If you would have asked me 15 years ago what I’d be doing today, the absolute last thing I would have said was teaching. But, here I am, 15 years into a teaching and training career with an official training company, spending most of my weeks teaching product development teams and leaders how to be customer-centric and build products customers love. As part of scaling Sense & Respond Learning we’ve brought on a group of certified training partners. At least once a month Josh Seiden and I are teaching these professional trainers how to teach our classes. I never had any formal training in instruction and teaching how to teach is a step even further away from that. Here’s how I’ve been approaching this with a little bit of help from our new friend, AI. 

See one. Do one. Teach One. And then what?

Originally from the medical field, the idea of “see one, do one, teach one” forms a big part of how I’ve learned to teach and how we’ve approached training our trainers. The idea focuses on three steps:

1. See the “procedure” – in our case, observe one of our classes to see how the class is taught. 
2. Do the “procedure” – take part in our classes as a student to experience it first-hand.
3. Teach the “procedure” – teach the idea in the class to someone else to reinforce the skill.

Just completing these steps isn’t necessarily enough to certify that someone is capable of teaching our material but it’s a solid start. To go further, Josh and I have had to extract the institutional knowledge that lives primarily in our heads into a fourth step in this process: teach how to teach. 

We’ve seen so many variations on these ideas and this material that a full third of the training-the-trainer work we do is focused on sharing these currently hidden tips, tricks, learning tools, anti-patterns and learning resources. Teaching how to teach is not something either one of us has a lot of experience with but it’s become both a critical value proposition to our trainers and their students as well as a bit of a bottleneck since all of that insight lives inaccessibly in our collective memories. 

AI helps us teach how to teach

To alleviate the bottleneck we’ve introduced AI into our teaching process. We’ve enabled a chatbot with not only our material but what anti-patterns to watch out for, what good looks like and most importantly the “why” behind it all. The bot allows our trainers to interact with the material they’re learning whenever they’d like. They can ask whatever questions they need without worrying about tying up a lot of our time or keeping others from getting their questions answered. 

As always, the early experiment of the bot was a set of manual prompts. These were designed to see how well the bot could answer tough questions about the material, how to teach it and whether the work the trainers and their students are producing is of high quality. The ultimate goal is to iterate the prompts into a bot that has a broadly accessible knowledge base not just for our trainers but for their students as well. This way as the trainers work through the see one, do one, teach one process they have a 24/7 resource able to help teach them how to teach. 

AI makes us better teachers

The fascinating thing about adding AI into our teaching process is that it forces us to, once again, teach the material and the teaching process itself. This time it’s to the bot. Unlike our human students it never tires and will ask questions infinitely. Going back and forth with it to figure out when it has it right “enough” has been a fascinating process in extracting, distilling and refining our tacit knowledge into actionable prompts for the bot. Ultimately, this has made the train-the-trainer process that much better for our training partners and our students. 

Have you taken a class from us lately? You should.