AI in Action: Equipping Professors to Prepare Students for an AI-Driven World

Anna Mills, English

Cerritos College

April 24, 2025

Licensed CC BY NC 4.0

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Welcome! Please share your name and discipline in the chat! What to expect:�

• Why AI Literacy is Important
• Principles for integrating AI to support critical thinking
• Critiquing AI examples of course concepts
• AI literacy lessons if we have time
• Brief Demonstration of how to use a couple of AI tools
• Q&A

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Slides: https://link.annarmills.com/CerritosAI

Feel free to put questions in the chat as we go!

What do our students need from us when it comes to AI?

What does our future with AI look like? It’s hard to distinguish hype from reality, but I think we can be pretty sure professionals will be using it

Hype? �“Artificial intelligence has arrived in the workplace and has the potential to be as transformative as the steam engine was to the 19th-century Industrial Revolution.” 

–McKinsey Digital report, “Superagency in the workplace: Empowering people to unlock AI’s full potential”

January 28, 2025

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Generative AI is starting to be integrated into familiar digital writing environments where it can be used in myriad ways throughout a task.

Google and Microsoft now offer AI text generation and text revision within Google Docs and Word, as does Grammarly

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So what skills do you need to work with generative AI?

• You ask it for what you want.
• Then you question what it gives you. You revise, reject, add, start over, tweak.

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To do this, you need

• critical thinking, reading, and writing skills.
• subject-matter expertise.
• knowledge of what kinds of weaknesses to look out for in AI. Let’s call that critical AI literacy.

Principles for integrating AI to stimulate critical thinking

First, how should we frame AI and specifically generative AI (GenAI)?

• “AI” or “Artificial Intelligence” usually refers to systems that predict outcomes. They’re trained through intensive statistical analysis of patterns in a large amount of data.
• Generative AI or GenAI produces text, images, and videos.
• Large language models (LLMs), a type of GenAI used in chatbots, are trained on text from the internet. They produce new text in response to a user’s request (except once in a while when they produce copied text).

Image by Kathryn Conrad & Rose Willis / Better Images of AI / Extraction Network 1 / CC-BY 4.0

Chatbots: word calculators, statistical predictors, answering “What would the humans say next?”

• You could think of these systems are essentially answering the question “What would the humans say next based on all the text I’ve seen?” over and over.
• There’s a little randomness baked in, so these systems may give different results each time.
• They’re calculating: they don’t think or experience.

Image by Yasmine Boudiaf & LOTI / Better Images of AI / Data Processing / CC-BY 4.0

Given many concerns about generative AI, should we be inviting students to use it?

• Concerns include inaccuracy, bias, privacy, lack of source citation, intellectual property rights, energy and water use, labor conditions, and existential risk.
• I respect the position of other educators who think we shouldn’t, but I do think we should. In short, generative AI is useful, widespread, and growing, so we need to understand how to use it and what it can do and so do our students around it. We should use that literacy as a basis for participating in making AI more ethical. Here’s a slide deck and a fuller discussion.

Students need practice identifying inaccuracy and bias in AI outputs to build the habit. We can’t work well with these systems unless we question them.

Principle 1: Help students build skepticism of highly plausible AI-generated outputs

Let’s look for sweet spots where critical AI literacy and existing learning outcomes can go together.

Principle 2: Choose AI uses that stimulate student thinking and writing to address existing learning goals

We don’t want to teach students to worship AI. Let’s invite them to engage with AI in ways that help them develop a sense of agency and of the value of their voice, ideas, and human judgment.

Principle 3: Help students build confidence and metacognitive awareness

One way to sum this up:

When it comes to learning,�� 👍 Yes to AI for input�� 👎 No to AI for output

One example: Critical reflection on AI examples of course concepts

Generate and critique examples of class concepts and how they apply to students’ real-world concerns. 

• Prompt: “Give an example of the use of regression analysis on data relating to anxiety and screentime.” (sample without sources/sample with sources)
• Prompt: “Give an example related to diet where correlation data is misleading and does not really reflect a causal relationship.”
• Prompt: “Give an example of a patient whose experiences point to the limitations of current DSM diagnostic categories.”

Model skeptical approaches to the AI outputs. (Share template phrases?)

Clarity

This sounds plausible because ______________, but it doesn't really make sense because ______________.

This sounds good, but it doesn't really fit the purpose. What we are looking for is ______________.

Accuracy

This is inaccurate because ______________.

The AI seems to have misinterpreted ______________.*

Variation: Invite students to evaluate the AI reasoning on a problem

In the AI Validation activity, students evaluate competing accounts of how to think about a problem

“Take a challenging problem on the topic your class is working on. It should be a problem where there is either one right answer or where there are answers that are “more right” than others.

Give the problem (and any context you would usually give to students) to an AI tool. Ask it to generate multiple solutions and explain its reasoning.” - Robert Talbert, AI Validation, AI Pedagogy Project

Let’s try it with a platform I want to share with you, Perplexity.ai, a search-chatbot combination, no login needed, Prompt it in one of two ways:

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• “Give an example to illustrate…” and specify a challenging concept you teach.

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• Give it a challenging problem. Tell the chatbot, “Give two different solutions and explain your reasoning.”

A quick tour of Perplexity.ai (a popular search-chatbot combination). Use the diamond dot icon to control whether it uses web sources, academic sources, social media (mostly Reddit), or none of the above.

Please share in the chat how it went!

• How well do the examples illustrate the concept?
• Do you see bias, inaccuracy or unwarranted assumptions?
• If so, would identifying those problems present the right level of challenge for students?
• How do the results with sources and the results without sources compare?

Further explorations with Perplexity

• Try attaching a class handout to your Perplexity search so that the output will be customized to your approach.�
• Make a Perplexity account and use the free credits for their Pro Search. Pro Search asks clarifying questions about your prompt and suggests followup questions.

Ways to use AI examples in class

• Generate live to illustrate a concept being discussed. Ask the class for a theme for the example. Then critique it together. This way you can model AI prompting strategies and troubleshooting.�
• Or choose generated examples ahead of time. Ask students to critique them together in groups or as homework. Consider sharing these template phrases for critiquing AI outputs from my open text How Arguments Work.�
• Assign students to prompt for examples on their own. Ask them to keep modifying the example until they are satisfied it illustrates the concept well.

Demonstrations of a few other AI tools

Prompting requires critical thinking

• Be specific (for example, tell it context, role, tone, style, examples)
• Ask it to ask you questions about what you want
• Get AI to take it step by step
• Push it to do better (iterate)
• Be playful and curious
• See Getting the most out of AI (prompting): Describe what you want and keep trying

Photo by Miguel Á. Padriñán on Pexels.com:

ChatGPT (OpenAI)

• Multimodal: you can upload files including images and ask questions about the image, such as a screenshot
• Browses to help answer

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Claude (Anthropic)

Tour of the interface

Projects

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NotebookLM (Google)

Podcasts and audio overviews

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Remember the warning that “AI makes up sources”? AI systems still make them up, but not as often as a year ago.

• Many AI systems now combine text generation with Internet or database search. This includes ChatGPT Plus, Google’s Gemini, Microsoft Copilot, and Perplexity.
• AI-based apps for academic research assistance include Elicit, SciSpace, scite_, Consensus, ResearchRabbit, Undermind, ConnectedPapers, Keenious, and others.

OpenAI’s DeepResearch

“OpenAI has revealed another new agentic feature for ChatGPT called deep research, which it says can operate autonomously to “plan and execute a multi-step trajectory to find the data it needs, backtracking and reacting to real-time information where necessary.”

Instead of simply generating text, it shows a summary of its process in a sidebar, with citations and a summary showing the process used for reference.”

“ChatGPT’s agent can now do deep research for you,” Richard Lawlor, The Verge, February 2, 2025

OpenAI’s Deep Research asks the user clarifying questions. Any chatbot can be requested to do the same…

For example, in response to a query about faculty professional development around AI, it asked,

• “Are you looking for global perspectives, or should the research focus on a particular region or country?
• Would you like examples of existing faculty development programs, case studies, or institutional policies?”

Gemini (Google)

DeepResearch prompt: “Research linguistic justice pedagogy in higher education.”

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Elicit answers a research question based on academic papers

Instead of searching on “teacher shortages students effects”

And also “educator shortages” and “instructor shortages,” with “impacts”

the student can just ask their question in one way.

Elicit lists papers and summarizes their elements

STORM

STORM

Two ways I hope to assign students to explore STORM skeptically this semester

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1. Invite them to generate a STORM article on their research topic and compare the content and sources to those of a Wikipedia article on the same topic�
2. Ask students to participate in the COSTORM roundtable of different AI expert personas discussing the student’s research topic and reflect on the experience (if COSTORM comes back online in time).

For more, see the Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models (preprint)

Sample custom bots

Writing these isn’t much different from prompting in general, but you might like to see samples before you start.

• My Grammar Explainer Bot prompt
• My Contradictory Chatbot prompt
• Mark Marino’s Coach Tutor
• PlayLab is a nonprofit whose purpose is to allow educators to make custom bots. There’s a waitlist, so if you aren’t able to get into the training, you can start out in the workspace I created for educators. For help getting started, see this asynchronous PlayLab.ai course.

Ask Contradictory Chatbot for Research a question

Go to https://bit.ly/CCforresearch (in the chat)

• Are colds contagious?
• Can cats stay healthy eating only vegetables?
• Does AI detection software ever flag student writing as AI?

Note: Sometimes it doesn’t follow instructions and fails to provide 3 contradictory answers or fails to provide sources.

Preparing Students for Critical Use of AI: �Critical AI Literacy Microlessons

TikTok video on ChatGPT as predictive text (3 minutes, by @mor10webn)

Computers are getting better at writing (7 minutes, from Joss Fong at Vox)

Share a short video that encourages skepticism of AI outputs?�

Share a chat session that suggests ChatGPT isn’t thinking, such as this session where it counts wrong. 

Assign an interactive reading?

Let Us Show You How GPT Works — Using Jane Austen from The New York Times gives readers the choice of seeing rough language model generations in the style of Harry Potter, Star Trek: The Next Generation, Shakespeare, or Moby Dick as well as Jane Austen.

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Sample

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Prompt: Hermione raised her wand.

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The BabyGPT language model’s output: "Professor Dumbledore never mimmed Harry.

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He looked back at the room, but they didn't seem pretend to blame Umbridge in the Ministry. He had taken a human homework, who was glad he had not been in a nightmare bad cloak.”

Model looking at the privacy policy

(Inspired by Autumn Caines’ blog on annotating privacy policies)

Share highlights from the OpenAI Privacy Policy (or another model's policy)

“We may use Personal Information for the following purposes:

• To provide, administer, maintain and/or analyze the Services;
• To improve our Services and conduct research;
• To communicate with you;
• To develop new programs and services…”

Image by GDJ on Pixabay.com

Show a video on AI bias

Show a video that gives an example of racism and sexism compounded by AI

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The Algorithms of Oppression video with Safiya Umoja Noble of USC (4 min) describes how she researched bias in Google search predictions on search terms like “black girls”

In this MIT Media Lab video, a computer recognizes Dr. Joy Buolomwini only after she dons a white mask. Her research pushed corporations to do better.

Invite students to read “How AI reduces the world to stereotypes” by Victoria Turk in restofworld.org

Just because AI can browse the web now doesn’t mean it “understands,” as in this test by Casey Newton shared on Threads (the link goes to The Onion).

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Giving students AI context: Background materials on AI capacities, risks, and ethical concerns you might consider assigning and discussing before activities involving AI

• MLA Student Guide to AI Literacy handout
• My Super Short Slide Orientation to AI for Students
• My extended AI Orientation for Students (comments welcome)
• My Assorted AI assignments, videos, and readings on Canvas Commons

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Pause for questions and comments

For further reflection:

• Does it seem possible to incorporate some AI literacy microlessons into your courses?
• Is this something you think teachers should do or not?
• What are the barriers?
• What more do you want to learn to get started incorporating AI literacy?

Further resources for using AI in pedagogy to stimulate critical thinking

Collections of ideas and tested pedagogical practices.

The AI Pedagogy Project from Harvard's metaLAB

See all the prompt ideas from Teaching with AI: A Practical Guide to a New Era of Human Learning by José Antonio Bowen and C. Edward Watson. Jose Bowen has made the prompts and descriptions of AI tools free on his website.

The bottom line: let’s get to know AI. Our voices are needed!

Be playful, be curious, be bold.

If we work in education, we likely have critical thinking and communication skills that will help us use AI.

Our students need our guidance, and our voices are needed in the larger policy conversations around AI in society.

Questions or comments?�Thank you, and please keep in touch!

AnnaRMills.com

Slides, open for commenting: https://link.annarmills.com/CerritosAI

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This presentation is shared under a CC BY NC 4.0 license.