Tag edtech

The Elective Course Effect: How Non-Major Requirements Can Shape STEM Identity

Dr. Rachelle Dené Poth Leave a comment

Guest post by Tessa Dodson. Opinions expressed are those of the writer.

Walk through almost any school, and you’ll hear similar suggestions that students interested in STEM should take as many math, science, and technology courses as possible. While this advice is well-intentioned, it overlooks an important truth.

Students don’t develop a strong STEM identity solely by taking more STEM classes. They develop it by becoming confident thinkers, effective communicators, creative problem-solvers, and lifelong learners. Many of those qualities are cultivated through nonmajor requirements, especially courses in languages, social sciences, and humanities.

Why Electives Matter More Than You Think

When students enroll in electives, they often encounter learning experiences that differ from their core STEM coursework. Language classes strengthen communication and cultural understanding, and arts courses encourage creativity, observation, and design. History and philosophy ask students to evaluate evidence, construct arguments, and understand context.

Meaningful elective experiences often carry over into STEM learning. Instead of treating the arts and STEM as competing priorities, schools that use interdisciplinary learning can help students develop broader and more holistic skills.

Think of a student working on an engineering design project. Technical calculations are important, but so are presenting ideas to classmates, working through disagreements within a team and adapting solutions based on feedback. These are precisely the types of skills students develop through thoughtfully designed courses.

1. Building Better Problem Solvers

Many STEM challenges have no single correct answer. Scientists evaluate competing evidence, and engineers balance trade-offs. Medical researchers consider ethical implications alongside scientific data. Modern workplaces require individuals who can analyze information and make informed decisions, and 88% of employers look for candidates with evidence of problem-solving on their resume.

Students become stronger problem solvers when they learn to approach complex questions from multiple perspectives. Humanities courses frequently ask students to interpret ambiguous information, defend positions with evidence, and recognize nuance. Arts courses encourage experimentation, revision, and innovation. Language learning develops adaptability and pattern recognition while requiring students to navigate unfamiliar situations. Many colleges prefer that incoming students have at least two years of study in a world language.

Problem-solving habits and skills transfer naturally into STEM disciplines. When schools intentionally preserve nonmajor requirements, they create more opportunities for students to practice flexible thinking before they encounter technical challenges.

2. Improving Communication Skills

One misconception about STEM careers is that success depends primarily on technical expertise. In reality, today’s scientists, engineers, and technology professionals spend considerable time communicating. They explain findings to clients, present proposals to leadership teams, collaborate across departments, mentor colleagues, and translate technical concepts for nontechnical audiences.

However, students rarely develop these skills through technical coursework alone. Humanities courses can strengthen organization and evidence-based reasoning. Foreign language courses improve listening, perspective-taking, and communication. These professional capabilities complement technical knowledge and make it more impactful. According to 37 executives from the chemical and pharmaceutical industries, collaboration and communication are among the most valuable nontechnical skills for scientists.

3. Boosting Creativity That Drives Innovation

Innovation rarely comes from repeating established or old practices. Instead, breakthrough ideas emerge when individuals connect concepts across different disciplines. Some of history’s most influential innovators drew inspiration from art, literature, philosophy, or music alongside scientific inquiry.

Today’s technology companies value employees who combine analytical thinking with creativity. Arts education plays an important role in promoting this mindset. Whether students are composing music, designing visual media, or performing theater, they learn to receive feedback, experiment with new ideas, and embrace revision as part of the creative process. Those same habits support engineering design cycles, software development, scientific experimentation, and product innovation.

Personal Growth Extends Beyond Career Preparation

Education serves a purpose that is beyond preparing students for a particular profession. It also helps young people develop into curious, empathetic, and resilient individuals who can adapt to changing circumstances throughout their lives.

Literature courses invite students to consider perspectives different from their own. Philosophy asks students to consider ethical questions that rarely have simple answers. The arts foster self-expression, perseverance, and confidence through creative exploration.

By providing these experiences, you can contribute to students’ personal growth, helping them become more reflective, emotionally aware, and open to new ideas. They also strengthen qualities like resilience, adaptability, and intellectual curiosity, which are just as valuable in a STEM career as technical expertise.

By providing opportunities for students to explore interests beyond their primary field of study, you reinforce the idea that education is about growing into capable, well-rounded people, not simply preparing to become future employees.

More Students Will See Themselves in STEM

Some students discover their interest in STEM only after connecting technical concepts with their personal passions. For example, a student who enjoys storytelling may become interested in data visualization. A musician may discover acoustical engineering, or a visual artist may pursue user experience design.

When you encourage students to explore subjects beyond their intended major, you create opportunities for students to combine their passions rather than choose between them. As students begin to see how different subjects intersect, they are more likely to view STEM as a field where their unique talents and perspectives are valued.

This broader, more inclusive approach is especially important for students who may not identify with traditional STEM careers. By demonstrating that there are many ways to contribute to STEM, you can help more students develop the capabilities and confidence that are essential to building a strong STEM identity.

What Educational Leaders Can Do

Consider how your school’s policies support interdisciplinary learning. Start by examining whether scheduling practices unintentionally discourage students from taking electives outside their intended majors. When every period is devoted to technical coursework, students may lose valuable opportunities for broader, well-rounded development.

Next, you can encourage collaboration across departments. Invite STEM and humanities teachers to co-design interdisciplinary projects that address authentic problems. Students might combine environmental science with persuasive writing, computer science with graphic design, or engineering with ethics.

You can also celebrate diverse pathways into STEM. Highlight alums and professionals whose careers show the importance of interdisciplinary experiences. Share examples of computer scientists who value philosophy or healthcare professionals whose language skills improve patient care. These stories can help students understand that success in STEM does not require limiting themselves to technical coursework.

Rethinking Success

The pressure to optimize courses for college admissions or career readiness can unintentionally limit students’ educational experiences. Valuable learning also takes place in classes outside a student’s major.

When schools value nonmajor requirements, they focus on developing adaptable thinkers rather than just technically skilled graduates. This broad approach helps students communicate effectively, think creatively, collaborate well, and become resilient learners. They gain confidence in academic mastery and in their ability to address real-world problems.

About Tessa

Tessa Dodson is the Senior Writer of Classrooms.com, where she researches and covers educational policy, professional development, teacher support systems, and integration challenges that K-12 and higher education institutions may face. She aims to research and provide actionable insights for students, educators, school administrators, and other leaders.

About Rachelle’s 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.

About Rachelle

Dr. Rachelle Dené Poth is a Spanish and STEAM: What’s Next in Emerging Technology Teacher. Dr. Rachelle Dené Poth is an edtech consultant, presenter, attorney, author, and teacher of Spanish and STEAM: Emerging Technology. Rachelle has a Juris Doctor degree from Duquesne University School of Law and a Doctorate in Instructional Technology. Rachelle’s focus was on the need for professional development for educators, specific to Artificial Intelligence. Rachelle specializes in Artificial Intelligence, AI and the Law, AI and Healthcare, Cybersecurity, and STEM. She has more than 8 years of experience teaching and presenting on AI in her classroom, as well as working with educators worldwide.

Rachelle is currently serving as the Grant Coach for an initiative through ISTE+ASCD and Pinterest. Rachelle works with a Task Force from 12 districts in the United States and assists with policy revision, professional development, and the design of digital wellness resources for students, educators, and families.

Rachelle provides professional development related to AI policy and implementation to school districts, universities, and organizations. She also presents and provides keynotes on AI at state, national, and international events and in schools. Rachelle also provides AI training for other industries, including business, healthcare, and legal fields.
Rachelle is an ISTE-certified educator and recipient of the ISTE Making IT Happen Award and several Presidential Awards for volunteer service to education. Rachelle received the EdTech Trendsetter Award from EdTech Digest in 2024 and 2026.

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: Weaving Strategies and Activities Into Any Content Area.” She has written curricula and courses on AI for all levels.

She is also a blogger for Defined Learning, EdTech K12, Edutopia, Getting Smart, and Tech & Learning. She is the host of the ThriveinEDU podcast, ISTE’s Learning Unleashed podcast, and The Lift by Amazon on BAM Radio Network. Contact Rachelle for your event!

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AI in Education vs. AI Education, Part V

Dr. Rachelle Dené Poth Leave a comment

Rethinking Learning and Assessment in the AI Era

Throughout this series, I have focused on the distinction between AI in education and AI education, the importance of moving from policy to practice, and the steps schools can take to build more intentional and responsible systems around AI.

But another question continues to come up in conversations with educators:

What happens to teaching and assessment when students have access to AI?

AI can brainstorm, summarize, explain, revise writing, solve problems, generate examples, create images, and produce polished responses in seconds. If it can complete part of an assignment, or sometimes most of it, we need to ask a more important question:

What are we actually assessing?

The focus should not simply be on whether students can produce a finished product. It should be on whether they understand, can explain, apply, evaluate, and think independently. Throughout this series, I have focused on the distinction between AI in education and AI education, but as I started winding down the short series, I recognized another question that continues to come up in conversations with educators:

What happens to teaching and assessment when students have access to AI?

I have heard it frequently, and it is a question that deserves attention because AI is powerful. It can brainstorm, summarize, explain, generate examples, revise writing, solve problems, create images, and produce responses within seconds.

So my thoughts are that if AI is able to complete part of an assignment, or potentially most of it, as educators, we need to really consider what it is that we are assessing. The answer should not be whether a student can produce a finished product (focus on process over product), but whether they understand, can explain, can apply, can evaluate, and can think on their own.

Start With the Learning Goal

Before deciding whether students should use AI, educators need to identify the instructional purpose of the learning experience.

  1. What should students know?
  2. What should they be able to do?
  3. What thinking should they demonstrate?
  4. What skills are we trying to develop?

Once those questions are clear, it is easier to decide what role, if any, AI should play in our instruction.

If the purpose of an assignment is to assess a student’s ability to organize and communicate their own ideas, then using AI to generate the response may interfere with the learning goal. If the purpose is to evaluate sources, revise weak arguments, compare perspectives, or improve a draft, AI may have an appropriate supporting role.

Instead of asking only, Can students use AI? I think a better question is:

What role should AI play in this particular learning experience?

Assess the Thinking, Not Just the Product

For many years, I was focused on the tools and final products to evidence learning. Whether it was an essay, a presentation, a project, or a worksheet. But now that we are in the AI era, we have to reconsider those final products. A final product does not always provide enough insight into what a student actually understands. We know that students may create great representations of their learning via final products, which they did without the use of AI, however, we may want more evidence of their learning along the way. Those products still matter, but in an AI era, we may need more evidence of the thinking behind them.

Some examples may be to ask students to provide:

  • drafts
  • annotations
  • reflection questions
  • process journals
  • checkpoints
  • revisions
  • explanations of decisions
  • demonstrations of how they reached their conclusions

These are not new strategies, but they are increasingly becoming more important, especially with AI. If the purpose of an assignment is student thinking, then the learning experience needs to make that thinking visible.

Decide What Role AI Should Play

One of the most important instructional decisions educators can make is determining the appropriate role of AI in an assignment.

In Part III, I shared an AI-use continuum that schools and educators can use as a starting point.

AI use may be:

  • not permitted
  • permitted with educator approval
  • permitted with disclosure
  • encouraged for a defined purpose
  • intentionally embedded in the assignment

I believe that the same continuum becomes especially useful when we think about assessment.

For example, AI might not be appropriate during an assessment designed to measure independent writing skills. We want students to develop student agency and be independent thinkers.

But AI could be intentionally included in an assignment that tasks students with critiquing an AI-generated response, identifying errors, comparing perspectives, or improving a weak argument. Even taking five minutes to have ChatGPT or any other LLM generate inaccuracies around a concept and then tasking students with critically evaluating it will make an impact on their learning.

Students might use AI to brainstorm ideas, but are still expected to create and defend the final product themselves. Being able to demonstrate learning, make thinking visible, and grasp the concepts and content they need to be successful, are essential.

Another idea is for students to partner with AI to receive feedback, rather than answers, and then explain which suggestions they accepted, which they rejected, and why. An activity like this really helps students to build those critical thinking and digital discernment skills. We always want to connect back to the learning goal and align with our instructional purpose.

Build in Evidence of Student Thinking

One of the best ways to preserve student ownership is to create opportunities for students to explain their thinking. It does not need to take a lot of time. It is possible through simple questions and activities. Some examples are to ask students:

  • Why did you make this choice?
  • How did you arrive at this conclusion?
  • What evidence supports your answer?
  • What did you change during the process?
  • What did AI contribute? What did you contribute?
  • What did you disagree with?
  • What did you verify? How?
  • Are you able to explain this without the use of AI?

These are just some of the guiding questions that can promote visible thinking and help students become more aware of their own learning process. Metacognition comes into play here.

For example, instead of asking students only to submit a final essay, educators might ask them to submit an outline, a short draft, be transparent about where they used AI, explain a revision they made, and briefly defend their final argument.

Here are some content area examples:

Science: Students might compare an AI-generated explanation with a verified source and break down and discuss where the response is incomplete or inaccurate.

Math: Students could analyze an AI-generated solution to a problem and explain whether the reasoning is correct.

Social Studies: Students could compare how AI explains the same historical issue from varying perspectives.

World Languages: Students might evaluate an AI translation and explain where meaning, tone, or cultural context changes and where there might be misunderstandings.  I have done this with my own students.

In learning, the final product still matters, but so does the process that produced it.

Productive Struggle

AI can make many tasks faster, but faster does not always mean better for learning. An additional concern is that because AI can produce answers so quickly, students will not experience productive struggle.  Students need opportunities to think through difficult problems, experience uncertainty, make mistakes, revise, and discover that their first idea is not always their best one.

If AI removes every challenge, it may also remove part of the learning.

I have explained to my own students about the importance of productive struggle. When they question me, I tell them that they need time to think through a difficult problem, to experience uncertainty, to make mistakes, to revise, and sometimes realize that the first idea is not always the best one.

If we rely on AI too much, it takes away the challenge and may also take away some of the opportunities for learning. And for this reason, completing things quickly and efficiently should not always be the goal in education. I’ve tried to convey that sometimes the process matters more than the speed. Sometimes finding the answer when working alone builds confidence. Sometimes struggling with a sentence or solving a math problem helps students develop the skills of resilience, collaboration, and student agency.

I consider this in my work and ask educators to consider which struggles are unnecessary barriers for students and which are essential parts of learning. We know that AI can help remove barriers, but pushing it further, it should not remove every challenge for students.

From AI Efficiency to AI Dependency

One of the biggest concerns I see developing is not simply whether students are using AI, but whether they are becoming overly reliant on it.

There is a difference. Think about the difference between using AI efficiently and relying on AI to do the thinking. Efficiency means selecting and using a tool or even a strategy to support a learning task while still maintaining ownership, judgment, and understanding. But on the other side, overreliance or dependency happens when students become unable or unwilling to complete the task without the tool.

Students need our guidance. In my work this past year with schools across the country, this is what I have heard from them. They want us to help them develop awareness and develop a checklist that they can work through to understand when they should and shouldn’t use AI. Some questions they can consider are:

  • Could I do this without AI?
  • Did AI help me think, or did it do the thinking for me?
  • Am I able to explain this in my own words?
  • Did I verify the information? How can I?
  • What decisions did I make? (not the AI)
  • What did I actually learn, and can I explain it to another person?
  • Would I still understand this if the tool were unavailable?

Questions like this will help students build more than AI literacy skills. They will build self-awareness, which is important because we know that responsible AI use is not just about knowing how to use a tool, but it is also about knowing when to use it, how much to rely on it, and when to step away from it.

Assessment is Evolving

Concerns came right away. “The kids are going to cheat.” “It’s the end of assessments as we know them.”  But AI does not mean we need to throw assessments aside. I believe that it means we have to be very clear about what we are assessing. Sometimes students ask simple questions. For example, as a Spanish teacher, can I give them the English word and have them match it with the Spanish word? But with AI, I have been thinking through this more. Here are my thoughts:

If we are assessing recall, there may be times when AI should not be available.

If we are assessing reasoning, students may need to explain their process.

If we are assessing creativity, students may need to show how their ideas developed.

For research skills, students may need to verify sources and defend why they trust them.

There are a lot of things to consider in our work as educators when it comes to AI. If AI is intentionally part of the learning experience, then evaluating how students use AI may itself have to become part of the assessment. I present these questions in sessions that I do and when talking with student focus groups. I ask them:

  1. Did you question the output?
  2. Do you recognize limitations?
  3. Can you identify bias?
  4. Are you able to verify claims?
  5. Can you make decisions about what to use and what to reject?

Students need to develop these skills because they are important, especially when considering their preparation for a successful future.

Where AI in Education and AI Education Meet

Throughout this series, I have focused on AI in Education and AI Education. Now, in this fifth and final part (I think), is where the distinction between them becomes especially important.

AI in education asks what role AI should play in the learning experience: whether students should use it, when, for what purpose, and under what expectations.

AI education asks whether students understand what AI is doing: whether they can evaluate its output, recognize limitations and bias, verify information, and make responsible decisions about its use.

Assessment brings both together because educators must evaluate not only what students produce, but also the thinking, judgment, and learning that led to it.

Students should not only demonstrate that they can use AI. They should demonstrate that they can think with it, think beyond it, and think without it when needed.

My Final Thoughts

Now that we have so many possibilities available because of AI, it does not make the learning process less important. It hopefully makes it more important and leads us to be more intentional in our instructional planning.

Educators have always been responsible for designing learning experiences that help students develop knowledge, skills, confidence, and independence, all of which will lead to future success.

AI challenges us to be more intentional and design learning experiences that make students’ thinking visible. We need to guide students to recognize the difference between using AI for enhancement versus replacement. And something that I’ve heard more frequently is not trading the efficiency that AI can promote for dependency on AI.

I think we are past whether or not AI belongs in education. It is here. Research and predictions for future work show that it will continue to be in demand. So as educators, we must prepare our students and ourselves to use it ethically and responsibly. We have to stay focused on how we can use it so it does not result in the loss of essential skills like critical thinking, productive struggle, reflection, creativity, and human judgment that make learning truly authentic and meaningful.

How we do this is an important question to consider as we continue moving forward in an AI-shaped world.

Thanks for reading this series and for the feedback.

Please subscribe to my ThriveinEDU newsletter to stay informed. And contact me for more information.

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 or email Rdene915@gmail.com, for my training and speaking services.

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AI in Education vs. AI Education, Part III

Dr. Rachelle Dené Poth Leave a comment

The First 5 Steps on the Roadmap for Moving Forward

In Part I, I explored the difference between AI in education and AI education and why both are essential if we want to prepare students for a rapidly changing world.

In Part II, I focused on the gap between policy and practice and introduced six areas that schools and districts should address as they move from conversation to implementation:

  • Establish clear, shared expectations
  • Invest in educator readiness
  • Teach AI literacy intentionally
  • Align AI use with digital wellness
  • Engage stakeholders
  • Review, measure, and adjust

Now, we have to consider how schools actually begin this work. In this part of the series, I will share the first five steps of the roadmap moving forward.

There is no single plan that will fit every school or district. Community needs, resources, policies, student populations, and levels of readiness will vary across school systems within states and across the country.

Given the pace at which AI is advancing, schools should not wait until they have every answer to every question asked. They just need a starting point, a shared process, and a willingness to learn and adjust along the way. And to be successful, they need to be involved in thoughtful and consistent conversations.

Having the Right People at the Table

AI implementation should not be the responsibility of one person, department, or leadership team. I have said this many times when presenting at conferences and working with school districts. AI implementation requires multiple perspectives.

In the past year, schools that have formed an AI Task Force and included members from different backgrounds and roles in education have had the most success.

School and district task forces should include:

  • classroom educators from varying grade levels and content areas
  • students
  • families
  • school and district leaders
  • curriculum and instructional technology staff
  • special education and student-support representatives
  • data privacy, cybersecurity, or legal personnel
  • community or workforce partners

Having members from each group leads to a more thorough evaluation and a deeper understanding of AI from different perspectives.

Educators understand classroom realities. Students understand how AI is being used. Families can ask questions, express concerns, and support needs.

On the tech side, technology and legal professionals can help address privacy, security, contracts, age requirements, and compliance with relevant laws. School leaders can connect the work to curriculum, professional learning, communication, and long-term planning.

Connecting these voices creates a stronger foundation for decisions and helps prevent policies from being created in isolation. And it does not require a large task force to be impactful. The goal is to make sure the people affected by the decisions have a meaningful role in shaping them.

Here are the steps that I recommend for schools. During my workshops, speaking events, and writing, I try to help build out policies and systems that will have an impact.  I also expand on each of these and create interactive experiences to help educators and students, develop skills and become more knowledgeable about AI and responsible use of it.

Step 1: Understand What Is Already Happening

Before schools write new policies or purchase new tools, they need to understand their current status.

Students and educators may already be using AI in a variety of ways, including:

  • brainstorming
  • lesson planning
  • generating questions
  • summarizing information
  • creating drafts
  • translating text
  • producing images
  • providing feedback
  • researching ideas
  • completing assignments

Some uses may be appropriate and productive, while others may raise concerns about privacy, accuracy, bias, academic integrity, or overreliance. My work with AI and the law addresses these concerns.

Schools cannot create effective expectations without first understanding what is happening. Over the past year, sitting with student focus groups, moderating panels, and visiting classrooms have all helped me to gain additional insights into what schools look like in an AI era.

Schools need to know where confusion exists, what educators need, what students already understand, and where gaps in guidance may be creating risk. The information gathered should guide the next steps.

Step 2: Define Shared Principles

Before writing detailed rules, schools should identify the principles that will guide AI use. These principles provide a common foundation across classrooms and grade levels, even when specific expectations vary. Common and shared language around AI is essential.

Possible shared principles might include:

  • Human judgment remains essential.
  • Learning remains the priority.
  • AI should support thinking rather than replace it.
  • AI use should be acknowledged when appropriate.
  • AI-generated content should be evaluated for accuracy, bias, and relevance.
  • Technology use should align with student well-being and instructional purpose.
  • Access and expectations should be equitable.

These principles can help educators make decisions when a new tool, classroom scenario, or student question arises. And they are especially important because schools cannot anticipate every possible use of AI. A policy can provide boundaries and shared principles that help people make responsible decisions within those boundaries.

Step 3: Create Clear Expectations for Use

One of the most common challenges educators face is determining when AI use should be allowed. The appropriate role of AI depends on the learning goal, the age of the student, the type of assignment, the information being shared, and the amount of independent thinking required. Schools may benefit from creating an AI-use continuum. For example:

AI Use Is Not Permitted

Students are expected to complete the task independently because the goal is to assess their individual knowledge, thinking, or skill.

AI Use Requires Educator Approval

Students may use AI only after discussing the intended purpose with the educator.

AI Use Is Permitted With Disclosure

Students may use AI for specific parts of the process but must explain how it was used.

AI Use Is Encouraged for a Defined Purpose

AI is intentionally used for brainstorming, comparison, feedback, revision, simulation, or another identified learning goal.

AI Use Is Embedded in the Assignment

Students are expected to interact with AI, evaluate its output, identify limitations, and reflect on its role in their work.

This type of continuum gives educators more flexibility and helps students understand that responsible use depends on context. The expectation should always connect to the purpose of the learning experience.

Step 4: Prepare Educators Through Practical Professional Learning

Educator readiness is one of the most important parts of implementation and it was the focus of my doctoral research two years ago.

Teachers should not be handed a policy and expected to figure out the rest on their own. They need time to explore, ask questions, test tools, and express concerns. Educators need opportunities to examine questions such as:

  • What is the learning goal?
  • How might AI support the learning?
  • How might it interfere with the learning?
  • What should students be expected to do independently?
  • What privacy or safety concerns exist?
  • Would another approach be more effective?

Having conversations and addressing questions like these will help educators build confidence and consistency.

Step 5: Teach AI Literacy Across the Curriculum

AI education should not only be addressed in a computer science class. AI literacy should be developed across subjects and grade levels. Some examples are:

  • In language arts, students might compare a human-written passage with an AI-generated one and analyze voice, evidence, and credibility.
  • In social studies, they might examine how bias appears in responses about historical events.
  • In science, students might verify an AI-generated explanation against trusted scientific sources.
  • In math classes, students might evaluate whether an AI-generated solution is correct and explain where the reasoning succeeds or fails.
  • In world language classes, students might compare AI translations and identify where meaning, tone, or cultural context is lost.

With activities like these, we can teach students how to question, evaluate, and make decisions about the use of AI and its accuracy.

These first five steps provide a practical starting point for schools and districts working to move from uncertainty to intentional action. By bringing the right people together, understanding current AI use, defining shared principles, creating clear expectations and common language, preparing educators, and building AI literacy across the curriculum, schools will establish a stronger foundation for responsible implementation. But the work does not end here.

In Part IV, I will continue the roadmap by exploring how schools can connect AI use with digital wellness, communicate clearly with students and families, and create an ongoing process for reviewing, measuring, and adjusting their approach.

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. Contact me via bit.ly/thrivineduPD or email Rdene915@gmail.com, for my training and speaking services.

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Image for AI in Education, generated by ChatGPT

AI in Education vs. AI Education, Part II: From Policy to Practice

Dr. Rachelle Dené Poth Leave a comment

What Must Happen Next

In Part I of this series, I shared the importance of distinguishing between “AI in Education” and “AI Education”, and why both must move forward together if we want to prepare students for a rapidly changing world.

That distinction is critical.

But it is not enough.

Across the conversations I continue to have with legislators, district leaders, and educators, the next question is becoming clearer:

What does this actually look like in practice?

Because the challenge right now is not awareness.

It is implementation.

Guidelines are being drafted. Policies are being written. Conversations are happening at leadership levels.

But in classrooms, the reality is often very different.

Teachers are still asking:

What should I allow? How do I design lessons so that students are still thinking and not reliant on AI? What should I do if students use AI in ways I did not anticipate? How do I explain responsible use to students and families?

This gap between policy and practice is one of the most important challenges we face. Policies can set direction, but practice determines the impact.

A policy may explain what is permitted, restricted, or expected. However, educators still need support to translate those expectations into lesson design, assessment, classroom conversations, and decisions about student use. I’ve mentioned this before in my Leading Forward in AI series, and I share it again. We need consistency, a shared language, and a classroom connection. Without that connection, even well-written policies may have little effect on classroom practice.

What I’m Seeing in Classrooms

In the schools I work with, students are already using AI tools—often more than adults realize. Students are:

  • brainstorming ideas
  • asking questions
  • exploring concepts
  • testing tools independently

And it is happening now, so this is not a future issue. And it is no longer a question of whether students will use AI, but rather whether they will be guided in how to use it responsibly.

Without guidance, students experiment in isolation and rely on AI too much, and possibly for the wrong reasons. With guidance, they learn to question outputs, verify information, protect their data, acknowledge their use of AI, and recognize when a tool is supporting their thinking rather than replacing it.

That difference matters.

Moving From Restriction to Responsibility

One of the most common responses to emerging technology has been restriction. Conversations about blocking access, limiting use, and controlling the learning environment of students have been happening even more.

In some situations, restrictions are necessary. Schools must consider student privacy, age requirements, academic integrity, instructional purpose, accessibility, and whether a tool has been properly vetted. But restriction cannot be the entire strategy.

We know that students will use AI outside of the classroom. While approaches that focus on restriction may be in the best interest of protecting students, they do not prepare students for long-term success.

In the future, students will use AI in higher education, the workplace, and in everyday decision-making, which is why they need guidance. By focusing only on restrictions, we miss out on the opportunity to teach responsibility. And responsibility prepares students for real-world environments.

With opportunities in our classrooms, we can support students as they learn about AI. Students need to know how to evaluate AI-generated information, disclose when they have used a tool, protect personally identifiable information (PII), recognize bias, and understand when AI use is appropriate.

What Effective Implementation Requires

From my experience working with districts across the country, successful implementation does not come from a single policy or a single training. It comes from strategic alignment.

Continue reading on LinkedIn

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.

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AI in Education vs. AI Education: Why Policy and Practice Must Move Together (Part I)

Dr. Rachelle Dené Poth Leave a comment


Posted via my LinkedIn page and ThriveinEDU newsletter.

Over the past year, I’ve had the tremendous opportunity of working with district leaders, educators, students, families, and even policymakers across the country. Throughout this work, one question has come up repeatedly:

Is there a difference between AI in education and AI education?

I will pause…to let you consider.

For me….

My answer is always yes.

Although the terms are often used interchangeably, they represent two distinct priorities. AI in education focuses on how artificial intelligence is being implemented in teaching, learning, and school and district operations.

AI education focuses on helping students understand artificial intelligence itself. They know how it works, how it generates information, how it influences decisions, and understand that it will shape their futures. These two phrases are not the same, and not having a clear distinction creates gaps in policy, instruction, and student preparedness.

When people hear “AI in education,” they often think about tools and how they are being used. One example I have shared is a student using AI to generate a first draft of an essay. AI in education asks: What classroom expectations and policies should guide this use?

AI education asks: Does the student understand how the AI generated that response, what biases may exist, and how to evaluate its accuracy?

In my work, I’ve come up with a series of questions as starting points for conversations:

  • How are schools using AI platforms?
  • What tools are allowed, and who is vetting them?
  • How are educators integrating AI into instruction?
  • What policies are in place or are needed to guide its use?

These are just a few of the important questions that need to be considered and answered specifically for AI implementation. However, there is another conversation that is equally important to have in our schools, and the focus is on AI education.

AI education is more than tools. It is about preparing students to understand artificial intelligence, how it works, how it processes and generates information, how it influences decisions, and how it will impact their future.

Both are important, and from the many opportunities I’ve had to work with educators and speak with students, it seems there is confusion. We need to align on the meaning of these terms so we can fully provide the learning support our students and schools need.

What I’ve Seen in Schools

Across the districts I have supported, interest in artificial intelligence has increased. During the past year, I’ve seen the mindset shift from one of hesitation to exploration.

Educators are curious. Students are experimenting. Leaders are asking thoughtful questions and also seeking guidance for their schools.

But when it comes to AI implementation, whether school- or district-wide, it is not always consistent, and consistency matters.

Some schools are exploring AI tools without clear guidance, while others are restricting its use out of caution. And some are writing policies without fully understanding and addressing classroom realities. And this is why I recommend that administrators involve educators, students, and families in the conversations or create a task force specific to AI. By doing this, schools can better understand how AI is being used, the support students receive at home and at school, and what their needs are. Because in many places, students are using AI outside of school without learning how to use it responsibly, which creates yet another gap.

It creates a gap between access and understanding and between use and responsibility. However, by establishing a policy and ensuring consistent implementation, we can work toward closing the gap and making meaningful progress in an increasingly AI-surrounded world.

This Also Matters for Legislators

Artificial intelligence is not a future issue. It is a present reality shaping:

  • How students learn
  • How educators teach
  • How information is created and consumed
  • How future work will be defined

Legislators throughout the country are increasingly being asked to make decisions about data privacy, student protection, AI tool access, digital equity, and workforce readiness. These are important decisions that carry real implications for classrooms.

But having an effective policy requires more than regulation. It requires understanding how AI is actually being used and how it should be used in educational environments.

I’ve reached out to and spoken with legislators from different states over the past six months, and some of the common thoughts around policies are:

-Policies that focus only on restrictions will fall short.

-Policies that ignore implementation will create confusion.

And policies that fail to address AI education will leave students unprepared.

Why Does This Matter for Educators

Educators are at the center of the shift in classroom instruction, especially now with AI. Educators are adjusting to technological changes, navigating new tools, fielding student questions, balancing innovation with responsibility, and working to support student learning in real time.

My own research showed that many educators are being asked to adapt without the necessary guidance or support. I’ve been asked many times:

  • “Do I need to teach about AI?”
  • “What should I allow in my classroom?”
  • “How do I know if students are using AI appropriately?”
  • “How do I design lessons where students are still doing the thinking and not having AI do the work for them?”

These are not simple questions with simple answers. They are instructional, ethical, and professional questions. And these questions require communication and preparation, and not just policy. It is a process and an iterative one.

The Risk: Where Do We Focus?

If we focus only on AI in education, we risk:

  • over-reliance on tools
  • inconsistent expectations
  • unclear boundaries for educator and/or student use
  • missed opportunities for deeper learning

If we focus only on AI education, we risk:

  • teaching theory without application
  • disconnecting learning from real-world tools
  • failing to prepare students for how AI is actually used now and the future possibilities

The solution? It’s not about choosing one over the other, but rather finding a way to align both in our schools, because that is how we guide students toward success.

What Alignment Looks Like in Practice

Across the districts I support, I see the most progress when schools intentionally connect AI in education with AI education. Schools making progress have:

Clear Expectations for Use: Students and educators understand when and how AI can be used, and what responsible use looks like.

Instruction That Builds Understanding: Students are not just using AI. They are learning how it works, the importance of questioning it, and how to evaluate its outputs.

Professional Learning for Educators: Teachers have the time, support, and guidance to meaningfully integrate AI into instruction. And this is consistent and ongoing throughout the year.

Policy That Reflects Practice: Policies are designed with classroom realities in mind and focus on guidance rather than restriction. Schools have committees or task forces to be better informed and able to adjust as needed.

Ongoing Conversations: Schools engage students, educators, and families in discussions about AI, digital wellness, and responsible technology use.

AI Literacy Is Workforce Literacy

The students graduating now will enter a workforce shaped by automation, intelligent systems, and rapidly evolving expectations regarding their skill sets.

According to global workforce trends and the World Economic Forum’s Top 10 Skills for 2030, technological literacy, AI understanding, and cybersecurity awareness are among the most in-demand skills for the coming decade.

And when it comes to AI literacy, we must remember that it is not just about technical knowledge. It is about:

  • critical thinking
  • ethical decision-making
  • information evaluation
  • adaptability
  • communication

These are the essential, in-demand skills that must be intentionally taught in our classrooms through a variety of learning opportunities and supports.

We Share Responsibility

Preparing students for an AI-shaped future requires collaboration between:

  • Educators
  • School leaders
  • Policymakers
  • Families
  • Communities

Each group plays a role in preparing students and guiding them toward future success.

Legislators can create frameworks that support responsible implementation and that focus on protecting students.

Educators can design learning experiences that build understanding and confidence and model appropriate and safe use of AI for students in their classrooms.

School leaders can align systems, expectations, and communication.

When everyone is involved in navigating the AI space together, it creates coherence.

Artificial intelligence is changing education. It is moving fast, however, when it comes to our work, the most successful systems are not those that move the fastest. Success comes with clarity. Clarity about expectations. Clarity about purpose. Clarity about how technology supports learning rather than replacing it.

Across the country, I have seen schools and districts working to build that clarity and consistency. They are asking questions and working together to find answers as a start. They are not seeking perfection, just ongoing progress.

Preparing students for the future

We cannot prepare students for the future by focusing only on the tools they use today. We must also prepare them to understand the systems shaping their world.

And the decisions we make now, at both the classroom and policy level, will determine whether students are ready not just to use technology, but to think critically, act responsibly, and lead in a world where artificial intelligence is part of everyday life.

That is the work ahead, and it is definitely the work worth doing.

AI in education matters, but AI education matters just as much. Think about your school and district. Are these distinctions clear? Stay tuned for part II in the series, with actionable strategies, and contact me to provide training for your school.

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. Contact me via bit.ly/thrivineduPD for my training and speaking services.

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 in AI: From AI Conversations to Sustainable Systems (Part IV)

Dr. Rachelle Dené Poth Leave a comment

In my last article, I shared 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. That work has provided me with insightful information and meaningful opportunities to learn from educators, students, and families.

Throughout these conversations, one message continues to stand out:

We cannot begin, and we cannot stay focused only on the tools and the tech.

We must move forward.

The Shift Schools Must Make Now

In Part II, I emphasized that educator readiness is the foundation of successful AI implementation. Schools that prioritize supporting educators are the ones seeing the most progress. And it starts with leadership and consistency. But readiness alone is not enough.

What I have learned from working with school Task Forces across the country is that they have had many conversations around AI, screen time, and tech use. They have explored the possibilities and understand the urgency with these topics, but they also have a similar question.

What do we do now? And this is where I believe that leadership matters most.

Moving From Conversations to Systems

Across the districts I continue to work with, I see a clear difference between schools that are talking about AI and schools that are leading with AI. I also see a difference between AI in education and AI Education. I recently met with a State Representative in Pennsylvania, and we had this conversation as well. The difference I’ve noticed and that we discussed is not just access to tools. It is about the presence of a system. Schools making meaningful progress are not relying on isolated efforts when they find time. Instead, they are building structures with a lens on consistency, clarity, and sustainability.

The system they are developing is focused on having:

  • clear expectations for the responsible use of all technology
  • consistent messaging across classrooms and grade levels
  • ongoing professional learning opportunities with follow-up support
  • shared language for students, staff, and families
  • opportunities for student voice and feedback

When these are part of the conversation, AI implementation becomes less about individual decisions, which leads to inconsistency,  and becomes more about a goal for collaborative and collective progress.

Consistency Builds Confidence

One of the most common challenges I have been hearing from both educators and students is inconsistency. I’ve met with student groups, interviewed educators, spoken with parents, and heard similar comments from educators and parents across the country.

In one classroom, the use of technology, and specifically AI, is encouraged. In another, it is restricted. In one classroom or school, the expectations are clear and known to all. In another, they are undefined or inconsistent.

Continue reading on LinkedIn and subscribe to my newsletter there as well.

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

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.

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

Tool, Companion, or Supplemental Brain? What AI Will Be Depends on YOU!

Dr. Rachelle Dené Poth Leave a comment

Guest post by Robert W. Maloy and Torrey Trust

What are GenAI technologies, and what do we want them to become? Right now, GenAI is an educational chameleon, aggressively marketed as an indispensable learning companion, an academic partner, and a labor-saving tool; and at the same time, widely critiqued as a dangerous source of misinformation and biased responses, an environmental degrader, and a privacy invader. Since GenAI is all of these things and more, how do we use these tools appropriately and thoughtfully?

What GenAI is and what it will become depends on YOU – how you think about its roles, use it in your teaching and learning, and describe its functions to others.

Let’s look at two currently popular descriptions and uses of GenAI: 1) GenAI as a companion; 2) GenAI as a productivity-enhancing tool.

First, GenAI is widely described and used as a supportive “companion” or helpful “partner.” The Harvard Business Review (2025) reported that therapy/companionship was the number one way people were using GenAI in 2025. An alarming number of teens acknowledge that GenAI chatbots are their virtual companions, even though this technology can exploit youngsters’ emotional needs in ways that lead to self-harm and other risks (Common Sense Media report, Robb & Mann, 2025). One of the key problems here is that GenAI is NOT human, and it is not even intelligent (at least in the way humans perceive and describe intelligence).

The Key Takeaway: Using terms like “partner” or “companion” to describe GenAI technologies humanizes tools that are not designed to provide the support, guidance, and level of intelligence that actual humans can provide.

Second, GenAI technologies are widely presented as productivity-enhancing, time-saving, efficiency-increasing tools for people to use to improve their lives. “Use ChatGPT to make life easier,” declared a recent email advertisement, where all one had to do was “just tap a chat to start.” Personal and professional productivity is also one of the top ways people are using GenAI technologies – from writing emails and reports, to planning vacations and meals, to studying for exams; and it is certainly true that GenAI technologies can do all these things and so much more really fast. Yet, personal autonomy, creativity, and agency is lost when one uses GenAI technologies to automate activities they formerly did without it.

The key takeaway: Avoid talking about GenAI as automating work and think directly about how it can augment or supplement your activities as a teacher and a learner.

So If not a human-like companion or a productivity-enhancing automation tool, then how can we think about the role of GenAI in education? We believe that GenAI is best used when it augments teaching and learning, kind of like the way a caddie in golf enhances the golf experience. As such, we offer a metaphor of GenAI as a caddie; but again remind you that it is not an actual caddie and we are not trying to humanize this tool.

Professional golfers and their caddies on the LPGA, PGA, and more than 20 professional golf tours worldwide offer a metaphor for thinking about, describing, and using GenAI. Each pro golfer has a caddy who carries their clubs and walks alongside them when they play competitive tournaments. sharing ideas and information about the shots they are playing. For instance, until recently, LPGA player Brooke Henderson’s caddy was her older sister, Brittany; PGA player Xander Schauffele’s caddy is Austin Kaiser (his college golf teammate at San Diego State University).

Caddies have detailed information about the course and provide suggestions and feedback about what shots to hit with which clubs. They help keep track of the pace of play and how conditions of the course may be changing due to wind, weather, and time of day. However, it is the golfer who remains totally in charge of the outcomes of the game. Caddies do not hit the golf ball; golfers do not always do what the caddy suggests. It is the golfer who must make decisions, hit the shots, and deal with consequences, both positive and negative, in terms of performance and score. Caddies are there to augment the golf experience and outcome.

When it comes to teaching and learning, GenAI can be that source of information, ideas, or inspiration like a caddie; and it is the teacher who must determine what to do with that information. They have the expertise; they understand their classroom dynamics and contexts; they know their students, their topic, their grade level, and their community.

The key is for the teacher to resist the temptation to automate their work by turning it entirely over to a GenAI technology, because in this case GenAI is in control of the shots, rather than the teacher. It is as if professional golfers let their caddies choose the club and then hit the ball for them. This is even more problematic when it comes to using GenAI to automate tasks. In our metaphor, the caddie is a human who has expertise and has played golf before; however, GenAI is not a teacher, has never taught, and has no idea what teaching is. Turning over any tasks to a tool that does not have any expertise in education can become really problematic. Teachers must maintain agency and exert control, deciding when to accept, when to reject, and when to modify whatever ideas and information the GenAI provides.

So, returning to our original statement, what GenAI is and what it will become depends on YOU – how you think about its roles, use it in your teaching and learning, and describe its functions to others. What do YOU want GenAI to be?

If you’re looking for ways to use GenAI to augment teaching and learning, check our the free online companion of our new book: GenAI and Civic Engagement: 75+ Cross-Curricular Activities to Empower Your Students published by ISTE (International Society for Technology in Education) or explore the bonus learning plans we’ve published on this blog: Learning Plans for Supporting Student Agency in the Age of AI & Learning Plans for Exploring Civic Issues with GenAI.

Nearly 50 years ago, at the outset of the computer revolution in schools, Seymour Papert asked: Will computers program the child, or will educators create the conditions where children program computers? For Papert then, as for us today in the age of GenAI, using technology remains a question of human control and user agency. GenAI can provide amazing resources, but it is essential that you retain your decision-making and personal creativity. Only then will the results be truly yours.

Torrey Trust, Ph.D., is a Professor of Learning Technology in the College of Education at the University of Massachusetts Amherst. Her work centers on empowering educators and students to critically explore emerging technologies and make thoughtful, informed choices about their role in teaching and learning. Dr. Trust has received the University of Massachusetts Amherst Distinguished Teaching Award (2023), the College of Education Outstanding Teaching Award (2020), and the International Society for Technology in Education Making IT Happen Award (2018), which “honors outstanding educators and leaders who demonstrate extraordinary commitment, leadership, courage, and persistence in improving digital learning opportunities for students.” More recently, Dr. Trust has been a leading voice in exploring GenAI technologies in education and has been featured by several media outlets in articles and podcasts, including Educational Leadership, U.S. News & World Report, WIRED, Tech & Learning, The HILL, and EducationWeek. www.torreytrust.com

Robert W. Maloy is a senior lecturer in the College of Education at the University of Massachusetts Amherst, where he coordinates the history teacher education program and co-directs the TEAMS Tutoring Project, a community engagement/service learning initiative through which university students provide academic tutoring to culturally and linguistically diverse students in public schools throughout the Connecticut River Valley region of western Massachusetts. His research focuses on technology and educational change, teacher education, democratic teaching, and student learning. He is co-author of AI and Civic Engagement: 75+ Cross-Curricular Activities to Empower Your Students, Transforming Learning with New Technologies (4th edition); Kids Have All the Write Stuff: Revised and Updated for a Digital Age; Wiki Works: Teaching Web Research and Digital Literacy in History and Humanities Classrooms; We, the Students and Teachers: Teaching Democratically in the History and Social Studies Classroom; Ways of Writing with Young Kids: Teaching Creativity and Conventions Unconventionally; Kids Have All the Write Stuff: Inspiring Your Child to Put Pencil to Paper; The Essential Career Guide to Becoming a Middle and High School Teacher; Schools for an Information Age; and Partnerships for Improving Schools.

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.