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Activity Number: 287 - Classroom Teaching and Pedagogy
Type: Contributed
Date/Time: Wednesday, August 11, 2021 : 1:30 PM to 3:20 PM
Sponsor: Section on Statistics and Data Science Education
Abstract #318912
Title: Incorporating Your Own Research in an Introductory Statistics Courses: A Case Study with Podcasts, Web Scraping, and Natural Language Processing
Author(s): Benjamin Williams* and Alyssa Williams
Companies: University of Denver and University of Denver
Keywords: natural language processing; general education; introductory statistics; pedagogy; scholarship of teaching and learning; web scraping
Abstract:

If a professor teaches the same introductory statistics class many times, it may become repetitive and boring. Even if professors want to include new material, it may not be feasible due to curriculum restraints. If a professor feels the material to be repetitive and is not enthusiastic about the class, the students may similarly become uninterested in the material. It may prevent them from pursuing statistics further, especially if the course is their first in statistics. To examine combatting this problem, we recommend introducing the professor’s own research into the introductory statistics curriculum. Although the professor may be researching complex topics, it is likely feasible to introduce the content to the students. We experiment with this by introducing web scraping and sentiment analysis of podcasts to students in an introductory statistics course through an in-class case study. The students were engaged in the case study because podcasts are of interest to them. The instructor was similarly energized by the experience. We describe the experiment and provide lessons learned and advice for other instructors who wish to emulate this method with their own research.


Authors who are presenting talks have a * after their name.

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