Online Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 216 - Contributed Poster Presentations: Section on Statistics and Data Science Education
Type: Contributed
Date/Time: Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
Sponsor: Section on Statistics and Data Science Education
Abstract #309789
Title: Engaging Everyone in a Multidisciplinary, Project-Based Introductory Statistics Course
Author(s): Shurong Fang*
Companies: John Carroll University
Keywords: project-based learning; Introductory Statistics; classroom interaction
Abstract:

Project-based learning encourages students’ critical thinking and requires students to participate in their own learning and answer their own question of interest. Using a new multidisciplinary project-based model helps improve classroom interaction and avoid students’ resistance, especially for under-representative students. In my Introductory Statistics course, students are from diverse background. They are provided a big dataset in real world at the beginning of the semester and choose a quantitative question of their own interest. They are required to watch educational videos before class so that they have more time to discuss their projects and interact with others in class. They learn Statistics while managing and analyzing data, interpreting results and communicating their findings. In the classroom, everyone is engaged because they are curious of their own questions. To assess this multidisciplinary project-based model, pre- and post-surveys and research efficacy questionnaires were given. The present results show that students had statistically significantly increasing confidence in their ability to apply statistics to solve problems (p-value less than 0.001).


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

Back to the full JSM 2020 program