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research-article

Cheat-resistant multiple-choice examinations using personalization

Author:

Sathiamoorthy ManoharanAuthors Info & Claims

Volume 130, Issue C

Pages 139 - 151

https://doi.org/10.1016/j.compedu.2018.11.007

Published: 01 March 2019 Publication History

Abstract

Multiple-choice examinations offer the ability to grade quickly as well as being able to assess concepts and understanding in a wide range of subjects. Consequently, many large classes use multiple-choice examinations. One problem, however, is that multiple-choice examinations are more prone to cheating than constructed-response style examinations. Multiple-choice examinations offer limited answer options, and these limited options can lead to sharing answers through collusion or gleaning answers from unwitting peers. To counter such cheating, this paper investigates a personalization approach to examinations whereby every student gets their own version of the examination that is different to the rest of their peers. Such personalization approach not only counters cheating, but also encourages students to focus on concepts rather than just answers. A software framework that facilitates generating personalized examination papers is developed, and the paper reports on the experience of using the approach in large classes. It discusses the administrative, technical, and pedagogical challenges posed by personalization and how these challenges might be overcome using the framework as well as accompanying processes. Surveys indicate that both students and staff are positive about using such a system.

Highlights

•

While multiple-choice examinations offer the scalability in large classes, they are also prone to cheating.

•

Students have been found to share answers to multiple-choice questions during examinations.

•

Cheating in multiple-choice examinations can be mitigated by personalizing questions and answer options.

•

A macro-based approach to personalization offers flexible and powerful ways to create individualized questions.

•

Personalization not only counters cheating, but also encourages students to focus on concepts rather than mere answers.

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Cited By

Stevens SPalocsay SNovoa L(2023)Practical Guidance for Writing Multiple-Choice Test Questions in Introductory Analytics CoursesINFORMS Transactions on Education10.1287/ited.2022.027424:1(51-69)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1287/ited.2022.0274
Cleophas CHönnige CMeisel FMeyer P(2023)Who’s Cheating? Mining Patterns of Collusion from Text and Events in Online ExamsINFORMS Transactions on Education10.1287/ited.2021.026023:2(84-94)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1287/ited.2021.0260
Noorbehbahani FMohammadi AAminazadeh M(2022)A systematic review of research on cheating in online exams from 2010 to 2021Education and Information Technologies10.1007/s10639-022-10927-727:6(8413-8460)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s10639-022-10927-7
Show More Cited By

Index Terms

Cheat-resistant multiple-choice examinations using personalization
1. Applied computing
  1. Education
2. Social and professional topics
  1. Professional topics
    1. Computing education

Index terms have been assigned to the content through auto-classification.

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cover image Computers & Education

Computers & Education Volume 130, Issue C

Mar 2019

191 pages

ISSN:0360-1315

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Elsevier Ltd.

Publisher

Elsevier Science Ltd.

United Kingdom

Publication History

Published: 01 March 2019

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Cited By

Stevens SPalocsay SNovoa L(2023)Practical Guidance for Writing Multiple-Choice Test Questions in Introductory Analytics CoursesINFORMS Transactions on Education10.1287/ited.2022.027424:1(51-69)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1287/ited.2022.0274
Cleophas CHönnige CMeisel FMeyer P(2023)Who’s Cheating? Mining Patterns of Collusion from Text and Events in Online ExamsINFORMS Transactions on Education10.1287/ited.2021.026023:2(84-94)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1287/ited.2021.0260
Noorbehbahani FMohammadi AAminazadeh M(2022)A systematic review of research on cheating in online exams from 2010 to 2021Education and Information Technologies10.1007/s10639-022-10927-727:6(8413-8460)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s10639-022-10927-7
Fatawi IDegeng ISetyosari PUlfa SHirashima T(2020)Effect of Online-Based Concept Map on Student Engagement and Learning OutcomeInternational Journal of Distance Education Technologies10.4018/IJDET.202007010318:3(42-56)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.4018/IJDET.2020070103

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