Computer science and non-computer science faculty members' perception on teaching data science via an experiential learning platform

Huan Chen, Ye Wang, You Li, Yugyung Lee, Alexis Petri, Teryn Cha

Abstract: Artificial intelligence (AI) has been widely adopted in higher education. However, the current research on AI in higher education is limited lacking both breadth and depth. The present study fills the research gap by exploring faculty members’ perception on teaching AI and data science related courses facilitated by an open experiential AI platform. Specifically, two focus groups are conducted among computer science and non-computer science faculty members to gauge their perception on the integration of AI in an experiential learning platform to teach data science, as well as their perception on AI powered data science curriculum in higher education. Findings reveal three major themes which are defining data science, assembling interdisciplinary teams, and building platform for connection. The study has both theoretical and practical implications.