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Evaluating the Effectiveness of Explicit Instruction in Reducing Program Reasoning Fallacies in Elementary Level Students

Published: 02 July 2019 Publication History

Abstract

Previous research in K-5 CS education has focused on improving students' engagement in programming using visual block-based environments like Scratch. However, little is known about how elementary school students' reason about programs. We define computational reasoning as the ability to read, write, trace and debug programs and predict program behavior. Recently, computing education researchers have become interested in exploring how elementary school students build their computational reasoning abilities. This poster presents results from a study which analyzed the role of explicit instruction in the form of 'laws of computation' in cultivating elementary school (4th and 5th graders) students' ability to reason about programs using Microsoft Kodu Game Lab. We used pretests to record students' default models of reasoning about programs and then used posttests to measure the effectiveness of intervention by noting students' reasoning responses on a similar program. Our findings indicate that by default students reason sequentially about program execution which can be incorrect in situations like parallel rule execution. We also found that the use of explicit instruction in the form of 'laws' is helpful for students to refine their understanding of program execution and to improve their reasoning ability.

References

[1]
Ashish Aggarwal, David S. Touretzky, and Christina Gardner-McCune. 2018. Demonstrating the Ability of Elementary School Students to Reason About Programs. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18). ACM, New York, NY, USA, 735--740.
[2]
Michael Clancy. 2004. Misconceptions and attitudes that interfere with learning to program. In Computer Science Education Research. London: Taylor & Francis Group, 85--100
[3]
David S. Touretzky, Christina Gardner-McCune, and Ashish Aggarwal. 2017. Semantic Reasoning in Young Programmers. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE '17). ACM, New York, NY, USA, 585--590.
[4]
Allen Tucker. 2003. A Model Curriculum for K--12 Computer Science: Final Report of the ACM K--12 Task Force Curriculum Committee. Technical Report. ACM, New York, NY, USA. ACM Order No.: 104043.

Cited By

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  • (2023)Revisiting Analogical Reasoning in Computing Education: Use of Similarities Between Robot Programming Tasks in DebuggingJournal of Educational Computing Research10.1177/0735633122114291261:5(1036-1063)Online publication date: 17-Mar-2023

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  1. Evaluating the Effectiveness of Explicit Instruction in Reducing Program Reasoning Fallacies in Elementary Level Students

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        cover image ACM Conferences
        ITiCSE '19: Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education
        July 2019
        583 pages
        ISBN:9781450368957
        DOI:10.1145/3304221
        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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        New York, NY, United States

        Publication History

        Published: 02 July 2019

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        Author Tags

        1. analogical reasoning
        2. computational reasoning
        3. elementary school students
        4. explicit instruction
        5. kodu
        6. program comprehension

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        • (2023)Revisiting Analogical Reasoning in Computing Education: Use of Similarities Between Robot Programming Tasks in DebuggingJournal of Educational Computing Research10.1177/0735633122114291261:5(1036-1063)Online publication date: 17-Mar-2023

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