What Effective AI Professional Learning Should Look Like
A single workshop or training will not adequately prepare educators for everything they need to know and do in regard to AI.
Throughout my work with educators and district leadership teams across the country, I have seen growing interest in and a need for AI professional learning. Educators want to understand what AI is, how it works, and how it can support their work, but they also want practical guidance about data privacy, academic integrity, bias, responsible classroom use, and appropriate student use. They need clear and consistent guidance that supports their practice.
A single workshop or training will not adequately prepare educators for everything they need to know and do. I have been passionate about this work for the past four years since starting my doctoral research, which focused on the need for effective AI professional development for educators.
A key takeaway from my research was the importance of ongoing, relevant, and supportive professional learning. My work with schools and educators has continued to reinforce that finding.
Effective AI professional learning cannot simply be about showing teachers the latest tools. Tools change, policies evolve, and new concerns emerge. If PD focuses primarily on a platform, what educators learn may become outdated before they have an opportunity to apply it in their practice. We need to build knowledge, confidence, and skills that educators can transfer regardless of what AI tools are available.
Start With Purpose, Not With Tools
For years, when I provided PD, I often focused on the tools. Over time, I recognized that technologies change, and what matters most is understanding the why behind using technology. The same is true with AI. Begin by asking why an educator might use AI rather than asking which AI tool they will use.
When I work with educators, I challenge them to identify specific needs in their own practice. Do they want to differentiate instruction? Create more accessible materials? Provide feedback? Redesign an assessment? Generate ideas? Reduce time spent on repetitive tasks? Starting with an instructional need keeps the focus on teaching and learning rather than technology for technology’s sake.
Providing guiding questions helps educators decide when AI is useful and when it is not. Effective professional learning should guide teachers to ask:
- What is the learning goal?
- What thinking should students do independently?
- Where might AI provide meaningful support?
- What would be gained or lost by using AI?
- What happens if AI completes too much of the work?
These questions will remain relevant even as the technology changes.
Connect Learning to Real Classroom Practice
Just as relevance makes learning more meaningful for students, professional learning needs to connect to educators’ actual roles and responsibilities. A kindergarten teacher, high school science teacher, school counselor, special education teacher, instructional coach, and district administrator may ultimately use the same AI platform, but they will not necessarily use it in the same way.
Professional learning should include realistic scenarios for grade levels and content areas, and provide an opportunity for participants to create something they can use right away. Teachers might revise an assignment, develop expectations for student AI use, evaluate an AI-generated response, design a differentiated resource, or create a lesson that requires students to verify AI output.
In my sessions, educators have found it valuable to work through scenarios with colleagues rather than just learn what AI can do. Some scenarios I use include a student using an unapproved chatbot, evaluating a biased AI-generated response, considering the consequences of exposed student information, or addressing suspected AI-assisted student work.
Discussions enable educators to collaborate and think about what they would do, consider the benefits and cautions of AI, and learn together. These conversations help them leave with a clearer understanding of AI and specific next steps for their own learning and practice.
Differentiate the Professional Learning
We differentiate learning for students, so we should think similarly about professional learning for educators. Everyone needs a solid foundation in AI literacy, but not everyone needs the exact same training.
Effective professional learning should provide opportunities for educators to explore how AI connects specifically to their work. Classroom teachers may need more support with instructional design, assessment, AI literacy, and appropriate student use. Administrators may focus more on leadership, policy, implementation, and communication. Technology teams may need more time on data privacy, security, and vendor vetting.
Professional learning should also account for differences in experience and comfort with AI. Two teachers in the same department may have very different starting points. One may already be experimenting with AI while another is still learning the basics. Providing opportunities for choice and time to learn with colleagues meets educators where they are without overwhelming them.
Address Privacy, Law, and Ethics
Responsible AI use cannot be an add-on at the end of professional learning. Privacy, safety, ethics, accessibility, and legal considerations need to be woven throughout the experience.
As an educator and attorney, I frequently work with schools that have questions about student data, approved tools, vendor agreements, copyright, accessibility, and academic integrity. Many educators have expressed not having enough guidance about what information can be entered into an AI platform or how to determine whether a tool is appropriate for students.
Educators need practical guidance rather than a list of laws without classroom context. Questions to consider:
- Why does entering identifiable student information into an unapproved platform create risk?
- What do age requirements mean for student access?
- What should educators look for in privacy policies?
- Why must AI-generated content be reviewed for bias and accuracy?
Schools need consistent expectations. Professional learning should connect directly to district policies and show what those policies mean in practice.
Make Professional Learning Active and Ongoing
In schools, a keynote or introductory workshop helps to build awareness and momentum, but it should serve as the beginning of the learning process rather than the entire strategy. Ongoing support might include workshops, content- or grade-level coaching, professional learning communities (PLCs), office hours, model lessons, and ongoing conversations.
The goal is not to become an AI expert. Educators need enough understanding and confidence to make informed decisions, recognize when AI adds value and when it does not, and guide students to do the same. When this is possible, we move from simple awareness of AI and its possibilities to intentional implementation.
Include Students and Families
AI professional learning should help educators understand how students are using these technologies. Students may be employing AI to brainstorm, translate, summarize, study, create images, or complete assignments. Some students may understand the limitations of these tools, while others may trust the output without questioning it.
Ask students how they are using AI. What do they think is permitted? What do they consider cheating? When do they believe AI helps them learn? When might they be relying on it too much? What do they know about the information they are sharing with AI tools? Student voice can reveal gaps between school policies and actual classroom practices. It can also help schools develop expectations that are realistic, understandable, and responsive to student needs.
Families should be part of the conversation as well. Parents and caregivers may have questions about why AI is being used, what tools students can access, how their children’s information is protected, how schools define appropriate use, or how AI changes the expectations for student work. Professional learning should prepare educators to answer these questions.
Build Systems That Can Adapt
Effective AI professional learning should be part of a larger system that involves leadership, policy, curriculum, technology, families, and students. District leaders must communicate a clear vision, provide guidance about approved tools, and reflect on decisions as the technology changes. Schools should also evaluate whether professional learning is making a difference in educators’ confidence, classroom decisions, assessment practices, and understanding of privacy expectations.
The measure of successful AI professional learning goes beyond the number of tools educators explore during a workshop; it is what happens after the workshop. Are educators asking better questions? Are they protecting student information? Are they making intentional choices about when AI adds value?
The tools in use today may not be the tools used next year, which is why understanding the fundamentals of AI and how it enhances learning is essential before diving into specific tools. Effective professional learning is not an experience that tells educators to embrace every new tool or avoid AI completely. The best learning helps educators understand AI, its capabilities, and guides them to approach it with curiosity, caution, and confidence, with the human side of education at the center.
Source: https://www.techlearning.com/technology/ai/what-effective-ai-professional-learning-should-look-like
