The purpose of this SIGMAA is to facilitate the exchange of
ideas about teaching statistics, the undergraduate
statistics curriculum and all other issues related to
providing students with effective and engaging encounters
with statistics in their courses of study. We also
hope to foster increased understanding of statistics among
members of the MAA, promote the discipline of statistics
among students, and work cooperatively with other
organizations to encourage effective teaching and learning
We had an exciting program at the Joint Mathematics Meetings
in San Diego, January 10-13, 2018!
A link to slides from the presentations will appear here shortly.
Session on Technology and Apps for Teaching Mathematics and Statistics (joint with the MAA Committee on Technology in Mathematics Education (CTiME))
Friday, January 12, 1:00-6:00pm, Saturday 9 to 10:15 a.m.
Description: One of the five skill areas in the American Statistical Association’s curriculum guidelines is “Data Manipulation and Computation” (pg 9), embracing the need for students to be competent with programming languages, simulation techniques, algorithmic thinking, data management and manipulation, as well as visualization techniques. Additionally, the recently revised Guidelines for Assessment and Instruction in Statistics Education (GAISE) continue to encourage active learning, a focus on conceptual understanding and statistical thinking, and the use of real data with a context and purpose, with additional guidelines to incorporate multivariate thinking and teach statistics as an investigative process. This session invites presentations on innovative use of software or technology, classroom activities, resources, data sets, case studies, and effective pedagogical approaches in teaching statistics. Papers on modern approaches to teaching from a simulation-based perspective and incorporating programming and data science ideas into the course are particularly encouraged.
Scholarship on Teaching and Learning in Statistics Education
Saturday, January 13, 1:00-3:55pm
Description: Statistics education research is an emerging field that has grown out of several disciplines including mathematics education and educational psychology. Research in statistics education is both qualitative and quantitative and ranges from classroom studies of new pedagogical methods to multi-institution research projects investigating how students learn statistics to the development of theoretical learning models. Journals such as the Journal of Statistics Education, Technology Innovations in Statistics Education, and the Statistics Education Research Journal provide central channels for the dissemination of statistics education research. This session invites presentations on research and scholarship in the teaching and learning of statistics at all levels from K-12 through postsecondary to the training of professionals. Presentations may include current research projects in the classroom or across institutions as well as reviews of the statistics education research literature.
“A Mathematician Teaches Statistics: The Road Less Traveled” on Wednesday, January 10, 3:50-5:10pm.
Description: With the recent rapid growth in statistics programs and the large number of required statistics courses in other disciplines, many statistics instructors do not have a graduate degree in statistics. Especially at smaller institutions without separate statistics departments, trained mathematicians who may not have taken a data analysis course are commonly asked to teach applied statistics courses, either voluntarily or involuntarily. Our panel will host several members of the mathematics and statistics community from a variety of institutions that were trained in mathematics and transitioned to teaching statistics. Panelists will share their journey and experiences in successfully transitioning from teaching mathematics to statistics, including how teaching statistics differs from teaching mathematics and advice for other mathematicians that find themselves in the same situation.
Patti Frazer Lock, St. Lawrence College
Chris Oehrlein, Oklahoma City Community College
Sue Schou, Idaho State University
Charilaos Skiadas, Hanover College
Guest Lecture by Rob Gould on “We Are All Data Scientists (Or We Should Be)” .
JMM 2017 Paper Presentations
The presentations at our JMM 2017 sessions were well attended
and enjoyed by many. Find the link to many of the presentation
slides below. Although these do not include audio for those of
you who were unable to attend, you may find interesting ideas
within these slideshows. The 2016 presentations are also
available at the link.