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GO!
eCOTS 2022 - Posters
Program
Keynotes
BoF
Breakouts
Posters
Workshops
Monday
, May 23rd
A Statistician Teaches Deep Learning: From Fundamentals to Applications
By David Han (UT San Antonio)
Examining Flipped Classrooms in Statistical Literacy Instruction during the Pandemic: Results from a Quasi-experimental Study with Multiple Instructors
By Leigh Harrell-Williams, Dale Bowman, Nataliya Doroshenko (University of Memphis)
Tuesday
, May 24th
Adding Authentic Assessment to a Group Data Collection Project
By Jane Oppenlander & Eva Williford (Clarkson University)
Building an inter-disciplinary statistics data repository
By Ryne VanKrevelen, Laura Taylor, & Mark Weaver (Elon University)
Determining an Appropriate Placement Test for Introductory Statistics: Preliminary Findings
By Katerina Allan & Douglas Whitaker (Mount Saint Vincent University)
Experience in Using R in Statistics Course
By Faruk Guder & Mary Malliaris (Loyola University Chicago)
Making Statistics Relevant for Students
By Asal Aslemand (University of Toronto, Mississauga Campus)
Pilot 2: Further Development and Psychometric Analysis Of The Student Survey of Motivational Attitudes Towards Statistics
By Matthew Dunham, Alana Unfried (California State University, Monterey Bay); Douglas Whitaker (Mount Saint Vincent University)
R you willing to accept the Challenge?
By Paul J. van Staden, Christine Kraamwinkel, Ricardo Marques Salgado, René Stander (Department of Statistics, University of Pretoria, South Africa)
Reliable Recall: The Process is the Point
By Nicholas Lytal (California State University, Chico)
Why Johnny Can’t See “The Big Picture of Statistics” and What We Can Do About It
By Rebecca L. Pierce (Ball State University) & Matthew T. Brenneman (Embry-Riddle Aeronautical University)
Wednesday
, May 25th
Adjunct Faculty and Technology in Statistical Education: A Qualitative Study
By Samantha Estrada, Martinez, Erica, Garrido, Sergio, Fernandez Da Silva, Ana (University of Texas at Tyler)
CAUSE Research: Connecting statistics and data science education researchers
By Matthew Beckman (The Pennsylvania State University); Laura Le (University of Minnesota)
Creating Interactive Tutorials for Teaching Statistics Online with learnr
By Chris Aberson (Cal Poly Humboldt)
Diversity, Belonging, and Introductory Statistics
By Kelly Bubp (Frostburg State University)
GAISE-ing on Social Justice
By David Han (UT San Antonio)
The Influence of Harvey and COVID on AP Statistics Students in Houston, Texas
By Rachael N. Becker, Meredith Paige Richards, Alexandra E. Pavlakis, Kessa Roberts (Southern Methodist University)
Use of small-scale classroom experiments to inform simulation-based statistical inference (SBI) pedagogy in tertiary classrooms
By Sophia Chung, Maddie Schroth-Glanz, Beth Chance (Cal Poly - San Luis Obispo)
Whole Hog Mastery Teaching and Learning in an Introductory Statistics Classroom
By Kevin M Cummins (California State University, Fullerton)
Thursday
, May 26th
Cobb’s Factor Diagrams for effectively introducing ANOVA
By Dan Adrian (Grand Valley State University)
Foundations for AI-assisted formative assessment feedback for short-answer tasks in large-enrollment classes
By Susan Lloyd & Matthew Beckman (The Pennsylvania State University)
Rate of Decline of Arctic Sea Ice and Regression Modeling
By Amanda Walker (Texas State University, San Marcos)
Statistics Education for Students With Visual Impairment
By Annabel Li (University of Northern Colorado)
Student Perceptions on Reproducible Research in Introductory Statistics Courses
By Nicholas Bussberg (Elon University)
Survey of Probability Attitudes
By Elizabeth Eisenhauer, Matthew Beckman, & Ephraim Hanks (The Pennsylvania State University)
Teaching modeling in introductory statistics: A comparison of formula and tidyverse syntaxes
By Amelia McNamara (University of St. Thomas)
Utilizing Open Source Resources to Teach Introductory Data Science
By Tyler George (Cornell College)
What Statistics Instructors Think Students Should Know
By Paulina Silva (University of California, Irvine)
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