ChatGPT has certainly been the topic of conversation in university hallways since it was released. It would be fair to say that a lot of the conversations have had negative undertones - what does ChatGPT mean for assessment and academic integrity, for example. However, ChatGPT and other large language models (like Bing Chat) also offer opportunities for teachers to improve their practice (for example, see this earlier post on assessment). Many teachers have been experimenting with ChatGPT, and developing new approaches, or adapting their existing approaches to take advantage of the opportunities presented by the large language models (LLMs). Personally, I've done a lot of playing with ChatGPT, but haven't really made full use of it. Yet.
Fortunately, the learning curve is being shortened by teachers and academics writing about their experiences. One example is this new working paper by Ethan Mollick and Lilach Mollick (both University of Pennsylvania). They discuss five teaching strategies that can be advanced by using ChatGPT, including:
...helping students understand difficult and abstract concepts through numerous examples; varied explanations and analogies that help students overcome common misconceptions; low-stakes tests that help students retrieve information and assess their knowledge; an assessment of knowledge gaps that gives instructors insight into student learning; and distributed practice that reinforces learning.
Mollick and Mollick helpfully provide prompts for both ChatGPT and Bing Chat that can be used for these purposes. It is clear from their choices of applications that these tools can help when creativity is lacking (new examples, explanations, analogies), saving teachers from having to come up with new applications (also in writing test questions). Distributed practice requires a lot of questions, and having a tool that can simply create new questions is helpful in this respect.
Mollick and Mollick's example prompts will get a teacher a lot of the way towards making the best use of ChatGPT. However, crafting prompts has become an art in itself. Fortunately, other teachers are offering help on this as well. In another new working paper, Tyler Cowen and Alex Tabarrok (both George Mason University, and perhaps best known as the authors of the Marginal Revolution blog) provide a lot of guidance on how to craft prompts that will assist with teaching and learning economics. Their advice is fairly high level, but will probably be more useful as LLMs develop over time. Their advice is sumarised as:
1. Surround your question with lots of detail and specific keywords
2. Make your question sound smart, and ask for intelligence and expertise in the answer
3. Ask for answers in the voice of various experts.
4. Ask for compare and contrast.
5. Have it make lists
6. Keep on asking lots of sequential questions on a particular topic.
7. Ask it to summarize doctrines
8. Ask it to vary the mode of presentation
9. Use it to generate new ideas and hypotheses
In my own use of ChatGPT, I have found making lists to be incredibly useful (and ChatGPT often seems to make lists without specifically being prompted to do so), as well as asking for answers to questions in the voice of various experts.
However, one part of Cowen and Tabbarok's paper caused me some concern (and some colleagues as well, after I shared it). They show ChatGPT solving some calculus problems step-by-step (as we would expect a student to do), including solving a system of demand equations for the perfectly competitive outcome, Cournot outcome, and monopoly outcome. I had though that we were still some time from having LLMs solve maths problems, but these things are moving so fast. LLMs can't draw graphs yet, but this recent post by Bryan Caplan shows that ChatGPT can explain a graphical solution to a problem in words, and do so very well. Yikes! I've been quite bullish about my assessment strategies being robust to LLMs for now, but I may have to reconsider weekly assignments (with many questions involving graphs) in my ECONS102 class.
LLMs offer both challenges and opportunities for teachers. They may prompt us to adopt more authentic assessments, and at the same time provide us with the opportunity to add significant value to students' learning experiences. At least, until the AIs take our jobs completely.
[HT: Marginal Revolution, here and here]
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