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Generative AI is a type of online tool that can produce unique text, images, audio, video, code and so on on request, and probably the most famous of which is ChatGPT.
Your requests are called prompts and depending on the tool, can be broad or quite specific. Some tools will also allow the results to be refined based on subsequent prompts. When given a prompt, the tool will use a complex algorithm and lots of statistics to produce something that most closely reflects what is being requested. These tools drawn so-called training data as the basis of their algorithms, often included in large parts of the web, and This is why they are called large language models. While while they’re seen as a threat within he particularly to assessment practises, it’s actually a bigger opportunity.
Traditional assessment practises will need to adapt to a world where students can instantly generate work that appears plausible on the surface, but generative AI can be integrated into assessments to make them more creative and better reflect the new AI advanced working practises that students will encounter after graduation. Many students may say generative AI as a useful time saver at best and as an easy way to cheat at worst.
Addressing this elephant in the room directly is a good way to get them to move beyond this thinking and towards productive use of generative AI. You might run an exercise where you generate some materials in front of the students, then collectively critique and correct it. This will show the students that you are aware of the tools and that they don’t really know anything and are just making things up. As they go through this process, the students will see that while generative AI may be a useful way to start a piece of work, there is a large amount of effort still required to turn it into something accurate and worthwhile, and it may be easier to start from scratch in the 1st place.
Once your students have moved beyond thinking that AI can do their assessments for them, you’ll be able to get them to explore it more creative and acceptable uses. For example, students might find that they are writing reports and presentations and need some images purely for visual interest rather than being important to the content. Rather than spending hours trying to find appropriate images that they can reuse, they could quickly generate some instead.
Likewise, when creating a video, they might use a generative AI tool to produce unique background music rather than using something commercial or one from a limited library of copyright free and overused tracks. Depending on your subject, there may be specific ways that generative AI could be used to assist students in their learning and production activities. For example, there are tools that can produce and check computer code once it can generate realistic voiceovers from text. Others that can create talking heads style presentation videos. Knowing what tools are available, their strengths and limitations, and how to ethically or legally use them is likely to become a useful employability skill, and also one that will benefit students as part of their studies.
