Meet Matt Beckman!

Hi, my name is Matt Beckman. I’m a part-time PhD student in my second year of the Statistics Education program at the U of M. I earned my Bachelor’s in Mathematics from Penn State University and a secondary education teaching certification in Pennsylvania prior to pursuing a Master’s in Statistics at the University of Minnesota which I completed in 2008. I currently work full time as a Statistician for a large medical device manufacturer in the Twin Cities called Medtronic. My responsibilities include statistical analysis for the Neuromodulation business and I volunteer as one of the instructors of a statistics curriculum developed by Medtronic to train engineers and other personnel across the company to use statistics effectively in their jobs.

In addition to my role as an instructor at Medtronic,I have benefited from a few diverse teaching experiences including student teaching placements as an undergraduate, a summer school position and independent tutor following graduation, a few appointments as a teaching assistant during my time in the Statistics Department, and two semesters as adjunct faculty at the U of M following completion of my Master’s. My research interests relate to my experience teaching statistics to quantitative professionals and teaching in intensive seminar environments, since these topics relate to my work at Medtronic.

Between a demanding full-time job, an awesome wife of two and half years, and our new puppy…it’s tough for me to find time for more than one or two classes per semester. In the spring I’m looking forward to taking EPSY 8271 which is a statistics education research seminar with my advisors Joan and Bob and several other friends in the program. It’s sometimes a challenge to keep up with everyone as a part-time student, so I’m excited to have a structured opportunity to see everyone each week in addition to honing my research interests.

Everson Invited to Blog for eLearn Magazine

Michelle Everson has been invited to write a monthly blog for eLearn Magazine. Her first contribution is aptly titled, Why Should Educators Blog? Reflective Writing Can Positively Affect Teaching.

Hopefully, Michelle will let us know each month when her new entry is posted and we will update you. In the meantime, catch up on some of her past scholarship for eLearn Magazine.

• 10 Things I've Learned About Teaching Online
• Group Discussion in Online Statistics Courses

Congratulations Ulrike!

And welcome to the newest Catalyst for Change, Max! Ulrike Genschel, a CATALST implementer from Iowa State, had a baby and he is definitely less than 0.01 (highly significant). We wish her and Max the best. Ulrike writes,

Max was born on Saturday, December 4th. Although a few weeks early, he is doing great and healthy.

Max-imum Likelihood

Are those concentric negative quadratic curves above Max's head?

Max implements a nap.

Meet Audbjorg Bjornsdottir!

Did someone say bootstrap?

Hi my name is Audbjorg Bjornsdottir but I go by Auja. I am a third year PhD student in statistics education. I have an undergrad in anthropology, a MA in sociology/criminology and a post-graduate diploma in teaching all from the University of Iceland. This year I also received my MA in statistics education.

Now I am taking two classes: MTHE 5314 Teaching and Learning Mathematics and CI 5325 Designing and Developing Online Distance Learning. Both these classes are very interesting and fun. Most of the students in the math education class are k-12 math teachers and I really enjoy hearing and getting to know their perspective toward teaching math or statistics at a level unfamiliar to me. The CI 5325 course is one of four courses that count towards a certificate in Online Distance Learning offered here at the U. Since I have been teaching introductory statistics online since spring 2009 I decided to get that certificate along with my Ph.D. degree. This course is the second one I take as apart of that certificate and I love it for its practicality. For example this semester I have been evaluating different content managing systems that are used in online teaching and at the end of the semester I am supposed to design my own course. The course is offered online; we are introduced to the latest technology (how to use it) and research in online teaching in a very much hands on and pragmatic approach. I benefit much from taking this course and the certificate because I have just begun the process of working on my dissertation, which will be about how to administer group quizzes successfully in an online introductory statistics course.

Congratulations Nick Horton!

Screen shot of Nick from the video.

Three faculty members were named 2010 recipients of the Kathleen Compton Sherrerd ’54 and John J. F. Sherrerd Prizes for Distinguished Teaching. They are: Nicholas Horton, associate professor of mathematics and statistics; Róisín O'Sullivan, associate professor of economics; and Michael Thurston, professor of English language and literature. The Sherrerd Prize is given annually to Smith faculty members in recognition of their distinguished teaching records and demonstrated enthusiasm and excellence.

You can watch Nick in a video here.

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!

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.