NSF Award
1912588
The Targeted Infusion Project (TIP) at Fisk University seeks to implement a novel infusion of the computer science and psychology curriculum. This project will enhance psychology students? abilities to understand artificial learning and cognition. This project will also develop a course in machine learning focused on social sciences. Novel aspects of this proposal include: providing an introduction to machine learning (ML) and applications to social science for balanced algorithm development; offering an experience of understanding learning and bias related to artificial intelligence (AI) protocols; creating computer science and social science curriculum modules relating to bias and learning in ML and AI ; and offering this experience at a HBCU, so that underrepresented students are funneled into STEM graduate schools and careers.<br/><br/>This proposal will incorporate quantitative methods and include research into lecture and laboratory components of social science and computer science courses. The goal of this project is to innovate the curriculum in order to better prepare students in the social sciences and computer sciences for an increasingly multidisciplinary worldview: 1) develop an introductory machine learning course for social sciences which balances between core machine learning concepts as well as application and implication to the social sciences, 2) develop a psychology course that focuses on deep learning paradigms in learning and cognition, 3) develop modules for other computer science and psychology courses which reinforce the connections between computer science and psychology. Together the objectives will provide a strong foundation in core scientific skills, particularly quantitative skills in computation, cognitive development, algorithm assessment, and problem solving. This interdisciplinary approach will synergize with several ongoing initiatives at Fisk University and have a transformative effect on student training, learning and careers in STEM disciplines.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
