W16: Topics for an Introductory Data Science Course


By Michael Posner


Information

Introductory data science courses are appearing at colleges, universities, and high schools around the country and the world. What topics do we cover in these courses, and how and why are these decisions made? How do we recognize the background knowledge of our students and how they hope to utilize their skills after this course (whether professionally, additional courses, or as an engaged citizen)? How is this course taught differently by computer scientists, statisticians, business analysts, mathematicians, journalists, etc. or in different departments? This poster will share results of a shortened version of the Data Science Topics survey, created by the MASDER research team. This survey collects information about what is taught in data science classes around the country, how much time is spent on each topic, how data science is defined in the class, who is teaching these classes, and the prerequisites of the courses. It also enables comparisons of how these differ by who is teaching class. We welcome new and experienced data science instructors as well as those planning on or interested in teaching such a course.


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