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Prompting the Physics Mind: The Role of AI Tools and Prompt Engineering in Addressing Metacognitive Learning Resource Gaps Among Undergraduate Physics Students

Dr. Rachelle Dené Poth Leave a comment

Guest post by Patricio Bastida Nava, undergraduate researcher at the University of Massachusetts Amherst.

“Give me six hours to chop down a tree, and I will spend the first four sharpening the axe.”

— Abraham Lincoln

The first time I realized how badly AI could fail a student was during my first semester at UMass Amherst. I was studying for my second Physics 181 midterm. I just couldn’t understand projectile motion and struggled with kinematics. None of it was clicking. So I did what felt productive: I asked ChatGPT to build me an interactive visualization, a map of how the problems fit together, something I could study from. The artifact it produced was beautiful. I felt prepared. There I was looking at the exam when I knew instantly that understanding the concept and actually solving a problem were two entirely different things. The exam did not ask me to recall relationships. It asked me to set up equations, choose coordinate systems, and grind through algebra with variables. I had outsourced the thinking and memorized the output. I felt deeply frustrated. I just didn’t know what was wrong with me or how to fix it. The gap between what I thought I knew and what I could do had never been so big.

That failure changed how I used AI. I stopped asking it to explain and started asking it to coach: generate problems, demand my reasoning before giving feedback, and adapt difficulty to my mistakes. My learning improved. As usual, this experience led to a very important question — if I was going through this situation, what was happening to everyone else?

Weeks later, Dr. Torrey Trust ran an exercise in her AI and Education seminar that gave me part of the answer. She asked students — biology, computer science, engineering, economics — what tool they turned to when a concept was not clicking. Nearly every hand pointed in the same direction: ChatGPT. Not because anyone had tested it against alternatives. Not because it produced the best learning outcomes. Because it was fast, and speed feels like understanding. Researchers call this the learning illusion: the subjective sense that you have learned something when you have only been exposed to it. In education research, metacognition (the practice of thinking about how you are learning and whether it is actually working) is the primary defense against this illusion. But metacognition is effortful, and ChatGPT is effortless. That is the trap.

I am a first-year physics student, but I am also a researcher. I never attended a traditional school. I earned my high school diploma in Mexico by examination alone. Everything I know, I taught myself, and for much of that process, AI was one of the only resources I had. That experience gives me no patience for the argument that AI is simply a shortcut. For students like me, it was the classroom. But it also gave me no illusions about its dangers, because I have lived both sides: the version of AI that builds understanding and the version that quietly destroys it. This past March, I co-presented original research at the SITE International Conference in Philadelphia with Dr. Trust, evaluating how well large language models actually support learning when measured against established instructional theory. What we found should matter to every STEM educator. Faculty need to stop relying on blanket AI bans, update their syllabus policies, and start teaching students how to use AI for metacognitive reflection and cognitive collaboration — because whether faculty act or not, students are already using these tools every day.

The Learning Illusion

Akgun and Toker published a 2025 empirical study comparing students using ChatGPT against students using traditional textbooks. The AI group showed short-term gains on simpler tasks, but their long-term retention was significantly worse. The AI was doing the thinking. The student was watching. In learning science, this is called cognitive offloading, and in physics, it compounds every week. A student who does not genuinely work through Newton’s Second Law in week three will be lost when momentum, energy, and wave mechanics arrive later.

The struggle is not the enemy of learning in physics. The struggle frequently is the learning.

Hon’s 2026 systematic review of studies from 2018 to 2024 confirms that AI tools consistently increased engagement but also produced over-reliance and inconsistent outcomes, with the biggest gaps in disciplines that require deep conceptual reasoning. Physics is exactly that kind of discipline. Yet every day, physics students everywhere open ChatGPT, paste in a problem, and read the solution. It feels productive. It is not.

When AI Actually Works

The picture is not uniformly negative. AI can sometimes teach better than a traditional classroom, but only when it’s designed very carefully. In 2025, Harvard researchers ran an experiment and found that students learned more physics and learned it faster when they used a custom-built AI tutor instead of sitting in a typical active-learning class. What made it work wasn’t the AI itself so much as the guardrails built into it: students had to walk through their thinking before getting any help, mistakes became useful signals rather than dead ends, and the system adjusted based on where each student was actually getting tripped up. Even then, the researchers noted it could have been even better with tighter controls on how quickly answers were revealed. When I tested the model myself, I found it still occasionally provided solutions faster than a student could meaningfully process them.

Kotsis frames this through cognitive load theory: AI must scaffold inquiry rather than replace it. When a student pastes a problem and copies the answer, they eliminate all cognitive load. When they prompt an AI to coach them step by step and require them to show their work first, they engage exactly the cognitive processes physics instruction is designed to build. Younis found measurable improvements in conceptual mastery among undergraduate physics students when AI was integrated this way.

The AI is the same either way. The learning is completely different.

What the Data Actually Shows

At SITE 2026, Dr. Trust and I set out to answer a specific question: do the study and learning modes that major AI companies have built — features these companies developed, by their own account, in partnership with educators and learning scientists — actually deliver a sound learning experience? We tested four platforms: ChatGPT, Gemini, Claude, and Perplexity. Our framework was Gagné’s Nine Events of Instruction, a model from the 1960s that defines the foundational conditions for effective learning, from gaining the learner’s attention and stating objectives through eliciting performance, providing feedback, and supporting transfer to real-world application.

Across all four platforms, two of Gagné’s events were nearly absent: Gain Attention and Inform Objectives. In practice, this meant that no tool consistently explained what the student should know or be able to do after the lesson, and no tool took meaningful steps to engage the student’s curiosity before presenting the content. Without a stated learning objective, a student cannot track their own progress, cannot reflect on whether they actually understood something, and cannot connect the current concept to the next one. In a discipline as cumulative as physics, that is not a minor gap. It is a structural failure.

The findings went deeper than missing events. Learning guidance was the most consistent behavior across all four tools, but the other behaviors followed a repetitive, formulaic pattern rather than adapting as the interaction progressed. Feedback was constantly present but shallow — short and generic, lacking the depth needed to actually support learning. Every tool works with enthusiasm and encouragement regardless of the quality of the student’s responses, making it dangerously easy to fall into a learning illusion: you feel like you understand because the AI keeps telling you that you are doing great. ChatGPT in particular overwhelmed users with multiple questions simultaneously, creating a mismatch between what it asked the learner to do and what its own interface allowed. Of the four tools, Claude was the only one that consistently pushed students toward critical thinking — and, perhaps tellingly, it is often perceived as the most frustrating to use.

There is something else important to say. The presence of a pedagogical behavior in an AI interaction does not guarantee its quality. A tool can ask questions without asking useful questions. Our research required classifying each interaction against Gagné’s events regardless of quality, then reexamining the qualitative texture of those interactions to understand what the numbers alone could not capture. What the data showed, across hundreds of interactions, is that the most sophisticated AI study modes available right now cannot consistently meet what a first-year education textbook from 1965 would call basic instructional standards — and these are the tools students are relying on every night.

The Missing Skill: Metacognitive Prompting

If the tools themselves are not pedagogically reliable, then the burden falls on how students use them. This is where metacognitive prompting becomes essential — and where the gap in instruction is most glaring. Consider two students preparing for the same Physics 181 midterm on the work-energy theorem. The first opens ChatGPT and types: “Teach me about the work-energy theorem for my exam.” The AI produces a tidy summary. The student reads it, feels reassured, and moves on. Cognitive offloading is complete.

The second student writes a different kind of prompt. They instruct the AI to act as a physics professor who will first provide a short conceptual explanation, then present a symbolic problem using only variables — no numbers. The prompt explicitly requires the student to show their full step-by-step reasoning, including a free-body diagram and force decomposition, before the AI reveals any solution. It instructs the AI to analyze the student’s reasoning, identify specific misconceptions, explain why each mistake matters conceptually, and provide metacognitive strategies — reflection prompts like “Which assumption did I make unconsciously?” or checklists for common errors. Only after this exchange does the AI present a worked solution, and it follows up with a new problem adapted to the student’s demonstrated weaknesses.

The AI is identical in both cases. The learning is not. The first student consumed information. The second student built understanding. The difference is not intelligence or motivation. It is whether anyone ever taught the second student that prompting is a skill, that the quality of what you ask determines the quality of what you learn, and that the goal is not to get the answer but to find out where your reasoning breaks. Nobody is teaching this. Not in physics courses, not in orientation, not in any syllabus I have seen.

What Needs to Change

A professor during my first semester dismissed AI with an analogy: “Do you send your computer to do workouts for you?” The analogy is not wrong about personal responsibility. But it assumes students have a proper gym, a qualified trainer, and enough time to use both. Most of us do not. Office hours last an hour. Textbooks do not ask you how you are thinking. AI is available at two in the morning when the exam is tomorrow, and the concept still will not click. For many of us, it is the only resource available long enough to actually help. That does not make it safe. It makes it necessary — and necessity without guidance is how students get hurt.

Three concrete changes could begin to address this, and none of them cost money. First, update syllabus policies. The University of Texas at Austin has published sample AI guidelines that move past blanket bans toward transparent policies treating AI as a citable tool with clear attribution requirements. Any university can adopt and adapt the same framework. Second, name the risk. Tell students explicitly what cognitive offloading is and why speed is not learning. Chen documents practical strategies for avoiding AI-driven learning illusions that could be incorporated into any course’s first-week materials. Third — and this is the intervention that does not exist yet — teach students how to prompt. Not as a computer science skill, but as a metacognitive one. A single module in the first week of a physics course, showing the difference between a prompt that offloads thinking and a prompt that forces reflection, would do more for student learning than any AI ban ever has. Resources for this already exist. EdTech Books publishes open-access materials — many peer-reviewed, others designed by scholars and educators — addressing how to design AI-integrated assignments and teach prompting for critical thinking rather than answer retrieval. One example is AI-Ready Educators and Students: Using the AUGMENT Framework to Teach and Learn with Generative AI, which offers a free, classroom-ready framework for exactly this kind of teaching. These resources exist right now, and most faculty have not seen them.

I want to be honest about the limits of this argument. Prompting is a patch. It is a patch for what is, at its core, a real and serious wound: AI tools built for speed rather than learning, that consume millions of liters of water annually, that encode biases, and that will not on their own produce the physicists this world needs. But we do not have time to wait for better tools, and the wound is already open. We do not have those tools yet. I am not sure we will have them in five years. Students are using these tools today with no guidance on how to use them well.

The question has never been whether students will use AI. The question is whether anyone will teach them the difference between a prompt that replaces their thinking and a prompt that sharpens it. That is a teaching problem, and it has a teaching solution. The goal is not to ban these tools or to endorse them. The goal is to give students the knowledge, the research, and the critical awareness they need to make an informed decision about how they learn — and then the freedom to make it. Right now, students are making that decision every day. They are just making it in the dark. The least any university can do is turn on the lights.

About the author

Patricio Bastida Nava is a Mexican undergraduate student at the University of Massachusetts Amherst, where he is pursuing a double major in Physics and Astronomy/Astrophysics alongside interdisciplinary studies in artificial intelligence and STEM education. His work sits at the intersection of AI research, instructional design, and applied technology. He has co-authored research on how generative AI platforms support teaching and learning, and designs corporate AI training programs grounded in prompt engineering and educational theory. He is also a member of UMass’s iCons program in the AI & Future of Work track. Beyond his academic work, Patricio serves in student technical leadership and is passionate about the role of AI, physics, and pedagogy in shaping the future of work and learning.

About Rachelle

If Your Organization Is Beginning This Work

I help schools and other organizations (law firms, healthcare professionals, business owners) implement AI responsibly through policy guidance, professional learning, and classroom-ready strategies grounded in both instructional practice and legal insight.

My sessions focus on helping teams:

• understand what AI can and cannot do

• recognize responsible-use considerations

• build confidence using emerging tools

•align implementation with organizational priorities

If your school, district, or organization is beginning conversations or looking to dive in and learn more about AI policy, professional learning, or responsible implementation, I’d welcome the opportunity to support your next steps through leadership workshops, keynote sessions, or strategic planning partnerships.

Preparing people is what makes AI implementation successful. Contact me via bit.ly/thrivineduPD for my training and speaking services.

Article content

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Leading Forward, Part V: How Do We Know It’s Working? Measuring What Matters in an AI-Driven World

Dr. Rachelle Dené Poth 2 Comments

Throughout this series, I’ve shared what I’ve learned from working alongside district leadership teams across the country as they navigate artificial intelligence, digital wellness, and purposeful technology use.

We’ve explored:

  • why curiosity is replacing fear
  • why educator readiness is the foundation
  • why leadership and systems matter

But there is another critical question schools must answer:

How do we know if it’s working? Because implementation is not the goal. Impact is.

The Problem With Measuring the Wrong Things

Screen time and effective use of technology are hot topics in conversations happening in schools across the country. In many districts, success with technology has typically been measured by:

  • number of devices available, so all students can participate in learning
  • tool adoption rates
  • platform usage
  • logins and activity

These metrics are easy to track. But they don’t tell the full story. I’ve said it many times in various ways, but a classroom full of students using devices does not automatically mean that impactful, meaningful learning is happening. Nor does it show true student engagement just by the use of devices.

More technology use does not automatically lead to deeper learning.

More screen time does not equal greater engagement or better outcomes

So we have to really think about what we are measuring. If we continue measuring what is easy, we risk missing what matters most. And we might miss providing the best learning experiences for students.

What Should We Be Measuring Instead?

Across the districts I work with, the leadership teams are beginning to shift their focus.

The districts making the most progress are beginning to ask different kinds of questions:

  • Are students thinking more deeply?
  • Are students asking better questions?
  • Are students able to evaluate information more critically?
  • Do students understand when and how to use AI responsibly?
  • Are students being guided in how to use technology and why they are using it?
  • Do educators feel confident in their instructional decisions?
  • Are they supported as technology changes?

These are harder to measure, but they are far more meaningful and provide greater insight that schools can act upon.

Indicators Schools Are Moving in the Right Direction

There are some clear indicators I have seen and read about that show schools are moving in the right direction.

1. Student Thinking Is Visible

Students are not simply submitting AI-generated responses. They are explaining their thinking, reflecting on their process, questioning outputs, and making revisions. They are being guided and understand how to use AI as support, not a replacement.

2. Educators Are Making Intentional Decisions

Teachers are not asking whether they can use a certain tool or platform. Instead, they are questioning when they should and what the impact will be. This shift shows greater confidence in the purposeful use of technology and in intentional lesson design. Quality over quantity.

Continue reading the rest and subscribe to my newsletter on LinkedIn.

Subscribe to my ThriveinEDU newsletter to stay informed.

If Your Organization Is Beginning This Work

I help schools and other organizations (law firms, healthcare professionals, business owners, psychologists) implement AI responsibly through policy guidance, professional learning, and classroom-ready strategies grounded in both instructional practice and legal insight.

My sessions focus on helping teams:

• understand what AI can and cannot do

• recognize responsible-use considerations

• build confidence using emerging tools

•align implementation with organizational priorities

If your school, district, or organization is beginning conversations or looking to dive in and learn more about AI policy, professional learning, or responsible implementation, I’d welcome the opportunity to support your next steps through leadership workshops, keynote sessions, or strategic planning partnerships.

Preparing people is what makes AI implementation successful.

Contact me to work with you or speak at your event. bit.ly/thriveineduPD See testimonials about my work via my website.

Article content

Leading Forward Part II

Dr. Rachelle Dené Poth Leave a comment

Preparing Educators for an AI Future Means Preparing Leaders First

In my last article, I shared my thoughts about what I’ve been learning from working with district leadership teams across the country as they navigate questions about artificial intelligence, digital wellness, and purposeful technology use. My work has provided me with tremendous opportunities to learn from educators, students, and families.

Conversations about screen time, purposeful technology use, and digital balance are happening everywhere.   What I’ve found most insightful is when students and educators have the chance to sit down and engage in open, honest conversations about these topics and learn from one another. I’ve noticed a common theme in most of these conversations. We have to focus on more than just the technology, especially when talking about AI use in schools. Frequently, the focus is first on specific tools. When talking about artificial intelligence happening in schools, the questions have been:

Which platform should we allow? What should students be permitted to use? What policies do we need?

These are important questions. But they are not the first questions schools should be asking.

The first question schools should be asking is:

How prepared are our educators to lead in an AI-shaped learning environment?

Successful implementation is not about technology adoption.

Introducing AI into classrooms is easy. Supporting educators to understand how to use it meaningfully is the real work. And with support comes confidence.

Educator readiness is the real implementation strategy

Across the districts I have worked with, I’ve noticed that the biggest predictor of successful AI integration is not the access to tools, but whether or not educators feel supported as they navigate the changes happening.

I believe that schools will see more progress and success when there are goals set. Educators must have time to explore. Expectations need to be communicated clearly and with a consistent message. Policies must be in place, and they should emphasize guidance rather than restriction. AI implementation and any technology integration succeed when educators understand not only how to use tools, but why they should use them, and what the impact is on student learning.  This is what I am hearing from students around the country. 

Across classrooms nationwide, students are using an increasing number of digital tools in their classes. However, I am hearing from them that they are not always consistently guided on how to use them safely, ethically, and responsibly. Students wanting clarity is a powerful insight. Students wanting more purposeful use of technology is an even more powerful insight. How can this happen?

By supporting educators, because it helps to then support students.

Leadership sets the tone

One of the most powerful influences on AI adoption, technology use, and the establishment of standards for communication and screen time in a school system is leadership modeling.

When administrators ask for feedback, communicate transparently, dive in to explore tools with teachers, and acknowledge uncertainty while providing direction, they create a safe environment for innovation. Leadership like this builds trust, and trust makes responsible implementation possible.

Preparing students means preparing adults first

Students will graduate and enter workplaces shaped by automation, intelligent systems, and evolving expectations around collaboration with technology. According to the World Economic Forum, technological literacy is #3 for 2030. #1 is AI and #2 is cybersecurity. Students are not the only ones preparing for that future. Educators need to be prepared so that our students are too.

Professional learning on AI is no longer an option. It is an essential part of instructional readiness. The schools making the most progress right now are engaging in conversations to build systems that help educators adapt confidently as change continues. And that may be the most important preparation strategy of all.

Supporting educators means strengthening entire school systems. This is one of the most important investments districts can make as they prepare students for an AI-shaped, AI-driven future.

Stay tuned for part 3 of this Leading Forward Series.

Subscribe to my ThriveinEDU newsletter to stay informed.

If Your Organization Is Beginning This Work

I help schools and other organizations (law firms, healthcare professionals, business owners) implement AI responsibly through policy guidance, professional learning, and classroom-ready strategies grounded in both instructional practice and legal insight.

My sessions focus on helping teams:

• understand what AI can and cannot do

• recognize responsible-use considerations

• build confidence using emerging tools

•align implementation with organizational priorities

If your school, district, or organization is beginning conversations or looking to dive in and learn more about AI policy, professional learning, or responsible implementation, I’d welcome the opportunity to support your next steps through leadership workshops, keynote sessions, or strategic planning partnerships.

Preparing people is what makes AI implementation successful.

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

Leading Forward in AI: What I’ve Been Learning from Schools Across the Country (Part I)

Dr. Rachelle Dené Poth Leave a comment

Subscribe to my ThriveinEDU newsletter to stay informed. (If you receive my newsletter, you may have read this, but just in case…here is part I)

Over the past eight months, I’ve had the opportunity to work with educators, school leaders, and district teams from twelve districts across the country as they navigate one of the biggest shifts education has experienced in decades: the arrival of artificial intelligence in everyday teaching and learning. This work is part of a national digital wellness and innovation initiative supporting districts as they develop responsible approaches to emerging technologies.

I work with a Task Force from each district to evaluate policies, create resources for families, and decide when and how to begin teaching students about AI, as well as how best to support educators. And some of these Task Forces include students and parents. We have had many conversations about digital wellness, digital citizenship, screentime, and, of course, AI.

The conversations about AI included shared concerns, questions, and challenges. However, what has stood out the most in these conversations with these schools is not fear. It’s curiosity.

In classrooms, teachers are asking thoughtful questions about how AI can support student thinking rather than replace it. Administrators are working to align emerging tools with existing priorities such as digital citizenship, academic integrity, and student wellness. District teams are exploring how policy can move beyond restriction toward responsible guidance. Some are even completely rewriting their policies to align with these changes and make sure that a common language is used.

Recently, my work has included:

• Supporting district digital wellness and AI implementation planning

• Leading professional learning sessions on responsible AI use

• Presenting on AI and the law for educators

• Visiting classrooms to observe how students are already interacting with AI tools

• Collaborating with leadership teams and developing next-step strategies for staff support

• Designing activities for administrators and educators to evaluate policies and effective AI use

One consistent theme continues to emerge:

Districts, educators, and students are ready to lead.

Educators are not waiting for perfect answers to the big AI questions. They are considering the best pedagogical practices for using AI that protect students while expanding opportunities.

The most successful districts I’m working with right now are focusing on three priorities:

  1. Supporting educator confidence: They need clarity, examples, and time to explore.
  2. Creating shared expectations for responsible use across classrooms and grade levels
  3. Preparing students to think critically about AI-generated information.

Artificial intelligence isn’t just a technology conversation.

It’s a leadership conversation.

And I’m excited to continue working with and learning alongside school districts as they move forward with clarity, purpose, and a strong commitment to keeping human relationships at the center of innovation.

Providing the training

Artificial intelligence is changing expectations across nearly every profession. Schools are not the only organizations preparing for this shift.

In my work as an educator, attorney, and national presenter on responsible AI implementation, I support organizations as they explore how AI connects to decision-making, ethics, communication, and everyday professional practice.

I help schools and other organizations (law firms, healthcare professionals, business owners) implement AI responsibly through policy guidance, professional learning, and classroom-ready strategies grounded in both instructional practice and legal insight.

My sessions focus on helping teams:

• understand what AI can and cannot do

• recognize responsible-use considerations

• build confidence using emerging tools

•align implementation with organizational priorities

If your school, district, or organization is beginning conversations or looking to dive in and learn more about AI policy, professional learning, or responsible implementation, I’d welcome the opportunity to support your next steps through leadership workshops, keynote sessions, or strategic planning partnerships.

Preparing people is what makes AI implementation successful.

Article content

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

Educator explaining AI literacy concepts on a smartboard to students with tablets and laptops

AI Literacy is Not Tool Mastery: How to Build Sustained Educator Capacity

Dr. Rachelle Dené Poth Leave a comment

Previous post on Getting Smart

Not long ago, artificial intelligence in education felt novel. It was something shiny, experimental, and, for many educators, possibly unsettling at times. When ChatGPT arrived in November 2022, the initial conversations and concerns were more focused on fear. I recall receiving emails, text messages, phone calls, and visits from educators who were concerned about cheating, plagiarism, lost skills, and what instantly felt like an overwhelming pace of change. It was something else to adjust to, not long after the overwhelming feeling that many felt in March of 2020. 

But since that initial adjustment to the increased use of AI in our world at the end of 2022 and through 2023, I’ve seen a shift happening. At first, there was skepticism, uncertainty, and hesitation, and not just in the world of education. However, as we’ve continued to adjust to new tools and new ways of working, I’ve noticed a shift from considering AI as a “what if” to the acceptance that AI is here and its use is increasing. It’s embedded in tools educators already use, and if it hasn’t already, then it will potentially slowly but surely become part of the daily routine and workflow of teaching and learning.

I’ve spoken about this shift from novelty to normalcy and how it brings a new challenge: educator upskilling.

A few years ago, I started researching the training available to educators and other professionals in AI. At the end of 2023, 87% of the educators in the United States had not received any training. In my workshops, some attendees are having their first training experience, more than 3 years after ChatGPT made its debut. So I think that we need to focus on an important question, whether in education or not. The question is no longer whether educators need professional learning around AI. Most people agree that they do. The bigger issue is whether we are approaching AI professional development in ways that are deep, sustained, and human-centered, or whether we’re still experiencing the one-and-done sessions that barely scratch the surface. With AI and the pace of change in education and the world, we need to do better and be prepared.

Shifting to Ongoing Capacity Building

When I completed my doctorate nearly two years ago, my research focused heavily on professional learning in emerging technologies, with a strong emphasis on AI. Even then, the message was clear. A single PD session, or even a series of short, tool-based trainings, was not enough, especially if completed early in the year or during a limited time span.

Yet, that is what I am learning about how AI PD is structured today. Through surveys in my sessions and conversations with other educators, there is a common experience happening, which is:

  • A 30-minute overview.
  • A 15-minute “certified educator” badge.
  • A walkthrough of one tool done well.

While these experiences can be helpful, especially for getting started and when time is limited, in the long term, they don’t build AI literacy. They build familiarity, whether with AI concepts or an AI tool. But familiarity is not AI literacy. Not for us as educators, nor for the students we are preparing for a future surrounded by AI and a world of work that seeks employees skilled in AI. 

Continue reading the original post on Getting Smart.

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks

************ Also, check out my THRIVEinEDU Podcast Here!

Join my show on THRIVEinEDU on Facebook. Join the group here.

A Closer Look at What’s New in Kira 2.0

Dr. Rachelle Dené Poth Leave a comment

In collaboration with Kira

During our ThriveinEDU livestream conversation about Kira, we explored a question that immediately resonated with educators:

What if planning, grading, and differentiation actually took half the time and still kept teachers in control of learning?

The question isn’t just about efficiency. It’s about sustainability and about supporting teachers to make instruction more responsive, more personalized, and more aligned to what students actually need in the moment, real-time responses, authentic feedback, and support from their teachers.

Kira recently released several new features (as part of their Kira 2.0 launch) that move beyond treating AI as a “lesson generator” or “assessment creator,” and it now works as a thought partner in the instructional workflow. After attending the Live Launch in New York on March 3rd and moderating the livestream, here are some of the biggest takeaways from the conversations that make the newest updates especially impactful for classrooms now.

Lesson/Course Studio

Many AI tools help teachers create one lesson at a time, which is highly beneficial and time-saving. But imagine you’re tasked with creating a course you’ve never taught or don’t have enough resources for. The amount of time needed is a bit overwhelming.

Kira’s Course and Lesson Studio helps educators generate both structured lessons and full, standards-aligned courses, including course outlines, unit sequences, lesson progressions, and assessments

Educators need to provide the topic, subject, grade level, and standards, and then, using this information or prompt, Kira builds the lesson with embedded formative checks already in place.

Formative assessment often happens after instruction, with Kira, teachers see student understanding during instruction.

As Rachel shared during the livestream:

“I don’t remember a time when I wasn’t taking work home or trying to get ahead of the game by planning out my week and then having to rewrite it midweek. It was so much work.”

Kira’s curriculum-building features help reduce that cycle in far less time. Rather than rewriting lessons to meet student needs, teachers start with a flexible structure they can adapt immediately, and, most importantly, stay in control. We are doing the editing, adjusting, and shaping of the lesson. This is an important distinction to make because it shows how crucial it is that teachers remain involved and review what has been generated.

Real-Time Insight Instead of End-of-Unit Surprises: Student Atlas

I have known about this for a few months and thought it was amazing. One of the most exciting updates in Kira 2.0 is Student Atlas, the platform’s student insight dashboard, now paired with Class Atlas, which brings those insights together at the class level.

Student Atlas provides:

  • concept-level mastery tracking
  • data confidence indicators
  • individual student support indicators
  • zones of proximal development insights
  • intervention suggestions

Rather than relying on a single quiz or test score, teachers can see which concepts students understand and where they’re struggling in real time. It enables us to see what concepts need reinforcing now, rather than waiting until the assessment is over and graded.

Class Atlas builds on this by turning individual insights into a clear, actionable class-wide view. Instead of opening 20+ student profiles and piecing things together, teachers can instantly answer: Where should I focus my instruction? and Which students need help with this skill? Teachers can even ask Kira to explain how it generated its recommendations, which helps schools as they look for tools and want to trust AI technologies.

Student Atlas also includes a data confidence indicator, helping educators assess the reliability of recommendations before making instructional decisions. That transparency supports professional judgment instead of replacing it.

Standards Alignment

Standards alignment is often one of the most time-consuming parts of planning, especially when building units or courses. And for educators teaching multiple courses, it is very time-consuming. But with Kira 2.0, that time requirement decreases because Kira 2.0 automatically tags lessons, activities, assessments, and questions to state standards, underlying skill progressions, and Bloom’s taxonomy levels.

Teachers can track how students are progressing through skills over time.

Supporting Multilingual Learners

Another standout feature we spoke about in the livestream is Kira’s built-in support for multilingual learners.

When gaps in understanding appear, Kira can generate:

  • scaffolded practice
  • targeted follow-up lessons
  • leveled reading supports
  • vocabulary scaffolds
  • translated instructional materials

Each of these supports is based on individual student performance, and not on a generic template that does not align with the student’s needs.

Differentiation is responsive rather than being reactive.

During the livestream, we talked about how, historically, differentiation required teachers to manually create multiple versions of lessons or assessments, which, of course, took a lot of time. With Kira, these supports are embedded directly inside the instructional workflow. Rachel said, “Especially talking about differentiation and the ease of it and being able to have the assistant nearby and go back and forth.”

Embedded support assists educators in providing what each student needs while giving them more time to work directly with each student.

Kira provides structure, but the teachers are the designers who provide the course’s vision.

Kira brings planning, assessment, differentiation, and student insight into one connected space. And when those pieces connect, teachers gain something incredibly valuable:

clarity
flexibility
time
and better visibility into learning

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks

************ Also, check out my THRIVEinEDU Podcast Here!

Join my show on THRIVEinEDU on Facebook. Join the group here.

From Awareness to Action: Responsible AI Adoption in Schools Now (Part 2)

Dr. Rachelle Dené Poth Leave a comment

In Part 1, I shared why understanding the legal landscape of artificial intelligence is essential as schools continue to explore how these tools can support teaching and learning. Schools everywhere are thinking through policies and how to best provide resources for educators, students, and families. Awareness of laws such as FERPA, COPPA, and GDPR, accessibility requirements, and concerns such as algorithmic bias and deepfakes set an important foundation for responsible implementation.

We need guidelines and guardrails. A common question I hear from educators and leaders after presenting sessions and workshops, or speaking at conferences, is: “What do we do next?”

Understanding the guardrails is only the first step. The real work begins when schools start building systems that support educators in applying this knowledge in practical, sustainable ways. And it requires true collaboration.

Responsible AI Adoption Is a Team Effort

One of the most important shifts happening right now is the recognition that AI adoption and policy development should not be the responsibility of a single person or a select few administrators or IT teams. Responsible implementation and policy development require collaboration across roles.

District leaders are shaping policy and expectations for the school community.

Technology teams are evaluating vendor compliance and infrastructure readiness. (I have a future post coming up about IT Teams and ongoing PD).

Instructional leaders are aligning tools with learning goals and supporting teachers with implementation.

Teachers are modeling and supporting ethical classroom use.

Students are exploring and developing AI literacy skills that will shape how they interact with technology throughout their lives.

What I truly believe is that when schools recognize AI is a shared responsibility rather than an isolated initiative, implementation becomes more intentional, reflective, and sustainable.

I consistently see this when working with districts across the country. The schools that are moving forward with confidence are not the ones adopting the most tools. They are the ones creating a community, developing a common language, and building shared understanding first.

Transparency Builds Confidence Across the Community

Another theme that has been coming up in conversations with educators and families is trust.

Families want and need to know:

What tools are being used?

What information is being collected?

How is student data protected?

How is AI, or any technology, being used in support of learning rather than replacing it?

Having clear answers to these questions helps to strengthen the essential partnerships between schools and families. It also creates opportunities for students to participate more actively in conversations about responsible technology use.

Transparency is not simply a compliance strategy. It is a relationship-building strategy. When schools communicate clearly and proactively, they reduce uncertainty and help communities better understand how innovation supports student success.

AI Literacy Is Now Part of Digital Citizenship

One of the biggest shifts happening in education right now is the expansion of digital citizenship to include AI literacy. We’ve been talking about media literacy, digital literacy, AI literacy, and even discernment. Our work is a bit more involved now, and we need to be prepared.

Students are already interacting with AI systems daily, both in and maybe more frequently outside of school. They need guidance, which means classrooms must play an essential role in helping students understand:

How to protect their personally identifiable information (PII)

How AI systems generate responses
How bias can appear in outputs
How misinformation spreads
How data is collected and used
How to evaluate whether a tool should be trusted

AI literacy is not about teaching students how to use a single platform. It is about helping them develop judgment.

When students learn how to ask better questions about technology, they become more confident learners and more thoughtful digital citizens. Emerging tools continue to shape how students research, communicate, and create, and as educators, we have to keep learning so we can guide them to use the tools available to them safely and successfully.

Accessibility and Equity at the Center

As schools explore AI tools, accessibility must be a part of every conversation.

AI has tremendous potential to support multilingual learners, provide personalized feedback, assist with reading and writing tasks, and help students access content in new ways. It has endless ways to support educators. Schools must continue evaluating whether tools meet accessibility expectations and support equitable learning experiences.

Responsible implementation means asking questions such as:

Does this tool improve students’ access?

Does it create barriers? There has been more talk about the digital divide recently.

Does it support multiple learning pathways?

Does it align with universal design principles? Or a Portrait of a Graduate or an AI-Ready graduate?

Technology should expand opportunity rather than narrow it.

Supporting Educators Through the Transition

One of the most encouraging things I have seen in my work with educators is their investment in learning and the desire to learn with and from their students.

Educators are exploring AI tools while also asking important questions about privacy, ethics, and instructional impact. This balance is exactly what responsible adoption should look like.

Professional learning plays an essential role.

Educators benefit from opportunities to:

Explore tools safely
Review privacy expectations
Understand policy implications
Design classroom strategies
Collaborate with colleagues
Develop shared language around responsible use

When professional learning includes both legal awareness and classroom application, educators feel more confident making decisions that support students. Confidence leads to stronger implementation. And this is the work I am most passionate about when working with schools.

Leadership Matters More Than Ever

School leaders are in a unique position to support responsible AI adoption by:

Developing clear expectations
Supporting cross-team collaboration
Communicating with families (consistently)
Reviewing vendor agreements carefully
Building a common language around the use of AI
Creating space for experimentation, but having guardrails in place

Moving Forward

Artificial intelligence is already part of the learning landscape. We should not be talking about whether schools should engage with AI, but rather deciding how they will engage with it.

When schools combine legal awareness, transparency, accessibility considerations, and strong professional learning structures, they create innovative environments built on human decision-making.

Students benefit when educators feel confident.

Educators benefit when leaders provide clarity.

Communities benefit when schools communicate openly.

Responsible AI adoption is about moving forward with purpose.

When schools take that approach and have a team to work with, they are preparing students to understand technology, question it, and be the ones who determine what comes next.

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks

************ Also, check out my THRIVEinEDU Podcast Here!

Join my show on THRIVEinEDU on Facebook. Join the group here.

AI and the Law: What Educators Need to Know About Responsible Use in a Rapidly Changing Landscape

Dr. Rachelle Dené Poth Leave a comment

By Dr. Rachelle Dené Poth, JD

Artificial intelligence (AI) is rapidly transforming education. From lesson planning support to personalized learning pathways and administrative efficiencies, AI tools are a more common part of everyday classroom practices. At the same time, the speed at which this technology has advanced and been adopted into classrooms has led to understandable uncertainty among educators, leaders, and families who are asking important questions. These groups are concerned with the data that is being collected, who owns AI-generated work, and what responsibilities schools have when students and educators use these tools.

As both an attorney and educator who has spent more than eight years researching, teaching, presenting, and writing about AI, I have worked with schools across K–12 and higher education that are navigating these exact questions. The legal implications of AI are not barriers to innovation, but I consider them to serve as guardrails that assist schools with adopting technology responsibly. The key is protecting students, educators, and institutions and staying informed. Understanding the legal landscape and any potential legal implications as a result of the use of AI in classrooms helps schools move forward with confidence rather than hesitation.

Why AI and the Law Matter in Education

AI relies on data in order to function effectively. When it comes to schools, this means having access to student information, classroom artifacts, writing samples, images, and even data related to physical or behavioral information. Intent is not the deciding factor. Even if educators believe they are only sharing minimal information, that does not clearly identify a student, family member, or colleague, even seemingly harmless details can qualify as personally identifiable information (PII).

I’ve often spoken about some examples like referencing a favorite restaurant, a local landmark, a pet’s name, or an extracurricular activity, all of which could make a student identifiable when combined with other data points. Last year, an educator in one of my sessions said, “Enough stars to still form a constellation,” and that has stuck with me and I have shared it in each AI and the Law session I have done. That is why evaluating tools carefully and teaching students to do the same are essential. I often reference scavenger hunts, in that educators should not feel like they are on a scavenger hunt when trying to find out what happens to their information. We need transparency from vendors so that educators are aware and informed.

AI is also changing how decisions are made in schools. With many advances, there are recommendation systems, automated feedback tools, and predictive analytics that can influence learning pathways, grading practices, and student support services. Having an understanding of how these systems work and how they should be used responsibly is becoming part of educators’ and school leaders’ professional responsibilities.

Key Laws That Shape AI Use in Schools

There are several important laws that guide how schools must approach AI.

FERPA (Family Educational Rights and Privacy Act) protects the privacy of student education records. When schools use AI-powered platforms that process student work or store learning data, they must ensure that these tools comply with FERPA requirements and clearly define how student information is handled.

COPPA (Children’s Online Privacy Protection Act) applies to students under the age of 13 and requires parental consent before collecting personal information through online services. Because many AI tools rely on user-generated input, COPPA compliance becomes especially important in elementary and middle school settings.

GDPR (General Data Protection Regulation), although it is a European Union law, is relevant to U.S. schools that use tools developed by companies that operate internationally. There are many platforms created outside of the United States that educators may be unaware of, and so understanding GDPR is essential. Many platforms now include cookie permissions and data-use customization features in response to GDPR requirements. These protections often benefit schools globally.

Schools should also consider state-level student data privacy laws, which are increasingly changing the expectations for vendor contracts, third-party integrations, and data retention timelines. District leaders and IT teams play an essential role in ensuring these requirements are addressed before tools are introduced into classrooms.

Data Privacy and Vendor Responsibility

AI tools require large amounts of data to function effectively. That data may be used to improve the tool itself, train additional models, or support integrations across connected platforms. Even when a tool states that it does not share user data, connected services or embedded features may still interact with stored information. I was asked two years ago, when speaking at LACOE in California during my AI and the Law session, if someone should “trust the platform when it says they do not share or store the data.” My instant answer was “No.” And it was for this exact reason.

Before introducing any AI platform in schools, educators and school leaders should review terms of service, privacy policies, and compliance documentation. Look for references to FERPA, COPPA, and additional privacy protections. Look for the date that the privacy policy was most recently updated. Districts should also confirm whether vendors use student information to train future AI models and whether contracts clearly define ownership and storage expectations.

This is where collaboration with district technology teams becomes essential. Responsible adoption is not an individual teacher’s decision. It is a system-level responsibility supported by leadership, policy teams, and instructional staff working together. Collaboration is key.

Transparency Builds Trust With Students and Families

Responsible AI adoption depends on communication. Families deserve clear explanations of the tools being used, the data being collected, and how that data is protected.

When working with students under age 13, written parental consent may be required. Even when it is not legally necessary, providing families with opportunities to ask questions strengthens trust and partnership. Transparency also empowers students. When students understand how AI systems work and the risks they may pose, they become more thoughtful digital citizens and more informed users of technology.

Schools that proactively communicate expectations for AI use are more likely to build families’ confidence and reduce misunderstandings about how these tools support learning.

Accessibility, Equity, and Emerging Legal Considerations

As schools adopt AI tools, accessibility and equity must remain part of the conversation. Laws such as Section 504 of the Rehabilitation Act and the Americans with Disabilities Act (ADA) require that digital learning tools be accessible to all students. If AI-powered platforms create barriers rather than support access, schools may face compliance concerns. We need to consistently audit the tools we are using. It must be an ongoing process.

Schools must also consider how AI intersects with Title IX responsibilities, especially with the rise of deepfake technology, which leads to new risks related to harassment and impacts student safety. Policies must be in place for addressing the misuse of generative AI tools and clearly define expectations and response procedures.

Algorithmic bias and fairness are important parts of the conversation. Schools should evaluate whether AI systems produce equitable outcomes across student groups and whether automated recommendations influence learning opportunities in unintended ways. Responsible implementation includes ongoing evaluation, not just initial approval.

Teaching Digital Citizenship With AI Literacy

Legal compliance alone is not enough. Students must also develop the skills needed to evaluate AI responsibly.

Developing skills in these areas means recognizing risks such as deepfakes and misinformation, bias in generated content, and cyberbullying that is supported by emerging technologies. Schools that integrate digital citizenship with AI literacy will guide students to become thoughtful participants in technology-rich environments rather than passive users who lack true understanding and AI literacy skills.

Clear expectations around appropriate use and academic integrity help students develop ethical decision-making skills that extend beyond the classroom.

Supporting Schools and Organizations Through AI and Legal Guidance

As AI adoption accelerates, schools will benefit from having a structured support system in place that connects legal awareness with thoughtful and purposeful classroom practice. Through my work with educators in K–12 and higher education, I provide professional learning experiences that help schools understand privacy requirements, implement responsible AI strategies, and align classroom applications with policy expectations.

My work includes keynote presentations, workshops, district leadership sessions, curriculum planning support, and customized training focused on data privacy, academic integrity, digital citizenship, accessibility considerations, vendor evaluation, and responsible AI adoption. Each training is tailored to address specific needs, ranging from introductory awareness sessions to deeper implementation planning and leadership strategy development.

In addition to supporting schools and universities, I work with organizations across other sectors to explore how to implement AI responsibly while remaining aligned with legal expectations and organizational values. Many industries face the same challenges that educators do, surrounding uncertainty about data privacy, questions about intellectual property ownership, concerns about transparency in decision-making systems, and the need to develop policies that support ethical innovation. My work helps organizations evaluate tools thoughtfully, identify potential risks early, and create practical guardrails that support responsible adoption rather than reactive compliance.

Organizations in healthcare, legal services, workforce development, nonprofit leadership, and corporate training environments are increasingly recognizing the importance of AI literacy for employees at every level. Through workshops, leadership sessions, and strategy conversations, I help teams understand how AI systems work, the legal considerations that may be applicable to them, and how to build cultures of responsible use that prioritize trust, security, and human judgment.

Moving Forward With Confidence

Artificial intelligence is already shaping how students learn, communicate, and prepare for future careers. The goal is not simply to adopt AI tools, but to adopt them responsibly. And this is where our work as educators comes in and why we need to dive in and learn with and guide our students.

When educators understand the legal landscape of privacy, accessibility, intellectual property, and ethical use, they can make informed decisions that support innovation and student protection. With thoughtful planning, collaboration, and transparency, schools will create learning environments where AI enhances opportunities while maintaining trust, safety, and integrity across the entire school community.

I work with schools and organizations, both in person and virtually, to support thoughtful and responsible AI implementation through professional learning, curriculum design, and resource development specific to educators, students, and families, using a common language. I have also collaborated with leadership teams to develop AI guidance frameworks, classroom-ready activities, and policies that reflect legal considerations.

The resources created help districts communicate clearly and consistently with families about AI use, support educators in building AI literacy, and provide students with age-appropriate strategies for using AI safely, ethically, and responsibly. By combining legal insight with classroom experience, I help schools move beyond uncertainty toward sustainable systems that include clear expectations, transparency, and actionable guardrails for responsible use.

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks

************ Also, check out my THRIVEinEDU Podcast Here!

Join my show on THRIVEinEDU on Facebook. Join the group here.

Brewing Better Teaching: Learning Latte with Learning Genie

Dr. Rachelle Dené Poth Leave a comment

In collaboration with Learning Genie: All Opinions are my own

If there’s one thing I value in education, it’s authentic and honest conversations about what’s really happening in classrooms. The January and February Learning Latte meetups with Learning Genie were exactly that.

These meetups offered grounded, reflective discussions about teacher preparation, real classroom challenges, and how tools like Learning Genie can support, rather than replace, our professional judgment. And with a focus on UDL, Portrait of a Graduate, and Differentiation, Learning Genie offers everything in one solution!

Here are some takeaways:

January: Teacher Preparation, TPA Season & the “Idea Inventory”

January’s Learning Latte meetup focused on the importance of and value in truly listening to educators.

One of the most important parts of the conversation came from Robert Mayfield, who addressed a challenge that many of us have seen and experienced firsthand: pre-service teachers during the TPA season.

If you’ve worked with student teachers, you may notice the impact of getting started and how they feel about it. They can be:

  • Overwhelmed
  • Time-strapped
  • Focused on and worried about meeting rubric requirements
  • Relying heavily on pre-existing lesson plans
  • Trying to survive and balance all of the new tasks that come with our work.

Robert highlighted a key concern: When pre-service teachers rely too heavily on ready-made lessons, they may miss the opportunity to build their own instructional toolkit. That’s where the concept of an “idea inventory” comes in.

What Is an Idea Inventory?

An idea inventory is not just a folder of saved lessons over the course of the school year or years. It is a curated, reflective collection of strategies used, activity ideas, differentiation techniques, assessment approaches, and adaptable frameworks.

The inventory includes:

  • Multiple entry points for learners
  • Flexible scaffolding ideas
  • Variations for different readiness levels
  • Culturally responsive examples
  • Developmentally aligned strategies

All of this is especially critical in early childhood and elementary settings, where differentiation is foundational.

The January discussion reinforced what I have noticed when working with other educators. New teachers need to understand how to differentiate effectively and have the resources they need to support their work.

This is where Learning Genie can make an impact. It supports reflective planning and enables teachers to connect observations to instruction. It makes differentiation visible, which is essential.

A good question to consider is: “How do we help future teachers think like designers of learning?”

Learning Genie supports that mindset shift. When teachers reflect on student observations and use those insights to plan intentionally, it helps build professional capacity and confidence. And it builds community when educators and companies connect!

Enjoy learning from and sharing feedback with Dr. Gene Shi

February: Classroom Voices & Real-World Experience

February’s Learning Latte offered a clear view and many insights into a lived classroom experience.

February’s meetup included educators Sandy Ferguson and Gina Ogilvie. Sandy began by sharing classroom experiences, grounding the conversation in real practice rather than theory.

I always want to know the stories of other educators, the why behind the choices in activities, strategies, and tools used in their classrooms, and the impact.

Many conversations about edtech center around the features, dashboards, and integrations. But I’ve long said and heard it in their message. What matters is the impact it makes inside the classroom.

Highlights from Sandy and Gina

  • Authentic Application
     The conversation centered on how Learning Genie supports educators’ daily work. It helps with lesson planning, documentation, and communication, and it is easy to navigate and use.
  • Alignment with Developmental Needs
     In early childhood, especially, the tools we use must align with how children learn best.
  • Teacher Confidence
     When educators feel supported in leveraging technology to provide meaningful and personalized instruction, their confidence increases. Teacher confidence impacts classroom climate and positively boosts student engagement and interest in learning.

What stood out is that technology works best when it amplifies teacher expertise, not when it replaces it. Shifting from replacement to the enhancement and transformation potential of these tools is important. And when it enhances our students’ learning opportunities. Check out this video to learn more.

Connecting January and February: A Common Theme

Both sessions highlighted:

  • The importance of reflective practice
  • The need for intentional differentiation
  • The value of building professional capacity over time
  • The role of tools in supporting rather than shortcutting professional growth

January focused on building the foundation by helping new teachers develop their idea inventory. February provided a clear view of what this looks like in action, with experienced educators using tools to refine their professional practice and deepen students’ learning impact.

Final thoughts

The best educational tools don’t give us answers. I think that they help us ask better questions.

How are we differentiating? What patterns are we noticing? How are we building our “idea inventory?”

How are we supporting new teachers before they burn out?

Use these questions as a focus point, and I think you will find that a tool like Learning Genie is a catalyst for transformational and meaningful instruction and learning.

Enjoy sharing about Learning Genie in Pittsburgh and other conferences and school PD sessions!

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks

************ Also, check out my THRIVEinEDU Podcast Here!

Join my show on THRIVEinEDU on Facebook. Join the group here.

Building Tomorrow’s Skills Today: Career-Connected Learning

Dr. Rachelle Dené Poth Leave a comment

Technology is evolving at a pace we have never experienced before. There have been so many changes in the world through artificial intelligence, automation, data science, and other emerging technologies. These are reshaping industries in real time. As an educator, I feel this shift daily, and I try to push myself to keep learning and looking for opportunities to do more for my students. The challenge is no longer simply preparing students for a job. It’s knowing how to prepare them for careers that may not even exist yet and also supporting them as they develop a variety of skills to be prepared.

When I think about how to prepare students for the uncertainty around the world of work, I look at insights from the World Economic Forum and its Future of Jobs research. While AI was listed as #3 for 2027 and is now listed as #1 for 2030, the other rankings reinforce what we already know: adaptability, analytical thinking, creativity, and resilience are becoming increasingly important in our world.

If we cannot predict the careers that will exist five or ten years from now, the best we can do is prepare students to be flexible thinkers, confident problem-solvers, and ethical technology users. And this is why I believe that career-connected learning is essential.

Redefining “Career Ready”

When I thought about “career ready,” I aligned it with strong academics plus essential skills of communication, collaboration, and the other “soft skills.” These are still relevant and necessary for success, however with the changes in technology, there are other areas that I believe must be addressed and become part of preparing students to be career-ready. remain foundational. Now, I include:

  • Digital and AI literacy
  • Ethical reasoning in technology use
  • Data awareness and cybersecurity knowledge
  • The ability to evaluate and question AI-generated information
  • Comfort navigating complex digital systems

Students need to understand how to use tools like generative AI. And that means using it to enhance and not replace their own learning. They can learn to brainstorm with AI, analyze outputs for bias or inaccuracy, and be able to recognize when human judgment must be at the forefront, providing consistent oversight. Research and interviews of employers have shown that employees will be expected to work alongside AI systems. That preparation has to begin in our classrooms from K through 12 and beyond.

Career-connected learning ensures students understand how what they are studying connects with real careers and real-world impact.

Why This Matters Now More Than Ever

According to projections highlighted by the World Economic Forum, millions of roles will be displaced due to automation, while millions of new ones will emerge. This is not the first time. More than 100 years ago, thousands of traffic light controllers in New York were displaced due to automation. They did not all lose their jobs, some shifted into others. And many of these new positions demand higher-order thinking, digital agility, and ethical decision-making.

I like to talk about some career options that minimally existed a few years ago:

  • AI prompt engineer
  • Ethical technologist
  • Data privacy consultant

These are some of the many growing fields of work and some which are increasing because of AI. I think about how we are preparing our students and believe that career-connected learning will help to show the connections between classroom content and workforce relevance. I also believe this is something that can be done in every classroom and in all content areas.

What Does Career-Connected Learning Look Like?

Career-connected learning is more than occasional career days. It is something that is embedded into daily instruction, not an extra element. It can include a variety of possibilities, such as:

  1. Project-based learning connected to community or industry challenges. (Builds relevance for students).
  2. Integration of AI, data science, and emerging technologies
  3. Authentic problem-solving rooted in real scenarios
  4. Partnerships with local businesses, universities, or nonprofits
  5. Coding, AI, and cybersecurity challenges

Through opportunities like these, we can foster the development of student agency. When students understand how what they are learning connects to real opportunities, it sparks curiosity, increases students engagement and motivation. Learning is more purposeful, authentic, and meaningful.

Some ideas:

Artificial intelligence is an area that students need to understand. They need to know, how AI systems function, how to evaluate the outputs, how bias can be embedded, and what the ethical responsibilities are for using AI. In career-connected classrooms, AI might be used to discuss and explore how the legal field, healthcare and business industries, and schools are using AI tools. They can engage in role-playing that focuses on ethical decision-making. The goal is for students to leverage AI as a partner, rather than a replacement in learning.

STEM is a great option to focus on career-connected learning. In my own classroom experiences, I’ve seen what happens when students combine AI tools with engineering design, language learning, and problem-solving. When students train image classifiers and then collaborate, problem-solve, and evaluate where the model fails, they are not just learning about the technology, they are developing skills in critical analysis and bias detection.

Cybersecurity is another area that is seeing tremendous growth. Students need to understand how their data is collected, protected, and in some cases, misused. There are hundreds of thousands of cybersecurity roles unfilled in the United States alone, yet many students and perhaps even educators, have not heard of careers such as a threat analyst or a security operations engineer. Lessons on cybersecurity can be done in all classes. Here are some examples that I have shared:

  • English: Analyze phishing emails as persuasive writing
  • History: Debate privacy vs. security
  • Math: Explore encryption models
  • Technology: Investigate AI-related vulnerabilities

Career-ready also means a Human-Centered Future

With all of the technology, especially with AI and automation, we have to keep focused on what makes us uniquely human. Technology will continue to evolve, even faster than it has been. But empathy, integrity, resilience, and collaboration will always matter and we need to make sure that students develop these skills.

With career-connected learning opportunities, we will prepare students for success in the future, even in careers that don’t exist. We will offer opportunities for them to discover their interests and purpose and be prepared to embrace the changes they will encounter and be successful.

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle received her Doctorate in Instructional Technology, with a research focus on AI and Professional Development. In addition to teaching, she is a full-time consultant and works with companies and organizations to provide PD, speaking, and consulting services. Contact Rachelle for your event!

Rachelle is an ISTE-certified educator and community leader who served as president of the ISTE Teacher Education Network. By EdTech Digest, she was named the EdTech Trendsetter of 2024, one of 30 K-12 IT Influencers to follow in 2021, and one of 150 Women Global EdTech Thought Leaders in 2022.

She is the author of ten books, including ‘What The Tech? An Educator’s Guide to AI, AR/VR, the Metaverse and More” and ‘How To Teach AI’. In addition, other books include, “In Other Words: Quotes That Push Our Thinking,” “Unconventional Ways to Thrive in EDU,” “The Future is Now: Looking Back to Move Ahead,” “Chart A New Course: A Guide to Teaching Essential Skills for Tomorrow’s World, “True Story: Lessons That One Kid Taught Us,” “Things I Wish […] Knew” and her newest “How To Teach AI” is available from ISTE or on Amazon.

Contact Rachelle to schedule sessions about Artificial Intelligence, AI and the Law, Coding, AR/VR, and more for your school or event! Submit the Contact Form.

Follow Rachelle on Bluesky, Instagram, and X at @Rdene915

**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks

************ Also, check out my THRIVEinEDU Podcast Here!

Join my show on THRIVEinEDU on Facebook. Join the group here.