Dr Mark Johansen - PhD Indiana
My primary research interests are the learning of categories and the associations between categories. Categories, e.g. cats, chairs, trees, games, etc., are a fundamental component of human cognition. Humans use categories constantly and mostly with little effort in their everyday lives, but this intuitive use gives little insight into where practical categories come from or how people learn them. I study category learning by have people learn new, unfamiliar categories and then evaluate what they have learned and how they have learned it by having them classify new cases in references to their newly learned categories. A key reason categories are useful is that they facilitate the prediction of hidden properties, for example, categorizing an animal as a cat means it’s likely that the animal has a heart, will purr when patted and might help eliminate a mouse infestation. So I also evaluate feature inference by having participants predict properties of new instances in relation to newly acquired categories.
I have recently become particularly interested in the use of virtual video-game environments to study learning. A problem with studying how people learn real-world categories is that it can be quite difficult to experimentally manipulate those categories in ways that allow precise hypothesis testing. Video games represent practical compromise in terms of providing a reasonably high level of realism while still allowing precise manipulation of the experimental.
The study of category learning has become a quite well formalized discipline where many mathematical models have been developed and evaluated. Much of my research is aimed generating data that will help to demonstrate the strengths and weaknesses of the present mathematical models of human learning as well as guide the creation of better models.
I teach on the research design and statistics modules at Levels 1 and2 (PS1015 and PS2006). While guiding students through the details of various formal statistical techniques (analysis of variance, correlation, regression, etc.), I spend a great deal of time emphasizing the intuitive aspects of statistics in the interpretation of experimental results: Human behaviour tends to be noisy and highly variable. Statistical analysis is an organizing tool that enables the researcher to distinguish real influences from random variability.