W06: Best practices for teaching an introductory data science course

Nicholas Horton (Amherst College)


Thursday, May 19th 11am-1pm


There has been dramatic growth in introductory data science at two- and four-year colleges, with more anticipated in the future. Beyond content and curriculum, what course designs are effective in developing a "coherent and engaging" (Dana Center, 2021) data science course? In this faculty development workshop, we share course design principles and practices that can help a diversity of students succeed. We will utilize the Dana Center Data Science Course Design framework to illustrate how (1) active learning, (2) growth mindset, (3) problem solving, (4) authenticity, (5) context and interdisciplinary connections, (6) communication, (7) technology, and (8) assessment can be organized within an introductory data science course. Participants will have the opportunity to explore some activities and approaches, to discuss best practices, and to share ideas and approaches. Faculty from two-year colleges are particularly welcomed given the expected growth of courses and programs at the associate's level.