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Activity Number: 196 - SPEED: Teaching Statistics: Strategies and Applications
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 11:15 AM
Sponsor: Section on Statistical Education
Abstract #332857
Title: Predicting Student Performance in Undergraduate Introductory Statistics Courses
Author(s): Dusty Turner*
Companies: USMA
Keywords: undergraduate statistics; linear models; R; prediction; education; army
Abstract:

With the ultimate goal of improving statistical education for undergraduate students, the Department of Mathematical Sciences at the United States Military Academy convened a study to investigate the educational effect of grouping cadets with similar mathematical abilities in the same classroom verses random assignment. Based off of 3 semesters of previous performance in USMA's Introduction to Probability and Statistics Course, we built a model to predict classroom performance for cadets in the Fall Semester of year 2017. Using these predictions, we placed half the students in classrooms of similar predicted mathematical abilities. The other half of students were randomly assigned to their sections. We took measures to control for class hour and instructor. This paper will present the methodology used to determine classroom assignment, limitations of the model, challenges in the experiment, and recommendations for future research to expand this study.


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

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