Measuring Ability to Learn Using Parametric Learning Gain Functions

One crucial function of a classroom, and a school more generally, is to prepare students for future learning. Students should have the capacity to learn new information and to acquire new skills. This ability to “learn” is a core competency in our rapidly changing world. But how do we measure ability to learn? And how can we measure how well a school has prepared their students to learn? In this paper we formally pose the problem, and introduce a grounded theory of how to measure ability to learn. Using simulations of students learning we provide initial evidence that this theory provides an elegant solution to this problem. We further validate our ideas using real world data from 70k middle-school students and show that our theory is more accurate and interpretable than current state-of-the-art models of learning gains. We consider our results a modest yet interesting first step for a novel type of test.