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Can contract cheating be detected by machine learning technology? (Part 1)

Episode #5 (Part 1)

In Part One of this two-part episode, Deakin University's Associate Professors Phillip Dawson and Wendy Sutherland-Smith share their backgrounds, what contract cheating is and the need for research in the use of authorship analysis technology to improve detection rates of contract cheating.

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Can contract cheating be detected by machine learning technology? (Part 2)

In Part Two of this two-part episode, Deakin University's Associate Professors Phillip Dawson and Wendy Sutherland-Smith dives into their findings from their research on the use of either authorship analysis technology to improve detection rates of contract cheating.

A/Prof. Phillip Dawson | Associate Director, Centre for Research in Assessment and Digital Learning, Deakin University

A/Prof. Wendy Sutherland-Smith | Faculty of Health, School of Psychology, Deakin University

In this two-part episode, Deakin University's Associate Professors Phill and Wendy stopped by for a chat about their research on the detection of contract cheating with Turnitin's Authorship Investigate technology. This research presents the first quantitative empirical study into the use of authorship analysis technology and machine learning to improve detection rates of contract cheating.

Part One covers Phill and Wendy's backgrounds, what contract cheating is and why there is a need for such research.

Watch part 2 →

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.