Get ready for Doing Journalism with Data MOOC

Exit Festival 2012 by Bernard Bodo. Creative Commons (CC BY-NC-SA 2.0)

Exit Festival 2012 by Bernard Bodo. Creative Commons (CC BY-NC-SA 2.0)

We’re excited! This MOOC from the European Journalism Centre  – “A free online data journalism course with 5 leading experts” – starts on Monday 19th May.

….and it’s not too late to join the party! I’m doing it because I want to keep building my Data Journalism skills and find out how data journalism is developing around the world. But, as an educator studying for a Masters in Blended/Online Learning, I’m also interested in the whole MOOC phenomenon.

So what’s the best way to get ready for this MOOC? Here are a few ideas.

Understand how Massive Online Learning works

Watch this for a quick familiarisation from Dave Cormier.

There are different platforms for MOOCs. Coursera is probably the best known, but there’s also Udacity and a platform created by the UK’s Open University called FutureLearn.  The Doing Data with Journalism MOOC will be using Canvas. I recommend adding the Canvas bookmarklet for this DJ course to your browser so it’s really easy to get to and a constant reminder you have work to do!

What kind of MOOC course are you doing?

Screenshot of Dave Cormier's MOOC video

Screenshot of Dave Cormier’s MOOC video

  • xMOOCs refers to the Coursera-type model where a teacher-expert transmits knowledge through carefully packaged videos and checks that knowledge has been acquired through computer-graded quizzes. Support comes from occasional tutor-participation in discussion forums. But support is also encouraged through students organising face-to-face meet-ups in their locality. There’s probably a Coursera meet-up group in your area!.
  • cMOOCs rely on a more connectivist approach, making use of the networked web 2.0 technology. There can be an emphasis on content creation, for example, as a way of building knowledge. They are more student-centred in that there is no set route through the course and a limited structure so there’s more learner autonomy. Webinars with guest speakers, blogs and online facilities for students to connect with each other are a strong feature. Support comes from peers and is facilitated by networked technology.
  • quasi-MOOCs are not much more than Open Educational Resources tutorials such as the Khan Academy and, more recently, Codecademy. The learning resources are asynchronous and don’t really offer social interaction unless students generate it themselves. quasi-MOOCs are not packaged as a course but as a series of standalone tutorials. So support would be minimal here.
  • Dead MOOCs OK, so this is my own category. I use it to describe archived MOOCs. So the actual MOOC is no longer running – the tutors aren’t around and the submission deadlines have passed – but you can still watch the video lectures and do the online quizzes. You won’t get a badge or certificate at the end but you can still learn.

I don’t know which model Doing Journalism with Data will follow so it’ll be interesting to find out.

You can read this article by George Siemens to learn more about the MOOC phenomenon.

Statistics: Making Sense of Data

By Ainali. Creative Commons CC-BY-SA 3.0

By Ainali. Creative Commons CC-BY-SA 3.0

Without a basic understanding of statistics, data doesn’t mean much. I’ve been taking this Statistics MOOC from the University of Toronto for the last couple of months. It uses the Coursera platform and, thanks to the video lectures from Jeffrey Rosenthal and Alison Gibbs, I can now only talk about data in a Canadian accent. It’s a great example of a dead, xMOOC! Even though the discussion forums are a year old, they’re still really useful when I get stuck (often.) The submission deadlines are long gone so I’m not going to get any badges or certificates, but I still get marks for the multiple choice quizzes I do and I can even do my assignments because the lecturers have supplied a “model answers” sheet for me to check against. It’s been a great way of brushing up my A-Level Statistics and putting it into a more practical context and I highly recommend adding some statistics to your Data Journalism skill set.

Let’s kill the myth that journalists can’t do maths here and now!

Explore examples of Data Journalism

This is a great way to get in the zone. Once you start looking, you’ll find loads of examples. Think about the kind of data that was used and where it came from. What journalistic processes were added to the raw data to make it journalism – e.g. context, visualisation, interactivity?

And a note of caution, just because it’s data doesn’t mean it’s journalism. You still have to check your facts, the data source and make sure you’re not asking your data to do more than it’s capable of. Here’s a cautionary tale you should read before embarking on your Data Journalism MOOC. It’s about this map of kidnappings in Nigeria produced by FiveThirtyEight.

See you there….

So, if you’re one of the 20 393 people already registered for the MOOC, I hope to see you online and share some learning. Do drop by and say hello!

Next job – I’ll be putting together a list of Top Tips for learning with MOOCs in the next day or so.

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