Untold Stories in Statistics Education Research: Contemplation to Publication and Beyond

Presented at: 11 September 2025; 15:00 UTC

Webinar duration: 90 minutes

Presenter(s): Elinor Jones (Chair), Larry Lesser, Mine Dogucu and 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.

Register here➶

Bios

Elinor Jones is a Professor (Teaching) at University College London (UCL) in the United Kingdom. She is a founder and chair of the Teaching Statistics Section➶ of the Royal Statistical Society (RSS). She co-chaired the organisation of the successful first UK Conference on Teaching Statistics (UKCOTS➶) in 2024, and continues to co-lead the UKCOTS committee. She is committed to supporting educators in engaging in scholarship and research in statistics education. She served as Editor for the 2023 IASE Satellite Conference Proceedings, is currently an Associate Editor for the Statistics Education Research Journal (SERJ) and the European Journal of Engineering Education, and is looking forward to her role as Editor of the 2026 ICOTS Proceedings.

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.

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➶.

Florian Berens is a research associate at the Hector Research Institute of Education Sciences and Psychology at the University of Tübingen. There and at the Tübingen Center for Randomized Controlled Field Trials in Education, he is working on ways to link different data formats within educational intervention studies. In particular, he uses linkages of survey data and test data with digital behavioral traces from digital learning systems. However, qualitative data forms are also considered for analysis. In this way, he attempts to form classical educational science approaches and modern learning analytics into a holistic view of learning processes.

A focus is on analyzing the effectiveness of educational technologies. Florian Berens examines ways to design feedback processes within digital learning environments and their cognitive and motivational effects. In addition to effects on learning performance, he considers effects on motivation, interest, self-concept, and subject-specific beliefs.

Register here➶