AI for learning development
Everywhere you turn, vendors are adding AI to their products. They promise faster, easier, better development with fewer people. But is this true? How can we evaluate the process and the results when AI is used? Let’s explore.
When you hand the work to a subject matter expert (SME)
It’s pretty common for subject matter experts to create and deliver classroom content. When they do:
- It’s built for their peers
- It resembles the ways they’ve been taught before (namely, higher education)
- It’s highly dependent on learner questions to supplant and clarify the content, and
- It’s often a consulting session in disguise
This is great when it meets learner’s needs – they get personalized, authoritative help quickly and cheaply. It’s been a favorite of every engineering organization I’ve worked in. But what if this has to work for remote employees, run regularly or run at scale?
This is when most companies turn to a recording of the classroom or or narrated video of the slide deck (for example, using Captivate). It’s cheap and gets content in front of many, but now the holes begin to appear. The value of the in-person course is in personalized consulting, and that’s now gone. So is the chance of questions that cover for unclear content, muddled sequencing, and learner misunderstandings.
Pairing instructional designers (IDs) with SMEs
Ensuring learning happens effectively and at scale is the bread-and-butter of an instructional designer’s work. Experienced IDs partner with a subject matter expert to connect the expert’s knowledge with the learner’s specialized needs. IDs can also shift content production work off the SME, albeit with extra content reviews and editing.
Note This assumes the ID has the necessary background to select and structure the most appropriate learning interventions. Junior IDs are often more focused on content creation rather than structuring the learning, so you may need to upskill them.
Initially, the ID’s role is to have fruitful discussions with the SME: Understanding the roots of the performance issue from the SMEs viewpoint, Helping the SME to unpack their knowledge back to the learner’s point of view, and Identify potential holes in learners’ knowledge.
Then they come to a common understanding of the path from where the learners are to where they need to be. This may involve skill decomposition, developing outlines, and brainstorming scenarios and/or practice problems. The ID and SME often come to a better understanding of how the subject area works in real life, which can lead to a better understanding of the roots of the problem. This iterative process is driven by the IDs insight into learner psychology and instructional techniques.
I firmly believe this work needs to happen before creating any content, and that this work can happen over and over in the development process.
In this process, the ID is teaching the SME how to think like an educator as they practice the work together. It’s the counterpart to putting the expert in a classroom where the ID is now the expert (in learning) and the SME learns by working together. This practice is crucial to internalizing these skills and can help the SME become a far more effective educator in the future.
If the goal is to enable SMEs to develop their own education in the future, this shared working and learning process is critical. Over time, the ID can shift to more of a consulting role, enabling the SME to develop on their own.
Next time
We’ll work through a scenario where a SME develops their first course using AI. We’ll explore the process, risks, and mitigations. Stay tuned!