Projects


AIMS Project

Adapting and Implementing Innovative Material in Statistics (AIMS) was an NSF-funded project from 2006–2010 that developed lesson plans and activities based on innovative materials that have been produced for introductory statistics courses (DUE-0535912). Initially written in 2005–2006, the AIMS lesson plans and student activity guides were developed to help transform an introductory statistics course into one that is aligned with the Guidelines for Assessment and Instruction in Statistics Education (GAISE) for teaching introductory statistics courses. The lessons, which build on implications from educational research, involve students in small and large group discussion, computer explorations, and hands-on activities. The lessons are described in full detail along with the research foundations for the lessons, in Garfield and Ben-Zvi’s book Developing Students’ Statistical Reasoning: Connecting Research and Teaching Practice.



BioSQuaRE Project

Biology Science Quantitative Reasoning Exam (BioSQuaRE) was a multi-institutional HHMI-funded project from 2013–2016 that developed an instrument to assess the quantitative readiness of students planning on majoring in biology or the life sciences (Grant #520076788).

Q6 group at Keck Science Center (Claremont, CA) Feb. 2016.
Front row: Marion Preest, Paul Overvoorde, Laura Ziegler, Liz Stanhope, Jason Belitsky, Tabassum Haque
Back row: Charles Umbanhowar, Peter Brodfuehrer, Greg Davis, Laura Le, Marcelo Vinces, Andrew Zieffler



CATALST Project

Change Agents for Teaching and Learning Statistics (CATALST) was an NSF-funded project from 2008–2012 that developed materials for teaching a radically different introductory statistics course based on randomization and bootstrap methods to provide students a deep understanding of statistical inference (DUE-0814433). The materials produced from this project include a set of in-class activities and an online-book of accompanying reading material.

The different versions of Statistical Thinking: A Simulation Approach to Modeling Uncertainty



e-ATLAS Project

Evaluation and Assessment of Teaching and Learning About Statistics (e-ATLAS) was an NSF-funded project from 2011–2013 that developed high-quality instruments to help evaluate the effectiveness of past and on-going efforts to reform the teaching and learning of introductory statistics at the tertiary level (DUE-1044812 & 1043141). Two instruments developed as part of this project were the Statistics Teaching Inventory (STI) and Goals and Outcomes Associated with Learning Statistics (GOALS). An additional instrument, the Basic Literacy in Statistics (BLIS), was developed by Laura Ziegler as part of her doctoral dissertation research was also a part of the e-ATLAS project.



Recent Blog Posts


Minnesota State High School Boys Hockey Predictions (Updated Quarterfinals)

In a previous post, I used Monte Carlo simulation to predict the winner of the 2018 Minnesota State High School Boys Hockey tournament. Now that the quarterfinal games have been played, I thought I would update my predictions. The process for this is to: Update the Elo ratings based on the quarterfinal games; Re-simulate the tournament I simulated the Class A state tournament 10,000 times using the same process as described in my previous post.

Minnesota State High School Boys Hockey Predictions

The state high school boys hockey tournament, scheduled for March 7–10, is one of the premiere sporting events in the state of Minnesota. According to Wikipedia, this event has drawn over 100,000 spectators 22 times in its history, eclipsing 135,000 spectoators in 2015. Many national caliber players played high school hockey in Minnesota, several taking part in the state tournament. Names like Neal Broten, Herb Brooks, and T. J. Oshie are alumni of state tournaments past.

College in the Schools

College in the Schools is a concurrent enrollment program in which existing University of Minnesota courses are taught in high schools by high school teachers. All schools wishing to offer a CIS course go through an application process, including an interview and approval by the post-secondary academic department sponsoring the course of any high school teachers who will be teaching the course. Since CIS is a concurrent enrollment program, students are enrolled simultaneously in the University of Minnesota course (EPsy 3264: Basic and Applied Statistics) and a course at their high school.

EPsy 3264: Basic and Applied Statistics

EPsy 3264 is a 3-credit course designed to engage students using a modeling and simulation approach to inference. This course fulfills the Mathematical Thinking component of the Liberal Education requirements at the University of Minnesota. Statistics is more than just an application of mathematics or a methodology used in some other discipline. Statistics is a principled way of thinking about the world. In particular, it is a principled approach to data collection, prediction, and scientific inference.