Contract Cheating in Higher Education: Global Perspectives on Theory, Practice, and Policy

This edited volume the first book devoted to the topic of contract cheating brings together the perspectives of leading scholars presenting novel research. Contract cheating describes the outsourcing of students assessments to third parties such that the assignments or exams students submit are not their own work. While research in this area has grown over the past five years, the phenomenon has been exacerbated by the COVID-19 pandemic. Themes addressed in this book include the definition of contract cheating, its prevalence in higher education, and what motivates students to engage in it. Chapter authors also consider various interventions that can be used to address contract cheatings threat to academic integrity in higher education including: assessment practice, education, detection strategies, policy design, and legal interventions. © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.

Contract Cheat Detection using Biometric Keystroke Dynamics

Contract cheating has become a profound issue in academics with the onset of the COVID-19 pandemic as digitised evaluation has become common practice. This evaluation method opens up for examining students remotely, either by online home exams or longer written assessments done away from the classroom. Contract cheating refers to a problem where the students hire a third party to complete their assignment and submit it for grading as their own. Manually dealing with contract cheating is a cumbersome task and tools for plagiarism detection are not able to detect contract cheaters as students do not use the work of other authors without consent. In this paper, a machine learning based system is designed to specifically detect the cases of contract cheating in academics. The system uses keystroke biometric behaviour where typing style is analysed to discriminate cheaters from genuine students. The experiments are conducted on two datasets where one is existing and another is designed by performing data collection in a university for recording the keystroke features. Two categories of keystroke dynamics, namely duration and latency-based features are studied for designing the various machine learning-based systems for investigating the efficient one. Furthermore, the performance of the systems are evaluated under the setting of zero false accusations in order to avoid genuine students being charged as imposters. © 2022 IEEE.

University students’ understanding of contract cheating: a qualitative case study in Kuwait

Contract cheating, or students outsourcing their assignments to be completed by others, has emerged as a significant threat to academic integrity in higher education institutions around the world. During the COVID-19, when traditional face-to-face instruction became unsustainable, the number of contract cheating students increased dramatically. Through focus group interviews, this study sought the perspectives of 25 students enrolled in first year writing in a private higher education institution in Kuwait during the pandemic in 2020–2021, on their attitudes towards contract cheating. MAXQDA 2020 was used to examine the data. The participants believe that the primary motivations for engaging in contract cheating are mainly the opportunities presented by online learning and the psychological and physical challenges they experienced during online learning. Those who did not cheat had some shared traits, such as a competitive spirit, confidence in their talents, and a strong desire to learn. Additionally, those with high moral values avoided cheating. To combat contract cheating, students believe that teaching and evaluation techniques should be drastically altered and that students should be educated about plagiarism, while institutions should impose tougher sanctions on repeat offenders.

Contract cheating: an increasing challenge for global academic community arising from COVID-19.

Due to COVID-19, universities with limited expertise with the digital environment had to rapidly transition to online teaching and assessment. This transition did not create a new problem but has offered more opportunities for contract cheating and diversified the types of such services. While universities and lecturers were adjusting to the new teaching styles and developing new assessment methods, opportunistic contract cheating providers have been offering $50 COVID-19 discounts and students securing the services of commercial online tutors to take their online exams or to take advantage of real-time assistance from 'pros' while sitting examinations. The article contributes to the discourse on contract cheating by reporting on an investigation of the scope and scale of the growing problems related to academic integrity exacerbated by an urgent transition to online assessments during the COVID-19 pandemic. The dark reality is the illegal services are developing at a faster pace than the systems required to curb them, as demonstrated by the results. The all-penetrating issues indicate systemic failures on a global scale that cannot be addressed by an individual academic or university acting alone. Multi-level solutions including academics, universities and the global community are essential. Future research must focus on developing a model of collaboration to address this problem on several levels, taking into account (1) individual academics, (2) universities, (3) countries and (4) international communities.