Degree Name

Doctor of Philosophy


School of Information Systems and Technology


Most educators strive to develop in their students a certain level of academic integrity that they hope will be carried into the workplace. Academic integrity can benefit higher education, workplaces and the greater society by promoting integrity, scientific progress and responsible citizenship. But, academic dishonesty has been a concern for academics and researchers as long as educational institutions have existed. In the last few decades, the concerns have increased due to an increase in the reporting of cases of cheating in academic settings.

To date, many studies have been carried out that report instances of increasing cheating, some have researched ways to curb academic dishonesty and others have focused on the factors that may have influenced students’ cheating behavior. But all measures currently in practice seem to be reactive, rather than proactive. Trying to assess why a student has cheated may not help understand why a student will be inclined to cheat in the future. There has been limited research into the factors that may influence a student’s likelihood to cheat.

Furthermore, over the past few years, researchers and academics have expressed growing concern over occurrences of academic dishonesty, especially among higher education students, sparked by advances in and the increased use of technology. It is believed that technology including the Internet has given students easy access to resources that can be easily copied and reproduced as their own thus potentially blurring students’ understanding of originality and ownership. This has also given birth to new types of academic dishonesty that can be grouped under a new term coined, e-cheating.

This thesis defines e-cheating, provides a consolidated list of factors that influence students’ likelihood to e-cheat and describes the development of the Khan’s Factor Model intended for use by individuals, researchers and industry to understand the factors that influence students’ likelihood to e-cheat. The research model has been developed by first using Interpretive Structural Modeling and then testing the model using Structural Equation Modeling. Moreover, data analysis and evaluation have validated the Khan’s Factor Model, and have provided insight into the various factors that do influence students’ likelihood to e-cheat, leading to recommendations that can help deter and curb e-cheating among higher education students, ultimately concluding that with ICT-savvy students in classrooms, stakeholders such as universities, teachers and parents need to work towards solutions that are intrinsically motivated in order to enhance overall student integrity.