Active learning strategies for bioinformatics teaching

The more I read about how active learning techniques improve student learning, the more I am inclined to try out such techniques in my own teaching and training.

I attended the third week of Titus Brown’s “NGS Analysis Workshop”. This third week entailed, as one of the participants put it, ‘the bleeding edge of bioinformatics analysis taught by Software Carpentry instructors’ and was a unique opportunity to both learn different analysis techniques, try out new instruction material, as well as experience different instructors and their way of teaching. On top of that the group was just fantastic to hang out with, and we played a lot of volleyball.

I demonstrated some of my teaching and was asked by one of the students for references for the different active learning approaches I used. Rather then just emailing her, I decided to put these in this blog post.

The motivation of turning to active learning techniques is nicely summarised in a post on the ‘communications of the ACM’ blog entitled “Be It Resolved: Teaching Statements Must Embrace Active Learning and Eschew Lecture”. I highly recommended reading it and checking out the references mentioned. I am by no means an expert in the area, and simply am learning by doing. I have no ways to measure whether the techniques I use are beneficial, but student responses strongly encourage me to keep applying them. My teaching is also very much influenced by my being a Software Carpentry instructor.

The following describes what I do in the de novo genome assembly module of the ‘High Throughput Sequencing technologies and bioinformatics analysis’ course I organise (link to materials). I used part of that module for the NGS Analysis Workshop (link).

On the benefits of ‘open’ for teaching

Open source, open data, open course

We recently had the third instalment of the course in Throughput Sequencing technologies and bioinformatics analysis. This course aims to provide students, as well as users of the organising service platforms, basic skills to analyse their own sequencing data using existing tools. We teach both unix command line-based tools, as well as the Galaxy web-based framework.

I coordinate the course, but also teach a two-day module on de novo genome assembly. I keep developing the material for this course, and am increasingly relying on material openly licensed by others. To me, it is fantastic that others are willing to share material they developed openly for others to (re)use. It was hugely inspiring to discover material such as the assembly exercise, and the IPython notebook to build small De Bruijn Graphs (see below). To me, this confirms that ‘opening up’ in science increases the value of material many orders of magnitude. I am not saying that the course would have been impossible without having this material available, but I do feel the course has become much better because of it.

‘Open’ made this course possible

This course used:

• openly available sequencing data released by the sequencing companies (although some of the Illumina reads are behind a – free – login account)
• sequencing data made openly available by individual researchers
• code developed for teaching made available by individual researchers under a permissive license
• open source software programs

(for a full list or resources, see this document).

I am extremely grateful to the authors/providers of these resources, as they greatly benefitted this course!

Thanks to:

• Titus Brown
• Ben Langmead
• Josh Quick and Nick Loman
• Illumina and PacBio

‘Opening up’ is the least I can do to pay back

In exchange, the very least I can do is making my final course module openly available as well.

The rest of this post describes the material and it’s sources in more detail.

Software Carpentry bootcamp: lessons learned

This post originally appeared on the Software Carpentry blog.

I am a biologist with no formal training in Computational Science. A couple of years ago, the increasing size of my data forced me to stop using Excel, and switch to the Unix command line and scripting for my analyses. In the process, I learned what I needed by mostly by just doing it, but also from books, websites, and of course google.

Almost exactly one year ago, I attended a Software Carpentry bootcamp. I had heard about Software Carpentry and its bootcamps through twitter, started following their blog and became convinced that this was something I wanted to attend. At some point, I fired off an email to Software Carpentry asking what it would take to have a bootcamp at our university, the University of Oslo in Norway. The answer came down to ‘get us a room and advertise the event, and we’ll provide teachers’. This, in fact, was what happened, and as teachers, we got Mr Software Carpentry himself, Greg Wilson, who taught together with a local teacher (Hans Petter Langtangen).