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Professional Development

Professional Development Around AI

Ongoing professional learning is essential for K–12 educators and library staff to integrate AI responsibly and effectively. Training keeps teams current on emerging tools, ethics, and instructional opportunities—while keeping students at the center.

How to use this page: Start with the featured WISELearn collection for turnkey decks, then use the PD strands in the accordion below to plan 60–90 minute sessions. When you are ready to go deeper, explore the External PD Resources & Links section at the bottom of the page to extend and customize your local plan.

Featured collection
Turnkey decks and activities you can adapt locally. (Membership required for the Digital Learning group.)

These six strands align with the PD agendas in the accordion below. Click a bubble to jump to a strand.

 

DPI Guidance & Professional Development Framework

Wisconsin DPI promotes a human-centered, ethics-driven approach to AI. Below are PD strands with concrete agendas, facilitator notes, and success criteria you can run as 60–90 minute sessions or stack into a full day.

Understanding AI & Machine Learning Basics

Build shared vocabulary, see how models learn, and examine limitations, ethics, and social impacts.

Segment Time Facilitator Notes
Warm-up: “What AI is / isn’t” sticky notes 10 min Collect misconceptions; define AI vs. rules-based tools.
Hands-on demo: Teachable Machine or “How Machines Learn” 15–20 min Teachable Machine shows pattern learning; discuss overfitting, dataset bias, and who is (and is not) represented in the data.
Prompting lab: improve an explanation for Grade 5 & Grade 10 15 min Compare outputs; note hallucinations; model fact-checking and citation.
Equity & privacy lens mini-case 10 min How biased data and poor privacy practices affect students with disabilities, multilingual learners, and other underrepresented groups.
Exit ticket & resources 5 min 1 thing learned, 1 concern, 1 classroom try-tomorrow.

Artifacts: shared slide deck copy, demo models, prompting examples. Success criteria: staff can explain “training data,” name at least two risks, and describe a verification step they would use with students.

Integrating AI into Subject Areas

Plan small, standards-aligned moves for ELA, Math, Science, Social Studies, CTE, and Libraries.

Discipline Try-Tomorrow Activity What to Watch For
ELA Compare human vs. AI poem; annotate voice, structure, originality. Students disclose AI help and keep the author’s voice.
Math Generate multiple solution paths; students critique and rank clarity. Emphasize mathematical reasoning over final answers; error-spotting.
Science Ask AI for hypotheses; class designs feasible tests and variables. Feasibility & safety; separating claim vs. evidence.
Social Studies AI writes a paragraph on an event; students identify missing perspectives and add sources. Bias detection; source triangulation.
Library/Media Compare AI-suggested sources with results from library databases. Identify where algorithms or AI shape what appears first and flag any AI-generated sources. Algorithm awareness; distinguishing peer-reviewed or curated resources from AI-generated content; reinforcing database use and citation.

Deliverable: a 2–3 week “mini-unit” outline (goals, tasks, AI use rules, assessment plan). Success criteria: AI supports—not replaces—student thinking.

Hands-On AI Experiences

Experience simple builds and SEL-aligned tools to understand potentials and guardrails.

  • Build a rules-based chatbot in Scratch or try Machine Learning for Kids.
  • Explore journaling/writing supports (e.g., Writable) and discuss disclosure, integrity, and AI’s appropriate role.
  • Design a “sandbox” pilot: three classroom activities, privacy guardrails, and a feedback form for students and staff.

Success criteria: pilot plan includes objectives, approved tools, disclosure language, and student reflection prompts.

Collaboration & Networking

Leverage statewide communities and schedule recurring share-outs.

  • Attend: SLATE, WEMTA, WDLC, WETL, and CESA trainings.
  • Monthly “Show & Tell” (45 min): two teacher demos, one tool vetting share, one student artifact spotlight.
  • Create a PD notebook (shared drive) with lesson artifacts, policies, and family communication templates.
Continuous Learning & Adaptability

Adopt a living roadmap and micro-credential growth.

  • Use DPI’s AI Roadmap (see pg. 19) to pace your PD pathway.
  • Study local models (e.g., Sun Prairie’s AI PD) and adapt artifacts.
  • Offer micro-badges such as “Ethical Prompting,” “Assessment with AI-Assist,” and “Privacy-First Lesson Design.”
 

External PD Resources & Links

Curated links aligned to the PD strands.

Understanding AI & Machine Learning Basics
Integrating AI into Subject Areas
Hands-On AI Experiences
Policy & Implementation Guidance
Continuous Learning & Adaptability
 

Explore more AI resources for educators:

For questions about this information, contact Amanda Albrecht (608) 267-1071, Amy Bires (608) 266-3851