Prof. John Kruschke. Model Exercises

Prof. John K. Kruschke, Indiana University

Model Exercises

In each of the exercises you generate data in a quick experiment and then explore whether a given model can account for your data. The experiments take 10 minutes or less, and the modeling is done entirely with pencil and paper (and maybe a calculator in a few spots). Each exercise is linked to summaries of results from a large number of people, along with summaries of how well the models can fit these average data.


Template similarity. Many things in the world look similar, yet we treat them very differently. On the other hand, if we treated differently everything that looks slightly different, then we could never generalize from what we've learned to any novel situation. In the linked experiment, you rate the similarities of letter-like patterns, and then examine whether a simple template model can account for your similarity ratings.
Category learning. You learn to categorize simple geometric shapes like the one shown here. Then you are shown new shapes, and must decide how best to categorize them based on what you learned before. You then test whether the data can be fit by three different types of model: Exemplar, prototype or rule.

Blocking of associative learning. In the experiment, you learn which symptoms indicate which (fictitious) diseases. You then are given new combinations of symptoms and asked to give your best diagnosis based on what you learned before. You then explore the predictions of a simple connectionist model to test whether is can match your behavior.

Additive integration of personality traits. When deciding whether or not to continue a relationship with a new acquaintance, we assess the various aspects of their personalities. If a person is funny but overbearing, how likable is she? If a person is kind but dull, how likable is he? In this exercise, you rate the likabilities of fictitious people with two personality traits, and then examine whether a simple additive model can account for your ratings.