Subject: Academic dishonesty, Contract cheating, Crowdsourcing, Social media, Versatile chatbots
Year: 2023
Type: Proceedings
Title: Evolution of academic dishonesty in computer science courses
Author: Zdravkova, Katerina
Abstract: Online exams and assignments during the COVID-19 pandemic have introduced new forms of student cheating. In order to maintain evaluation criteria and preserve established ethical standards, professors have introduced new methods to minimize cheating. When returning onsite, the newly created cheating techniques evolved once again. They were supported by special groups on social networks dedicated to easier liquidation of exams and getting better grades. Crowdsourcing became frequent, particularly for homework assignment preparation. Recently, ChatGPT has become a new ally of students. This paper presents the evolution of student cheating in several computer science courses taught by the author of this paper. All examples of cheating are supplemented by the detecting methods and own applications used to prevent them from occurring again. The paper ends by predicting who will win in the eternal war between students and professors, at least in the short run.
Publisher: Universitat Politecnica de Valencia
Relation: Proceedings of 9th International Conference on Higher Education Advances (HEAd’23)
Identifier: oai:repository.ukim.mk:20.500.12188/26846
Identifier: http://hdl.handle.net/20.500.12188/26846Identifier: http://dx.doi.org/10.4995/HEAd23.2023.16081
