Skillshare on The Carpentries

Export to Etherpad: a New Extra in the Instructor-Training Repository

Wed, 09 Oct 2019 00:00:00 +0000

Building Tools for Instructor Training Workshops

Wherein we talk about building tools to help instruct instructors learning how to instruct. Got that? No? Me neither. As a fairly newly minted instructor-trainer, one of my internal gripes about preparation was the need to create the Etherpad training template which serves as a shared note-taking space and workbook for the class.

Preparing this etherpad involves either editing an old text file which isn’t maintained as part of the normal lesson maintenance process (as that sort of maintenance would be tedious in the extreme) or laboriously copying and typesetting exercises from their beautiful (but non-translatable) html form into the limited number of styles allowed on the Etherpad. As I was getting ready to teach in July, the amazing Instructor Training Maintainers team were in the middle of the June release – and every time I had prepared the document, another exercise would be improved. This wonderful process of improvement, in the moment, was more than a little frustrating.

Tips and Tricks for Teaching R

Fri, 17 May 2019 00:00:00 +0000

Following a few Data Carpentry workshops, we (a.k.a. Bianca and Katrin) shared some of the strategies we employ to enhance participants’ R learning experience in a Community Discussion with other Carpentries Instructors from Africa. In this post, we will expound on some of these strategies and welcome you to try them in the workshops you facilitate, and share your outcomes with the broader Carpentries community.

Pen-on-paper exercise

In the R episodes on Data Manipulation and on Visualisation, code and challenges become quite complex and may contain new concepts of coding as well as of data analysis for novices. Individual code blocks can easily run over several lines when using pipes (%>%) or when building plots with ggplot, thus increasing cognitive load for learners. To enhance understanding of the concepts behind the R commands and also to give participants a break from sitting in front of the computer, we included group exercises with pen and paper. We divided participants into groups of four to five and gave each group a blank sheet of paper (it works particularly nice with big sheets stuck to a wall so the groups can stand around it). We then wrote a challenge on the Workshop Etherpad/whiteboard and asked the groups to discuss and write down the steps (not necessarily the commands) they would need to subset their data accordingly.

What’s New at ORCID? A Joint Library Carpentries/ORCID Webinar!

Wed, 17 Apr 2019 00:00:00 +0000

This post originally appeared on the Library Carpentry website

By Alice Meadows, Chris Erdmann

We are delighted to announce that Library Carpentries and ORCID are co-hosting a webinar on What’s New at ORCID. Registration is free – just add your name here – and there will be plenty of opportunity for questions and discussion.

This webinar, at 10am ET on Thursday, May 16, will focus on ORCID’s new API v3.0, launching in May, which includes some valuable new features for researchers, their organizations, and the wider community alike:

Carpentry on a Chromebook

Fri, 15 Mar 2019 00:00:00 +0000

Since grad school, I’ve appreciated the ability to jump between the command line terminal, desktop apps, and the browser. I recently needed a new laptop. I have long been primarily a Mac user, and I looked at new and refurbished Mac, linux, windows, and ultimately Chromebook laptops.

The price of a Chromebook made it an extremely attractive choice, but could it serve as my main laptop? There are many blog posts and reddit subthreads describing hacks for dual boot or VM terminals in unstable developer mode. However, I discovered Google recently released a Linux (beta) app within the stable ChromeOS channel, called “Crostini”. This allows users to simply opt-in to Linux on the settings page; no flags, no developer mode, no complicated hoops. The system requirements for Crostini mean that only a few Chromebooks are currently supported; I went with the Acer Chromebook 11 CB311-8H.

Load Magic for Python and a call to discuss how we deliver exercises to learners

Fri, 28 Sep 2018 00:00:00 +0000

This post describes a teaching tip I shared at CarpentryCon 2018 and how it thrust me into deeper Carpentries involvement. It also aims to start a larger conversation about how we deliver exercises in workshops and how the lesson infrastructure can better support instructors and learners.

Let’s talk about exercises

One challenge I had before my first workshop was figuring out how to deliver exercises to learners. I asked around, but when I thought about myself as a learner trying to do exercises based on the descriptions I got, I imagined being confused and distracted. I found the load magic of IPython/Jupyter notebook to give exercises to learners that enabled them to focus on the concepts I was teaching, not fumble with tools. I shared the idea at CarpentryCon, got great feedback, and have thought more about how we could update the infrastructure to support it over the past few months. In The Carpentries, teaching and learning come first, so before the lesson infrastructure committee implements changes, we wanted to get more feedback on the general approach, and how instructors are delivering and would like to deliver exercises. I wanted to share my path on how I got to this question, why I’m interested in addressing it, and start that conversation.

Want to Organise a Workshop on Image Processing?

Mon, 17 Sep 2018 00:00:00 +0000

I wanted to organise a workshop on image processing for PhDs in the medical domain. I usually use Software Carpentry lessons in my workshops, but there are no lessons on image processing. Before starting to re-invent the wheel, I thought I should ask the Software Carpentry community if anybody had given a workshop like that recently.

Hey guys, image processing lesson anyone?

I was hit by a wave of suggestions and existing materials — and although not everything fitted in the scope of my workshop, it sure made my life a lot easier! Here is a summary of some of the useful links which were shared.

Report: Lesson Infrastructure Breakout at CarpentryCon

Thu, 14 Jun 2018 00:00:00 +0000

One of the breakout sessions at CarpentryCon focussed on lesson infrastructure: the template we use for our lessons and how this template and the platform that we use to deliver this material (GitHub Pages & Jekyll) could be improved/better utilised. The session was led by François Michonneau, our Curriculum Development Lead, with notes taken by Toby Hodges. This blogpost is a summary of the discussion in that session. You can see the original notes on this etherpad.

My Favorite Tool is Git

Wed, 25 Oct 2017 00:00:00 +0000

This post originally appeared on the Data Carpentry website

I love Git and GitHub.

I only use them for work I care about. Examples include lesson development for R workshops, my recent performance review packet, and collaborative projects on species distribution modeling. Oh, and Software Carpentry workshop websites (obviously).

Why I like Git:

The version control system and the companion remote host system (GitHub or Bitbucket or CloudForge, etc.) provide a great versioning and collaboration platform, the highlights of which have been enumerated many times over and in such depth that I won’t talk about them here.

The Magic of Minute Cards

Thu, 29 Jun 2017 00:00:00 +0000

This post originally appeared on the Data Carpentry website

They only take a minute (hence the name: minute cards), but their benefits last a lot longer. During instructor training workshops, we use minute cards to get feedback from learners. They provide formative assessment for the instructors since the cards tell instructors what they are doing well (or not so well) so class teaching can be adjusted accordingly.

Minute cards can alert instructors to questions and misconceptions that have arisen. They are also useful post-workshop to help instructors reflect on how they teach, and what improvements they might need to make in the future either to the lesson itself, or to how they teach it.

Best recipe - just add statistics and science

Fri, 27 Jan 2017 00:00:00 +0000

This post originally appeared on the Data Carpentry website

We’d like to talk about our experiences working together as a domain scientist and a statistician and encourage you do this too!

When we say working together, we mean that we collaborate in the best sense – we each bring our strengths and those strengths are complementary. We have some suggestions for you as you get started. First, the domain scientist should look at how statistics is organized at their institution. Does your university have consulting statisticians or research-active faculty or both? Consulting can also be done as part of statistics students’ training. Most larger universities have both consulting and research. Some scientific questions naturally flow into research on new statistics methods and concepts, and other science questions are a better fit for an analysis method that has already been published. Talk to the consulting center first if you have one.

Soft(ware) Skills

Thu, 19 Jan 2017 00:00:00 +0000

This post originally appeared on the Data Carpentry website

I think, in the end, technology and data science are about communication.

As a biologist with a physics degree, I’ve always been called on by my peers to help out with the more ‘mathy’ parts of their work. As early as my masters, my friends and collaborators would send me their data, here and there, to have a look and make suggestions for how to proceed. More often than not, I’d either send it back to them asking lots of questions, or spend hours of my own time, cleaning, manually manipulating data until it was in a form that I could query it and looks for patterns.

How I Developed a Workflow for Success in Graduate School

Tue, 20 Dec 2016 00:00:00 +0000

This post originally appeared on the Data Carpentry website

My home state of Michigan and the surrounding Great Lakes area cradles 20% of our planet’s freshwater resource and yet growing up next to these ecosystems, I knew almost nothing about their biological inner workings. Now, as a PhD student and environmental microbial ecologist, I explore the most abundant and amazing inhabitants of the lakes in my backyard: the diverse communities of tiny microbes.

Climate Science and the Command Line

Mon, 12 Dec 2016 00:00:00 +0000

This post originally appeared on the Data Carpentry website

Climate science has a pretty high profile these days, particularly in my personal area of research, which involves quantifying the role humans have played in climate change (otherwise known as “climate attribution”). Behind the glamorous media coverage and international meetings, however, research in this field centers around the most unglamorous tool of all: the command line. From data management and workflow coordination to remotely accessing supercomputing facilities and backing up code, the command line is the most critical part of my toolbox. Let me explain…

Hand-crafted relational databases for fun and science

Mon, 05 Dec 2016 00:00:00 +0000

This post originally appeared on the Data Carpentry website

I’m a microbial ecologist that is primarily interested in understanding the ecological causes and consequences of plant-microbe interactions. Like many ecologists these days, my research spans the gamut from field to lab to laptop. Often the work involves collecting some leaves from plants in the field or from plants in a greenhouse, and then culturing from those leaves the fungi that live asymptomatically within them (a.k.a. endophytic fungi). Sometimes studying these communities relies on culturing the organisms in Petri dishes, and sometimes on directly extracting the DNA or RNA from the samples and sequencing that. One of the hardest things for me has been simply keeping track of what samples came from where, when, and who did what to which samples. To give an example: Let’s say I’ve got a fungal culture growing in a Petri dish, and I want to know how many times it has been subcultured (that is, regrown from an existing culture), when those subculturing events happened, what kind of plant tissue the original progenitor culture came from, and where that plant tissue itself came from out in the field. Oh and then downstream, I also want to know something about all the other such fungi that came out of that same plant and all their metadata as well. And I want to be able to get all of that programmatically.

Making use of Data Skills

Thu, 01 Dec 2016 00:00:00 +0000

This post originally appeared on the Data Carpentry website

Data Carpentry learners and instructors come from a variety of backgrounds and research disciplines. Many of us, myself included, don’t think of ourselves as “computer people.” We’re here because, at some point in our career, we found ourselves doing repetitive and error-prone computational tasks by hand when someone looked over our shoulder and said “Why on earth are you doing it like that!?” This person may then have leaned over our keyboard, typed for a few minutes, and finished the work that would have taken us the rest of the day. At least in my case, this happened routinely, every time a certain person happened to walk past my work station, until it eventually became more work to try to justify my process (“But I only have to do this once”. I’d say) than to capitulate and try to learn the computer magic.

I think I can - Self-Efficacy and the Carpentry Learner

Tue, 20 Sep 2016 00:00:00 +0000

This post originally appeared on the Data Carpentry website

The Little Engine that Could had it absolutely right. Thinking you can is one of the best ways to succeed at a host of activities ranging from public speaking and bungee jumping to cooking a souffle and learning R. What the Little Engine didn’t know, however, is that this concept of “thinking I can” is actually a theory known as self-efficacy, and plays a major role in how we approach our goals.

How to approach selecting a license for data release

Mon, 13 Jun 2016 00:00:00 +0000

This post originally appeared on the Data Carpentry website

A question recently came up on the SWC Discuss mailing list about how to select a license for publicly released data. Answering these questions without knowing the life story of the data in question can only be done in vast generalities, but there are some nearly universal issues that everyone should consider.

No person will be able to tell you definitively which license is the best. Your selection will be determined by the kind of data you are using, community standards, and your personal preference. There are pros and cons to permissive versus restrictive licenses, which you will need to evaluate using your own preferences.