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Generative AI tools create new content based on what they learn from their database(s). To make use of these tools, understanding how they work can improve how you and your students use them, or prompt them. We’ll explain ChatGPT as an example, below.

Though sometimes used interchangeably, ChatGPT and GPT are actually different pieces of technology. Built by the same research company, Open AI, the interactive chatbot app we know and use is ChatGPT. This chat platform is powered by GPT, a Large Language Model. Large Language Model (or LLM) refers to the technology that drives Natural Language Processing chatbots like ChatGPT, Bard, and Bing. LLMs “are trained on massive amounts of information scraped from the internet” and are designed to predict words based on likelihood, and cannot necessarily distinguish true information from predicted word sequences (Reidl 2023).

LLMs often “hallucinate” or offer information that isn’t true, nor can it be cited (Weise and Metz, 2023). But GPT models are continuously being improved. For example, while the industry standard is still GPT-3, newer versions such as GPT-4 will continue to be developed (Alston 2023).

Yes/no flow chart beginning with "Does it matter if the outpput is true?"

Flowchart adapted from the original created by: Aleksandr Tiulkanov (January 2023) in ChatGPTand Artificial Intelligence in Higher Education: Quick Start Guide. UNESCO.

Despite the tendency to hallucinate, text-based AI tools can still be extremely useful, if they’re prompted appropriately. “Prompting” in the context of AI refers to the specific language entered into a chatbot platform like ChatGPT. Also called “prompt engineering,” teaching students to skillfully craft input into an AI tool can help them learn how to ask useful questions of AI. (To explore more on prompt engineering, see Alby 2023, Chen 2023, Huang 2023, Riedl 2023, Saravia 2023, and Weise and Metz 2023.)

Below, we include a list of AI tools grouped by which learning activity you’d like your students to do; each of which have unique prompting specificities.

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AI tool by activity

Platform/application summaries

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CNDLS resources


Presentations and events

A.I. workshop series

What We’re Learning About Learning podcast episodes

Contact CNDLS for a consultation on working with AI in your classroom.

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Resources by discipline

How might generative AI impact teaching and learning in your discipline, in particular? Browse the list of resources below, which capture discipline-specific approaches to addressing the use of AI tools in the classroom.

Note the following research tools can be used across disciplines:


Second language learning


Science, Technology, Engineering, and Math (STEM)

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Alston, E. (2023) ”ChatGPT vs. GPT-3 and GPT-4: What’s the difference?Zapier.

Chen, Brian X. (May 2023). “Get the Best from ChatGPT with these golden prompts.” New York Times.

Huang, P. (June 2023). ChatGPT Cheat Sheet. The Neuron.

Riedl, A. (2023). A Very Gentle Introduction to Large Language Models without the Hype. Medium.

Saravia, E. (2022). Prompt Engineering Guide. Democratizing Artificial Intelligence Research, Education, and Technologies.

Weise, K. and Metz C. (2023). When A.I. Chatbots Hallucinate. The New York Times.

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