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Mastery Learning in Computer Science Education

Published: 29 January 2019 Publication History

Abstract

Mastery learning is a pedagogical approach in which students must demonstrate mastery of the currently assessed unit of material before being permitted to progress to the next unit. Recent work has suggested that mastery learning may provide a solution to the divergent outcomes observed in introductory computer science (CS) courses. While mastery learning has shown benefits outside of CS, it has received less attention in CS education, and there is no existing overview of the approaches that have been used in this discipline. To remedy this, we review the literature on the use of mastery learning in computer science. We find that while mastery learning has been applied successfully in CS education, the literature is sparse and lacks a unified approach and generalisable results.

References

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Cited By

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  • (2024)Goodbye Hello World - Research Questions for a Future CS1 CurriculumProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699591(1-2)Online publication date: 12-Nov-2024
  • (2024)The CS1 Python Bakery: A Modern "Batteries Included" Open-Source Curriculum with All the FixingsProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653630(667-673)Online publication date: 3-Jul-2024
  • (2024)Steering Student Behavior and Performance Toward Success with Mastery Learning through Policy OptimizationProceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 110.1145/3649165.3690109(144-150)Online publication date: 5-Dec-2024
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    ACE '19: Proceedings of the Twenty-First Australasian Computing Education Conference
    January 2019
    131 pages
    ISBN:9781450366229
    DOI:10.1145/3286960
    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].

    In-Cooperation

    • The University of Newcastle, Australia
    • CORE - Computing Research and Education
    • The University of Auckland

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 January 2019

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    Author Tags

    1. Keller plan
    2. PSI
    3. mastery learning
    4. pedagogy

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    • Research-article
    • Research
    • Refereed limited

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    ACE'19
    ACE'19: Twenty-First Australasian Computing Education Conference
    January 29 - 31, 2019
    NSW, Sydney, Australia

    Acceptance Rates

    ACE '19 Paper Acceptance Rate 15 of 36 submissions, 42%;
    Overall Acceptance Rate 161 of 359 submissions, 45%

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    Cited By

    View all
    • (2024)Goodbye Hello World - Research Questions for a Future CS1 CurriculumProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699591(1-2)Online publication date: 12-Nov-2024
    • (2024)The CS1 Python Bakery: A Modern "Batteries Included" Open-Source Curriculum with All the FixingsProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653630(667-673)Online publication date: 3-Jul-2024
    • (2024)Steering Student Behavior and Performance Toward Success with Mastery Learning through Policy OptimizationProceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 110.1145/3649165.3690109(144-150)Online publication date: 5-Dec-2024
    • (2024)Teaching CS1 with a Mastery Learning Framework: Changes in CS2 Results and Students' SatisfactionProceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 110.1145/3649165.3690105(221-227)Online publication date: 5-Dec-2024
    • (2024)Traditional vs. Flexible Modalities in a Data Structures ClassProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630952(1112-1118)Online publication date: 7-Mar-2024
    • (2024)Specifications and Contract Grading in Computer Science EducationProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630929(477-483)Online publication date: 7-Mar-2024
    • (2024)Do Behavioral Factors Influence the Extent to which Students Engage with Formative Practice Opportunities?Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630833(18-24)Online publication date: 7-Mar-2024
    • (2024)Extreme Ungrading: Rewilding the Classroom through Human-Centered DesignExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3644048(1-9)Online publication date: 11-May-2024
    • (2024)Mastery learning in CS1: a longitudinal study during and post-pandemicDiscover Education10.1007/s44217-024-00361-x3:1Online publication date: 2-Dec-2024
    • (2023)Applications of Programming as Theory Building in Computer Science EducationProceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 210.1145/3587103.3594137(621-622)Online publication date: 29-Jun-2023
    • Show More Cited By

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