USCOTS 2021 - Posters

Async-01: Explore Culturally Relevant Data through a Map of Segregation And Redlining

By Immanuel Williams (California Polytechnic State University); Travis Weiland (University of Houston)

Async-02: What are the introductory statistics tasks that require the highest self-efficacy for community college students?

By Samantha Estrada, Emily Santistevan, & Erica Martinez (University of Texas at Tyler)

Async-03: Addressing Diversity, Inclusion, and Equality in a Methods Course

By Steven Foti (University of Florida)

Tuesday, June 29th

Tu-01: Program Evaluation Through Alignment of Student Perceptions, Outcomes Assessment, and Faculty Perceptions in an Undergraduate Statistics Major

By Alyssa Hu, Matthew Beckman, & Dennis Pearl (Penn State University)

Tu-02: Updating an Introduction to Biostatistics course to better support diversity, equity, and inclusion

By Amber L Lin & Priya Srikanth (Oregon Health & Science University)

Tu-03: Computing in the Statistics Curriculum: Lessons Learned from the Educational Sciences

By Amelia McNamara (University of St Thomas); Chelsey Legacy, Vimal Rao, Robert delMas, Andrew Zieffler (University of Minnesota); Matthew Beckman, Elle Basner Butler (Penn State University)

Tu-04: DataSpace: Integrating Stories, Visualizations, and Statistical Models

By Bowen Mince, Shonda Kuiper, Linh Tang, Britney He, & Senay Gokcebel (Grinnell College)

Tu-05: A Fresh Shot at Statistics in the Classroom: Three Perspectives using World Cup Soccer Player Data

By Brenna Curley (Moravian College); Anna Peterson (Iowa State University)

Tu-06: Case-based data ethics to inspire an inclusive data science community

By Cassandra Pattanayak (Wellesley College)

Tu-07: Holy Deviations! Stories, Superheroes, and Data Science Education

By Charlotte Bolch (Midwestern University); Daniel Maxwell (University of Florida); Justine Andersen, Elli Rhodes (Sequential Artists Workshop)

Tu-08: The State of Computing in Introductory Statistics

By Chelsey Legacy, Laura Le, Andrew Zieffler (University of Minnesota); Elizabeth Fry (St. Catherine University)

Tu-09: Beyond normal: Understanding power with R Shiny

By Christian Stratton (Montana State University); Jennifer Green (Michigan State University)

Tu-10: R/Shiny Apps for teaching introductory statistics

By Craig Lazarski & Jeffery Painter (Cary Academy)

Tu-11: Should Introductory Statistics Classes Include Multifactor Statistical Design of Experiments (DoE)?

By David Fluharty (Ivy Tech Community College)

Tu-12: Connecting to an API and Creating a Word Cloud in R

By Justin Post (North Carolina State University)

Tu-13: Learning R by Solving Puzzles

By Kelly Nicole Bodwin (California Polytechnic State University)

Tu-14: Welcome to the Jungle ... Garden: Using Data from my Backyard Garden to Teach Introductory Data Science

By Lisa Lendway (Macalester College)

Tu-15: Which Mnemonics do College Students Recall, Explain, and Apply?

By Megan Mocko (University of Florida); Amy Wagler, Lawrence Lesser, Wendy Francis (University of Texas at El Paso)

Tu-16: bootEd: An R package for introducing students to bootstrap intervals with assumption checking

By Njesa Totty (Oregon State University)

Tu-17: Using IPUMS Data for Course Projects

By Ryne VanKrevelen (Elon University)

Tu-18: Independent Summer Statistics Community (ISSC): Building a sustainable online undergraduate student community with Cocurricular Activities and Experiential Learning Opportunities

By Samantha-Jo Caetano (University of Toronto)

Tu-19: Teaching Statistical Writing

By Scott Thatcher, Scott Alberts, & Hyun-Joo Kim (Truman State University)

Tu-20: The value of Log files of students’ interaction with software applications: Performance Evaluation in Correlation Guessing

By Shunqi Zhang, Dennis Pearl, Matthew Beckman, Neil Hatfield, & Yiyun Gong (Penn State University)

Tu-22: An interactive web applet for exploring the impact of unequal variances on the t-test

By Thomas J. Faulkenberry (Tarleton State University); Ruth Horry (Swansea University)

Tu-23: The Potential of Collecting Data on Student Sleep Habits

By Travis Loux (Saint Louis University)

Tu-24: The value of Log files of students’ interaction with software applications: Replicating a Bayesian Network analysis across multiple years data

By Yiyun Gong, Dennis Pearl, Matthew Beckman, Neil Hatfield, & Shunqi Zhang (The Pennsylvania State University)

Tu-25: Infusing Activities Centered Around Diversity, Equity, and Inclusion into Statistics Courses

By Kirsten Doehler & Heather Barker (Elon University)

Wednesday, June 30th

We-01: Using video examples to improve students’ understanding of hypothesis test selection

By Abra Brisbin (University of Wisconsin-Eau Claire)

We-02: Should we Spend Classroom Time Together? A Comparison of Synchronous and Asynchronous Remote Delivery Modalities in an Introductory Biostatistics Course

By Amanda Rae Ellis & Jennifer Daddysman (University of Kentucky)

We-03: Learning Design and Student Behavior in a Fully Online Course

By Anelise Sabbag (California Polytechnic State University - San Luis Obispo)

We-04: Evaluating statistical knowledge and skills of future teachers through teaching activities

By Anne-Sophie Charest (Université Laval)

We-05: Teaching Intro Stat in a World Beyond 'p < 0.05'

By Catherine Case (University of Georgia)

We-06: Active Learning in Math & Stats: A Graduate Teaching Assistant Training and Development Program

By Chelsea Uggenti (The University of Western Ontario)

We-07: Progressing through stations to begin a second course in statistics with students from diverse statistical backgrounds

By Daisy Philtron (The Pennsylvania State University)

We-08: Characterizing AP Statistics Teachers' Beliefs and Practices

By David J. Stokes (North Carolina State University)

We-09: Students’ Motivational Attitudes about Statistics: Results from the S-SOMAS Pilot

By Douglas Whitaker (Mount Saint Vincent University); Leyla Batacki (Elizabethtown College); Wendine Bolon, Marjorie Bond (Monmouth College); April Kerby-Helm (Winona State University); Alana Unfried (California State University - Monterey Bay)

We-10: Using Student-Generated JMP Output and Analysis to Guide Class Discussion

By Elise Lahiere (Montclair State University)

We-11: Virtual Tactile Resampling for Permutations and Bootstraps

By Jonathan Wells (Reed College)

We-12: Promoting Student Choice in Initial Interactions with Pre-Recorded Lecture Material

By Julie Deeke (University of Michigan)

We-13: Sampling Distributions Exploration Activity

By Keisha Brown (Georgia State University)

We-14: Stats Class "Stanza Part" with Poetry!

By Larry Lesser (The University of Texas at El Paso)

We-15: Expanding Opportunities: Facilitating Discussions to Improve Measurement Practices in Statistics Education Research

By Leigh Harrell-Williams (U of Memphis); Corinne Manley (U of Florida); Hartono Tjoe (Penn State), Stephanie Casey (Eastern Michigan University), Christopher Engledowl (New Mexico State); Doug Whitaker (Mt. St. Vincent); Charlotte Bolch (Midwestern)

We-16: Expanding Opportunities in a Statistics Capstone Course

By Lisa W. Kay (Eastern Kentucky University)

We-17: Developing Interactive Statistics Apps: A look at the project and student experience

By Maria Tackett, Shari Tian, Sean Li, & Emmanuel Mokel (Duke University)

We-18: Flipping the Intro Stats Classroom with the Integrated Statistics Learning Environment (ISLE)

By Marian Frazier (College of Wooster)

We-19: Probability Exercise: Groups of Vaccinated Couples and Immunity

By Michael D. Larsen (Saint Michael's College)

We-20: Using Interleaved Practice to Teach Statistics

By Paulina Silva (University of California, Irvine)

We-21: SCRATCH self-introduction project – one stone two birds!

By Shu-Min Liao (Amherst College)

We-22: Putting things in order with mean, median, and mode: a fairy tale on indices of central tendency for primary-school

By Susi Osti, Katia Ambrosino, Monica Bailot, & Sara Letardi (Istat . Italian National Institute of Statistics); Francesca Parpinel & Debora Slanzi (Ca’ Foscari University of Venice); Maria Pia Perelli (Didactic Research Centre Ugo Morin)

We-23: Teaching Bootstrapping Methods with R programming

By Xuemao Zhang (East Stroudsburg University)

Thursday, July 1st

Th-01: Progressing: Implementing Proficiency Grading During a Pandemic

By Bradford Dykes (Grand Valley State University)

Th-02: Incorporating Data Management into Statistics Courses

By Busra Ceviren & Jessica Logan (The Ohio State University)

Th-03: Partnering to Prepare Tomorrow’s Life Sciences Researchers

By Bethany White & Jastaranpreet Singh (University of Toronto)

Th-04: New Perspectives on Understanding Graduate Student Instructors’ Longitudinal Experiences with Active Learning

By Elijah Meyer (Montana State University); Jennifer Green (Michigan State University); Liz Arnold (Colorado State University)

Th-05: Building Informal Statistical Inference about Correlation

By Elise Lahiere, Youngjun Kim, Katie Monahan & (Montclair State University)

Th-06: Survey of Attitudes toward Probability

By Elizabeth Eisenhauer & Matthew Beckman (Pennsylvania State University)

Th-07: Confidence disparities: Pre-course coding confidence predicts greater statistics intentions and perceived achievement in a project-based introductory statistics course

By Janet Rosenbaum (SUNY Downstate Health Sciences University); Lisa Dierker (Wesleyan University)

Th-08: Beyond Active Learning: Preliminary hypotheses on the factors that impact gains in introductory statistics: Comparing Simulation vs Consensus Curriculum, Face to Face, Hyflex, and Online Synchronous Modality, and Instructor Factors

By Jennifer McNally & Laura Callis (Curry College)

Th-09: Incorporating anti-racist work into statistics courses

By Jessica Logan (The Ohio State University)

Th-10: Midterm project - role switch

By Jing Chang (College of Saint Mary)

Th-11: Understanding Student's Thoughts about Experimental Design

By Brein Mosely, Kelly Findley, & Karle Flanagan (University of Illinois at Urbana-Champaign)

Th-12: An Alternative to Graded Homework: Online Discussion Boards

By Laura Taylor (Elon University)

Th-13: SOMAS/DS: Measuring the Learning Environment, the Instructor, and the Student

By Marjorie Bond (Monmouth College), Leyla Batakci (Elizabethtown College), April Kerby-Helms (Winona State U), Alana Unfried (California State U, Monterey Bay) and Doug Whitaker (Mount Saint Vincent U)

Th-14: Preparing nurses for the next pandemic: the role of statistics educators moving forward

By Matthew Hayat (Georgia State); Melinda Higgins (Emory), Myoung Jin Kim (Illinois State); Wei Pan (Duke), Yelena Perkhounkova (University of Iowa), Todd Schwartz (University of North Carolina at CH)

Th-15: Fostering critical thinking needed to get started with spatio-temporal data analysis

By Megan Heyman (Rose-Hulman Institute of Technology); Annie Liner (Indiana State University)

Th-16: Examining the Use of the LOCUS Assessment with Undergraduate Students

By Nathan Hebert & Douglas Whitaker (Mount Saint Vincent University)

Th-17: Mastery Based Grading in Upper-level Statistics Courses

By Neil J. Hatfield (Pennsylvania State University)

Th-18: GitHub and intro stats: technology to support group and project-based learning

By Nicholas J. Horton (Amherst College); Maria Tackett (Duke University)

Th-19: Can assessments make you job-ready?

By Pakhi Sharma, Darsy Darssan, Alexandra Robbins-Hill, & Gail Williams (The University of Queensland)

Th-20: Investigating Connections Between College-Level Statistics Courses and Teaching K-12 Mathematics

By Rachel Tremaine & Elizabeth Arnold (Colorado State University)

Th-21: Storyboarding as Part of the Process of Statistical Investigation

By Sara Stoudt (Smith College); Deborah Nolan (University of California, Berkeley)

Th-22: Students' perspectives on entering a data science career after experiential learning with local community organizations

By Vimal Rao, Chelsey Legacy, & Andrew Zieffler (University of Minnesota)

Th-23: Use of Data and Technology in the AP Statistics Classroom - Themes from Teacher Interviews

By Zachary Vaskalis & Hollylynne Lee (North Carolina State University)

Legend

Breakout
Keynote
Birds of a Feather
Posters & Beyond
Tech Talk
Other
Zoom Webinar
Zoom Meeting
Gather Town

Note: All times are listed in Eastern Time.