Beth Chance is Professor of Statistics at Cal Poly, San Luis Obispo. Dr. Chance has been involved in statistics education research for several years, especially in the areas of assessment and technology, and she has background in program evaluation and curriculum development.  She is an award winning teacher (American Statistical Association’s Waller Education Award) and her applets have been recognized by Merlot. With Dr. Allan Rossman and others she has co-authored three introductory textbooks that focus on using active learning and constructivism to improve students’ statistical thinking and literacy, and a new textbook for a second course in statistics is coming this fall. Dr. Chance has received several NSF grants for her work and is a fellow of the American Statistical Association. She was 2018 Chair of the Section on Statistics Education (American Statistical Association).

Mine Çetinkaya-Rundel is Professor of the Practice at the Department of Statistical Science at Duke University and Data Scientist and Professional Educator at RStudio. Mine’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and under-represented minorities in STEM. Mine works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. She also organizes ASA DataFest, an annual two-day competition in which teams of undergraduate students work to reveal insights into a rich and complex dataset. Mine has been working on the OpenIntro project since its founding and as part of this project she co-authored four open-source introductory statistics textbooks (including this one!). She is also the creator and maintainer of and she teaches the popular Statistics with R MOOC on Coursera.

Ulrike Genschel is an Associate Professor in the Department of Statistics at Iowa State University. Her research interests include statistics education, education research methodology, and the gender gap in the STEM sciences. She has published papers and given presentations on introducing large datasets and case-based learning into the classroom, engaging learners with formative assessment, and the role of gender differences related to mathematical self-efficacy. She is co-leading Iowa State’s participation (an NSF IUSE proposal led by the CIRTL community,, through the University of Wisconsin) to develop a suite of discipline-specific professional development programs to prepare graduate students for their future teaching responsibilities and to advance evidence-based teaching practices for diverse learners in STEM disciplines.

Nick Horton is Beitzel Professor of Technology and Society and Professor of Statistics in the Department of Mathematics and Statistics at Amherst College. He is a fellow of the ASA and the AAAS and recipient of the ASA’s Founder’s Award for Distinguished Service. He received the 2009 ASA Waller Education Award and the 2015 Robert V. Hogg Award for excellence in teaching introductory statistics, among others. He is one of the lead developers of the R Mosaic package for facilitating use of R in statistics courses to a broad audience. He is also co-author of Modern Data Science with R (CRC Press). Nick serves as co-chair of the National Academies Committee on Applied and Theoretical Statistics. He has held numerous leadership positions in the ASA including Chair of the Section of Statistics Education and lead author of the ASA Curriculum Guidelines for Undergraduate Programs in Statistical Science. As Section Chair, he reinstated and developed the Section’s mentoring program for younger faculty.

Jingchen (Monika) Hu is an assistant professor of statistics at Vassar College. She actively develops teaching and learning material for Bayesian methods at the undergraduate level, and conducts research on undergraduate Bayesian education. She is a co-author of Probability and Bayesian Modeling (CRC Press), a textbook suitable for a year-long probability and Bayesian statistics sequence for undergraduate students. Her other research interests include statistical data privacy through methods of synthetic data and differential privacy. She has active research collaborations on statistical data privacy with researchers from the U.S. Bureau of Labor Statistics, the National Center for Science and Engineering Statistics (NSF), and most recently, the OpenDP community. Monika leads a senior seminar on statistical data privacy at Vassar and routinely involves undergraduates in such projects, some of which result in peer-reviewed journal publications. She is currently collaborating on a textbook/reference book on this topic with two co-authors.

Yue Jiang is Assistant Professor of the Practice of Statistical Science at Duke University. A biostatistician by training, Yue has applied research interests in public health and biomedicine, and routinely involves undergraduate students in such projects. He is also working with the Duke University School of Medicine to revamp their statistical and quantitative literacy module for medical students. Finally, Yue has pedagogical interests in formally developing and directly teaching peer review skills and will be leading a Birds of a Feather discussion group on the topic prior to this year’s JSM.

Allan Rossman is Professor of Statistics, Cal Poly - San Luis Obispo. Allan co-author of several innovative textbooks, all rooted in an active learning pedagogy. He has given scores of workshops for teachers and future teachers, including as part of the Project NExT program. With Tom Short, he directed the STATS workshop series through the MAA in the 1990s to prepare instructors in mathematics departments to teach statistics, and has received several NSF grants for his innovative pedagogy. He was a member of both GAISE guidelines writing committees and recently received the Waller Distinguished Teaching Career Award recognizing his national and international impact in statistics education. He has also led the Journal of Statistics Education interview series of statistics educators since 2011. He writes a weekly blog about teaching introductory statistics at

Sara Stoudt is an applied statistician with research interests in ecology and the communication of statistics. Stoudt received her doctorate in statistics from the University of California, Berkeley, and she is starting as an Assistant Professor in the Department of Mathematics at Bucknell University in the fall. Follow Sara on Twitter (@ sastoudt) and check out her recent book with Deborah Nolan, Communicating with Data: The Art of Writing for Data Science.

Allison Theobold is an Assistant Professor of Statistics at Cal Poly in beautiful San Luis Obispo, California. Allison received her doctorate in Statistics, with an emphasis in Statistics Education, from Montana State University. Allison’s work focuses on innovation in statistics and data science education, with an emphasis on equitable pedagogy and learning trajectories. Allison is also interested in exploring pedagogical approaches for enhancing retention of under-represented students in STEM, including creating inclusive discoursive spaces and equitable group collaborations. Allison is actively involved in the Carpentries community, both as a certified instructor and a curriculum maintainer for the R Social Science curriculum.

Jennifer Ward is an Associate Adjunct Instructor at Clark College and Portland Community College, in the Portland, Oregon area. Jennifer earned her Master’s in Statistics from Portland State University. Her interests lie in designing courses to be culturally responsive, inclusive, and incorporating social justice topics into her lessons. She’s also a trained online instructor and has taught online courses for over a decade. Jennifer is actively involved in the ASA’s Section on Statistics and Data Science Education Mentoring Program and runs the adjunct mentoring program at Clark College. Starting next winter, she’ll take office as an At-Large member on the Executive Committee for the Section on Statistics and Data Science Education and a co-chair for USPROC, a collaboration between the ASA and CAUSE.