Learning Looping: From Natural Language to Worked Examples

  • Leigh Ann Sudol-DeLyser
  • Mark Stehlik
  • Sharon Carver
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7315)

Abstract

One important introductory concept in many CS courses is repetition (looping), the automated repeating of individual commands. In this work, we present results from a study of college undergraduates’ naive conceptions of repetition, their difficulties with learning to construct valid repetition statements, and their abilities to apply what they have learned to new problem solving situations. Although computer programming is a new topic when high school or college students encounter it for the first time, students can draw upon their previous life experiences when solving problems. Those conceptions that align with CS topics [2,3] have been shown to be influenced by students’ prior experiences. Alignment through analogies can be helpful [1] although where the scientific concept differs, common knowledge can hinder learning [4].

For many students, the topic of looping is their first encounter with nonlinearity in their programs. Until this point, each line of code is executed once, and then control moves to the next line of code. Such linearity makes reasoning about the programs straightforward. With the addition of looping, in the code you will need to evaluate a termination condition and then either repeat prior lines of code, or move to the next statement after the loop. While returning to a previous command or location is not unusual in everyday life and natural language, it is an important change in the way that novices see their code.

Keywords

Natural Language Transfer Test Nest Loop College Undergraduate Learn Loop 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Mayer, R.: The psychology of how novices learn computer programming. ACM Comput. Surv. 13(1), 121–141 (1981)CrossRefGoogle Scholar
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    Simon, B., Bouvier, D., Chen, T., Lewandowski, G., McCartney, R., Sanders, K.: Common sense computing(episode 4): Debugging. Computer Science Education 18, 117–133 (2008)CrossRefGoogle Scholar
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    Sudol, L.A., Stehlik, M., Carver, S.: Mental models of data. In: Proceedings of the 9th Koli Calling International Conference on Computing Education Research (2009)Google Scholar
  4. 4.
    Vosniadou, S.: Mental models in conceptual development. Model Based Reasoning: Science, Technology, Values 1 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Leigh Ann Sudol-DeLyser
    • 1
  • Mark Stehlik
    • 1
  • Sharon Carver
    • 1
  1. 1.Carnegie Mellon UniversityUSA

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