Tuesday morning, bright an early at 8:30am, was our session titled “Novel Approaches to First Statistics / Data Science Course”. For some students the first course in statistics may be the only quantitative reasoning course they take in college. For others, it is the first of many in a statistics major curriculum. The content of this course depends on which audience the course is aimed at as well as its place in the curriculum.

Of the many provocative and exciting discussions at this year’s Statistics Research Teaching and Learning conference in Rotarua, NZ, one that has stuck in my mind is from Lucia Zapata-Cardona, from the Universidad de Antioquia in Columbia. Lucia discussed data from her classroom observations of a teacher at a middle school (ages 12-13) in a “Northwest Columbian city”. The class was exciting for many reasons, but the reason that I want to write about it here is because of the fact that the teacher had the students structure and store their own data.

One of the many nice things about summer is the time and space it allows for blogging. And, after a very stimulating SRTL conference (Statistics Reasoning, Teaching and Learning) in Rotorua, New Zealand, there’s lots to blog about.
Let’s begin with a provocative posting by fellow SRTL-er Tim Erickson at his excellent blog A Best Case Scenario. I’ve known Tim for quite awhile, and have enjoyed many interesting and challenging discussions.

This last weekend I helped Danny Kaplan and Kathryn Kozak (Coconino Community College) put on a StatPREP workshop. We were also joined by Amelia McNamara (Smith College) and Joe Roith (St. Catherine’s University). The idea behind StatPREP is to work directly with college-level instructors, through online and in community-based workshops, to develop the understanding and skills needed to work and teach with modern data.
Danny Kaplan ponders at #StatPREP
One of the most interesting aspects of these workshops were the tutorials and exercises that the participants worked on.

Part of the reason why we have been somewhat silent at Citizen Statistician is that it’s DataFest season, and that means a few weeks (months?) of all consuming organization followed by a weekend of super fun data immersion and exhaustion… Each year that I organize DataFest I tell myself “next year, I’ll do [blah] to make my life easier”. This year I finally did it! Read about how I’ve been streamlining the process of registrations, registration confirmations, and dissemination of information prior to the event on my post titled “Organizing DataFest the tidy way” on the R Views blog.

I meant to write this post last year when I was teaching a large course with lots of teaching assistants to manage, but, well, I was teaching a large course with lots of teaching assistants to manage, so I ran out of time…
There is nothing all that revolutionary here. People have been using Slack to manage teams for a while now. I’ve even come across some articles / posts on using Slack as a course discussion forum, so use of Slack in an educational setting is not all that new either.

On the first day of an intro stats or intro data science course I enjoy giving some accessible real data examples, instead of spending the whole time going over the syllabus (which is necessary in my opinion, but somewhat boring nonetheless).
One of my favorite examples is How to Tell Someone’s Age When All You Know Is Her Name from FiveThirtyEight. As an added bonus, you can use this example to get to know some students’ names.

Learning to swim in the data deluge

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