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Research in Statistics Education: It's Not a Solo Sport


Abstract

The goals of this session are (1) to increase participants' awareness of the value of (and frequency of) collaborations in conducting statistics education research, (2) to convey -- through personal descriptions -- several different models of collaboration (who is involved, how they work together, some benefits derived from the collaboration, and some obstacles that were overcome, etc.), and (3) to give the participants a chance to network and begin to find people with common interests who might be potential collaborators. To achieve these objectives and to keep the session interactive and contextualized, the format will include a short icebreaker to get people thinking about their own collaboration experiences and research interests, followed by a panel of 3-4 people representing different collaborations in statistics education research who will share their experiences, time for audience discussion with the panelists, and a meet-n-greet activity at the end to help people initiate potential research collaborations.

Panel Members

Cliff Konold (representing the Scientific Reasoning Research Institute at Univ. of Massachusetts)
Carl Lee (representing his collaboration with Maria Meletiou)
Bob delMas (representing collaborations with Joan Garfield and Beth Chance)
Marsha Lovett (collaborations with statisticians at Carnegie Mellon)

Bio-Sketches

Cliff Konold is Associate Research Professor in the Scientific Reasoning Research Institute at the University of Massachusetts, Amherst where he has directed numerous projects focused on understanding and developing statistical reasoning. He currently directs the NSF-funded Tinkerplots project, which is developing data-analysis software and curriculum materials for the middle school. This work builds on his many years of research studying how both young children and adults reason about chance and data and on the role technology can play in the development of their thinking.

Carl Lee graduated from the Department of Statistics Iowa State University in 1984. He is a full professor of Statistics in the Department of Mathematics and a senior research fellow at the Center for Applied Research & Technology at Central Michigan University. He is an elected member of the International Statistical Institute. He currently serves as an advisory board member in Statistics Education Research for the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE). He was the former university assessment coordinator for Central Michigan University and served as President of Mid-Michigan Chapter of ASA for five years. His current research interests are in statistics education, data mining, and generalized distributions.

Robert delMas is an Associate Professor of Statistics and Mathematics in the General College of the University of Minnesota. His primary research interest is in the study of educational experiences that promote conceptual change and development. Dr. delMas is an experienced programmer who has developed several software programs designed to facilitate students' conceptual development in statistics. He is a co-principal investigator with Joan Garfield and Beth Chance on the NSF-funded ARTIST project, serves as an associate editor for the Journal of Statistics Education, is a member of the ASA/AMATYC Joint Committee on Statistics Education, and serves on the Research Advisory Board of CAUSE.

Marsha Lovett is Associate Director of the Eberly Center for Teaching Excellence and Assistant Professor of Psychology. She received her doctorate in Cognitive Psychology from Carnegie Mellon and, except for a year as a visiting scholar at UC Berkeley's School of Education, has spent her academic career in Pittsburgh, Pennsylvania. Her research interests center on learning during problem solving, specifically on how students acquire effective problem-solving strategies in statistics and how individual differences between students impact the learning process.

Results

Handout (PDF)