Manuscript with arrow icon Book and magnifying glass icon Cross-check icon Process checklist icon Reputation ribbon icon Graduation cap icon Question speech bubble icon Headset call icon Mobile phone call icon Login arrow icon B+ Paper Icon Feedback Speech Bubble Icon Similarity Check Icon Professional Development Icon Admin Training Icon Instructor Training Icon Student Training Icon Integrations Icon System Status Icon System Requirements Icon Menu Icon Checkmark Icon Download Icon Rubric Icon Prompt Icon QuickMark Set Icon Lesson Plan Icon Success Story Icon Infographic Icon White Paper Icon White Paper Icon Press Release Icon News Story Icon Event Icon Webcast Icon Video Icon Envelope Icon Plaque Icon Lightbulb Icon Training Icon Search Icon Turnitin Logo (Text and Icon) Icon Facebook Icon Twitter Icon LinkedIn Icon Google Plus Icon Lightbulb Icon Binoculars Icon Drama Masks Icon Magnifying Glass Icon Signal Check Indicator Bars Red Flag Icon Analysis and Organization Icon
Contact Sales

​Three in five University students who engage in contract cheating will be caught by markers using machine learning software, new academic research has found.

The research conducted by Associate Professors Phillip Dawson and Wendy Sutherland-Smith from Deakin University, in collaboration with Principal Product Manager Mark Ricksen from academic integrity solutions provider Turnitin, is the first of its kind into the potential promise of machine learning to address the problem of contract cheating.

Contract cheating occurs when students outsource their assessed work to a third-party and submit it under the pretense of being their own work. Contract cheating is problematic and prevalent in Australia, with six percent of University students admitting to having obtained an assignment through a third-party.

The research presents the first quantitative empirical study into the use of either authorship analysis technology or machine learning to improve detection rates of contract cheating. Using an early alpha version of Turnitin’s new Authorship tool, which evaluates whether an assignment was written by the same student or not, 24 experienced markers were asked to spot contract cheating in bundles of 20 student assignments, which included 14 legitimate assignments and six purchased from cheating sites.

When markers were paired with a machine learning system and provided with authorship report for an assignment, their accuracy of detecting contract cheating increased significantly, from 48 percent to 59 percent, without a significant increase in false positives (incorrectly flagging contract cheating); in other words, markers were able to accurately identify three out of five cases of contract cheating.

The authorship report generated for markers provides an analysis of the student assignments’ linguistic attributes, such as sentence complexity, sentence length, and other stylometrics, as well as document information such as date created and last modified. The report does not specify whether contract cheating has occurred, but rather provides a recommendation for investigation based on statistical measures.

Phillip Dawson, Associate Director, Centre for Research in Assessment and Digital Learning, at Deakin University said the research demonstrated how machine learning can be an effective component of institutional strategies to address contract cheating.

“When markers were provided with a copy of the authorship report to review evidence and corroborate information, they were able to more accurately determine whether assignments had been authored by the student or if contract cheating had occurred. In addition to potentially improving detection rates, authorship analysis approaches using machine learning also offer benefits in terms of raising awareness about contract cheating and efficiently providing evidence if they wish to take their suspicions further.”

Following this alpha version, Turnitin is in development of a machine learning prediction model to offer a more robust recommendation system that prioritizes papers across a corpus of documents or students in a cohort by level of suspicion of inconsistent behavior. Turnitin believes this will replicate the “gut feeling” a marker experiences when suspicion of authorship of a student’s work occurs.

“Whilst Authorship Investigate was in early stages of development when this study was conducted, we’re pleased to see the value of the tool in the detection process, in bringing together all submissions made by a student and allowing rapid scanning of key points of evidence,” said Mark Ricksen, Principal Product Manager at Turnitin.

“Collaboration with higher education institutions and industry enables us to constantly test and iterate our tool so it can be used in a better, faster and more impactful way by markers to address contract cheating. There’s also potential for the software to speed up the investigation process by highlighting submissions of concern by a student and potentially determining the direction and focus of any investigation.”

This study was published in Assessment & Evaluation in Higher Education on 23 September 2019.

You can access the report here.

About Deakin University:

Established in 1974, Deakin University is one of Australia’s largest universities, with five campuses including an online Cloud Campus. Globally connected with internationally recognized quality research and teaching programs, Deakin ranks 261 in the prestigious Academic Ranking of World Universities (ARWU) putting Deakin in the top 1% of the world’s universities.


About Turnitin

Turnitin is your partner in fostering original thinking and supporting authentic learning. Turnitin solutions promote academic integrity, streamline grading and feedback, and improve outcomes across educational levels and content areas. Turnitin leverages cutting-edge technology to provide tools that prevent plagiarism, deliver formative and summative feedback, surface actionable reporting, and investigate academic misconduct. Growing from one million student paper submissions in 2002 to one billion in 2018, Turnitin serves over 15,000 institutions globally and is headquartered in Oakland, Calif., with international offices in the U.K., Netherlands, Australia, Korea, India, and throughout Latin America. @Turnitin