It includes 5 articles:

1. The Right to Transparency and “”Notice””
2. The Right to Human Oversight and Appeal
3. The Right to Data Sovereignty and Intellectual Property
4. The Right of all Students to Safely Use AI
5. The Right to Share in AI and its Benefits

If you have been wondering about student voice in the AI in Education conversation, this document is a great place to start thinking about student perspectives. What do you think a Faculty AI Bill of Rights would look like?

Check out the .

1. Instructor aids (e.g., lesson planning, teaching support)
2. Student exercises (activities that guide learning or reflection)
3. Other prompts (general-purpose uses)

The goal is to help users get better, more structured outputs from AI by using well-designed prompt templates. All prompts are openly licensed (Creative Commons), meaning they can be reused and adapted with attribution.

Check it out here: 

The course is uniquely designed to deliver bite-sized learning content and daily challenges to users entirely over text message. Users can complete the course in seven days by engaging for just 10 minutes a day. The text message-based design is intended to be as accessible as possible to all Americans, including those without a laptop or with limited access to the internet.

The course engages participants with daily content that directly aligns with the five foundational areas outlined in the Labor Department’s recently-released .

But how can we manage this? Over the last several years, Educational Technologist Eric Curtis has been having this academic integrity discussion with thousands of educators around the world. He has assembled feedback and resources in a 1-hour webinar with support materials.

The handbook covers use cases spanning teaching and instruction, student support services, assessment, research, accessibility, governance, workforce development, and more. Each entry includes the institution involved, the AI tools used, a description, and a direct link to the primary source. It draws on validated case studies from institutions like ASU, Purdue, Georgia State, Northeastern, the University of Michigan, and dozens of others, as well as findings from my Forbes Higher Education coverage.

As institutions navigate AI adoption, there’s no single place to see what’s actually being tried, what’s working, and where the gaps are. This resource is meant to fill that need — not as a static document, but as a living, growing repository shaped by the community. Consider sharing your own use cases!

Access the .

Why is this such an important post to read? The key issue isn’t whether AI might affect cognition. That is a broader and ongoing research question supported by diverse studies on cognitive offloading and educational impacts. Instead, how we interpret and communicate evidence is what is critical here. The post highlights the importance of scrutinizing research methodology before adopting headlines about AI’s harms or benefits. In teaching and policy conversations, this means encouraging nuanced engagement with research on AI and critical thinking, distinguishing between correlation and causation, and integrating AI in ways that support, rather than inadvertently replace, deep learning and reasoning.

If you have found a quality research article on the impact of AI on learning, please share it with us by emailing it to umpi-ctl@maine.edu.

Read the full post here:

Pookins, N. (2026, February 15). Highly-Cited “AI Erodes Critical Thinking” study appears to be AI generated slop. Nebu’s Newsletter. Substack. 

Beyond background and experimentation, the AI Pedagogy Project supplies a growing repository of ready-to-use, educator-designed assignments and activities that integrate AI tools in classroom contexts. For example, one assignment — “A Tale of Two Critiques” — asks students to compare a human-written critique of a text with a critique generated by an AI model, fostering critical reading and reflection. Another, “AI Image Remixing,” invites students to experiment with AI-based image generation or remix tools, prompting discussion around creativity, authorship, and the limits of machine-generated media. These assignments can be adapted to different disciplines, class levels, and learning goals — offering an accessible way for faculty to incorporate AI into their teaching without needing deep technical background.

Check it out here: 

The review found positive associations between ChatGPT use and several student outcomes:

• Improved academic performance compared with control conditions.
• Boosts in affective-motivational states, meaning students felt more motivated or positive about learning tasks.
• Increases in higher-order thinking propensities, suggesting students may engage more with critical thinking when ChatGPT is used thoughtfully.
• Reduced mental effort reported by learners in some contexts.

Interestingly, the review did not find that ChatGPT use changed students’ self-efficacy (their confidence in their own learning ability). This suggests that while tools can help performance, they don’t automatically make students feel more capable. The article doesn’t just stop at findings — it critiques the quality of current research and offers propositions for future work.

The review suggests that ChatGPT used as part of regular classroom practice — not just as an add-on — shows the strongest effects. This article provides evidence that ChatGPT should be integrated in ways that promote higher-order thinking, e.g., through scaffolding questions, collaborative prompts, or guided inquiry.

Read the full article here:

Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025). Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies. Computers & Education, 227, 105224. 

Create a free account to try it out. When participants enter a question or response for their chat partner on a challenging topic, Sway will evaluate the message for inflammatory or unproductive content and provide a suggested way to rephrase their post. The Sway Guide will also interject comments and prompts throughout the discussion as a facilitator and provide factual information to learners related to the content when asked.

To see it in action and hear from the developers, register for the February 19 Beyond Bots session listed in the events below.

Check it out here: 

You may have noted in your AI policy in your syllabus that students may not use AI for assessments, but what about during the learning process? Many aspects of effective learning are counterintuitive: productive struggle leads to better learning, re-reading and highlighting do not improve memory, we don’t always prefer the most effective learning techniques, etc.

We can’t assume that students will intuitively understand the most effective ways to use AI for learning, so it’s up to us to provide this guidance for them. Consider providing some suggestions to learners about how they might use AI to help them understand a reading assignment, quiz themselves to prepare for an assessment, or explore difficult concepts with personally relevant examples. You can find more ideas here: .