USCOTS 2017 - Posters

Friday May 19th, 9:45 am – 10:45 am

P1-01: Student-driven Simulations for the Statistics Classroom

By Kelly Findley (Florida State University)

P1-02: R Simulation Apps for Learning Probability using ‘Shiny’

By Roger Johnson (South Dakota School of Mines & Technology)

P1-03: Building your Multiple Regression Model with Bricks

By Laura Ziegler and Anna Peterson (Iowa State University)

P1-04: Multi-institution Assessment Results from Courses Using and Not Using Simulation-based Inference

By Beth Chance, Soma Roy, Stephanie Mendoza, and Brannden Moss (Cal Poly, San Luis Obispo); Nathan Tintle (Dordt College); Todd Swanson and Jill VanderStoep (Hope College)

P1-05: Exploring Methods for Introducing Confidence Intervals

By Upneet Cheema and Beth Chance (Cal Poly, San Luis Obispo)

P1-06: Modules for Teaching Statistics with Pedagogies using Active Learning (MTStatPAL)

By Ginger Rowell, Lisa Green, Scott McDaniel, Nancy McCormick, and Jeremy Strayer (Middle Tennessee State University)

P1-07: Teaching Post-Secondary Introductory Statistics Students Sampling Distributions: Computer versus Tactile Simulations

By Stacey Hancock (Montana State University); Wendy Rummerfield (University of California, Irvine)

P1-08: Implementing an Interdisciplinary NSF S-STEM Program at Small Liberal Arts Colleges

By Ivan Ramler (St. Lawrence University)

P1-09: Results of a Two-Semester Study on Mnemonics Usage in an Online Introductory Statistics Course

By Megan Mocko (University of Florida); Lawrence M. Lesser, Amy E. Wagler, and Wendy S. Francis (The University of Texas at El Paso)

P1-10: The Attitudes and Beliefs of Exemplary Statistics Teachers

By Douglas Whitaker (University of Wisconsin, Stout)

P1-11: Research and Data Ethics in the Statistics Classroom

By Douglas Whitaker (University of Wisconsin, Stout)

P1-12: Impact of Quiz Assignment and Scoring Methods on Course Completion Rates and Exam Scores in an Online Introductory Statistics Course

By Stefanie R. Austin and Whitney A. Zimmerman (The Pennsylvania State University)

P1-13: A MOOC and PLT: Blending Two Professional Development Models to Enhance Teaching Statistics

By Kemal Akoğlu and Hollylynne Lee (North Carolina State University)

P1-14: Writing Assignments in a Second Statistics Course

By Amy Wagaman and Kristen Brookes (Amherst College)

P1-15: 2016 Presidential Election Predictions in the Undergraduate Statistics Classroom

By Alana Unfried (California State University, Monterey Bay)

P1-17: Does Encouragement Lead to Better Attitudes? A Randomized Encouragement Study of the Effect of Weekly Emails in Online and Flipped Classrooms

By Nathan Taback and Alison Gibbs (University of Toronto)

P1-18: Flipping Online: Creating an Active Learning Classroom in an Online Course

By Laura Le and Ann Brearley (University of Minnesota)

P1-19: Introductory Statistics Students’ Conceptual Understanding of Study Design and Conclusions

By Elizabeth Brondos Fry (University of Minnesota)

P1-20: Providing Real-time Instructor Feedback about Undergraduate Learning in Statistics through Machine Learning Algorithms

By Alex Lyford (University of Georgia)

P1-21: STATS4STEM: Data, Computing, and Assessment Resources for High-School Statistics Students

By Eric Simoneau (stats2stem.org)

P1-22: Online Statistics Tutoring at the College Level

By Kayla Montomery, Ann Marie Gardner, Katie Klick, Zach Ricci, Whitney Zimmerman, Glenn Johnson, Neill Johnson (The Pennsylvania State University)

P1-23: Data in Search of a Context: An Icebreaker Activity

By Alex White, Amanda Walker, and Layla Guyot (Texas State University)

P1-24: Impact of Working with Real Data on Perceptions of the Importance of Statistical Inference

By Andrew Sage and Ulrike Genschel (Iowa State University)

P1-25: Teaching Statistical Graphics and Visualization in a Modern, Data-Obsessed World

By Rebecca Nugent and Sam Ventura (Carnegie Mellon University)

P1-26: Using Guided-Inquiry Activities to Dig Into Data in Introductory Statistics

By Amanda Sutherland and Beth Dodson (Shenandoah University)

P1-27: Extending Hands-on Activities Using StatCrunch to Teach Statistical Inference

By Ryne VanKrevelen, Laura Taylor, and Heather Barker (Elon University)

P1-28: Symbulate: A Python Package for Simulation

By Kevin Ross and Dennis Sun (Cal Poly, San Luis Obispo)

P1-29: Investigating Levels of Graph Comprehension Using the LOCUS Assessments

By Carlotte Bolch (University of Florida)

Saturday May 20th, 9:45 am – 10:45 am

P2-01: Using Pig Dice to Explore Probability, Simulation, Distributions, and Informal Inference

By Laura Hildreth and Jennifer Green (Montana State University)

P2-02: Poll Monday - Thinking Tuesday - Results Wednesday: Structured Learner Engagement Activities Anyone Can Use!

By Dennis Pearl and Glenn Johnson (The Pennsylvania State University)

P2-03: Project SMILES: Student-Made Interactive Learning with Educational Songs in Introductory Statistics

By John Weber (Perimeter College at Georgia State University); Lawrence M. Lesser (The University of Texas at El Paso); Dennis Pearl (The Pennsylvania State University)

P2-04: Students Generating and Using Their Own Data in a 5-day Basic Statistics Course

By Eirini Koutoumanou and Angie Wade (University College London)

P2-05: Student Designed Data-Oriented Class Projects for a Forensic Science Course

By Elizabeth J. Malloy, Richard Bennett, and James E. Girard (American University)

P2-06: A Service Learning Project in an Introductory Course: Visualizing Relationships in 2-1-1 Data

By Carolyn Cuff and Sam Hockenberry (Westminster College)

P2-07: Show Me How to Simulate It (from Scratch!): A Project to Compare Methods for Calculating the Confidence Interval for a Population Proportion

By Maureen Petkewich and Brian Habing (University of South Carolina)

P2-08: Development of Introductory Statistical Courses in the Japanese Massive Open Online Course: A Preliminary Report

By Shizue Izumi and Masahiko Sue (Shiga University, Japan)

P2-09: Real Data Oriented Project-Based Learning Model of Shiga University: Results from Pilot Classes

By Shizue Izumi (Shiga University, Japan)

P2-10: DYOD (Download Your Own Data)

By Robin Lock, Ivan Ramler, and Choong-Soo Lee (St. Lawrence University)

P2-11: Developing a Research and Writing Intensive Introductory Statistics Course for Science Majors

By Jessica Chapman (St. Lawrence University)

P2-12: Using R in a Probability Course

By Qing (Wendy) Wang (Wellesley College)

P2-13: A First Look at Training GTAs to Foster Active Learning and Teaching for Conceptual Understanding

By Kristen E. Roland and Jennifer J. Kaplan (The University of Georgia)

P2-14: Let’s Help Teddy: Activities Developed to Foster Active Learning and Conceptual Understanding in an Introductory Statistics Course

By Kristen E. Roland and Jennifer J. Kaplan (The University of Georgia)

P2-15: What We Learned about the Design of a Flipped Classroom in an Introductory Statistics College Course

By Marggie D. González-Toledo, Pedro A. Torres-Saavedra, Dámaris Santana-Morant, and Yareliz Román (University of Puerto Rico at Mayaguez)

P2-16: Using Rubrics to Score Data Analysis Assignments in Large Enrollment Introductory Statistics Classes

By Beth Johnson and David Holmes (George Mason University)

P2-17: Pigskin Probability

By Carl Miller (Northern Kentucky University)

P2-18: Take a Risk: Inference for the Relative Risk via Resampling

By Bernhard Klingenberg (Williams College); Christine Franklin (American Statistical Association)

P2-19: Modules for Infusing Data Science into the Statistics Curriculum

By Adam Loy (Lawrence University); Laura Chihara (Carleton College); Shonda Kuiper (Grinnell College)

P2-20: Test Your Knowledge about Two-year Colleges in the U.S.

By Monica Dabos (College of the Canyons); Michael Posner (Villanova University)

P2-21: Exploring the Law of Large Numbers through the Egg Roulette Game in Fathom

By Amanda Walker and Alex White (Texas State University)

P2-22: Temperature of the Great Lakes

By Laura Ring Kapitula (Grand Valley State University)

P2-23: Statistical Graphics and Visualization: Course Learning Objectives and Rubrics

By Jerzy Wieczorek (Carnegie Mellon University)

P2-24: Databases! A Visual Introduction to the Data Science Techniques of Database Querying and Design

By Jennifer Broatch (Arizona State University)

P2-25: Connecting to Real World Data: The Case of AirBnB

By Jodi Fasteen (Carroll College)

P2-26: Characterizing Common Errors in Simulation-Based Inference

By Catherine Case (University of Georgia); Tim Jacobbe (University of Florida)

P2-27: Teaching Introductory Statistics Concepts in an Interdisciplinary Honors Course

By Lisa W. Kay (Eastern Kentucky University)

P2-28: What Do Faculty in the Health Sciences Know about Statistics?

By Matthew Hayat (Georgia State University); Michael Jiroutek (Campbell University); MyoungJin Kim (Illinois State University); Todd Schwartz (University of North Carolina, Chapel Hill)

P2-29: Tips and Pitfalls of Converting to Simulation-based Inference for Large Lectures

By Daisy Philtron and Pat Buchanan (The Pennsylvania State University)

P2-30: Mixing It Up: Evaluating the Impact of Purposeful Content Re-sequencing in an Undergraduate Introductory Statistics Course

By Samantha Robinson (University of Arkansas, Fayetteville)

Legend

Birds of a Feather
Breakout
Keynote / Panel
Workshop
Poster Session
Tech Talk
Sponsored
Other

※ Denotes tentative session.

* Denotes repeated session.

Note: All times are listed in Eastern Time.