Welcome to the Computational Studies of Language and Learning Lab (CSLLL) at the University of California Riverside. The lab is directed by Dr. Jon A. Willits and focuses on computational, neurobiological, experimental, and naturalistic studies of language and learning. Our primary aim is to study in how people and machines learn languages and other forms of complex knowledge, and how that knowledge is represented in biological and digital systems. We 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. We are also excited to apply our theories and models to applications in clinical psychology and developmental disorders, such as children and adults with autism, schizophrenia, and hearing disorders.

The lab makes use of a wide range of methodologies to study language and learning.

1. The first key focus of the lab 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.
   
2. The second key focus of the lab 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.
3. The third key focus of the lab is to conduct behavioral experiments to test the hypotheses generated by our big data analyses and computational models. In the lab we use a wide range of experimental methodologies, including EEG experiments of brain function, eye-tracking, and creative use of computer games for data collection.

The CSLLL is located on the 2nd floor of the Olmsted Hall, Room 2139.