Generative AI Literacy Course

The Generative AI Literacy Course has been designed to support staff and students at the University of Cambridge in the use of generative artificial intelligence (GenAI) tools such as ChatGPT and Microsoft Copilot in an educational context. Given the diverse approaches to these developing technologies and variety of discipline specific context in which they may be used, the course offers a broad overview of what these tools are and how to use them, as well as how to be a responsible and informed user.

We would like to explore opportunities to expand this content with additional perspectives, insight, and more discipline focused content to provide more suitable context at a departmental, faculty, or college level. If you are interested in contributing to these ideas or discussing how we can work with you on additional content, please email info@blendedlearning.cam.ac.uk.

The course is available to all staff and students at the University of Cambridge and can be access on Moodle via the link below. 

Cambridge GenAI Literacy Course

 

 

Course Overview

The course is broken down into three modules, expand the content below to find out more about each one.

The first module explains the historical context behind these tools prior to their wide and rapid adoption in 2022 and demonstrates how large language models work to process user input (prompts) and provide seemingly intelligent responses. We briefly explore the idea of meaning, how humans interpret and communicate, and how we now communicate with technologies such as ChatGPT.

By the end of the module you will be able to:

  • Define GenAI and explain how it differs from other types of AI.
  • Summarise the history and evolution of GenAI, highlighting key milestones and breakthroughs.
  • Describe the fundamental components of GenAI, and how GenAI models are trained, including the role of machine learning and neural networks.
  • Compare and contrast the processes by, and contexts in, which GenAI creates meaning with human systems of communications.
  • Recognise the dynamic relationship between GenAI software and users, and evaluate the implications for education.

Module two builds upon the fundamentals introduced previously and expands on how you, as a user, may determine when and how to use these tools to support teaching and learning activities. You will be introduced to two simple frameworks; one to support your decision making process when identifying if GenAI is a suitable solution, the other to inform your prompt-writing to get the most out of these technologies whilst mitigating some of the inherent risks in their use.

By the end of this module, you will be able to:

  • Engage with AI tools safely and ethically, developing the necessary skills and competencies to navigate their use in academic settings.
  • Apply effective prompting techniques to optimise interactions with AI tools, ensuring efficient outputs that minimise unnecessary interactions and reduce environmental impact.
  • Explore teaching and learning strategies that leverage AI prompting techniques and tools to enhance education in an informed, ethical, and sustainable manner.
  • Evaluate case studies of AI integration in teaching and learning, with a focus on sustainability and the environmental impact of AI usage.

After exploring how to use GenAI tools, the final module explores further how to use tools such as ChatGPT and Microsoft Copilot responsibly. Information in this module is designed to provide an overview of some of the risks and challenges in using GenAI and inform you in being a responsible user. You will explore issues relating to Data & Privacy, Ethical use, Environmental impact, and review a suite of Policies to develop your own D.E.E.P. understanding of GenAI.

By the end of this module, you will be able to:

  • Outline some common concerns about data use, misuse, bias and poisoning, and the associated considerations for educators and students in the HE sector.
  • Describe the environmental impacts of GenAI and summarise relevant steps to mitigate them for individuals and HE institutitons.
  • Recognise the ethical challenges of GenAI use in HE and outline suitable risk reduction approaches for staff, students, and institutions.
  • Identify common privacy concerns and suitable mitigating actions for GenAI users in HE.
  • Compare approaches to GenAI related policy and guidance across the UK HE sector and at the University of Cambridge.