Week two...

So my first full week of teaching is done. It was mostly good. I had fun using a dataset today of the Steelers' Preseason Roster. Got some nice insight on a histogram of weights from one of the students who obviously has a significant knowledge of football. Anyway, here are some brief reflections on the week:

Monday: In-class activity
I created an in-class activity on sampling methods using the concept of a tree farm with different stands that I needed to sample in order to determine if I should harvest the trees or not. Overall I think it went well. The students turned in their reports and with the exception of a few groups still not quite getting the concept of parameter and statistic, they seemed to understand how to choose the proper sampling technique for the situation.
Areas of improvement: Although I would use the activity again, I need a better introduction to it. There were a few points to the project that I did not do well explaining and some refinement to the setup of the problem would improve the project. The other thing I would change, in retrospect, is my interaction with students during the project. While I was available to answer questions, it would have been better for me to mingle among the students more, try to learn more names and ask some leading questions to the groups. The classroom space made it difficult to do this so I might ask the groups to spread out more so that I can mingle among them more freely.

Wednesday: There was a lot of administrative stuff I had to take care of before I could begin lecture. This kind of threw off the flow of the class in general. My lecture was also not my best either. I think it was a mix of being slightly underprepared and a slightly boring topic (pie charts, boxplots, and frequency and relative frequency (still not sure everyone gets the difference). I'll have to come up with a better activity to make the topic more interesting next time.

Friday: This was a pretty good day. The kids did well with the activities and the topics (descriptions of sampling distributions and graphic representations of quantitative variables). This is where I used the Steelers dataset. I had the kids write a one-minute paper at the end of class (which I haven't read through yet) about the distribution of the weights of the Steelers' Roster. We'll see if they got how to use the vocab and such.

Next week it gets more mathy so we'll see how it goes. I'm still trying to come up with some good activities for the normal distribution... we'll see how it goes.

First Week of Teaching

So I made it through and I have to say I thoroughly enjoy teaching and continue to be affirmed in my decision to focus my career on teaching and university education and curriculum. Although in general things went well, there were a few minor glitches:

1. I need to keep track of time better, or shorten my lessons slightly. I'm not going horribly overtime, but a few minutes makes the students antsy and they stop paying attention
2. Because of my overtime ways, I continue to forget end-of-class reminders. I think I am going to try posting a sticky note on the computer screen to remind me to remind students of things at the end of class.
   

I've enjoyed the lesson planning aspects of the teaching, but the time required to create each lesson is a little more than I can spare at this moment (I keep feeling my neglected research breath down my neck...). Hopefully it will get faster as I get better at it. Plus, I need to start borrowing more ideas from others for activities instead of trying to create my own.

One highlight of the week was that Jon Stewart decided to teach five minutes of my class for me. I was teaching about bias in polls and surveys and he provided an excellent analysis on where bias occurs in polls an why.

The Daily Show With Jon Stewart	Mon - Thurs 11p / 10c
Poll Bearers
www.thedailyshow.com
Daily Show Full Episodes Political Humor Healthcare Protests

Next week we start to get into the more meaty topics like numerical summaries of data. A whole new slew of vocabulary for my students to learn, but the upside is they get to make pretty graphs!

CAUSEweb

Consortium for the Advancement of Undergraduate Statistics Education

A national organization whose mission is to support and advance undergraduate statistics education, in four target areas: resources, professional development, outreach, and research.

Hopefully I will be able to publish some of the curriculum I develop over the next year through this website.

Philosophy of Teaching

Below is the philosophy of teaching essay I submitted when I first applied for the PtP program. It will be interesting to see how my teaching philosophy evolves over the next year...

Effective teaching consists of three components: foundation, exploration and reinforcement. The foundation is often a lecture component that reinforces basic concepts and general ideas. The exploration is a hands-on activity that provides a guided exploration of a concept. The exploration component may be an in-class activity, a project or a homework assignment done prior to the lesson. The reinforcement component of the lesson continues to instruct and reinforce the concept after the instruction ends. Usually, reinforcement is in the form of a problem set or exam, but may overlap with the exploration component in the form of a class project. The three component lesson allows a teacher to effectively teach basic concepts, provide real-life application and promote retention of the concept. The three component lesson also allows a teacher to appeal to different learning styles.

The Preparing the Professoriate program will provide a platform for me to develop into a more effective teacher. Each aspect of my program outline will provide a means to develop all three components of effective teaching. Through the use of Faculty Mentor evaluations, student surveys, and self-reflections, I will track my advancement in each area throughout the PtP program. In addition, I will focus a large part of program on development of exploration activities for statistics education that I will implement and evaluate throughout the year. The project will culminate in a collection of best practices for statistics education that will provide the necessary tools to encourage graduate teaching assistants to incorporate the constructivist style of teaching.