An AI professional development session can introduce teachers to several tools and still leave them unsure about what to do in their next lesson. Knowing how to generate a worksheet is useful. Deciding whether that worksheet is accurate, appropriate, accessible, and worth using requires a different kind of preparation.
When planning AI professional learning, I would begin with a teaching problem teachers recognise: adapting a reading task, reviewing feedback, designing an assessment, or helping students evaluate AI-generated claims. That gives participants a clear purpose for trying a tool and a basis for judging its contribution.
The AI professional development planning template below helps school leaders, instructional coaches, and teacher educators connect that purpose to practical activities, evidence of learning, and classroom follow-up. It is my suggested planning resource, informed by the sources listed at the end. It has not been formally validated.
What Should AI Professional Development Include?
UNESCO’s AI Competency Framework for Teachers provides a useful starting point. It covers a human-centred mindset, AI ethics, foundations and applications, pedagogy, and professional learning. This gives planners a broader view of teacher development than proficiency with individual products.
The design of the learning experience matters too. Darling-Hammond, Hyler, and Gardner’s review identifies recurring features of effective teacher professional development, including content focus, active learning, collaboration, modelling, coaching, feedback, reflection, and sustained learning opportunities. Their review concerns teacher professional development generally; it does not establish the effectiveness of this particular AI template.
Learning Forward’s Standards for Professional Learning also place attention on evidence, implementation, and learning design. Together, these sources support a plan that connects an initial workshop to supported classroom use and review.
AI Professional Development Planning Template
Copy the table into a shared planning document. Complete the purpose, learning outcome, and evidence sections before selecting a tool.
| Planning area | Questions and fields to complete |
|---|---|
| Session details | Title: ___. Facilitator: ___. Date and duration: ___. Follow-up date: ___. |
| Participants and context | Who is attending? Which subjects and grade levels do they teach? What experience, concerns, access needs, and school expectations should shape the session? |
| Teaching need | What specific problem are teachers addressing? What evidence suggests it deserves attention? |
| Teacher learning outcome | By the end, teachers will be able to ___. Use an observable action such as evaluate, revise, compare, design, or justify. |
| AI competency focus | Which knowledge, judgement, or ethical issue will teachers develop? Identify a relevant UNESCO competency area where useful. |
| Classroom connection | Which curriculum outcome, teaching task, or student need will anchor the work? What thinking must remain with the teacher or student? |
| Tools and materials | Which locally approved tool, sample output, curriculum document, or rubric is needed? Prepare sample outputs for participants who cannot access the tool. |
| Privacy and participation | What information may participants enter? Use fictional or specifically approved materials. Check local requirements, account conditions, and accessibility before the session. |
| Modelled example | What will the facilitator demonstrate? Include the reasoning used to check, revise, or reject an output. |
| Participant practice | What will teachers actually do? Specify the task, materials, and product they will create or evaluate. |
| Feedback and discussion | Who will review the work? Which criteria will guide feedback? How will participants consider different defensible decisions? |
| Evidence of teacher learning | What will show that participants met the outcome? Examples include an annotated output, revised task, or explanation supported by curriculum criteria. |
| Classroom trial | What small use will teachers try? With which class, over what period, and with what support? |
| Follow-up and evaluation | What evidence will teachers bring back? Who will facilitate review? What would justify continuing, revising, or stopping the approach? |
| Responsibilities and resources | Who arranges access, supports participants, answers policy questions, and schedules follow-up? What time or funding is required? |
The privacy and participation section draws on UNESCO’s guidance concerning human agency, data protection, inclusion, and the educational suitability of generative AI. Local policies and approved procedures should determine the specific arrangements.
Related: AI Disclosure Statement Examples for Students
Completed Example: Evaluating AI-Generated Reading Questions
Here is an illustrative plan for a teacher-facing use of AI. The activities and timings are suggestions, not a research-tested programme.
| Planning area | Example |
|---|---|
| Teaching need | Teachers want additional reading questions but need to judge their alignment with the text and intended learning. |
| Participants | Middle-school teachers with mixed experience using generative AI. |
| Learning outcome | Teachers will evaluate an AI-generated question set, revise unsuitable questions, and explain their decisions using the text and curriculum outcome. |
| Competency focus | AI pedagogy, ethical judgement, and understanding the limitations of generated content. |
| Materials | A permitted reading passage, curriculum outcome, prepared AI question set, and evaluation checklist. |
| Modelled example | The facilitator checks whether a question is answerable from the text and whether it elicits the intended reading skill. |
| Practice | Teachers annotate the question set, identify weaknesses, revise selected questions, and explain what they retained or removed. |
| Feedback | A colleague checks alignment, answerability, clarity, accessibility, and assumptions about students’ background knowledge. |
| Evidence of learning | An annotated original, revised questions, and a short rationale. |
| Classroom trial | Teachers use the reviewed questions in one suitable lesson, if school expectations permit. |
| Follow-up | Teachers discuss where students struggled, which responses showed the intended thinking, and what needs further revision. |
In this example, producing more questions is only one part of the work. The session gives teachers time to examine what those questions ask students to do.
Sample 90-Minute AI Professional Development Agenda
This agenda introduces the approach. Classroom trials and follow-up should be scheduled separately.
| Time | Activity |
|---|---|
| 0–10 minutes | Introduce the teaching need, learning outcome, and participation arrangements. |
| 10–25 minutes | Model the task and explain the decisions involved in evaluating an output. |
| 25–50 minutes | Participants complete a practical task using live tools or prepared examples. |
| 50–65 minutes | Exchange feedback and revise the work against agreed criteria. |
| 65–80 minutes | Plan a small classroom trial and identify evidence to collect. |
| 80–90 minutes | Review learning, identify support needs, and confirm the follow-up date. |
How Can You Tell Whether the Professional Development Helped?
An exit survey can tell you whether teachers found the session useful. To examine learning, also look at what participants produced and the reasoning behind their decisions.
For the reading-question example, can teachers identify a question that the passage cannot answer? Can they revise it while preserving the intended learning demand? Can they explain why an apparently polished question is unsuitable for their students?
Follow-up should examine classroom experience as well. Teachers might bring a revised resource, notes about its use, and appropriately handled evidence of student responses. Look for both benefits and difficulties. Increased confidence, attendance, and tool use do not by themselves establish improved teaching or student learning.
The plan should leave room for a teacher to conclude that a proposed use of AI adds little value. That decision can demonstrate careful professional judgement.
Sources Behind This Planning Template
These sources inform different parts of the template. The professional development review supplies general research evidence; the frameworks and guidance supply planning principles. None validates this exact template.
- Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO.
Useful for selecting competency goals that include ethics, human agency, pedagogy, and professional learning.
Read the framework. - Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017). Effective teacher professional development. Learning Policy Institute.
Supports the emphasis on active learning, modelling, collaboration, feedback, coaching, and sustained opportunities to learn.
Read the report. - Learning Forward. (n.d.). Standards for professional learning.
Useful for planning learning activities, implementation support, and the use of evidence to review professional learning.
Explore the standards. - Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO.
Informs the attention to human agency, privacy, inclusion, and the educational suitability of AI use.
Read the guidance.
