By Karle Flanagan (University of Illinois Urbana-Champaign)
Information
During the past 6 years at UIUC, we have grown our introductory Data Science course from just 18 students in Spring 2019 to over 1800 students this past academic year, making it one of the fastest growing data science courses in the nation. In order to create a course that’s both scalable and accessible, we have developed different teaching strategies and technologies to successfully do this. In this poster, I will share how:
1) Our students use industry standard tools. They download Python and git onto their own computers. They use jupyter notebooks and Visual Studio code to program and set up their own personal repository on GitHub to turn in assignments.
2) We do interactive demonstrations in class using simple technology that we built to teach complicated concepts. For example, we have technology to help do the Monty Hall problem and the Birthday Problem live in class.
3) We have a free public website that is used as a supplement to our in person lectures. This resource can be found at discovery.cs.illinois.edu.
4) We use real datasets that students find interesting. For example, data that is collected from our students and data that is themed around UIUC (course GPAs, Illini football, etc.).
5) We built a free “clicker” that can be used to assess students quickly and easily during class. Students scan a QR code and can answer multiple choice and numeric questions instantly. We can then download the data and analyze it live in class.