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abstract

How do we Help Students “See the Forest from the Trees?”

Published:07 August 2022Publication History

ABSTRACT

For students to write code, they should be able to understand the purpose of code written by others. How students learn to read code at a higher-level beyond tracing (mental execution) is not well-understood. The goal of my research is to understand how to teach students to read code at a higher-level.

References

  1. Ruven Brooks. 1983. Towards a theory of the comprehension of computer programs. International journal of man-machine studies 18, 6 (1983), 543–554.Google ScholarGoogle ScholarCross RefCross Ref
  2. Malcolm Corney, Donna Teague, Alireza Ahadi, and Raymond Lister. 2012. Some empirical results for neo-Piagetian reasoning in novice programmers and the relationship to code explanation questions. In Proceedings of the fourteenth australasian computing education conference, Vol. 123. 77–86.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Kathryn Cunningham, Sarah Blanchard, Barbara Ericson, and Mark Guzdial. 2017. Using tracing and sketching to solve programming problems: replicating and extending an analysis of what students draw. In Proceedings of the 2017 ACM Conference on International Computing Education Research. 164–172.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Adrienne Decker, Lauren Margulieux, and Briana Morrison. 2019. Using the SOLO Taxonomy to Understand Subgoal Labels Effect in CS1. ICER’19 - Proceedings of the 2019 ACM Conference on International Computing Education Research, 209–217. https://doi.org/10.1145/3291279.3339405Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Françoise Détienne and Elliot Soloway. 1990. An empirically-derived control structure for the process of program understanding. International Journal of Man-Machine Studies 33, 3 (1990), 323–342.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Mohammed Hassan and Craig Zilles. 2021. Exploring ‘reverse-tracing’ Questions as a Means of Assessing the Tracing Skill on Computer-based CS 1 Exams. In Proceedings of the 17th ACM Conference on International Computing Education Research. 115–126.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Mohammed Hassan and Craig Zilles. 2022. On Students’ Ability to Resolve their own Tracing Errors through Code Execution. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education. 251–257.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Cruz Izu and Claudio Mirolo. 2020. Comparing small programs for equivalence: A code comprehension task for novice programmers. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. 466–472.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Raymond Lister, Elizabeth S Adams, Sue Fitzgerald, William Fone, John Hamer, Morten Lindholm, Robert McCartney, Jan Erik Moström, Kate Sanders, Otto Seppälä, Beth Simon, and Lynda Thomas. 2004. A multi-national study of reading and tracing skills in novice programmers. ACM SIGCSE Bulletin 36, 4 (2004), 119–150.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Claudio Mirolo, Cruz Izu, and Emanuele Scapin. 2020. High-school students’ mastery of basic flow-control constructs through the lens of reversibility. In Proceedings of the 15th Workshop on Primary and Secondary Computing Education. 1–10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Nancy Pennington. 1987. Stimulus structures and mental representations in expert comprehension of computer programs. Cognitive psychology 19, 3 (1987), 295–341.Google ScholarGoogle Scholar
  12. Donna Teague, Malcolm Corney, Alireza Ahadi, and Raymond Lister. 2013. A qualitative think aloud study of the early neo-piagetian stages of reasoning in novice programmers. In Proceedings of the 15th Australasian Computing Education Conference [Conferences in Research and Practice in Information Technology, Volume 136]. Australian Computer Society, 87–95.Google ScholarGoogle Scholar
  13. Donna Teague and Raymond Lister. 2014. Longitudinal think aloud study of a novice programmer. In Conferences in Research and Practice in Information Technology Series.Google ScholarGoogle Scholar
  14. Benjamin Xie, Greg L Nelson, and Andrew J Ko. 2018. An explicit strategy to scaffold novice program tracing. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education. 344–349.Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Conferences
    ICER '22: Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 2
    August 2022
    57 pages
    ISBN:9781450391955
    DOI:10.1145/3501709

    Copyright © 2022 Owner/Author

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    • Published: 7 August 2022

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