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Warming up to AI

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Here we offer some playful entry points into the topic of generative AI in education. This module serves as a warm-up to further engagement with this topic and the modules in this guide.

Key points from the previous module

Introduction to AI Teaching Guide

  • We developed this guide for primary instructors and teaching teams.
  • The modules are flexible and can be completed in any order.
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Outcomes for this module

It is normal and natural to feel a wide range of emotions in response to the potentially disruptive nature of generative AI tools in relation to teaching and learning. No matter how you are feeling, we hope that this module can move you toward acceptance and curiosity about new possibilities, increasing your motivation to continue engaging with the modules in this guide.

This module is designed to help you:

  • Reflect on your emotional state with regard to AI in education.
  • Describe how a growth mindset, community, and well-being can support you in engaging with AI.
  • Use humor and play to foster feelings of acceptance, curiosity, and motivation regarding generative AI tools.

Diverse emotional responses to AI

Generative AI, a relatively new technology, has quickly gained attention in higher education. Teachers and students hold diverse perspectives on the meaning and future of AI tools for our society, including diverse emotional responses. People have valid reasons for this range of feelings. We hope this module helps you to reflect on your feelings and what underlies them as part of preparing to learn more about AI tools and their relationship to teaching and learning.

Begin by considering how you feel about the future of AI in education and why, then respond to the poll below.

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Strategies for adapting to an AI world

In the current landscape of technology and higher education, change can be unpredictable. We expect that AI-generated language technologies will increasingly become a part of our everyday lives and will continue to develop new capacities. We choose to accept these new technologies and thoughtfully engage with them. Whatever the challenges and stressors, three key strategies can serve us well: cultivating growth mindsets, building communities, and valuing well-being.

A growth mindset means that you believe in your ability to learn new things, grow, and become a better educator or learner at any point in your lifetime (Yeager & Dweck, 2020). Even a complex institution like ours can adapt and learn to navigate new technological landscapes. We encourage you to approach these modules with the mindset of a new learner.

We note the value of connecting with a community of other learners (Slavin, 1996). It is impossible for one person to have the time, energy, and capacity to navigate the complexities of teaching and learning with a rapidly evolving technology like AI. We should rely on each other's expertise and avoid working in isolation. By sharing ideas and supporting one another, we can all do better. We encourage you to connect with colleagues and to seek support when engaging with these modules.

Mental and physical well-being provides the foundation for any work you do (Duckworth, Quinn, & Seligman, 2009). We define the pursuit of education as a fundamental good, but we know that life consists of more than just the work we do. Know that we can rarely come to terms with big opportunities and challenges like this one quickly. We encourage you to be mindful of your well-being as you go through these modules. Pace yourself, make space for curiosity and joy, and take care of yourself as you need it.

Humorous perspectives on AI

Humor can be an effective way to enhance learning. When approaching a new and possibly challenging topic, a bit of levity can help to increase motivation and reduce anxiety (Banas et al., 2011). We don't know what the future of AI holds for higher education, but we hope that you can find some fun and joy on this journey, wherever it may take you.

The satirical news website, The Onion, offers this slideshow titled "Timeline of Artificial Intelligence" which gives a humorous take on some historical milestones in the development of AI.

The image "Chihuahua or muffin?" by Karen Zack was reinterpreted as an insightful jab at machine learning in the meme "How to confuse machine learning".

A meme titled "How to confuse machine learning" showing a grid of photos of blueberry muffins and chihuahua faces that look very similar.
Nesher86. (2021, May 14). How to confuse “Machine Learning” 🤯 [Reddit Post]. R/ProgrammerHumor.


AI chatbots as toys

Even at this early stage, we can probably agree that AI chatbots have many potential applications. Perhaps you see them as writing machines, productivity boosters, or something out of science fiction! We suggest approaching an AI chatbot as firstly a toy. Consider some ways you might play and have fun with AI chatbots. In the next modules, we will ask you to practice using an AI chatbot, so why not ask a chatbot to help you with one of these fun activities? 

  • Create a recipe for a new fusion dish.
  • Brainstorm ideas for a vacation to a fantastical world.
  • Write a silly song or poem.
  • Plan a themed surprise party for a special guest of honor.
  • Play a guessing game about animals, movie stars, or other topic.
  • Provide song recommendations based on your creative descriptions.

Assess and reinforce your learning

We offer this activity for you to self-assess and reflect on what you learned in this module.

Stanford affiliates

  • Go to the Stanford-only version of this activity
  • Use your Stanford-provided Google account to respond.
  • You have the option of receiving an email summary of your responses
  • After submitting your responses, you will have the option to view the anonymized responses of other Stanford community members by clicking Show previous responses.

Non-Stanford users

  • Complete the activity embedded below.
  • You have the option of receiving an email summary of your responses.
  • Your responses will only be seen by the creators of these modules.
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Works cited

Banas J., Dunbar, N., Rodriguez, D., & Liu, S. (2011). A Review of Humor in Educational Settings: Four Decades of Research, Communication Education, 60:1, 115-144, DOI: 10.1080/03634523.2010.496867

CHIHUAHUA OR MUFFIN SERIES. (n.d.). Karen Zack 📠 Creative™. Retrieved April 8, 2024, from 

Duckworth, A. L., Quinn, P. D., & Seligman, M. E. P. (2009). Positive predictors of teacher effectiveness. The Journal of Positive Psychology, 4(6), 540-547. 

Hessel, J., Marasovic, A., Hwang, J. D., Lee, L., Da, J., Zellers, R., Mankoff, R., & Choi, Y. (2023). Do Androids Laugh at Electric Sheep? Humor “Understanding” Benchmarks from The New Yorker Caption Contest. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 688–714.

Nesher86. (2021, May 14). How to confuse “Machine Learning” 🤯 [Reddit Post]. R/ProgrammerHumor.

Pandya, H. (2023, March 3). 6 Stand-ups Analyze ChatGPT’s Attempts to Steal Their Jobs. Vulture.

Slavin, R. E. (1996). Research on Cooperative Learning and Achievement: What We Know, What We Need to Know. Contemporary Educational Psychology, 21(1), 43-69.

Timeline Of Artificial Intelligence. (2023, July 13). The Onion.

Yeager, D. S., & Dweck, C. S. (2020). What can be learned from growth mindset controversies? American Psychologist, 75(9), 1269–1284.

Preview of the next module

Defining and accessing generative AI tools

An introductory explanation of generative AI tools including key concepts and terms.

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Learning together with others can deepen the learning experience. We encourage you to organize your colleagues to complete these modules together or facilitate a workshop using our Do-it-yourself Workshop Kits on AI in education. Consider how you might adapt, remix, or enhance these resources for your needs. 

If you have any questions, contact us at This guide is licensed under Creative Commons BY-NC-SA 4.0 (attribution, non-commercial, share-alike) and should be attributed to Stanford Teaching Commons.