R4DS: the next iteration

6 min readDec 22, 2017

Background

In August of 2017 I launched an experiment, referred to as the R for Data Science Online Learning Community, with the goal of creating a supportive and responsive online space for learners and mentors to gather and work through the R for Data Science text.

Like most online learning endeavors, we had a massive surge of interest at the onset, with exponential drop-offs week after week as we progressively worked through each chapter based on an established schedule. Although everyone who messaged me had their own individual reasons for dropping out, the underlying premise was the same: the pace of the group was too overwhelming.

With that in mind, I’m excited to announce the changes we’re making to the group, which will be launching on December 30th, 2017!

Group structure

Content

The aim of this group is focused on moving through the R for Data Science text, which walks readers through the major features of the tidyverse in the context of data science.

Sign ups

Instead of running on a cohort model, with sign-ups taking place during a specific time of year, the group will (for the foreseeable future) always be open.

Initial invites will go out on December 30th, and then approximately once a week thereafter.

Please note: if you sign up on December 30th after the initial invites go out, you will receive your invite the following week.

You can sign up for the group here!

Slack

This online learning community will continue to use Slack as its primary forum.

Within the Slack group we will have the following channels:

A single channel corresponding to each section of the text, where conversations related to specific chapters within that section can take place (edit: originally the idea was to have a channel for each chapter, however a list of almost 40 channels is… overwhelming!)
A datasets channel, where members are free to share datasets for community members to work with
An error messages channel, where members are able to share error messages they receive when working on projects that are not directly related to chapters within the text
A general channel, which serves as a catch-all channel for conversations that don’t necessarily fall into an existing channel
An introductions channel as a place to say hello and share a bit of information about yourself
A pilot programs channel, where group members can discuss ideas for small-scale programs as well as receive feedback and guidance on getting their programs up and running
An R resources channel, where members can request resources, as well as share tutorials, links, and other R resources that they’ve found helpful
A stats and analysis channel, which will serve as the main channel for questions related to data analysis
A wiki channel, where anyone interested in contributing to our wiki can discuss the wiki
A wins channel, where members can share the things that are going well in the R for Data Science mentorship and/or learning journey, and receive kudos from the group!

Pilot programs

In an effort to empower community members to take on leadership roles, if there is a program and/or project that you would like to see created, please share your idea in the #pilot_ideas channel! Within the #pilot_ideas channel we will help you think through the idea as well as set you up with a channel to carry out your idea with group members who choose to participate.

Pilot programs that people have expressed an interest in include, but are not limited to, a recurring talk on an aspect of R — given by a community member, a time-based move through the curriculum, and a group that uses a specific data set to work on projects by applying what you’ve learned in the text.

The idea behind pilot programs is twofold:

Develop community leadership
Test out ideas for scalability and sustainability before determining whether or not they should be rolled out to the entire community, or remain as small-scale projects

Content creators

We would love to have community members create content related to both R as well as their participation in the R for Data Science Online Learning Community! If you’re not sure where to start, tutorials and content on the following would be a fantastic addition to the community:

how-to: github, especially contributing to the wiki
how-to: screenshots
how-to, benefits of: reprex
troubleshooting R and RStudio installation
how-to: use Slack, get the most out of Slack in this group

Types of members

Learners

You are developing your skills in R
You are developing your skills in data analysis
You have regular access to both a computer and internet connection
You are comfortable installing software on your computer

Mentors

You enjoy contributing to the creation of a positive online learning community
You don’t get frustrated when someone asks (for the 100th time) what a factor is — in fact, you’re excited to come up with multiple methods to help ensure that someone is learning and mastering the material
You have 1–2 hours a week that you can spend answering questions via Slack, and working with learners to help them expand their skill set
Many mentors identify themselves as such by setting their Slack status to “M”

Administrators (new)

If you are interested in being a group administrator and working on group logistics (channel creation, sending out invites, answering administrative questions, etc.) please be in touch with @kierisi. At this point in time there is no formal process for becoming an administrator, as we are waiting to see how many people are interested.

Slack tips

If you’re not familiar with Slack, it is worth the time to get to know the settings in Slack as soon as possible, otherwise this experience will be 210% overwhelming!

Some helpful things to know how to do in Slack:

Questions you might have:

I was in the first round, how do I sign up again?

If you joined the Slack group in the first round, you’re already signed up! All you need to do is log in to the Slack group again.

How is this different from the first round?

The first round followed a curriculum that went through specific chapters each week. This iteration of the group will not follow a pre-established curriculum, but instead serve as an ongoing space to ask questions and share advice related to the R for Data Science text.

Who can join?

Anyone interested in creating and participating in a supportive, welcoming space for those learning R for data science. Specific community expectations can be found in our Code of Conduct.

I don’t agree with the Code of Conduct

Then this is probably not the group for you.

Where do I sign up?