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Grading at scale in earsketch

Authors:

Avneesh Sarwate,

Creston Brunch,

Sebastian SivaAuthors Info & Claims

L@S '18: Proceedings of the Fifth Annual ACM Conference on Learning at Scale

Article No.: 50, Pages 1 - 4

https://doi.org/10.1145/3231644.3231708

Published: 26 June 2018 Publication History

Abstract

This paper explores some of the challenges posed by automated grading of programming assignments in a STEAM (Science, Technology, Engineering, Art, and Math) based curriculum, as well as how these challenges are addressed in the automatic grading processes used in EarSketch, a music-based educational programming environment developed at Georgia Tech. This work-in-progress paper reviews common strategies for grading programming assignments at scale and discusses how they are combined in EarSketch to evaluate open ended STEAM-focused assignments.

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Cited By

Adkins KJoyner DJoyner DKim MWang XXia M(2024)Newly Created Assignments and The First Repository Effect on Inter-Semester PlagiarismProceedings of the Eleventh ACM Conference on Learning @ Scale10.1145/3657604.3662043(211-220)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3657604.3662043
Messer MBrown NKölling MShi M(2024)Automated Grading and Feedback Tools for Programming Education: A Systematic ReviewACM Transactions on Computing Education10.1145/363651524:1(1-43)Online publication date: 19-Feb-2024
https://dl.acm.org/doi/10.1145/3636515
Ding SSmith JGarrett SMagerko B(2024)Redesigning EarSketch for Inclusive CS Education: A Participatory Design ApproachProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3659383(720-724)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3659383
Show More Cited By

Grading at scale in earsketch
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs

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Information & Contributors

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cover image ACM Other conferences

L@S '18: Proceedings of the Fifth Annual ACM Conference on Learning at Scale

June 2018

391 pages

ISBN:9781450358866

DOI:10.1145/3231644

Conference Chair:
Rose Luckin
UCL Institute of Education, UK
,
Program Chairs:
Scott Klemmer
University of California at San Diego
,
Kenneth Koedinger
Carnegie Mellon University

Copyright © 2018 ACM.

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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New York, NY, United States

Publication History

Published: 26 June 2018

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National Science Foundation

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L@S '18

L@S '18: Fifth (2018) ACM Conference on Learning @ Scale

June 26 - 28, 2018

London, United Kingdom

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L@S '18 Paper Acceptance Rate 24 of 58 submissions, 41%;

Overall Acceptance Rate 117 of 440 submissions, 27%

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Cited By

Adkins KJoyner DJoyner DKim MWang XXia M(2024)Newly Created Assignments and The First Repository Effect on Inter-Semester PlagiarismProceedings of the Eleventh ACM Conference on Learning @ Scale10.1145/3657604.3662043(211-220)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3657604.3662043
Messer MBrown NKölling MShi M(2024)Automated Grading and Feedback Tools for Programming Education: A Systematic ReviewACM Transactions on Computing Education10.1145/363651524:1(1-43)Online publication date: 19-Feb-2024
https://dl.acm.org/doi/10.1145/3636515
Ding SSmith JGarrett SMagerko B(2024)Redesigning EarSketch for Inclusive CS Education: A Participatory Design ApproachProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3659383(720-724)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3659383
Joyner DRusch ADuncan AWojcik JPopescu DSpikol DViberg OMartínez-Monés AGuo P(2023)Teaching at Scale and Back Again: The Impact of Instructors' Participation in At-Scale Education Initiatives on Traditional InstructionProceedings of the Tenth ACM Conference on Learning @ Scale10.1145/3573051.3593389(144-155)Online publication date: 20-Jul-2023
https://dl.acm.org/doi/10.1145/3573051.3593389
Blanchard JHott JBerry VCarroll REdmison BGlassey RKarnalim OPlancher BRussell SQuille KAlshaigy BBecker BQuille KLaakso M(2022)Stop Reinventing the Wheel! Promoting Community Software in Computing EducationProceedings of the 2022 Working Group Reports on Innovation and Technology in Computer Science Education10.1145/3571785.3574129(261-292)Online publication date: 27-Dec-2022
https://dl.acm.org/doi/10.1145/3571785.3574129
Tharmaseelan JManathunga KReyal SKasthurirathna DThurairasa T(2021)Revisit of Automated Marking Techniques for Programming Assignments2021 IEEE Global Engineering Education Conference (EDUCON)10.1109/EDUCON46332.2021.9453889(650-657)Online publication date: 21-Apr-2021
https://doi.org/10.1109/EDUCON46332.2021.9453889
Shimmei MMatsuda N(2019)Evidence-Based Recommendation for Content Improvement Using Reinforcement LearningArtificial Intelligence in Education10.1007/978-3-030-23207-8_68(369-373)Online publication date: 21-Jun-2019
https://doi.org/10.1007/978-3-030-23207-8_68

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