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Novice Java Programming Mistakes: Large-Scale Data vs. Educator Beliefs

Published: 03 May 2017 Publication History
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  • Abstract

    Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much opportunity for misunderstanding, and the penalties are harsh: failing to produce the correct syntax for a program, for example, can completely prevent any progress in learning how to program. Because programming is inherently computer-based, we have an opportunity to automatically observe programming behaviour -- more closely even than an educator in the room at the time. By observing students’ programming behaviour, and surveying educators, we can ask: do educators have an accurate understanding of the mistakes that students are likely to make? In this study, we combined two years of the Blackbox dataset (with more than 900 thousand users and almost 100 million compilation events) with a survey of 76 educators to investigate which mistakes students make while learning to program Java, and whether the educators could make an accurate estimate of which mistakes were most common. We find that educators’ estimates do not agree with one another or the student data, and discuss the implications of these results.

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    • (2024)Confidence vs Insight: Big and Rich Data in Computing Education ResearchProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630813(158-164)Online publication date: 7-Mar-2024
    • (2023)Student Code Refactoring MisconceptionsProceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 110.1145/3587102.3588840(19-25)Online publication date: 29-Jun-2023
    • (2023)Exploring the Responses of Large Language Models to Beginner Programmers’ Help RequestsProceedings of the 2023 ACM Conference on International Computing Education Research - Volume 110.1145/3568813.3600139(93-105)Online publication date: 7-Aug-2023

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    Published In

    cover image ACM Transactions on Computing Education
    ACM Transactions on Computing Education  Volume 17, Issue 2
    June 2017
    107 pages
    EISSN:1946-6226
    DOI:10.1145/3090098
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 03 May 2017
    Accepted: 01 August 2016
    Revised: 01 August 2016
    Received: 01 March 2016
    Published in TOCE Volume 17, Issue 2

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    Author Tags

    1. Programming mistakes
    2. blackbox
    3. educators
    4. java

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    View all
    • (2024)Confidence vs Insight: Big and Rich Data in Computing Education ResearchProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630813(158-164)Online publication date: 7-Mar-2024
    • (2023)Student Code Refactoring MisconceptionsProceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 110.1145/3587102.3588840(19-25)Online publication date: 29-Jun-2023
    • (2023)Exploring the Responses of Large Language Models to Beginner Programmers’ Help RequestsProceedings of the 2023 ACM Conference on International Computing Education Research - Volume 110.1145/3568813.3600139(93-105)Online publication date: 7-Aug-2023
    • (2023)Evaluating Distance Measures for Program RepairProceedings of the 2023 ACM Conference on International Computing Education Research - Volume 110.1145/3568813.3600130(495-507)Online publication date: 7-Aug-2023

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