Tuesday, October 26, 2010

Meet Jiyoon Park!

Hi all!

Jiyoon Park considers her own
neuroscientific process.
This is Jiyoon Park, another Ph.D. student in the Statistics Education Program at the University of Minnesota. This is my third year of studying statistics education. My undergraduate studies were in mathematics education in Korea, and afterward, I taught mathematics in a high school in Seoul for four years. I got my Master's degree in mathematics education at UT-Austin, and came to Minnesota in 2008. 

Now I am taking two courses, and teaching one statistics course. The courses I am taking are--EPSY 8215 (Advanced Research Methodology, Dr. Harwell) and EPSY 8114 (Mathematical Cognition, Dr. Varma). The research methods course is a requirement for all EPSY Ph.D. students. This is very helpful course to learn about experimental design in educational settings, especially if you are at the beginning stage of your dissertation. This course is designed to help us prepare an oral prelim paper, as well as, the methodology section of the dissertation.  I am taking the cognition course because I wanted to learn something about "reasoning", "problem solving", and approaches to "understanding people's thinking process". These are all related to the topic of my dissertation.  In addition to the topics of cognition and thinking, we are also learning about neuroscientific approaches to understanding people's thinking process, which is really fun!

Saturday, October 16, 2010

Following Recipes: Statistics and a Failed Blackberry Pie

I am a passionate and confident cook, but I am a little afraid of making pies. The pie crusts in particular intimidate me. Last week I watched a video on food52 on the making of a prizewinning blackberry pie. I watched every detail, read the recipe, and was determined to make a perfect blackberry pie. I assembled all the ingredients and tried to replicate every step I had seen on the video. When the pie was finished, it looked perfect. I was euphoric: I did it! Then, I cut into the pie to serve it, and it collapsed into a mess of soggy bottom crust and juices everywhere.

What went wrong? I had followed the recipe exactly. That is where I went wrong. My intuition had told me to bake the bottom crust first, because that is what I had done before with fruit pies, to keep it from getting soggy. I also should have added more thickener to the berries. By blindly following a recipe, I had ignored the general cooking wisdom I had gained over the years. Perhaps the berries I used were juicier than those in the video, perhaps my dough was a little wetter than theirs

So how does this relate to statistics? We are designing and teaching an intro stats course that is all about teaching students to really cook (do statistics) rather than just follow recipe. So many introductory courses teach students step-by-step procedures that they follow without thinking or critiquing, like novices. In these courses we may try to provide some theory or rationale for what we do, but we still are teaching recipes, rather than real cooking techniques.

In our CATALST course we aimed to teach students the cooking method of creating models and using them to simulate data, and to use there data to test whether an observed value or difference is surprising, given a particular model. We have spent almost half the course helping students think about models, how to create them using TinkerPlots™ software, how to generate data from them, and how to use the data to evaluate their observed data in order to draw inferences. We hope we are building a foundation of knowledge to enable students to use this approach in their future classes or work---whether they use this particular software tool or not. Rather than walk out of class with a recipe for a t-test that they may or may not ever use again, we hope our students will leave class with some experience doing statistics and the ability to think statistically about real world problems and the nature of statistical inferences.

Even though I tried to reproduce the blackberry pie recipe exactly, I had no way of knowing if my ingredients were exactly the same, my oven the same temperature, my pan the same as theirs, etc. All those things can make a big difference, and a wise cook knows this and can try to compensate and adjust as needed. A novice, follows the instructions blindly, as I did this time. In statistics too, following a procedure blindly, like running a t-test to compare two samples of data, can give different results depending on the characteristics of the samples, where the data came from, etc. We want our students to think critically and statistically when using statistical methods, drawing on their “cooking” knowledge about data, sampling methods, variability, distributions, etc. My pie fiasco served as a reminder of the importance of thinking and questioning rather than blindly following a recipe.

--- This essay was written by Joan Garfield.

Beth Chance's Visit

Joan Garfield expounds on Beth Chance's visit to the University of Minnesota October 3–4.

Last week (Editors Note: It was almost two weeks ago now since I am not too fast at posting these.) Beth Chance spent a few days with us. It began with a Sunday afternoon run around Lake Harriet, followed by dinner with my husband Michael and me, along with Andy and Lauren Zieffler. 

Early Monday morning Beth visited our experimental CATALST course, being taught by Laura Le. She collected  and summarized minute papers that students wrote about their experiences in the course and using TinkerPlots™ software.  After class Beth attended our weekly CATALST meeting with our team of Bob, Andy, me, Laura Le, Laura Ziegler , Rebekah  and Jiyoon. We debriefed that morning’s class, discussed the feedback on the minute papers, and then had a lively discussion of the next unit in the class on comparing groups using randomization tests and bootstrap confidence intervals. 

The Statistics Education Catalyst group met with Beth for lunch. Each person shared their current work and projects and Beth shared her sabbatical plans. She offered to participate on students’ doctoral committees since there are no graduate students in statistics education at Cal Poly. Beth talked a little about AP Statistics and put in a plug for people in our group to sign up to be readers this summer (along with Laura Z. who has done this for several years). Since them Michelle has completed the application and perhaps a few others will as well! 

After lunch we had a conference call with Allan and John to talk about our CATALST course and plans for the third unit which keeps evolving. The final activity of the day was a meeting with Michelle, Beth and me to talk about Beth’s involvement in co-teaching our graduate course, Becoming a Teacher of Statistics this spring. Beth will be visiting us again sometime this spring  and we look forward to her next visit!

Meet Laura Le!

Life as a (2nd year statistics education PhD)
graduate student...double-fisting espresso

Hello out there…

Laura Le reporting here.  I'm another Ph.D. graduate student in the Statistics Education department at the University of Minnesota, kicking off my second year in the program.  I obtained a mathematics/stastistics BA degree from Luther College in 2006 and continued on to get a Master's Degree in Statistics from the University of Minnesota.

The question I get a lot is, "how in the world did you get into statistics education?" Here's my story (short and sweet): My mama always told me i was going to be a teacher, but I was in denial about it for many years.  When I entered my Master's Degree program, I didn't know what I wanted to do with a statistics degree.  I knew I liked math and learning about a lot of different other fields so statistics seemed like a good fit.  Then the statistics department gave me the opportunity to teach my own class, and I got hooked on teaching statistics. The end.  :)

This semester, I'm taking three courses in the Educational Psychology department: Survey Design, Implementation and Analysis, Hierarchical Linear Modeling, and Qualitative Research Methods.  They are all really interesting topics and are a good balance for coursework.  In particular, Qualitative Research Methods intrigue me. It is a type of research methodology I haven't been exposed to much, but knew it was out there.  I'm learning a lot about the field, like how good qualitative research should be conducted and what are different types of qualitative methods (e.g., biography, phenomenology). I'm looking forward to one of the assignments in class, collecting observations from a public place.  I think this will definitely be useful for my career as a statistics educator.

This is Laura Le, signing out.

Sunday, October 10, 2010

George Cobb & the Cobb-O-Lantern

George and the Cobb-O-Lantern at Stat Chat in October 2009.

Friday, October 8, 2010

Meet Rebekah Isaak!

Rebekah tries out a new hairstyle at the Renaissance Festival

Greetings! My name is Rebekah Isaak and I am a second year Ph.D. student in Statistics Education at the University of Minnesota. I have my Bachelor of Science in Mathematics from Drexel University. This fall, I am taking three courses in the Department of Educational Psychology: EPSY 8264 (Advanced Multiple Regression), EPSY 5247 (Qualitative Research Methods), and EPSY 5244 (Survey Design). All three courses are practical and fascinating, but Survey Design is currently the most applicable to my research interests. 

As a project for the Survey Design course, I am designing and piloting a survey to measure mathematics, computation, and statistics instructors’ perceived value of online presentations, called M-CASTsto their own teaching after viewing them. As a piece of the NSF-funded Project MOSIAC, these presentations are designed to “improve undergraduate STEM education by better integrating Modeling, Statistics, Computation, and Calculus" and to "provide a quick and easy way for educators to share ideas, get reactions from others, and form collaborations". I plan to use the data gathered to identify M-CASTs that seem to be of pedagogical value. Extensions of this work might use M-CASTs of perceived value as examples in order to identify the characteristics of M-CASTs that contribute to “effectiveness” in the teaching of the concepts they cover.

Thursday, October 7, 2010

A Real Photo of Allan and Beth Together

It's Probably Time to Introduce Another Graduate Student...

Becoming a Teacher of Statistics over Roast Beef

Michelle Everson describes her meeting with Beth Chance And Allan Rossman,
On Friday,October 1st, I met with Beth Chance and Allan Rossman. Beth and Allan were heading through Minnesota on their way to give a workshop in Eau Claire, Wisconsin. We met at Arby's in Osseo, MN, and had dinner together. Our main purpose in meeting was to talk about the "Becoming a Teacher of Statistics" course. Beth is now on sabbatical and is interested in finding out more about the course, and she'd like to be involved in some way with the course when it is taught again in the spring. We talked about this, along with a variety of other things, and it was nice to have the opportunity to hear more about what Beth and Allan are doing and to get to know them better. I always enjoy spending time with them, and I continue to learn so much from them.
Blogger's Note: There are no pictures of Allan and Beth together that come up on a Google image search, but here is a picture of a book they wrote where their names appear together. 

Note to the Blogger's Note: If the a priori null hypothesis had been that there are no images of Beth and Allan together that would come up in a Google search, this blogger would have put even money on the null being rejected at the 0.0001 significance level.

Saturday, October 2, 2010

Meet Laura Ziegler!

From time to time we will put up posts that introduce you to some of the Catalysts for Change. For our inaugural post in this vein, we invite you to meet Laura Ziegler, one of the graduate students in Statistics Education at the University of Minnesota.

Laura and her husband on their wedding day.
Hello!  My name is Laura Ziegler, and I am working on a Ph.D. in Statistics Education. This is my first year at University of Minnesota, but I already have a Master's Degree in Statistics. I am currently taking 4 classes: EPSY 5221 (Principles of Educational and Psychological Measurement), EPSY 5247 (Qualitative Methods in Educational Psychology), EPSY 5243 (Principles and Methods of Evaluation), and MTHE 8571 (Research in Mathematics Education). All of my classes are very interesting and useful, in particular the math education research course. We have a group of 8 students in the class and 3 of us are not Mathematics Education majors. We have a lot of good discussions and it is interesting to see how education research is similar and/or dissimilar in different fields. One benefit of this class is that we write a research proposal. This is a good way to get feedback on a proposal to see where you can make improvements.

Congratulations Tamara!

Tamara Moore
Tamara J. Moore (assistant professor of mathematics education, curriculum and instruction, and co-director of the STEM Education Center) has received a $400,109 Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF), to research implementing K-12 engineering standards through science, technology, engineering, and mathematics (STEM) integration.

The award is one of NSF's highest honors for early-career faculty whose research builds a firm foundation for a lifetime of integrated contributions to research and education. The grant will begin October 1, 2010, and will continue for five years.