PHOTO
Dubai, UAE: A research team led by Canadian University Dubai (CUD) has identified a new technology-based approach to tackling academic integrity using machine learning techniques. The research is the subject of a recent article, “Machine learning based approach to exam cheating detection”, published in PLOS ONE, a prestigious academic journal ranked 30th worldwide across all disciplines by Google Scholar.
The academic study was initiated as the COVID-19 pandemic forced education institutions around the world to adopt remote teaching and assessment methods. The project was led by Dr. Firuz Kamalov, Associate Professor, Department of Electrical Engineering at CUD, in collaboration with, Dr. Hana Sulieman, Professor, Department of Mathematics and Statistics at American University of Sharjah (AUS), and Dr. David Santandreu Calonge, Associate Professor and Director, Corporate Training, at CUD.
Explaining the rationale behind the study, Dr. Kamalov said, “One of the greatest challenges in online education is preserving the academic integrity of student assessments. The lack of direct supervision by instructors during final examinations poses a significant risk of academic misconduct. We set out to explore new approaches to detecting potential cases of cheating on the final exam, using machine learning techniques.”
The new method uses an algorithm to identify cases of cheating using a post-exam analysis of student grades. The inputs to the algorithm are sequences of grades – from quizzes, midterm exams, and the final exam of an entire class. The method takes account of the grades prior to the final exam, grades on the final exam, and the overall performance of the class, in order to make a judgement.
It is anticipated that the new technique can supplement the work of commercial plagiarism detection software and potentially provide an alternative, non-intrusive deterrent to remotely-invigilated exams. Speaking about the potential impact of the research, Dr. Santandreu Calonge
said, “The insights gained from this study may be of assistance to academics and administrators interested in preserving the academic integrity of course assessments. It also lays the groundwork for future educational research into outlier detection techniques.”
This project adds to the University’s growing body of collaborative research that is supporting the growth and advancement of the UAE knowledge economy. Dr. Kamalov concluded, “Our joint work with AUS shows that the UAE is becoming a hotbed for high-quality research with real-life impact that has the potential to change practices around the world. At CUD, we remain committed to building further relationships in the region that will create more opportunities for students and faculty members to grow and prosper in an environment conducive to creativity and innovation.”
The complete article is freely available online at: https://doi.org/10.1371/journal.pone.0254340
About Canadian University Dubai
Canadian University Dubai, established in 2006, is a higher academic institution located in Dubai, United Arab Emirates (UAE). Ranked in the top 2% of universities worldwide and top 4 in the UAE according to the QS World University Rankings 2022, CUD offers a broad range of academic programs at undergraduate and graduate levels, based on the Canadian curriculum, and serves as a gateway for students to pursue higher education, research, and employment opportunities in Canada.
© Press Release 2021
Disclaimer: The contents of this press release was provided from an external third party provider. This website is not responsible for, and does not control, such external content. This content is provided on an “as is” and “as available” basis and has not been edited in any way. Neither this website nor our affiliates guarantee the accuracy of or endorse the views or opinions expressed in this press release.
The press release is provided for informational purposes only. The content does not provide tax, legal or investment advice or opinion regarding the suitability, value or profitability of any particular security, portfolio or investment strategy. Neither this website nor our affiliates shall be liable for any errors or inaccuracies in the content, or for any actions taken by you in reliance thereon. You expressly agree that your use of the information within this article is at your sole risk.
To the fullest extent permitted by applicable law, this website, its parent company, its subsidiaries, its affiliates and the respective shareholders, directors, officers, employees, agents, advertisers, content providers and licensors will not be liable (jointly or severally) to you for any direct, indirect, consequential, special, incidental, punitive or exemplary damages, including without limitation, lost profits, lost savings and lost revenues, whether in negligence, tort, contract or any other theory of liability, even if the parties have been advised of the possibility or could have foreseen any such damages.
