I always find that statistics are hard to swallow and impossible to digest. The only one I can ever remember is that if all the people who go to sleep in church were laid end to end they would be a lot more comfortable.
~Mrs. Robert A. Taft
I received a degree in Mathematics Education from Saint Cloud State University in 1997. From 1998-2002, I took a job teaching high school students the beauty of mathematics. During those four years I began a Master's Degree in the History of Mathematics, again at Saint Cloud State University. I also had a wonderful opportunity to develop and teach the high school's Advanced Placement Statistics course. This inspired me to continue my graduate education at the University of Minnesota, this time emphasizing statistics education. In 2006, I obtained a Ph.D. in Quantitative Methods in Education with a concentration in Statistics Education.
I currently teach both undergraduate and graduate level statistics courses in the Educational Psychology department at the University of Minnesota. Prior to this gig, I taught a variety of mathematics and statistics courses at ROCORI High School (Cold Spring, Minnesota) and a mathematics course at Saint Cloud State University. In total I have taught mathematics or statistics for the last ten years.
Statistics education is a fairly young area of research that has been influenced by several other fields of study such as psychology and mathematics education. Researchers working in this field have generally focused their efforts on how to improve student learning of statistics, often via improving statistics instruction. The Research Advisory Board of the Consortium for the Advancement of Undergraduate Statistics Education, in fact, suggests that the results of statistics education research should have direct implications for instruction, and further, that research studies should specifically address classroom implications. Since it is an interdisciplinary field of inquiry, statistics education research has not endorsed any one particular empirical research method. Researchers have employed many differing methodologies to help provide answers to a variety of research questions in this field.
The CAUSE Research Advisory Board has put together a list of readings to assist people wishing to learn about research in statistics education or to provide background for those wanting to do research in this area. The list includes readings about the nature of statistics and how it differs from mathematics, summaries of research, discussions of research issues in statistics education research, and books devoted to research in statistics education. It also includes readings related to different topics of interest in statistics education research (e.g., technology, assessment) and concepts that are often included in the statistics curriculum (e.g., data, center, and variability).
There are several journals that publish statistics education research. Three journals that publish on statistics education exclusively are:
In my dissertation research, I used linear mixed-effects models to examine students' development of covariational reasoning during an introductory statistics course. This has sparked an interest in further examining student's development, or growth, of statistical reasoning. I am also interested in statistical computing and in thinking about different ways to integrate computing into the statistics curriculum. Deb Nolan and Duncan Temple-Lang have an interesting paper on how broadly teachers of statistics need to be thinking about computing in today’s day and age available here. Lastly. I am interested in data visualization and how data will be displayed and conveyed in Web 3.0.
I am also involved in many research projects involving statistic education research. Most of these projects are collaborations with colleagues and students in the Statistics Education graduate program at the University of Minnesota. We are a collaborative research team of statistics education professionals who are striving to accelerate the change of content and pedagogy in introductory statistics. You can read more about our work at the Catalysts for Change Blog. Below is a list of some of the projects we are currently working on.
I have recently finished work on a manuscript for John Wiley & Sons, Comparing Groups: Randomization and Bootstrap Methods Using R. It was written as a textbook intended for use in graduate statistics courses offered in social science programs. The content provides the statistical foundation for researchers interested in answering questions about group differences through the introduction and application of current statistical methods made possible through computation—including the use of Monte Carlo simulation, bootstrapping, and randomization tests. Rather than focus on mathematical calculations like so many other introductory texts in the behavioral sciences, the approach taken in this monograph is to focus on conceptual explanations and the use of statistical computing. We agree with the sentiments of David Moore, who stated,
At the heart of every chapter there is an emphasis on the direct link between research questions and data analysis. Purposeful attention is paid to the integration of design, statistical methodology and computation to propose answers to research questions based on appropriate analysis and interpretation of quantitative data. Practical suggestions for analysis and the presentation of results based on suggestions from the APA Publication Manual are also included. These suggestions are intended to help researchers clearly communicate the results of a data analysis to their audience.
To see what else I have been working on, you can scan my current Curriculum Vitae. Here is also some of the research work that has been published:
2009, Statistics Education Research Journal
2008, Journal of Statistics Education
2008, Statistics Education Research Journal