Cheating with ChatGPT and Techniques of Neutralization.

Bibliographic Details
Title: Cheating with ChatGPT and Techniques of Neutralization.
Authors: Hawdon, James1 (AUTHOR), Costello, Matthew2 (AUTHOR) mjcoste@clemson.edu, Reichelmann, Ashley V.1 (AUTHOR)
Source: Deviant Behavior. Jan2025, p1-22. 22p.
Subject Terms: *ARTIFICIAL intelligence, *NEUTRALIZATION theory, *STUDENT cheating, *CHATGPT, *COLLEGE students
Abstract: This paper utilizes neutralization theory to understand cheating with AI-assisted programs among university students. Using data collected from undergraduate students across the United States, we explore how criminological concepts and demographics predict the number of times someone cheated over the past year as well as the likelihood of using AI-assisted tools to cheat. We find agreement with cheating neutralization techniques, general cyber-neutralization techniques, and the presence of deviant peers positively associate with all cheating outcomes, while sense of guilt is inversely associated. Low self-control is positively associated with use of AI-assisted misconduct, but not the number of times students cheated. [ABSTRACT FROM AUTHOR]
Copyright of Deviant Behavior is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Cheating with ChatGPT and Techniques of Neutralization.
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  Data: <searchLink fieldCode="AR" term="%22Hawdon%2C+James%22">Hawdon, James</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Costello%2C+Matthew%22">Costello, Matthew</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> mjcoste@clemson.edu</i><br /><searchLink fieldCode="AR" term="%22Reichelmann%2C+Ashley+V%2E%22">Reichelmann, Ashley V.</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Deviant+Behavior%22">Deviant Behavior</searchLink>. Jan2025, p1-22. 22p.
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  Data: *<searchLink fieldCode="DE" term="%22ARTIFICIAL+intelligence%22">ARTIFICIAL intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22NEUTRALIZATION+theory%22">NEUTRALIZATION theory</searchLink><br />*<searchLink fieldCode="DE" term="%22STUDENT+cheating%22">STUDENT cheating</searchLink><br />*<searchLink fieldCode="DE" term="%22CHATGPT%22">CHATGPT</searchLink><br />*<searchLink fieldCode="DE" term="%22COLLEGE+students%22">COLLEGE students</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper utilizes neutralization theory to understand cheating with AI-assisted programs among university students. Using data collected from undergraduate students across the United States, we explore how criminological concepts and demographics predict the number of times someone cheated over the past year as well as the likelihood of using AI-assisted tools to cheat. We find agreement with cheating neutralization techniques, general cyber-neutralization techniques, and the presence of deviant peers positively associate with all cheating outcomes, while sense of guilt is inversely associated. Low self-control is positively associated with use of AI-assisted misconduct, but not the number of times students cheated. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Deviant Behavior is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1080/01639625.2025.2456067
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: NEUTRALIZATION theory
        Type: general
      – SubjectFull: STUDENT cheating
        Type: general
      – SubjectFull: CHATGPT
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      – SubjectFull: COLLEGE students
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      – TitleFull: Cheating with ChatGPT and Techniques of Neutralization.
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            NameFull: Costello, Matthew
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            – D: 24
              M: 01
              Text: Jan2025
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              Y: 2025
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