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Investigating the Progression of Programmers' Mental Models

Published:29 June 2023Publication History

ABSTRACT

Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model based learning and visualizations. However, there is a significant lack of empirical research on mental models formed during the comprehension of parallel programs. We present an empirical method for externalizing and mapping mental models of learners and its novel application to a programming context. Participants externalize their mental models by drawing diagrams to depict the execution of a parallel program during a code tracing task. The code tracing task is performed prior to and during instruction on parallel programming in C using OpenMP. The progression of the mental models is analyzed using a rubric to determine how they developed and changed as participants learned. This poster presents our work in progress and preliminary results.

References

  1. Eric Aubanel. 2020. Parallel Program Comprehension. In 31st Annual Workshop of the Psychology of Programming Interest Group (PPIG 2020).Google ScholarGoogle Scholar
  2. Leah Bidlake, Eric Aubanel, and Daniel Voyer. 2023. Progression of Programmers' Mental Models Learning Parallel Programming. https://osf.io/u29hr/?view_only=6b172c0ba55d4737baaa28e3db445910Google ScholarGoogle Scholar
  3. Jean-Marie Burkhardt, Francoise Détienne, and Susan Wiedenbeck. 2002. Object-oriented program comprehension: Effect of expertise, task and phase. Empirical Software Engineering, Vol. 7, 22 (2002), 115--156.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Norbert M. Seel. 2001. Epistemology, situated cognition, and mental models: ?Like a bridge over troubled water". Instructional Science, Vol. 29, 4 (Jul 2001), 403--427. https://doi.org/10.1023/A:1011952010705Google ScholarGoogle ScholarCross RefCross Ref
  5. Norbert M. Seel. 2017. Model-based learning: a synthesis of theory and research. Educational Technology Research and Development, Vol. 65, 4 (Aug 2017), 931--966. https://doi.org/10.1007/s11423-016--9507--9Google ScholarGoogle ScholarCross RefCross Ref

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          cover image ACM Conferences
          ITiCSE 2023: Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2
          June 2023
          694 pages
          ISBN:9798400701399
          DOI:10.1145/3587103

          Copyright © 2023 Owner/Author

          Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 29 June 2023

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