Untold Stories in Statistics Education Research: Contemplation to Publication and Beyond
| Date | 11 Sep 2025 |
| Time | 15:00 - 16:30 in UTC |
| Presenter |
Ellinor Jones
Larry Lesser
, The University of Texas at El Pase
Mine Dogucu
, University of California Irvine
Florian Berens
|
Many research endeavours have a backstory which is more complex, nonlinear, messy, and instructive than the final article suggests. This webinar brings together authors of diverse statistics education studies to share how their research unfolded over time, including unanticipated obstacles, conflicting reviewer feedback, and evolving perspectives. Expect honesty, practical wisdom, and a deeper appreciation for the start-to-finish journey of ‘doing research’ in statistics education.
Presenters
About the presenter
About the presenter
Biography:
Larry Lesser has worked since 2004 at The University of Texas at El Paso➶, where he is a Professor in the Mathematical Sciences Dept. He has won national and state recognitions within and beyond his discipline, is an elected Fellow➶ of the American Statistical Association, and was interviewed about his career in the March 2020 Journal of Statistics and Data Science Education➶. Lesser’s work has yielded state and NSF grants, textbooks, and 140 peer-reviewed papers -- including curriculum innovations (for introductory statistics, statistical literacy, and math-for-liberal-arts courses) and statistics education quantitative or qualitative research on language, equity, ethics➶, teacher preparation, intuition/misconceptions, mnemonics, and edutainment. His experience also includes working as a state agency staff statistician, chairing a high school math department, authoring textbooks, serving a term as the assistant editor for Statistics Education Research Journal and two terms as an associate editor for Journal of Statistics and Data Science Education.
About the presenter
Biography:
Mine Dogucu is Associate Professor of Teaching in the Department of Statistics at University of California Irvine. Her goal is to create educational resources for statistics and data science that are accessible physically and cognitively. Her work focuses on modern pedagogical approaches in the statistics curriculum, making data science education accessible, and undergraduate Bayesian education. She is the co-author of the book Bayes Rules! An Introduction to Applied Bayesian Modeling➶. She works on a few projects funded by the United States National Science Foundation and the National Institutes of Health. She writes blog posts about data, pedagogy, and data pedagogy at DataPedagogy.com➶.