🤖 What 22 states say about AI in edu

🗳 Poll: Learning from other districts’ AI efforts

This week’s question: What kind of content would you like to see discussed in this newsletter?

🟨🟨🟨🟨⬜️⬜️ Imagining the role of AI in learning (18)
⬜️⬜️⬜️⬜️⬜️⬜️ More AI tech tools (3)
🟨🟨⬜️⬜️⬜️⬜️ How to form -- and adjust -- AI policy (10)
🟩🟩🟩🟩🟩🟩 Developing AI literacies (students / teachers) (26)
🟨⬜️⬜️⬜️⬜️⬜️ How to prepare students for the future (7)
⬜️⬜️⬜️⬜️⬜️⬜️ Other ... (3)

Some of your responses:

• Voted “Imagining the role of AI in learning”: Since we need to imagine what type of world our students will move into and be ready to prepare them for that, it only makes sense to try to imagine the role of AI in their learning. — Anna-Marie Robertson

• Voted “Developing AI literacies”: AI is still vastly unknown to many teachers and students. Just like we teach math and reading skills, we need to educate ourselves and our youth about AI as well. — Crystal Blais, Tech Coach

• Voted “Imagining the role of AI in learning”: This really is a moment of "What SHOULD they learn/know?" in education. Students used to need to remember how to rotate crops, or use an abacus, or properly complete a Scantron sheet. Yes, learning the new EdTech tools is important, but I feel we (as an industry) keep dodging the question of whether we are still teaching relevant skills.

• Voted “How to form and adjust AI policy”: Before any implementation of AI tools, I think a district policy needs to be in place. Once a solid policy is adopted, leaders will understand the tools and be more readily available to support teachers and students in the use of AI.

🗳 This week’s poll

Today’s newsletter focuses on what state departments of education are advising about to AI. It’s up to schools and districts to take action. And we can learn a lot from each other.

So today’s question: What are you most curious to learn?

Instructions:

1. Please vote on this week’s poll. It just takes a click!

2. Optional: Explain your vote / provide context / add details in a comment afterward.

3. Optional: Include your name in your comment so I can credit you if I use your response.

💡 Analyzing 22 states’ AI in edu guidance

If you’re in the United States, you might be in one of the 22 states where the department of education has offered guidance on AI in K-12 education.

• You might have read your state’s AI guidance. (Or not. Some are pretty long.)

• You might wonder what other states are saying — and if you can learn something from that.

• You might be curious about what the state documents have in common — or what makes certain ones unique.

Let’s do some analyzing.

I put all 22 state guidance documents — plus the recently released U.S. Dept. of Ed. guidance document — into NotebookLM, Google’s AI-fueled research assistant.

• You can add sources (PDFs, websites, videos, copied text, etc.) to NotebookLM and ask it questions in the chat.

• It can also generate documents, like a briefing doc, FAQ, timeline, study guide, and table of contents.

• NotebookLM also creates an incredible audio overview — a podcast interview-style summary with very real human voices.

• You can read all about NotebookLM in my post.

I found all of those documents in one handy page on the AI for Education website. (Most are PDFs. A few are websites. One of them wasn’t compatible with NotebookLM.)

I put them into NotebookLM. I asked it a bunch of questions. And I generated a podcast-style audio summary you can listen to.

Here are my human observations and summaries of what it concluded …

Commonalities among the documents

Not surprisingly, NotebookLM told me that the most common themes among all of the documents were:

• the need for AI literacy for all stakeholders

• the potential benefits of using AI in education

• the importance of addressing ethical concerns related to AI

• the rapid pace of AI development and the need for ongoing learning and adaptation

It used the words “exciting possibilities,” “significant challenges,” and “thoughtful and deliberate approach.”

There’s a ton of discussion around AI literacy right now, so that point was expected. It also notes the need for ongoing learning — where school and district PD on AI is lagging behind at large.

Ethical concerns regarding AI in education

The most common concerns expressed in the documents:

• bias (and its impact on marginalized communities)

• privacy (regarding collection of student data)

• transparency and accountability (of AI actions and decisions)

• cheating and plagiarism (in today’s education system)

• impact of AI on the role of teachers (to enhance, not replace)

Unique points among individual state guidance documents

Some states offered unique perspectives, suggestions, and information as compared to other states. They include …

• Connecticut: the importance of the “human in the middle” and the understanding that AI tools aren’t sentient and require human interpretation/discernment

• Indiana: calls for schools to “normalize the use of intelligent systems in the classroom” to prepare students for an AI future

• Kentucky: suggests three paradigms for AI use: AI-directed, AI-supported, and AI-empowered

• Mississippi: offers strategies for detecting plagiarism, including document version history and the use of AI detection tools (even though they’re often wildly inaccurate)

• North Carolina: in contrast to Mississippi (above), it suggests not using AI detectors and focusing on student reflection and the process (not end product)

• Washington: offers the SHIFT framework to evaluate AI outputs:

  • S) Start your curiosity engine: What intrigues me about the output AI gives me?

  • H) Hone in on a detail: What specific details did AI get right or wrong and how do I know?

  • I) Identify your context: How does AI fit into the bigger picture of my work?

  • F) Frame it from a new perspective: Can I think of a different perspective that AI could help me uncover?

  • T) Talk about what's missing: What limitations or challenges of AI should I consider?

U.S. Dept. of Ed. guidance less common in state guidance

The U.S. Dept. of Education guidance document emphasized certain points more than the states commonly did, like …

• Virtual listening sessions for community engagement: Gather feedback from the community from multiple sessions.

• Evidence-based approach to AI adoption: Ensure that AI tools (and the way they’re used) are linked to evidence of success in their use.

• Research-practice partnerships: Connect with researchers from universities or nonprofits to better navigate the complexities of AI implementation and evaluation.

Contradictions among state guidance documents

This was interesting to me — but not very surprising. Here’s where some of the documents contradicted each other:

• AI detectors: Many states advised against solely relying on AI detectors to determine inappropriate AI use. Mississippi’s guidance document said “educators should be taught to recognize AI-written communication, such as repetitive sentences, overly complicated vocabulary, inconsistent tone, or divergent writing styles.” (Umm, no … these aren’t hallmarks of AI-generated writing, and AI can be prompted NOT to write in these ways.)

• Student interaction with chatbots: States offered mixed guidance on AI chatbot interaction with younger students. North Carolina cited concerns with cognitive readiness, while others encouraged teacher supervision and age-appropriate implementation.

Preparing students for an AI-driven workforce

Several state guidance documents emphasize the importance of preparing students for an AI future — and developing the skills that will help them succeed and thrive. They include …

• Fostering AI literacy: Help students understand how AI works, develop AI skills, promote digital literacy

• Cultivating essential skills for an AI-augmented workplace: emphasize critical thinking and problem solving, nurture creativity, enhance collaboration and communication

• Address ethical considerations: promote ethical AI use, cultivate digital citizenship

• Connect education to future career pathways: showcase real-world applications, highlight transferable skills, embrace lifelong learning

Conclusion: What will you do in your school/district?

More and more states will surely continue to offer guidance on how we respond to growing AI technologies in our world and in our schools.

What we can ask ourselves about this:

• What are states suggesting that I haven’t considered yet?

• What applies in my unique community — and what might need to be adjusted/added/removed based on our uniqueness?

• How do we balance teaching AI literacy with core academic curriculum already in place?

• How ambitiously / aggressively do we encourage AI implementation and education?

Want to dive deeper? Here are some steps you can take …

• Listen to the 15-minute audio summary that NotebookLM created for me.

• Read the full responses that NotebookLM gave me about these guidance documents.

• Check out your own state’s AI guidance document here.

• Check out the U.S. Department of Education’s AI guidance document.

• Read about UNESCO’s AI competency framework for students — and its framework for teachers

✍️ Can you cite AI in classwork? Should you?

Often, when I present to teachers at schools, districts, and conferences, this topic comes up.

Can you cite AI in classwork? Should you?

Teachers are so conditioned to say “cite your sources” that it’s easy to say “cite your sources” with AI. It just rolls off their tongues.

But is AI a source?

Here’s a similar question … is Google a source?

Just because MLA, APA, and Chicago have citations for AI doesn’t mean that we should use them as a primary source for information.

If you’ve wanted to better understand this topic, you should check out this article.

📚 New AI resources this week

1️⃣ The Most Likely Machine: Algorithms power the world, but they can make mistakes. Build your own algorithm and see how it impacts the future – for good and for bad.

2️⃣ aiEDU AI Project Dashboard: Browse a variety of unique, engaging projects for high school students. Choose what’s right for your classroom from our mix of independent and teacher-led projects in a variety of subjects.

3️⃣ CoSN K-12 Generative AI Readiness Checklist: A questionnaire designed to guide K-12 school districts in understanding key factors to consider before implementing Gen AI technologies.