Extending Professional Learning with AI

As a learning designer and facilitator, I know that the best professional development is not one-and-done. However, I've attended many convocations, keynotes, conference sessions, and single webinars and workshops, and these one-off learning experiences are very common.

As an education consultant and external partner, I'm often designing exactly these types of experiences myself: conference sessions, school districts' summer learning, or single district-wide days. I align my work with standards, conference goals, or district initiatives, but I often miss out on opportunities to follow up with participants in concrete ways. I'm always on the lookout for ways to extend the learning beyond the synchronous "seat time."

That extension can occur both before and after the session. When participants engage with content before they arrive or after they leave, those extra opportunities to retrieve and apply ideas can help make the learning stick, even after a single session.

Since the recent Learning Professional journal focuses on Learning with AI, I want to share how I'm experimenting with AI tools to support educators before and after my sessions. I first shared ideas about chatbots in this LFTX post, and I continue to refine my approach of using AI to support the design of my learning experiences. Here are four ways I'm experimenting with AI tools across the learning arc.

Review

One strategy I use to prime participants is sending thoughtful pre-emails with a mix of logistics, content, and ways to connect. (See Setting the Stage with Pre-Emails.) I'm now adding interactive Canva Code tools to that pre-session mix.

For a recent webinar, attendees had different levels of familiarity with content from The Art of Gathering, so I used Canva Code to create an optional vocabulary drag-and-drop game for reviewing key concepts before joining. 

I've also been experimenting with Google Vids to create short videos that usher participants into the learning experience, using videos, images, text, and GIFs related to the session content. I've been sharing these right before a session begins, but I'm now thinking I can send similar videos in a pre-email to build curiosity or afterward to help participants retrieve key ideas. (Here's a 25-minute walk-through of Google Vids, plus a recent example I played before a webinar on NotebookLM.)

Google Vids Demo

Once participants arrive, those early touchpoints have already started doing some of the work, but the real processing happens after.

Reflect

After sessions I attend, I want to reflect on what I've learned. I want my attendees to have that opportunity, too.

"We do not learn from experience... we learn from reflecting on experience."

~ John Dewey

One of my first AI experiments was creating a custom GPT to walk educators through a reflection process. This Reflection Coach Bot offers options for a long or short reflection, or it can suggest ways to organize ideas and materials. I share the link during sessions and in follow-up emails. A few people have tried it, and I'm still tweaking the experience, but it's an anonymous way to have an AI thought-partner help process the learning.

I also created this LMS Play-to-Practice Processor (a Gemini Gem) for a group of K-12 librarians (complete with librarian puns.) I gave participants about four minutes during the session to start a three-question reflection and encouraged them to return to it later.

My first custom chatbot experiments were with SchoolAI, an education tool that allows the creator to access chat transcripts, which is useful if you want to collect data. (Just be sure to let participants know you can see their responses!)

Now, before I build any chatbot, I think carefully about what I want participants to carry forward. (See Design Before We Build.) After clarifying that purpose, I can start a prompt like: "Help me design a simple reflection chatbot for [audience]. It should help users [goal]."

Reflection is a starting point, but participants often need a way to return to the materials themselves, and that's where curation comes in.

Revisit

Google's NotebookLM has been one of my favorite tools since its launch. When I curate session resources (slides, notes, supporting research, etc.) in a Notebook and share it, participants can later "chat" with those materials to revisit key concepts. Tony Vincent shared this idea in one of his newsletters last fall, and I've now tried it for one of my own sessions.

One benefit of NotebookLM is that the chat stays anchored to the resources I upload, so responses reflect the same processes, language, and research I've provided. One limitation: Notebooks can't be shared outside an organization, so I use a personal Google account when presenting to learners outside my district.

The Studio in NotebookLM continues to evolve, and audio and video overviews, infographics, quizzes, and flashcards are all now possible. I might send an audio summary in a follow-up email, or create flashcards participants can use to revisit content or share with colleagues. (This video, "How I'd use NotebookLM for studying to learn ANY subject," offers a helpful overview and connects the features to the learning sciences.)

NotebookLM continues to surprise me with new features, and one emerging possibility has me especially curious.

Reach

I'd love for a follow-up email to include a summary or job aid as a visual or infographic. Early AI tools struggled to generate images with accurate text, but the latest models are improving quickly, and I think this possibility is coming soon. I'd love to upload session materials and takeaways and have AI generate a visual that feels like a natural extension of the session.

NotebookLM now includes an infographic feature, and I'm seeing examples pop up in sessions and on social media. I added this post to a new Notebook and it generated this infographic. (I specified a “concise” visual and added the LFTX brand colors, but that’s the only prompt I provided. The result is somewhat close to what I might share as a summary.)

In a recent session, a participant used Gemini to create a graphic from a PDF she uploaded, and the information was almost entirely accurate.

I'm still developing my prompting skills for these types of visuals, but as both my skills and the tools improve, I think a well-designed visual souvenir, either digital or printed, could be a meaningful way to extend the learning.

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Whether the souvenir is a visual, a bot, or a curated notebook, the goal is the same.

The Learning Forward Implementation Standard reminds us that "applying new learning requires multiple cycles of practice, reflection, and adjustments as well as support structures to guide educators as they transform new learning into practice," and I'm finding ways AI can help do exactly that.

In The PD Book, Elena Aguilar and Lori Cohen write: "Professional development is defined by its impact. PD is successful if, after the learning experience, the learner can do something else, or do something different."

Extending learning beyond the session is one way we can move closer to that impact.

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Learning Inspiration:

Just Did Some Professional Development - Now What? Rick Wormeli

Kathryn Laster brings over 30 years of education expertise as a math teacher, instructional coach, and digital learning consultant. As an independent consultant, she creates and facilitates transformative learning experiences through intentional, human-centered, tech-infused design, with a goal of normalizing excellence in professional learning.

Connect with Kathryn at kathrynlaster.info and at Refined Learning Design.