USCOTS 2023 - Breakouts

Friday June 2nd, 9:30 am – 10:45 am ET

1A: How to read a research paper: tips for teaching students

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

1B: Integrating social justice issues within the postsecondary educational statistics curriculum

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

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

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

1D: Departmental transition from lecture based instruction to active learning in intro statistics

Carrie Lineberry (Randolph Community College)

1E: Active learning in online/hybrid introductory statistics courses: exploring collaborative keys

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

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

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

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

1H: Climate forward statistics courses

Kathy Gray (California State University, Chico)

Friday June 2nd, 1:15 pm – 2:30 pm ET

2A: Writing for learning: How to implement writing at scale

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

2B: Alternative grading: a more meaningful representation of student learning

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

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

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

Silas Bergen (Winona State University)

2F: Teaching statistics from primary source documents

Beverly Wood (Embry-Riddle Aeronautical University), Dominic Klyve (Central Washington University)

2G: Demystifying the publishing process for statistics education journals

Laura Le (Univ. of Minnesota), Matt Hayat (Georgia State), Rob Gould (UCLA), 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 ET

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

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

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

3C: Introducing data science and data moves with CODAP

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

3D: How to communicate in an online statistics course

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

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

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

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

3G: Supporting professional development through teaching assistantships

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

Saturday June 3rd, 9:30 am – 10:45 am ET

4A: Supportive activities for students learning how to communicate about data

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

4B: Outreach opportunities for statistics and data science programs

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

Hunter Glanz (California Polytechnic State University)

4D: Discussing the role of the instructor and the instructional designer in a fully asynchronous statistics course.

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

4E: Developing data storytellers using story builder in CODAP

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

4F: Revising college GAISE

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

4G: Stuart Hunter's 100th Birthday session

Bradley Jones

Legend

Breakout
Keynote
Workshops
Posters & Beyond
Exhibitors
Research Satellite
Other

Note: All times are listed in Eastern Time.