Automatically Learning to Teach to the Learning Objectives

We seek to automatically identify which items to include in a set of curriculum, and how to adaptively select these items, in order to maximize student performance on some specified set of learning objectives. Our experimental results with a histogram tutoring system suggest that Bayesian Optimization can quickly (with only a small amount of student data) find good parameters, and may help instructors identify misalignment between their course, and their desired learning objectives.