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Determining the Propensity for Academic Dishonesty Using Decision Tree Analysis.

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Title: Determining the Propensity for Academic Dishonesty Using Decision Tree Analysis.
Authors: Wray, Barry A. (AUTHOR), Jones, Adam T. (AUTHOR), Schuhmann, Peter W. (AUTHOR), Burrus, Robert T. (AUTHOR)
Source: Ethics & Behavior. 2016, Vol. 26 Issue 6, p470-487. 18p. 1 Diagram, 13 Charts.
Subjects: Business, Student cheating, Deception, Decision trees, Statistics, Data analysis, Codes of ethics, Undergraduates, Data analysis software, Descriptive statistics
Abstract: This article investigates the propensity for academic dishonesty by university students using the partitioning method of decision tree analysis. A set of prediction rules are presented, and conclusions are drawn. To provide context for the decision tree approach, the partition process is compared with results of more traditional probit regression models. Results of the decision tree analysis complement the probit models in terms of predictive accuracy and confirm results previously found in the literature. In particular, students' moral character--whether they believe cheating is acceptable--is found to be the most important factor in determining the propensity for academic dishonesty. [ABSTRACT FROM AUTHOR]
Copyright of Ethics & Behavior is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. 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.)
Database: Psychology and Behavioral Sciences Collection
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PubType: Academic Journal
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  Data: Determining the Propensity for Academic Dishonesty Using Decision Tree Analysis.
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  Data: <searchLink fieldCode="AR" term="%22Wray%2C+Barry+A%2E%22">Wray, Barry A.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jones%2C+Adam+T%2E%22">Jones, Adam T.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schuhmann%2C+Peter+W%2E%22">Schuhmann, Peter W.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Burrus%2C+Robert+T%2E%22">Burrus, Robert T.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Ethics+%26+Behavior%22">Ethics & Behavior</searchLink>. 2016, Vol. 26 Issue 6, p470-487. 18p. 1 Diagram, 13 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Business%22">Business</searchLink><br /><searchLink fieldCode="DE" term="%22Student+cheating%22">Student cheating</searchLink><br /><searchLink fieldCode="DE" term="%22Deception%22">Deception</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+trees%22">Decision trees</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Codes+of+ethics%22">Codes of ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduates%22">Undergraduates</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink>
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  Data: This article investigates the propensity for academic dishonesty by university students using the partitioning method of decision tree analysis. A set of prediction rules are presented, and conclusions are drawn. To provide context for the decision tree approach, the partition process is compared with results of more traditional probit regression models. Results of the decision tree analysis complement the probit models in terms of predictive accuracy and confirm results previously found in the literature. In particular, students' moral character--whether they believe cheating is acceptable--is found to be the most important factor in determining the propensity for academic dishonesty. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Ethics & Behavior is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=117900806
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        Value: 10.1080/10508422.2015.1051661
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