Computational models of human social behavior and neuroscience: An open educational course and Jupyter Book to advance computational training

Abstract

We present a semester-long educational course (see 14-week schedule) and Jupyter Book that provides introductory training in specifying, implementing, and interpreting computational models that characterize human social behavior and neuroscience. Through readings, discussions, and labs (e.g., Jupyter Notebook tutorials using Python), students will receive hands-on training in using mathematical models to test specific theories and hypotheses and explain unobservable aspects of complex social cognitive processes and behaviors. These aspects broadly include learning from and for others, learning about others, and social influences on decision-making and mental states. Background in introductory psychological science and basic research methods/statistics is highly recommended prior to participating in this course. Programming experience is helpful, but not required or expected. Although the course content is tailored for undergraduate students, it was developed to be easily adapted for trainees at higher career stages.