In academia, instruction usually stops at the (real or virtual) classroom door. When students enter the workforce, they’re typically on their own if they have questions about how to apply what they learned in a real-world situation. Certainly, it’s unreasonable to expect instructors to field emails, texts, and calls from former students during the workday, but a lot of learning happens while actually on the job, where people apply the skills learned in a classroom.
Learning by doing
I and many others believe learning works best when it’s driven by the learner’s questions in an interactive and personalized setting. People learn best through doing. And even within the context of online learning, we think the most value comes from using knowledge to complete a real-world task.
Certainly, many topics can be learned by reading a book or watching a video outside of a class. But when you get confused, you may need an interaction to help you understand where your train of thought diverged or to show you a different way of learning you’ve not seen before.
But providing that interaction outside of the classroom when questions arise is no simple task. How can we take that rich content prepared for a course and make it accessible in context in vivo? Great teachers don’t scale. We can’t copy their minds and hand them out to former students to help them use their skills on the job.
AI and real-time learning
This is a perfect application for artificial intelligence (AI), but the solution isn’t to replace teachers. Rather, AI can help facilitate the learning process with the help of subject-matter experts. People often think of AI as a sort of Magic 8 Ball that provides answers to questions. But I firmly believe that “black boxes” don’t belong in education, because it’s hard to learn when we don’t know know how the AI arrived at its answers. Google’s AlphaGo, for example, beat the best Go players in the world, but its moves were bewildering, even to professional players, and the AI can’t explain why it made the plays that it did.
When AI looks at and explains things in a more human way, learning is easier. In academia, we can leverage AI to understand student questions in the way humans understand it and then partially automate the process to provide people with answers that have been validated by a human expert. Understanding the meaning of a question is much more difficult than it might seem at first glance. To provide relevant answers, the AI needs to understand not just the literal meaning of the words, but also the context from which the question originates to help disambiguate what’s not understood.
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