Webinars

This is the third webinar in a series designed for a broad audience of statistics and data science education researchers: young scholars beginning their research journeys, scholars from other disciplines interested in transitioning to statistics and data science education research, and existing statistics and data science researchers looking for new directions for their work.This session will focus on theoretical frameworks: an important but often misunderstood element of education research. An initial talk will provide an overview of theoretical frameworks: what they are (and are not), why researchers need them, and how they benefit both the individual and the field. A second talk will discuss an example research study illustrating the use of a theoretical framework in statistics education. After the formal presentations, there will be time for audience questions and related discussion.Presenters Bios:Denise A. Spangler is in her 8th year serving as Dean of the Mary Frances Early College of Education at the University of Georgia. She is a former elementary school teacher, a member of the UGA Teaching Academy, and a recipient of the Richard B. Russell Award for Excellence in Undergraduate Teaching. Through her research she seeks to understand how novice teachers put into practice what they have learned from their teacher education programs, their experiences in schools, and their own experiences as students and how they balance these sometimes competing experiences.Dr Katie Makar is a Professor in Mathematics and Statistics Education at The University of Queensland and President of the Mathematics Education Research Group of Australasia (MERGA). Her award-winning research focuses on mathematics teachers' learning of pedagogies that support complex problem solving and children's statistical reasoning in an era of data science. Funded by over $1.6 million in grants and consultancies, Katie's classroom-based research collaborates with practicing teachers to seek pragmatic solutions to improving teaching and learning.

This is the second webinar in a series designed for a broad audience of statistics and data science education researchers: young scholars beginning their research journeys, scholars from other disciplines interested in transitioning to statistics and data science education research, and existing statistics and data science researchers looking for new directions for their work.This session will focus on qualitative research: a family of "small n" research approaches that provide deep insights into human experience. An initial talk will provide an overview of qualitative research, followed by a discussant who will respond and add unique perspectives from the statistics education community. After the formal presentation and discussant contributions, there will be time for audience questions and related discussion.For reference, the prior webinars in this series are: What is Scholarship and Research in Statistics and Data Science Education? This webinar series is co-organized by CAUSE Research, the RSS Teaching Section, and Researchers of Statistics Education (RoSE) Network. Speaker Bio (Nicola Sochacka)Dr. Nicola (Nicki) Sochacka co-directs the ProQual Institute for Interpretive Research Methods, which builds capacity for high-quality qualitative and mixed methods research in STEM education. Drawing on the strengths STEM scholars bring to educational research—content expertise, teaching experience, and a drive for positive change—Nicki helps researchers design strategic, well-aligned studies through ProQual’s 9-week online course. This novel, person-centered program empowers participants to make informed decisions at every stage of the research process. Prior to founding the ProQual Institute, Nicki was Associate Director for Research Initiation at the Engineering Education Transformations Institute (EETI) at the University of Georgia. Supported by over $3.5M in NSF funding, her research explored empathy in engineering, the role of shame in identity development, arts-STEM integration, and innovative approaches to interpretive research. She is an experienced mentor, writing coach, and advisor who thrives on helping scholars design, publish, and propagate meaningful interpretive work. Discussant Bio (Kelly Findley)Kelly is a Teaching Associate Professor at the University of Illinois Urbana-Champaign. He earned a PhD in Curriculum and Instruction from Florida State University, focusing his dissertation on the disciplinary perspectives and experiences of graduate teaching assistants in statistics. Kelly primarily conducts qualitative research that seeks to capture rich examples of student thinking. He aims to create work that builds theory regarding both students' intuition about statistical concepts and students’ perspectives of the broader discipline.    

This talk is designed for a broad audience of statistics and data science education researchers: young scholars beginning their research journeys, scholars from other disciplines interested in transitioning to statistics and data science education research, and existing statistics and data science researchers looking for new directions for their work. The talk will begin with a description of the types of research areas and questions of interest to the field of statistics and data education research. As time allows, we will consider how to move from interesting ideas to researchable questions and how to connect ideas to existing literature to maximise the potential of your research to move the field of statistics and data science education research forward. After the formal presentation and discussant contributions, there will be time for audience questions and related discussion. This webinar series is co-organized by CAUSE Research, the RSS Teaching Section, and Researchers of Statistics Education (RoSE) Network. Speaker bio: Dr Jennifer J Kaplan has been an active researcher in statistics and data science education since the early 2000s. She served as the Editor of Regular Papers for the Statistics Education Research Journal (SERJ) from 2018 – 2023 and has been an Associate Editor for the Journal of Statistics and Data Science Education (JSDSE) since 2010. She is probably best known for her research in lexical ambiguity, studying the effects of the use of statistical terms that have competing meanings in everyday usage. In general, her research program combines learning in undergraduate statistics courses in HE with professional development of instructors of undergraduate students. Dr Kaplan is currently the Director of the PhD Program in Mathematics and Science Education (MSE) at Middle Tennessee State University (MTSU) and lives within biking distance of the geographic center of the state of Tennessee. Discussant bio: Professor Rhys C Jones (Professor of Statistical Literacy) is an internationally recognised educational leader with extensive experience in curriculum development and theory, statistics education, and engaging students in small and large classroom settings (offline and online). Rhys is an International Statistical Institute Elected member, a member of both the Teaching Statistics Section and the Education Policy Advisory Group of the Royal Statistical Society, and a trustee of the Teaching Statistics Trust. He has held lecturing positions at Cardiff University, London Southeast College, and Birmingham City University. Over his career, he has taught in a variety of fields, at undergraduate and postgraduate levels, including statistics, quantitative methods, mathematics for science, teacher training, research methods, biomedical science, nutrition and organic chemistry, health and well-being, and clinical anatomy and physiology. His primary research contributions are in the areas of curriculum development, randomness misconceptions, and the role of context in statistics education.