GenAI’ze your classroom
A guide with practical examples to help lecturers enrich their courses with generative AI
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2024
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Educational Material
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Abstract
With the release of ChatGPT-3 in fall 2022 (OpenAI, 2022), technological developments in the field of artificial intelligence have posed a major challenge for the higher education landscape. Generative AI (GenAI) and the new AI-based tools such as Microsoft Copilot, GitHub Copilot, ChatGPT, Google Gemini, Wolfram Alpha and many more are here to stay. Their emergence and widespread availability are creating benefits and obstacles to teaching activities. As a lecturer you have probably asked yourself: Do I have to do something about GenAI in my course? If you must or want to do something, what can you do?
During our work in the Department of Environmental Systems Science (D-USYS) and the Zurich-Basel Plant Science Center (PSC), it quickly became clear that one of the most important needs of our lecturers was to integrate the training and use of AI-based tools into the subject-specific context of existing courses. The necessary considerations included, for example, the adaptation of course descriptions in the course catalog, the definition of the use of AI in learning, performance and examination tasks, as well as the redesign of teaching materials, exercise descriptions and performance records.
In this best practice collection, we address this uncertainty and have summarized our recommendations and some of our best practice examples. Lecturers are welcome to adapt them to their teaching context! The examples and the course materials were developed for classes at the Bachelor’s and Master’s level at D-USYS of ETH Zürich. The main focus was on testing and implementing GenAI for information management and scientific writing in the classes in a meaningful way.
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ETH Zurich, Department of Environmental Systems Science and Zurich-Basel Plant Science Center
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02222 - Zurich-Basel Plant Science Center / Zurich-Basel Plant Science Center