USCOTS 2025 - Breakouts

Friday July 18th, 9:45 am – 11:00 am

B1A: Models for incorporating data science in introductory statistics courses: What you’re already doing

Nathan Tintle (University of Illinois - Chicago), Beth Chance + Soma Roy + Karen McGaughey (Cal Poly - San Luis Obispo), Todd Swanson (Hope College), Jill Vander Stoep (Hope College)

B1B: Leveraging data technologies to model bigger datasets

Nicholas J. Horton (Amherst College), Johanna S. Hardin (Pomona College)

B1C: A regression-forward framework for introductory statistics courses: Unifying the "grab bag" of tests

Zachary Binney (Oxford College of Emory University)

B1D: Potential models for teaching introductory statistics online

Jacqueline Herman (Northern Kentucky University)

B1E: Let's build and share social justice statistical education resources

Jess Kunke (University of Washington), Tyler George (Cornell College)

B1F: A useful model of designing homework assessments in the age of LLMs

Keegan Kang (Bucknell University)

B1G: What would Fisher do? Supporting students from study design to building useful models

Marina Ptukhina (Whitman College), Julie Garai (Incredible Health)

B1H: Making a mathematical statistics course more modern

Jessica Chapman (St. Lawrence University), Matt Higham (St. Lawrence University)

B1I: Using evidence-based strategies to engage & motivate students in large introductory statistics lectures

Sheri Johnson (Kennesaw State University), Susan Hardy (Kennesaw State University)

B1J: From sketchy intuitions to imperfect rules: Using digital image data from drawings to introduce informal classification models

Anna Fergusson (University of Auckland | Waipapa Taumata Rau)

Friday July 18th, 2:45 pm – 4:00 pm

B2A: Leveraging LLMs for student feedback in introductory data science courses

Mine Cetinkaya-Rundel (Duke University)

B2B: Before the CART: Modeling diagnosis with classification trees in CODAP

Tim Erickson (Epistemological Engineering)

B2C: Using games to help students use models to make decisions

Shonda Kuiper (Grinnell College), Tyler George (Cornell College), Lisa Kay (Eastern Kentucky University), Abhishek Chakraborty (Lawrence University)

B2D: Teaching applications: Enhancing statistics instruction for secondary preservice teachers

Maria Cruciani (Michigan State University), Liz Arnold (Montana State University), Jennifer Green (Michigan State University)

B2E: Equitable practices for integrating pair programming in the classroom

Judith Canner (California State University Monterey Bay), Allison Theobold (Cal Poly San Luis Obispo)(

B2F: No grades, No problem: Ungrading in undergraduate and graduate statistics courses

Wendy Moore (Cal State East Bay)

B2G: Building a thinking classroom (BTC) to improve student learning in statistics and data science

Nathan Charles Kenny (Hillcrest High School), Justin Post (North Carolina State University)

B2H: Teaching useful statistical models in a non-calculus-based applied bayesian statistics course

Dr. Dobrin Marchev (Columbia University), Dr. Banu Baydil (Columbia University)

B2I: Role play: A useful model for engaging students in statistics classes

Taeyong Park (Carnegie Mellon University Qatar)

B2J: Making social science students count: The pedagogic model of the Manchester Metropolitan Q-Step Centre

Simon Massey (Manchester Metropolitan University), Muzammal Mann (Manchester Metropolitan University)

Saturday July 19th, 9:45 am – 11:00 am

B3A: Courses modeled on the new College GAISE recommendations

Patti Frazer Lock (St. Lawrence University)

B3B: Can the usefulness of publishing models for statistics and data science education journals be improved?

Juana Sanchez (UCLA), Jeffrey Witmer (Oberlin College and Conservatory), Susan Peters (University of Louisville), Jennifer Green (Michigan State University), Helen MacGillivray (Queensland University of Technology)

B3C: Memorable models for learning: Modeling making (a meaningful multitude of) human- and AI-created mnemonics

Megan Mocko (University of Florida), Larry Lesser (The University of Texas El Paso)

B3D: What makes a good project?

Ji Y. Son (California State University, Los Angeles), Immanuel Williams (Cal Poly San Luis Obispo)

B3E: Scaffolded learning in data science through assessment and practice

Hunter Glanz (Cal Poly San Luis Obispo)

B3F: Exploring alternative grading models for teaching statistics

Nicholas Bussberg (Elon University), Ryne VanKrevelen (Elon University), Heather Barker (Elon University)

B3G: Exploring models, building collaboration: Intro to Process-Oriented Guided Inquiry Learning in statistics

Jessie Oehrlein (Fitchburg State University), Chris Oehrlein (Oklahoma City Community College)

B3H: Integrating Poisson regression into the undergraduate curriculum

Paul Roback (St. Olaf College), Laura Boehm Vock (St. Olaf College)

Saturday July 19th, 2:30 pm – 3:45 pm

B4A: Useful models for collaborative faculty development

Jonathan Wells (Grinnell College), Melissa Crow (New College of Florida), Marian Frazier (Denison University)

B4B: Classify this! Adventures in algorithms

Andrew Zieffler (University of Minnesota), Chelsey Legacy (University of Minnesota), Regina Lisinker (University of Minnesota), Pablo Vivas Corrales (University of Minnesota)

B4C: Engaging students with sports examples through SCORE

Robin Lock (St. Lawrence University), Nick Clark (University of St. Thomas - MN), Ivan Ramler (St. Lawrence University), Michael Schuckers (UNC - Charlotte)

B4D: Going viral with statistics: Teaching data analysis through TikTok

Hannah Kurzweil (Data Science 4 Everyone)

B4E: Essentials of the scholarship of teaching statistics

V. N. Vimal Rao (University of Illinois), Nina Bailey (Montclair State University)

B4F: No bones about it: Engaging with data analysis through an authentic anthropology problem

Rose Mary Zbiek (The Pennsylvania State University), Susan Peters (University of Louisville), Matthew Johnson (The Pennsylvania State University)

B4G: Teaching probability through play: A high school carnival project including community outreach

Emily Buhnerkempe (University of Illinois Laboratory High School)

Legend

Breakout
Keynote
Workshops
Posters & Beyond
Exhibitors
Research Satellite
Other

Note: All times for USCOTS 2025 are listed in Central Time.