It embarrasses me to look back on how I taught statistics ten years ago. Were I still teaching in a university, I would not be teaching the same things the same way I did then. I did the best I can, and the course was better than many, but I know so much more now about what is important, and how it should be taught. And I hope that ten years from now, I will have learned even more, and would make more improvements. I propose that if you aren’t a little embarrassed at how you were teaching ten years ago, then you probably should be. And if you have not changed anything in your courses, you might like to think again. The fields of statistics and statistics education are progressing and changing, and we should not be teaching a twenty-first century subject using twentieth century technology and pedagogy.
Web lists are a popular way to get ideas across, and they involve numbers, which I like. So here is my list of 20 ways to improve as a teacher of statistics. The ideas are a mix of conceptual, practical and attitudinal, in no particular order.
This is pretty much sums up my philosophy on life. If we only do things we feel comfortable about, we are unlikely to discover the possibilities at the edge of our competence. I wrote some time ago about the knife edge of competence. We don’t want to live on it, but we do need to spend some time there. I believe that if we never have a “great idea” that turns out not to work, then we aren’t being imaginative enough. Throughout my career as a university academic, I had some fairly disastrous lectures or lessons at times, but they were well and truly outweighed by the great ideas that really did work. Experiment – if you never have a failure you aren’t trying hard enough.
Each year or semester we can take a look at a certain concept or technique that did not really work, and see if we can tweak it. We can change the way we assess one piece of work, or use a different data set. Continuous improvement is important. I recently gave a daylong seminar for 80 Statistics Scholarship students in the Waikato. It was a blast – though exhausting. It is tempting to just put the notes away for next year, but I have jotted down in my timing sheet, which activities did not work as well as I would like, and ideas to get the students writing some more. Next time I present it, there won’t be big changes, but I plan to improve it a little at a time.
People in Christchurch understand catastrophic change. Our earthquakes gave me the opportunity to do away with face-to-face lectures in my course. We don’t need to wait for a natural disaster, though. Sometimes we have fiddled around the edges of a course for long enough, and the underlying premises are getting stretched. It is time to draw a line at the bottom and start again. I was happy to be able to help the Statistics Department at the University of Canterbury reshape their introductory statistics offerings, beginning with the philosophy and learning objectives. Sometimes things are so broken, we need to start again, and sometimes it is invigorating to be able to use a scorched earth approach to course development.
When we are looking for inspiration on how to improve our statistics teaching, we can’t find better than the MOOC put on by HollyLynne Lee and her team. Here is what she says:
Here at the Friday Institute at NC State, I am offering a Massive Open Online Course for Educators (MOOC-ED) that is focused on “Teaching Statistics Through Data Investigations”. The course is designed to target pedagogy and content for teachers (preservice, practicing, college-level teaching assistants, and teacher educators) in middle school, high school, and AP/ intro college levels. There will be many choices and options in the course for teachers to focus their learning around content that they teach. You can see a more detailed description of the course here: http://go.ncsu.edu/tsdi
I enrolled in this course in its previous offering and found it extremely helpful and inspiring. It is based in the U.S. and uses their terminology, but as the NZ curriculum is based on the GAISE document, there is plenty of common ground. What I could most useful was reading the comments of the other participants, and finding what experiences are universal. I wrote about this here.
I love the ideas I get from Twitter. Ideas expressed in 140 characters or less (plus pictures) can be the start of other ideas. You get to make friends with people you have never met (as opposed to Facebook where you get to “unfriend” people you have known all your life.) There is such a diversity of talent in the world, and by building up an international pool of colleagues in statistics education we can be inspired and encouraged. Taking part in the MOOC mentioned in idea 4 will help you build up your community and linkages.
It is the sad truth in many tertiary establishments that spending too much time reworking a course and improving your teaching can be at the expense of your research programme. I am not well placed to advise in this area as I never did get a very good research programme and took redundancy to avoid being punished for my choices with reducing resources for research. However I do know that some academics do manage to do research in the pedagogy of their subject. For example:
Nathan Tintle recently sent out an invitation to participate in introductory statistics assessment project as follows:
Dear Statistics instructor,
We recently received NSF funding to facilitate assessment of (algebra-based) introductory statistics courses, with a focus on gaining a better understanding of potential differences in student learning between “traditional” and simulation/ randomization-based introductory statistics courses. As such, we are asking you to consider having your students participate in the assessment project regardless of how much (if any) simulation- and randomization-based inference methods you use in your course. If you are interested in participating, please fill out this short survey, as soon as possible, but early enough to allow time to set up individualized links for your class before your term starts: https://www.surveymonkey.com/s/9SYS8H3 .
If I had a class I could have participate in this, I would definitely do it. Nathan has assured me that instructors from other countries are also welcome to take part. Here is an opportunity to see how much difference you make in the course. Do your students actually learn things? And answering questions about how a course is taught and assessed is a great way to start thinking about improvements. AND you can build up your professional learning community.
When I was teaching introductory Management Science, I would dread the regular Excel upgrades. They were enough to make me have to redo my notes and screenshots, but they NEVER addressed the appalling Statistics Analysis ToolPak. I love Excel more than is probably moral, but I am very alive to its faults and weaknesses. As computers get more and more powerful, and different techniques are developed and become possible, the potential uses of technology change. I believe that AP statistics still uses handheld calculators, but I also believe that this is a mistake, possibly encouraged by the manufacturers. AP statistics should be examined using computer output. No one should be calculating statistics of any kind by hand. Ever! See my post on this here. Changing technology forces us to rethink what we are trying to do and why.
Or cease to use a textbook. Or write one of your own. The first thing I ever read of George Cobb’s was an analysis of textbooks, back in the later years of last century. I strongly agree with his analysis that the questions were the most important part. This is even more applicable in these days of free online information of varying value. Depending on how confident the instructor is, a textbook can be a great help, but often they are expensive doorstop/lucky charm combinations
This one is obvious. It’s my source of all good ideas.
That will do for Part 1. I have at least another 10 points for the second part of this series.