Determining the Propensity for Academic Dishonesty Using Decision Tree Analysis. Issue 6 (17th August 2016)
- Record Type:
- Journal Article
- Title:
- Determining the Propensity for Academic Dishonesty Using Decision Tree Analysis. Issue 6 (17th August 2016)
- Main Title:
- Determining the Propensity for Academic Dishonesty Using Decision Tree Analysis
- Authors:
- Wray, Barry A.
Jones, Adam T.
Schuhmann, Peter W.
Burrus, Robert T. - Abstract:
- 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.
- Is Part Of:
- Ethics & behavior. Volume 26:Issue 6(2016)
- Journal:
- Ethics & behavior
- Issue:
- Volume 26:Issue 6(2016)
- Issue Display:
- Volume 26, Issue 6 (2016)
- Year:
- 2016
- Volume:
- 26
- Issue:
- 6
- Issue Sort Value:
- 2016-0026-0006-0000
- Page Start:
- 470
- Page End:
- 487
- Publication Date:
- 2016-08-17
- Subjects:
- academic dishonesty -- decision tree analysis -- probit regression
Ethics -- Periodicals
170.5 - Journal URLs:
- http://www.informaworld.com/smpp/title~db=jour~content=t782890670~tab=issueslist ↗
http://www.tandfonline.com/toc/hebh20/current ↗
http://www.tandfonline.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1080/10508422.2015.1051661 ↗
- Languages:
- English
- ISSNs:
- 1050-8422
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3814.655500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 35.xml