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Detecting and understanding students' misconceptions related to algorithms and data structures

Published:29 February 2012Publication History

ABSTRACT

We describe the first results of our work towards a concept inventory for Algorithms and Data Structures. Based on expert interviews and the analysis of 400 exams we were able to identify several core topics which are prone to error. In a pilot study, we verified misconceptions known from the literature and identified previously unknown misconceptions related to Algorithms and Data Structures. In addition to this, we report on methodological issues and point out the importance of a two-pronged approach to data collection.

References

  1. V. L. Almstrum, P. B. Henderson, V. J. Harvey, C. Heeren, W. A. Marion, C. Riedesel, L.-K. Soh, and A. E. Tew. Concept inventories in computer science for the topic discrete mathematics. SIGCSE Bulletin, 38(4):132--145, Dec. 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. C. Chang, P. J. Denning, J. J. Cross II, G. Engel, R. Sloan, D. Carver, R. Eckhouse, W. King, F. Lau, S. Mengel, P. Srimani, E. Roberts, R. Shackelford, R. Austing, C. F. Cover, G. Davies, A. McGettrick, G. M. Schneider, and U. Wolz. Computing Curricula 2001: Computer Science. Journal on Educational Resources in Computing, 1, 2001. Article 1, 240 pp.Google ScholarGoogle Scholar
  3. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms. MIT Press, Cambridge, MA, 2nd ed., 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Eckerdal, R. McCartney, J. E. Moström, M. Ratcliffe, and C. Zander. Can graduating students design software systems? In Proc. 37th SIGCSE Symp. Computer Science Education, pp. 403--407. 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. A. Eckerdal and M. Thuné. Novice Java programmers' conceptions of "object" and "class", and variation theory. In Proc. 10th ITiCSE Conf. Innovation and Technology in Computer Science Education, pp. 89--93. 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. D. Ginat. The baffling CS notions of "as-if" and "don't-care". In Proc. 41st SIGCSE Symp. Computer Science Education, pp. 385--389. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. K. Goldman, P. Gross, C. Heeren, G. L. Herman, L. C. Kaczmarczyk, M. C. Loui, and C. Zilles. Identifying important and difficult concepts in introductory computing courses using a Delphi process. In Proc. 39th SIGCSE Symp. Computer Science Education, pp. 256--260. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. G. L. Herman, M. C. Loui, and C. Zilles. Creating the digital logic concept inventory. In Proc. 41th SIGCSE Symp. Computer Science Education, pp. 102--106. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. S. Holland, R. Griffiths, and M. Woodmann. Avoiding object misconceptions. In Proc. 28th SIGCSE Symp. Computer Science Education, pp. 131--134. 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. L. C. Kaczmarczyk, E. R. Petrick, J. P. East, and G. L. Herman. Identifying student misconceptions of programming. In Proc. 41st SIGCSE Symp. Computer Science Education, pp. 107--111. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. C. Loftus, L. Thomas, and C. Zander. Can graduating students design: revisited. In Proc. 42nd SIGCSE Symp. Computer Science Education, pp. 105--110. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. M. McCracken, V. Almstrum, D. Diaz, M. Guzdial, D. Hagan, Y. B.-D. Kolikant, C. Laxer, L. Thomas, I. Utting, and T. Wilusz. A multi-national, multi- institutional study of assessment of programming skills of first-year CS students. SIGCSE Bull., 33:125--180, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. N. Ragonis and M. Ben-Ari. A long-term investigation of the comprehension of OOP concepts by novices. Computer Science Education, 15(3):203--221, Sept. 2005.Google ScholarGoogle ScholarCross RefCross Ref
  14. K. Sanders, J. Boustedt, A. Eckerdal, R. McCartney, J. E. Moström, L. Thomas, and C. Zander. Student understanding of object-oriented programming as expressed in concept maps. In Proc. 39th SIGCSE Symp. Computer Science Education, pp. 332--336. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. O. Seppala, L. Malmi, and A. Korhonen. Observations on student misconceptions -- a case study of the build-heap algorithm. Computer Science Education, 16(3):241--255. 2006.Google ScholarGoogle ScholarCross RefCross Ref
  16. A. E. Tew and M. Guzdial. Developing a validated assessment of fundamental CS1 concepts. In Proc. 41st SIGCSE Symp. Computer Science Education, pp. 97--101. 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Conferences
      SIGCSE '12: Proceedings of the 43rd ACM technical symposium on Computer Science Education
      February 2012
      734 pages
      ISBN:9781450310987
      DOI:10.1145/2157136

      Copyright © 2012 ACM

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      Publication History

      • Published: 29 February 2012

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      SIGCSE '12 Paper Acceptance Rate100of289submissions,35%Overall Acceptance Rate1,595of4,542submissions,35%

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