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Abstract Details

Activity Number: 654
Type: Topic Contributed
Date/Time: Thursday, August 3, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract #324749 View Presentation
Title: Graduate Students Teaching Simulation-Based Inference
Author(s): Laura Ziegler*
Companies:
Keywords: Statistics Education ; Reform Curriculum ; Teaching Assistants ; Mentoring
Abstract:

As new recommendations on content and pedagogy are given to statistics educators, it may be necessary to redesign statistics courses. As a result, many graduate student instructors may be expected to teach unfamiliar statistical methods. What can we do to help graduate students be successful in teaching with new curriculum? This question was examined when a multi-section introductory statistics course at Iowa State University went through a curriculum redesign. This new curricula was developed to incorporate randomization tests and bootstrap intervals in addition to methods based on theoretical distributions such as the t-distribution. Graduate student instructors teach lectures and lead lab sessions for this course and were expected to promote a learning environment where undergraduate students work collaboratively with their peers. Multiple methods to help graduate student instructors succeed in teaching the new curricula were used including providing feedback based on classroom observations and discussions in group meetings. Based on our experiences, we provide suggestions on how to mentor graduate students in teaching new curricula on simulation-based inference.


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