The Challenges of Maintaining Academic Integrity in the Era of Machine-Generated Learning

Dear Colleagues,

Effective learning and teaching are key research topics in higher education. Quality education is unattainable without respect for academic integrity. Whereas academic integrity refers to respectful and fair behaviours, academic dishonesty refers to offences that include cheating, plagiarism, fabrication, and facilitation. Higher education institutions play a twofold role. First, they grant technical knowledge and professional skills to the new generations and focus on their students’ best possible academic outcomes (i.e., excellent grades). Second, they strengthen students’ values, principles, and moral development. Differently stated, higher education institutions aim to create responsible, honest, and ethically acting citizens, for which the promotion of academic integrity is key. Yet, studies have shown the omnipresence of academic dishonesty as a normalized student behaviour that goes back decades, and that most students engage in academic dishonesty at some point in their studies.

The phenomenon of academic dishonesty represents a severe and extensively researched problem in education and psychology. Previous research in the field of academic integrity and dishonesty have linked it to individual and situational characteristics. Others have found differences in academic integrity between learning environments, which is especially relevant during and post the COVID-19 pandemic. The academic misconduct rate increased with the transition to emergency remote teaching during the pandemic due to both the increased psychological stress and the unique learning characteristics of unplanned online teaching. Emergency remote teaching is most likely to be used again when large-scale emergencies occur, and planned online and hybrid teaching are here to stay. Thus, continuous research on academic integrity in these environments is highly important.

Recent research has also allowed the development of detection tools for academic dishonesty, which have been improved but also challenged with technology’s rapid development. As automated detection tools improve, and decrease academic misconduct rates, students and third-party companies find new ways to bypass detection, raising the need for the continuous exploration of new and improved ways for maintaining academic integrity.

In an era when machine learning and artificial intelligence are becoming more present in everyday life in general and in academic writing specifically, while hybrid and remote teaching are also on the rise, we are to face new challenges yet to be fully uncovered. This Special Issue of Societies aims to explore the dynamic relationship between learning environments, technology, machine learning and academic integrity. We invite researchers to submit empirical and theoretical contributions concerning the maintenance of academic integrity in today’s complex times.

I look forward to receiving your contributions.

Dr. Yovav Eshet
Guest Editor

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