My background is in intelligent tutoring systems. In intelligent tutoring systems, an artificial intelligence agent typically monitors student performance and reacts accordingly, giving feedback or support where necessary.
One of the interesting things about developing an online class is that because students are already engaging with a software system, the infrastructure and context necessary for an intelligent tutoring system are already present. What’s more, not only are they present, but they’re directly integrated into the context of the lesson. Whereas oftentimes intelligent tutoring systems are separate activities that complement a previously-received lecture, putting the learning online from the get-go allows us to integrate intelligent tutoring directly into the context of the lesson.
This development is in its infancy as far as I’m concerned, but I wanted to explain one way in which we use this in our Georgia Tech OMS class. Throughout the course, we have 125 interactive exercises each equipped with an AI agent – which I’ve taken to calling a ‘nanotutor’ to reflect the tiny scope of the skills that these agents teach – that gives students feedback on their latest responses. Let’s walk through an example of an exercise.