Michael Jones, Lecturer in Writing and Communications at Nazarbayev University, Kazakhstan, reflects on how his research into students’ navigation of the ethics of AI in academic writing has informed his teaching practice.
Artificial Intelligence (AI) has moved from being a distant technological prospect and has permeated through higher education, reshaping the way that students engage with writing, researching and communicating. Whilst AI has the potential to democratise access to knowledge in ways that have never been seen, it has also brought into focus the way that institutes look at plagiarism and authorship, questioning the very foundation of assessment. These tensions are central to research that I recently conducted at Nazarbayev University in Kazakhstan, where I explore how students are navigating the ethics of AI in academic writing.
Kazakhstan has a rapidly developing higher education sector which offers a unique lens into global debates surrounding AI. Nazarbayev University, where I teach, is an English medium university which is situated in a multilingual environment with international faculty and students. The position I am in, someone from the Global North who is working and researching in the Global South in a liberal arts style university, creates a unique site to explore how ideas of integrity and identity intersect.
How students are actually using AI
The attitudes students have towards AI vary significantly, from seeing it as a shortcut with little regard for academic integrity, to cautious use for fear of accusations of plagiarism. What happens in Kazakhstan reflects broader issues in international higher education where trust, integrity and cultural context all matter.
Drawing on a survey conducted with students from the writing centre, along with a series of semi-structured interviews, the findings so far highlight the diversity and complexity in student practices. Whilst some are using it for drafting or outlining parts of their work, or as grammatical support, others present more problematic uses.
Telegram groups seemed to have popped up with students sharing detection-avoidance strategies and humaniser software in a kind of underground network which normalises the practice of academic dishonesty. Some students phrase this as a type of innovation while others think that it is outright cheating. Whilst I know this might sound all doom and gloom, it does not have to be. These findings underscore the need for the education of students by faculty on AI use, not prohibition.
From policing to literacy
This means that teachers will have to take on a role which focuses less on policing AI and more on equipping students with the critical literacy skills to use these tools wisely. This philosophy underpins the framework for my new course, AI and Multimodal Communication, giving students hands-on experience of using AI tools. We learn that prompting should now be seen as a skill, similar to how we view synthesis or paragraph structure. How a question is phrased and the language that is used, shapes the answer that the AI responds with, and in turn shapes the knowledge that is accessed by the student.
Unpacking bias by examining how often outputs reflect Western or English-language dominant perspectives can encourage students to question whose knowledge is being privileged and at what expense. Through these approaches, students will begin to view AI not as a finished product that they can hand in, but as just another tool in their arsenal when learning and discovering.
However, ethics is something that cannot remain abstract, it must also be practiced. In my writing class, I have designed an activity which encourages students to critically reflect on what responsible use of AI should look like. Students are broken into groups and given two texts, one AI and one a student created from a previous semester. Their task is to go through the text and identify which one is which and why. By engaging with AI directly, it gives students the opportunity to see the capabilities and pitfalls of AI whilst creating their own sense of what is appropriate. Rather than simply abiding by institutional rules governing the use of AI, students can make their own ethical judgement that can be transferred beyond the classroom.
Building an institutional culture of innovation
Embedding AI into higher education is no small feat. This issue sits at the intersection of institutional caution and rapid technological change. Universities which rely on plagiarism detection rather than investing in AI literacy create a culture of fear surrounding AI at the expense of innovation.
AI is not going anywhere, and it will continue to reshape the way we write, communicate, and even govern the higher education space. The task we face is looking at how we can embed AI into curricula in ways which strengthen learning rather than undermine it.
How are you teaching AI use and what challenges are you encountering?
