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• W2407508737 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." @default.
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• W2407508737 date "2015-06-03" @default.
• W2407508737 modified "2023-09-26" @default.
• W2407508737 title "Determining the Propensity for Academic Dishonesty Using Decision Tree Analysis" @default.
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• W2407508737 doi "https://doi.org/10.1080/10508422.2015.1051661" @default.
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