Tuesday, Aug 6: 9:35 AM - 9:40 AM
3569
Contributed Speed
Oregon Convention Center
Introductory data science classes cover a range of topics, including data gathering, exploration, modeling, and visualization. However, data science is still a young discipline, which means little is known about which topics students particularly struggle with.
This paper analyzes student data from three interactive, online data science textbooks. Activity metrics like average number of attempts, proportion of students giving up, and average time to completion, will be used to quantify student struggle. Struggle data from conceptual and programming-based activities will be aggregated from over 50 institutions to identify challenging topics in a first data science course. Data will also be compared between book versions to determine if certain tasks are more difficult in Python or R, or if programming language does not affect performance. Although specific activities are limited to a single course platform, challenging topics and lessons learned will apply broadly.
data science
student struggle
online learning
interactive textbooks
Main Sponsor
Section on Statistics and Data Science Education