research-article

How much randomization is needed to deter collaborative cheating on asynchronous exams?

Authors:

Craig ZillesAuthors Info & Claims

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

Article No.: 62, Pages 1 - 10

https://doi.org/10.1145/3231644.3231664

Published: 26 June 2018 Publication History

Abstract

This paper investigates randomization on asynchronous exams as a defense against collaborative cheating. Asynchronous exams are those for which students take the exam at different times, potentially across a multi-day exam period. Collaborative cheating occurs when one student (the information producer) takes the exam early and passes information about the exam to other students (the information consumers) that are taking the exam later. Using a dataset of computerized exam and homework problems in a single course with 425 students, we identified 5.5% of students (on average) as information consumers by their disproportionate studying of problems that were on the exam. These information consumers ("cheaters") had a significant advantage (13 percentage points on average) when every student was given the same exam problem (even when the parameters are randomized for each student), but that advantage dropped to almost negligible levels (2--3 percentage points) when students were given a random problem from a pool of two or four problems. We conclude that randomization with pools of four (or even three) problems, which also contain randomized parameters, is an effective mitigation for collaborative cheating. Our analysis suggests that this mitigation is in part explained by cheating students having less complete information about larger pools.

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Cited By

Chen BLewis CWest MZilles CJoyner DKim MWang XXia M(2024)Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS CourseProceedings of the Eleventh ACM Conference on Learning @ Scale10.1145/3657604.3662046(75-85)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3657604.3662046
Mahinpei RXu IWolfman SMoosvi FStephenson BStone JBattestilli LRebelsky SShoop L(2024)A Generalized Framework for Describing Question RandomizationProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3635599(1736-1737)Online publication date: 14-Mar-2024
https://dl.acm.org/doi/10.1145/3626253.3635599
Gulati RWest MZilles CSilva MStephenson BStone JBattestilli LRebelsky SShoop L(2024)Comparing the Security of Three Proctoring Regimens for Bring-Your-Own-Device ExamsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630809(429-435)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630809
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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 ACM 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

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Published: 26 June 2018

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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

Chen BLewis CWest MZilles CJoyner DKim MWang XXia M(2024)Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS CourseProceedings of the Eleventh ACM Conference on Learning @ Scale10.1145/3657604.3662046(75-85)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3657604.3662046
Mahinpei RXu IWolfman SMoosvi FStephenson BStone JBattestilli LRebelsky SShoop L(2024)A Generalized Framework for Describing Question RandomizationProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3635599(1736-1737)Online publication date: 14-Mar-2024
https://dl.acm.org/doi/10.1145/3626253.3635599
Gulati RWest MZilles CSilva MStephenson BStone JBattestilli LRebelsky SShoop L(2024)Comparing the Security of Three Proctoring Regimens for Bring-Your-Own-Device ExamsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630809(429-435)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630809
Cordova J(2023)The Generation of a Large Bank of Randomized Questions in a Discrete Structures CourseJournal of Computing Sciences in Colleges10.5555/3636971.363697239:2(10-18)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.5555/3636971.3636972
Wortzman BStephens-Martinez KMinnes MOla OBlank ADoyle MStephenson BDorn BSoh LBattestilli L(2023)Who's Cheating WhomProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 210.1145/3545947.3569609(1210-1211)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1145/3545947.3569609
Hickman HMcKeown PBell T(2023)Beyond Question Shuffling: Randomization Techniques in Programming Assessment2023 IEEE Frontiers in Education Conference (FIE)10.1109/FIE58773.2023.10342976(1-9)Online publication date: 18-Oct-2023
https://doi.org/10.1109/FIE58773.2023.10342976
Goolsby-Cole CBass SStanwyck LLeupen SCarpenter THodges L(2023)Issues of Question Equivalence in Online Exam PoolsJournal of College Science Teaching10.1080/0047231X.2023.1229062952:4(3-5)Online publication date: 30-Aug-2023
https://doi.org/10.1080/0047231X.2023.12290629
Railing BMerkle LDoyle MSheard JSoh LDorn B(2022)Exam TimeProceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 210.1145/3478432.3499123(1138-1138)Online publication date: 3-Mar-2022
https://dl.acm.org/doi/10.1145/3478432.3499123
Fowler MSmith DEmeka CWest MZilles CMerkle LDoyle MSheard JSoh LDorn B(2022)Are We Fair?Proceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499388(647-653)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499388
McMahon CYao BYokota JGarcia DMerkle LDoyle MSheard JSoh LDorn B(2022)Lessons Learned from Asynchronous Online Assessment Formats in CS0 and CS3Proceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 110.1145/3478431.3499386(640-646)Online publication date: 22-Feb-2022
https://dl.acm.org/doi/10.1145/3478431.3499386
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