Tom Mitchell of CMU has a fascinating slide talk available online about Human and Machine Learning. Mitchell’s expertise is definitely weighted to the computer science side, but he is also concerned with the cognitive neuroscience component of human learning. Which I just want to point out early on is somewhat orthogonal to anything I am trying to do–I will have very little to say about dopamine response, though there is a natural connection between dopamine response and reinforcement learning as it pertains to machines (scholarpedia on reinforcement learning from both algorithmic and neuronal perspectives).
This work helps me bring into relief the parts of machine learning and human learning that I am personally focused on, at least for now, which subsumes formal education (or school learning, K-16) and educational measurement on the human learning side and data mining and pattern recognition on the machine learning side. Formal education helps to distinguish between the kind of learning humans do when they acquire the skill to recognize a chair for what it is (pre school, presumably) vs when they learn to answer word problems which might involve algebraic solution.
Traditional education research involves a lot of theory of cognition and a lot of case studies, trials, interviews and assessments. But today a whole lot of education is happening in online or computer-based environments, and with that the sheer quantity of hard data increases by at least a factor of 100 (easily more). Educational measurement has gotten more sophisticated as well, employing a growing statistical arsenal. It is irresistible to bring some of these techniques to the data, which is what I actually do. But I’m trying to resist it a little bit at the moment, because I think there is a learning moment for me to use machine learning techniques to better mine these data, to recognize new patterns and to develop new educational metrics. I want to write a machine learning algorithm which will come up with IRT by itself…and then come up with something even better. The long-term objective of all of this learning about learning is to improve (formal) education.