State, Challenges, and Future of Teaching Intensive Positions at R1 Universities

Analisa Flores Chair
University of California-Riverside
 
Yingzhou (Joyce) Fu Panelist
University of California Riverside
 
Uma Ravat Panelist
 
Maria Tackett Panelist
Duke University
 
Alex Reinhart Panelist
Carnegie Mellon University
 
Marcela Alfaro Cordoba Panelist
University of California Santa Cruz
 
Marcela Alfaro Cordoba Organizer
University of California Santa Cruz
 
Tuesday, Aug 6: 10:30 AM - 12:20 PM
1529 
Topic-Contributed Panel Session 
Oregon Convention Center 
Room: CC-E145 
With the academic landscape continually evolving, understanding the state and prospects of teaching-intensive positions in statistics is the starting point for reshaping how our departments work. This panel will provide a comprehensive overview of teaching-intensive positions at R1 universities in the United States, offering a collection of journeys of statisticians in these roles. We will shed light on the ranks, tenured or not tenured options, expectations, and career advancement opportunities, highlighting the unique demands and rewards of this career path. Our panelists, composed of teaching professors, will discuss key topics such as how different paths can lead to the same position and how they are shaping their roles in their institutions.

This panel is relevant to a diverse audience, including graduate students exploring potential career paths in education, early-career statisticians aspiring to secure teaching-intensive positions, department chairs seeking insights into diversifying their faculty, and instructors nationwide who are curious about new ways to define a teaching-focused career.

The session format will be as follows: introduction by moderator (10 mins), followed by 10 minutes for each panelist to explain their paths to the position and their activities in a typical school year (50 mins). Then a series of questions from the moderator to highlight the different challenges and paths: how they distribute their time, advancement steps and expectations in their institution, and how they see this position in the future of departments of statistics (40 mins). To wrap up, the moderator will take questions from the public (10 mins).

Applied

Yes

Main Sponsor

Section on Statistics and Data Science Education

Co Sponsors

Business Analytics/Statistics Education Interest Group
Caucus for Women in Statistics
Section on Teaching of Statistics in the Health Sciences