing educators are often baffled by the misconceptions that their CS1 students hold. We need to understand these misconceptions more clearly in order to help students form correct conceptions. This paper describes one stage in the development of a concept inventory for Computing Fundamentals: investigation of student misconceptions in a series of core CS1 topics previously identified as both important and difficult. Formal interviews with students revealed four distinct themes, each containing many interesting misconceptions. Three of those misconceptions are detailed in this paper: two misconceptions about memory models, and data assignment when primitives are declared. Individual misconceptions are related, but vary widely, thus providing excellent material to use in the development of the CI. In addition, CS1 instructors are provided immediate usable material for helping their students understand some difficult introductory concepts.

References

[1]
Almstrum, V. L., Henderson, P. B., Harvey, V., Heeren, C., Marion, W., Riedesel, C., Soh, L., and Tew, A. E. 2006. Concept inventories in computer science for the topic discrete mathematics. In ACM SIGCSE Bulletin, 38, 4 (Dec. 2006), 132--145.
[2]
Bayman, P. and Mayer, R. E. 1983. A diagnosis of beginning programmers' misconceptions of BASIC programming statements. Commun. ACM 26, 9 (Sep. 1983), 677--679.
[3]
Bonar, J. and Soloway, E. 1985. Preprogramming knowledge: a major source of misconceptions in novice programmers. Hum.-Comput. Interact. 1, 2 (Jun. 1985), 133--161.
[4]
Bowen, C. W. 1994. Think-Aloud Methods in Chemistry Education. In Journal of Chemical Education. 71, 3 (Mar. 1994), 184--190.
[5]
Confrey, J. 1990. A review of the research on student conceptions in mathematics, science, and programming. Review of Research in Education, 16, 3 (1990), 3--56.
[6]
Fleury, A. E. 1991. Parameter passing: the rules the students construct. In Proceedings of the Twenty-Second SIGCSE Technical Symposium on Computer Science Education (San Antonio, Texas, United States, March 07 - 08, 1991).
[7]
Goldman, K., Gross, P., Heeren, C., Herman, G., Kaczmarczyk, L., Loui, M. C. and Zilles, C. 2008. Identifying important and difficult concepts in introductory computing courses using a Delphi process. In Proceedings of the Thirty-Ninth SIGCSE Technical Symposium on Computer Science Education (Portland, OR, United States, March 12-15, 2008).
[8]
Herman, G. L., Kaczmarczyk, L., Loui, M. C., and Zilles, C. 2008. Proof by incomplete enumeration and other logical misconceptions. In Proceedings of the Fourth International Workshop on Computing Education Research (Sydney, Australia, Sep. 06 - 07, 2008).
[9]
Herman, G. L., Loui, M. C., and Zilles, C., Creating the Digital Logic Concept Inventory. In Proceedings of the Forty-First ACM Technical Symposium on Computer Science Education, Milwaukee, WI, March 10-13, 2010.
[10]
Hestenes, D., Wells, M., and Swackhamer, G. 1992. Force concept inventory. The Physics Teacher, 30 (Mar. 1992), 141--158.
[11]
Holland, S., Griffiths, R., and Woodman, M. 1997. Avoiding Object misconceptions. In Proceedings of the Twenty-Eighth SIGCSE Technical Symposium on Computer Science Education (San Jose, California, United States, February 27 - March 01, 1997).
[12]
Kolikant, Y. B.-D. and Mussai, M. 2008. "So my program doesn't run!" Definition, origins, and practical expressions of students' (mis)conceptions of correctness, Computer Science Education, 18, 2 (Jun. 2008), 135--151.
[13]
Kvale, S. 1996. Interviews: An Introduction to Qualitative Research Inquiry. Sage Publications, Thousand Oaks, CA.
[14]
Ma, L., Ferguson, J., Roper, M., and Wood, M. 2007. Investigating the viability of mental models held by novice programmers. In Proceedings of the Thirty-Eighth SIGCSE Technical Symposium on Computer Science Education (Covington, Kentucky, United States, March 07 - 11, 2007). SIGCSE '07.
[15]
Madison, A. and Gifford, J. 2003. Modular programming: Novice misconceptions. Journal of Research on Technology in Education, 34, 3 (Spr. 2003), 217--229.
[16]
Mayer, R. E. 1981. The Psychology of How Novices Learn Computer Programming. ACM Comput. Surv. 13, 1 (Mar. 1981), 121--141.
[17]
Miles, M. B. and Huberman, A. M. 1994. Qualitative Data Analysis: An Expanded Sourcebook, 2nd Edition. Sage Publications, Thousand Oaks, CA.
[18]
Pea, R. D. 1986. Language-independent conceptual "bugs" in novice programming. Journal of Educational Computing Research, 2, 1 (1986), 25--36.
[19]
Sanders, K. and Thomas, L. 2007. Checklists for grading Object-oriented CS1 programs: concepts and misconceptions. In Proceedings of the Twelfth Annual Conference on Innovation and Technology in Computer Science Education (Dundee, Scotland, June 25 - 27, 2007).
[20]
Spohrer, J. C. and Soloway, E. 1986. Alternatives to construct-based programming misconceptions. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Boston, MA, United States, April 13 - 17, 1986).
[21]
Stanovich, K. E. 2003. The Fundamental Computational Biases of Human Cognition: Heuristics That (Sometimes) Impair Decision Making and Problem Solving. In The Psychology of Problem Solving, J. E. Davidson and R. J. Sternberg, Eds. Cambridge University Press, Cambridge, UK, 291--342.
[22]
Strauss, A. and Corbin, J. 1998. Basics of Qualitative Research. Sage Publications, Thousand Oaks, CA

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cover image ACM Conferences
SIGCSE '10: Proceedings of the 41st ACM technical symposium on Computer science education
March 2010
618 pages
ISBN:9781450300063
DOI:10.1145/1734263
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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Published: 10 March 2010

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Author Tags

  1. concept inventory
  2. cs1
  3. curriculum
  4. misconceptions
  5. pedagogy
  6. programming

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Cited By

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  • (2024)Experience Report: Identifying common misconceptions and errors of novice programmers with ChatGPTProceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training10.1145/3639474.3640059(233-241)Online publication date: 14-Apr-2024
  • (2024)Using Benchmarking Infrastructure to Evaluate LLM Performance on CS Concept Inventories: Challenges, Opportunities, and CritiquesProceedings of the 2024 ACM Conference on International Computing Education Research - Volume 110.1145/3632620.3671097(452-468)Online publication date: 12-Aug-2024
  • (2024)The Correctness of the Mental Model of Arrays After Instruction for CS1 StudentsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630943(806-811)Online publication date: 7-Mar-2024
  • (2024)Investigating Student Mistakes in Introductory Data Science ProgrammingProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630884(1258-1264)Online publication date: 7-Mar-2024
  • (2023)SIDE-lib: A Library for Detecting Symptoms of Python Programming MisconceptionsProceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 110.1145/3587102.3588838(159-165)Online publication date: 29-Jun-2023
  • (2023)Taking Stock of Concept Inventories in Computing Education: A Systematic Literature ReviewProceedings of the 2023 ACM Conference on International Computing Education Research - Volume 110.1145/3568813.3600120(397-415)Online publication date: 7-Aug-2023
  • (2023)Examples of Unsuccessful Use of Code Comprehension Strategies: A Resource for Developing Code Comprehension PedagogyProceedings of the 2023 ACM Conference on International Computing Education Research - Volume 110.1145/3568813.3600116(15-28)Online publication date: 7-Aug-2023
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  • (2022)Mapping Computational Thinking Skills Through Digital Games Co-Creation Activity Amongst Malaysian Sub-urban ChildrenJournal of Educational Computing Research10.1177/0735633122112110661:2(355-389)Online publication date: 31-Oct-2022
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