Faculty » Jon A. Willits

In my research, I do computational, neurobiological, experimental, and naturalistic studies of language and learning. My primary aim is to study in how people and machines learn languages and other forms of complex knowledge, especially meaning and semantic knowledge. I am interested in how that knowledge is represented and used in biological and digital systems. I study language and learning in people of all ages, from infants who are learning language for the first time to elderly adults who are learning a new skill or a second language. A big part of my research is also focused on applying theories and models of language and learning to applications in social psychology, clinical psychology and developmental disorders, such as children and adults with autism, schizophrenia, and hearing disorders.

My research makes use of a wide range of methodologies to study language and learning. My first key focus is "Big Data" analyses of naturalistic data, looking at how children and adults learn in the real world, and how the structure of the environment contributes to learnability. My second key focus is to build computational models of learning and knowledge representation. Computational models help us to be rigorous and explicit in our claims about how learning occurs, and lead to testable hypotheses about when learning is easy and when learning is difficult. My third key focus is to conduct behavioral experiments to test the hypotheses that were generated by the big data analyses and computational models. In these experiments, I use a wide range of experimental methodologies, including EEG experiments of brain function, eye-­‐tracking, and creative use of computer games and other programs to measure people’s accuracy and reaction time in behavioral situations.

Selected Publications

Willits, J. A., Jones, M. N., & Landy, D. (2016). Learning that numbers are the same, while learning that they are different. Proceedings of the 37th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Baayen, R. H., Shaoul, C., Willits, J. A. and Ramscar, M. (2015). Comprehension without segmentation: A proof of concept with naive discrimination learning. Language, Cognition, and Neuroscience.

Willits, J. A., Amato, M. S., & MacDonald, M. C. (2015). Verb knowledge and event knowledge in language processing. Cognitive Psychology, 78, 1-­27.

Willits, J. A., Seidenberg, M. S., & Saffran, J. R. (2014). Statistical structure in language: Contributions to noun-­‐verb differences in acquisition. Cognition, 132, 429-­436.

Rubin, T., Kievit-­‐Kylar, B., Willits, J. A., & Jones, M. N. (2014). Organizing the space and behavior of semantic models. In P. Bello, M. Guarini, M. McShane, & Scassellati (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Jones, M. N., Willits, J., & Dennis, S. (2014). Models of semantic memory. In J. R. Busemeyer & J. T. Townsend (Eds.) Oxford Handbook of Mathematical and Computational Psychology.

Willits, J. A. (2013). Nonadjacent dependencies in language and thought: Not so difficult after all. In N. Taatgen, H. van Rijn, L. Schomaker, & J. Nerbonne (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 2570-2575). Austin, TX: Cognitive Science Society.

Willits, J. A., Wojcik, E. H., Seidenberg, M. S., & Saffran, J. R. (2013). Toddlers activate lexical semantic knowledge in the absence of visual referents: evidence from auditory priming. Infancy, 18, 1053-­‐1075.

Willits, J. A., Seidenberg, M. S., & Saffran, J. R. (2009). Verbs are lookING good in early language acquisition. In N. Taatgen, H. van Rijn, L. Schomaker, & J. Nerbonne (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 2570-­‐2575). Austin, TX: Cognitive Science Society.

Willits, J. A., Amato, M. S., & Sussman, R. S. (2008). Event knowledge versus verb knowledge. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 2227-2232). Austin, TX: Cognitive Science Society.

Willits, J. A., Duran, N. D., D’Mello, S. K., & Olney, A. (2007). Distributional statistics and thematic role relationships. In D. McNamara, & G. Trafton (Eds.). Proceedings of the 29th Annual Conference of the Cognitive Science Society (pp. 707-­712). Austin, TX: Cognitive Science Society.