USCOTS 2023 - Breakouts

Friday June 2nd, 9:30 am – 10:45 am

1A: How to read a research paper: tips for teaching students (Room 107)

Ciaran Evans (Wake Forest University), Nicole Dalzell (Wake Forest University)

1B: Integrating social justice issues within the postsecondary educational statistics curriculum (Room 109)

Julie Lorah (Clemson University), Christy Brown (Clemson University)

1C: Different perspectives on course topics in Intro data science…Including yours! (Room 108)

Michael Posner (Villanova University), April Kerby-Helm (Winona State University)

1D: Departmental transition from lecture based instruction to active learning in intro statistics (Room 104)

Carrie Lineberry (Randolph Community College)

1E: Active learning in online/hybrid introductory statistics courses: exploring collaborative keys (Room 105)

Nicola Justice (Pacific Lutheran University), Anelise Sabbag (California Polytechnic State University at San Luis Obispo)

1F: Effective teamwork and communication: process oriented guided inquiry learning (POGIL) in the statistics classroom (Room 106)

Leigh Johnson (Capital University), Tracey Murray (Capital University)

1G: Climate forward statistics courses (Room 112)

Kathy Gray (California State University, Chico)

1H: Introduction to the sports content for outreach, research, and education (SCORE) network (Room 204)

Ivan Ramler (St. Lawrence University), Michael Schuckers (St. Lawrence University), Robin Lock (St. Lawrence University)

Friday June 2nd, 1:15 pm – 2:30 pm

2A: Writing for learning: How to implement writing at scale (Room 107)

Krista Varanyak (University of Virginia), Rich Ross (University of Virginia)

2B: Alternative grading: a more meaningful representation of student learning (Room 109)

Allison Theobold (Cal Poly, San Luis Obispo), Ciaran Evans (Wake Forest University), Jessie Oehrlein (Fitchburg State University), Sara Stoudt (Bucknell University)

2C: Engaging students in data science with authentic data (Room 108)

Sheri E. Johnson (The Mount Vernon School), Merve Kursav (Dartmouth College), Scott Pauls (Dartmouth College), Christine Franklin (American Statistical Association)

2D: Flipping to make time for communicating about data (Room 104)

Marian Frazier (College of Wooster), Melissa Crow (New College of Florida), Megan Mocko (University of Florida), Jonathan Wells (Grinnell College)

2E: What belongs together? Using elemental groupings and Gestalt principles to help students design more insightful data visualizations (Room 105)

Silas Bergen (Winona State University)

2F: Teaching statistics from primary source documents (Room 106)

Beverly Wood (Embry-Riddle Aeronautical University)

2G: Demystifying the publishing process for statistics education journals (Room 112)

Laura Le (Univ. of Minnesota), Matt Hayat (Georgia State), Jennifer Green (Michigan State), Jennifer Kaplan (Middle Tennessee State), Susan Peters (Univ. of Louisville), Andrew Zieffler (Univ. of Minnesota)

Friday June 2nd, 4:00 pm – 5:15 pm

3A: (Bio)statistical Literacy: what is it, and how can we teach it? (Room 107)

Steven Foti (University of Florida), Michael R. Jiroutek (Campbell University), Laura Le (University of Minnesota), V.N. Vimal Rao (George Washington University)

3B: Positioning students in data science classrooms (Room 109)

Sunghwan Byun, Emily Thrasher, Jeanne McClure, Hamid Sanei (North Carolina State University)

3C: Introducing data science and data moves with CODAP (Room 108)

Tim Erickson (Epistemological Engineering and Lick-Wilmerding High School)

3D: How to communicate in an online statistics course (Room 104)

Jacqueline Herman (Northern Kentucky University), Ella Burnham (Gustavus Adolphus College), Erin Blankenship (University of Nebraska-Lincoln)

3E: If I can see it, I'll understand it: using visuals to teach statistical concepts (Room 105)

Beth Chance (California Polytechnic State University), Emily Robinson (California Polytechnic State University)

3F: Hypothetical thinking (about confounding): why and how to teach it (Room 106)

Milo Schield (University of New Mexico), Larry Lesser (The University of Texas at El Paso)

3G: Supporting professional development through teaching assistantships (Room 112)

Julie Deeke (University of Illinois Urbana-Champaign), Kelly Findley (University of Illinois Urbana-Champaign)

Saturday June 3rd, 9:30 am – 10:45 am

4A: Supportive activities for students learning how to communicate about data (Room 107)

Amy Wagaman (Amherst College), Pam Matheson (Amherst College)

4B: Outreach opportunities for statistics and data science programs (Room 109)

Wesley Cox (Iowa State University), Ulrike Genschel (Iowa State University), Anna Peterson (Iowa State University), Laura Ziegler (Iowa State University)

4C: Data for all: a general education course in the undergraduate curriculum (Room 108)

Hunter Glanz (California Polytechnic State University)

4D: Discussing the role of the instructor and the instructional designer in a fully asynchronous statistics course (Room 104)

Juana Sanchez (UCLA Department of Statistics and Data Science), Sirui Wang, (UCLA Online Teaching and Learning)

4E: Developing data storytellers using story builder in CODAP (Room 105)

Heather Barker (Elon University), Emily Elrod (Elon University)

4F: Revising college GAISE (Room 106)

Patti Frazer Lock (St. Lawrence University), Jamis Perrett (Brigham Young University), Robin H. Lock (St. Lawrence University)

4G: An Homage to Educator Par Excellence, J. Stuart Hunter, on the Occasion of His One Hundredth Birthday (Room 112)

Dick DeVeaux (Williams College), Doug Montgomery (Arizona State University), Roger Hoerl (Union College), Ron Snee (Snee Associates), Bradley Jones (JMP Statistical Discovery Software)

Legend

Breakout
Keynote
Workshops
Posters & Beyond
Exhibitors
Research Satellite
Other

Note: All times are listed in Eastern Time.