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Nick Tierney's (mostly) rstats blog

2020-05-30

Some ideas on teaching

Categories: blag teaching rstats Tags: teaching rstats

6 minute read

On July 31, 2018, I presented a talk at the SSA Victoria branch called: “Rethinking teaching statistical computing: Understanding how learning works means we need to rethink how we teach.". The abstract for the talk was:

Researchers, analysts, and statisticians need to perform analyses, and this (usually) means that they need to learn how to code. They are, however, often not taught how to code. So how do they start? This talk discusses evidence based principles on teaching from the book: “How Learning Works”, and how they can be applied to teach statistical computing. The talk is based off of Nick’s experience going through Software Carpentries Trainer Training curriculum, and his experience learning and teaching R over the past 5 years.

Writing is hard, and putting content somewhere is better than nowhere.

Ever since UseR!2018 in Brisbane, seeing Roger Peng’s keynote, “From tapply to tidyverse and the accompanying blog post, I have always had ambitions to write a blog post that summarises my thoughts of a talk that I give. Unfortunately, I haven’t ever managed to do this.

So, since writing this blog post it has been nearly … two years since I gave the talk at SSA, I figured it is better to get something out, rather than nothing. Also, Garrick Aden-Buie gave me a friendly push in the right direction to get this post out.

Learning to teach

In 2015 I helped contribute some teaching material to SEB113, the mandatory introductory statistics subject for science students at QUT. I worked closely with Sam Clifford, to create teaching material in video form, which was shared with students as an R markdown document. From 2015 onwards, I’ve had a great opportunity to undertake training with The Carpentries as an Instructor Trainer by Karen Word, where we read through the fantastic book, How Learning Works: Seven Research-Based Principles for Smart Teaching. As well as taking RStudio‘s Teach the Tidyverse in 2018.

My point is, I feel very lucky to have received some amazing education from inspiring folks like Karen Word, Garret Grolemund, and Sam Clifford. Over the years, I’ve taken a bunch of notes from these times. I had great ambitions of writing up all these notes into something super coherent and well put together.

Instead it’s been in my drafts folder since 2018-08-01. So, here’s something a bit more scrappy, but hopefully useful.

Reading over these notes reminds of how much I can improve my own teaching. There are so many ideas where I’m like:

Yes, 100% I will do that

And then it ends up being something I don’t do, because it’s hard, or it takes more time, or I find myself running out of time. For me, these are things like getting students to do more exercises throughout class, and providing frequent opportunities for feedback, and incorating peer review into class.

Also full disclosure, I was making these notes for myself, and in the process might have copied a bit closely from slides or texts. It has been so long since I’ve collected these notes, that I can’t actually remember where they came from. I just figured I’d rather get this content out there - but keep in mind that it’s most likely from one of these sources:

Some notes on teaching I’ve collected

Course climate:

Understanding Learning:

Practical approaches:

Getting Feedback:

Key points for teaching:

Three key points for R content:

Some abbreviated notes of the seven principles from How Learning Works

Recommended resources from here

Read the book, “How learning works” - even if you only skim through the start and end of each of the chapters, I guarantee you that you will learn something. I should read this again.