Generative AI for Students: Ethics & Academic Integrity

Overview

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Generative AI for Students: Ethics & Academic Integrity is for university students in all subject areas who want to use generative AI tools responsibly in study, research and academic writing. The course introduces what AI tools can and cannot do, how they may support academic work, and where careful judgement is needed. You will explore issues such as plagiarism, authorship, academic integrity, bias, and data sensitivity, while developing a more critical and reflective approach to AI use. Through practical examples, you will learn how to evaluate AI tools, recognise their limits, and decide when and how they can be used appropriately in a university context. No prior technical knowledge is required, making the course accessible to learners from any discipline. By the end of the course, you will be better prepared to make informed choices about AI, use it in ways that support learning, and maintain good academic practice in your own work.

Syllabus

AI for Students: Using AI Tools in Study and Research

Our first module introduces you to what we mean by AI and GenAI, as well as the concept of digital literacies. We'll cover here the ways in which the tools work and the different categories of tools available. You'll be able to use the information here to boost your confidence in using the various types of AI tools available, as well as being able to discern what the tools do and how they might benefit you in your work, research and study.

AI Capabilities and Human Responsibilites

Our second module expands on the use of AI and GenAI tools. We'll cover here the role of the human and the computer in our tasks when studying and researching for university. We'll also look at the types of tools available in more depth and detail. We'll discuss how and why these work in particular ways, the benefits of using particular types of tools for particular types of work, and the role of AI in your studies. We'll also cover the crucial and important elements of some of the challenges and problems in using AI, including the human and environmental costs, the data biases, and the social issues involved.

Academic Integrity

We've covered now the ways in which you can use AI tools in your studies and research, the types of tools available to you, and some of the wider issues or problems with using AI tools. Below, you'll cover the key elements of academic integrity and good academic practice (including avoiding plagiarism!) when using AI tools. We'll look at the key principles of academic integrity in an AI-powered world, as well as thinking about the rules of research and using data with confidence and confidentiality.