Database Education in the Era of Data Science & AI: Do We Need to Rethink Pedagogy?
The growing demand for lifelong learning coupled with the widespread use of relational database management system (RDBMS) in the commercial world and the growth of Data Science and AI have generated increasing demand for database-related courses in academic institutions and beyond. Learners with diverse backgrounds and abilities aspire to take these courses, even with limited Computer Science knowledge. In this panel, we shall discuss whether we need to rethink the methods we traditionally adopt in teaching database courses and the topics we teach in database courses. Is the way we traditionally teach key concepts (e.g., SQL, relational query processing) need a revisit? Are our different modes (lectures, text book, off-the-shelf RDBMS) of teaching effective to diverse groups of learners (e.g., learners with disabilities, learners with non-CS background)? Can we leverage technology to augment database education? What are the challenges if we indeed need to rethink the way we teach database systems? How can we address them as a research community?
Panelists
- George Fletcher, TU/e, Netherlands
- Mukesh Mohania, IIIT Delhii, India
- Yo Ehara, Tokyo Gakugei University, Japan
- Chiemi Watanabe, Tsukuba University of Technology, Japan




Panel Co-chairs
- Ladjel Bellatreche, ISAE-ENSMA, France
- Sourav S Bhowmick, Nanyang Technological University, Singapore
- Toshiyuki Amagasa, University of Tsukuba, Japan