Students in HE – some interesting bits..

Hey up – it is a new year and at Visualising HE towers we made a new year’s resolution that we would keep up with the latest HE data releases. So we were pleased that HESA provided us with an early new year present in the form of some summary student statistics loveliness.

The lovely people in Cheltenham have taken a slightly different tact with this release with an approach guiding the reader through the analysis and allowing the draw down of the data that supports each chart so that you can revisit the story for additional insight.  This approach has not had universal acclaim (a superb WonkHE article on the subject) but it gave us rich pickings for our Visualising HE fun.

So where to start? With all the discussions around Brexit and the widening discussions around the value international students have on the UK economy it was felt that looking at where the students come from would be worth a peak.

Take 1: UK vs. Non-UK Enrolments

The first viz uses data from figure 6 and focuses on Higher Education Institutions (HEI) and to what degree their enrolments come from the UK against non UK enrolments.

UK vs Not UK (1)

The interactive viz is here and the vispiration came from the great Ben Jones blog post.

The main takeaways from this is that (unsurprisingly) the number of UK enrolments is quite spread with most HEI taking in sizeable cohorts.  When looking at non UK enrolments there are many HEI taking small amounts then a few taking in the larger numbers.

In terms of interesting HEI the University of Manchester stands out just through its sheer size both for UK and Non UK enrolments where it is among the largest in both categories. Imperial College has a slightly different balance with nearly as many non UK enrolments as UK.  Then the reverse of that is Sheffield Hallam who have a large UK cohort and a small non UK cohort.

Take 2:  UK, Other EU and Non-EU 1st year enrolment Trends

The second viz uses data from figure 8 and builds onto the international question by separating the EU and Non-EU entrants to deliver a quick insight into the general trends across the sector. Figure 8_visualisingHE

The interactive viz is here.

The main takeaways from this visualisation are the predominance and continued growth of UK domiciled students entering at first degree in UK HE in 2016/17, and the continued proportional decline of the Non EU first degree postgraduate research (PGR) and postgraduate taught (PGT) student populations.

The filters on the top right of this dashboard allow us to delve further into the data set and see the trends at country level. It appears that the the decline of the Non EU entrants at a postgraduate level is most prominently observed at HEIs in Wales, where first year enrolments on both PGT and PGR programmes have experienced the sharpest decline during the last four years.Adam's UK-EU-NonEU Enrolmentspng.png

Take 3: Subjects’ Popularity and the Gender Gap

The third viz uses the data from figure 12 and presents an overall view of the new enrolments in the sector with a slight focus on the subjects’ popularity (science vs. non-science enrolments) and the gender gap (male vs. female enrolments).


The interactive viz is here.

The main takeaways from this dashboard are that enrolments in the science subject areas, represented with blue diamonds, have increased more than enrolments in the non-science subject areas, shown as grey circles, since 2012/13.

A further insight is available through the in-built #VizInTooltips available on hover. From these we can see that first year enrolments on ‘Computer science’ related programmes have increased at both First degree and Postgraduate Taught (PGT) levels.

Summary - Computer Science.png

The dashboard also highlights that the ‘Business & administrative studies’ appear to attract similar numbers of male and female students. All of the subjects dominated by male enrolments are from the science field. However, the gender gap has been gradually decreasing for some of them: ‘Architecture, building & planning’ is a good example where the difference has decreased from 28 to 20 percentage points.

Summary - Architecture.png

Take 4: Top 10 Non-EU Domiciles

The last take on HESA’s SFR for 2016/17 uses data from figure 11 and is the colourful  #Coffetableviz style visualisation of the Top 10 Non-EU Domiciles for First Year enrolments in the UK.

Non EU international dom first year enrolments to UK HE_white

The interactive viz is here.

The main takeaways here are the solid first position for enrolments from China and the fact that the top 10 domiciles have remained the same since 2011/12. Other more noticeable changes include Nigeria’s decline from 4th to 6th position (shown in orange) and Hong Kong’s rise from a steady 6th to a 4th position from last year (shown in light green).

That’s it for now from us. Thank you for reading and we hope you enjoyed exploring our data visualisations!


Dave, Adam and Elena


Destination: Europe

In today’s globally connected world we experience the notion of a border mainly when we go through passport control at the beginning or the end of a journey. For the education sector, it means that now studying abroad has never been easier, especially for those who live in Europe. So what does the student mobility within Europe look like?

To answer this question, I have decided to look at the Higher Education data from Eurostat and find out the number of enrolled students within each European country who are from a different European country. The full dataset contains student enrolments from some countries outside of Europe, too, but for the purpose of this exercise only European origin and destination countries have been included.

Why visualising student mobility within Europe?

Choosing the topic wasn’t easy. In fact, Dave Kirk helped me with this a few months ago when Dave, Adam , Stephen and I launched #VisualisingHE. He and Adam were enthusiastically listing topics and datasets they were looking forward to exploring as part of the project but I was struggling to come up with something that I could talk about with so much excitement.

Big Map 3.png

Then Dave asked me: what are you passionate about? And it didn’t take me long to come up with an answer – I am an Eastern European and I cannot imagine who and where I would be today if I hadn’t been given the opportunity to undertake my bachelor’s degree in the UK! Therefore, I decided to look into the topic and  develop a pretty, colourful and informal visualisation that represents the beauty of studying abroad… in Europe.

What influenced the design and choice of charts?

Probably the better question here is not ‘what’ but ‘who’ influenced the choices I have made as part of the design process. Having decided on the overall ‘feeling’ I wanted to my visualisation to convey, I had to think about whether I wanted my dashboard to be in a #coffeetableviz (i.e. poster) style or be leaning towards the exploratory side. I will leave it to you to decide where precisely on the informative vs. exploratory spectrum the end result lies, but I will let you know whose work gave me the inspiration:

  • for poster style infographic I would always go to Pooja Gandhi’s fantastic work first: if you haven’t visited her tableau public profile, do it! I find her work truly inspiring – she knows how to deliver a clear message in a dataviz by seamlessly combining text and graphs.
  • for visualising the inflow vs. outflow concept I was inspired by Neil Richard‘s viz on the Eurovision song contest. When I first saw his viz, I remember thinking: ‘Oh, well it is clear to me what the visualisation is telling me.’ Plus, I really liked the flags.
  • for colours I got inspired by Jeffrey Shaffers Beautiful Trash.

Then the idea of a Sankey sprung to my mind and that was it – I was going to do a Sankey and practice my great arc curves on a map. I started with the great arc curves as I had already done these for a project at work. For the data structure I followed this summary and to get the lines curved, I found this post useful. Building the Sankey wasn’t too difficult either – there are plenty of blog posts written by the community that explain how to do it. I read a few and after deciding I did not want to use custom SQL, I found this post helpful.

What were the challenges?

Just as I was thinking I was making some really good progress, I came across Ravi Mistry and Nicco Cirones very interesting work on ERASMUS. It was great! I loved it… but it also had a map of Europe with curves, and a Sankey, and was talking about students studying in Europe… Oh dear, I didn’t want to copy their work… Even though I hadn’t seen it until I was alredy halfway there with my viz, if I were to use exactly the same combination of graphs would have still made me feel as if I had copied it. At this point I had two options: drop the topic, or think really hard how to make my visualisation different. A few days later I was going through some of my favourite dashboards on Tableau Public and then, inspired by Adam McCann’s beautiful Beatles Analysis, I decided to develop an ‘hourglass’, or a double Sankey, chart (I don’t know if this chart has a name) to show the inflow vs. outflow relationship. Not long after I had my first draft:

Student Mobility

Another big decision making point in the process of developing this dashboard was around my choice of font. It crossed my mind that there is this thing about safe fonts for tableau public. After a quick check on Google I thought I should try and use a web safe font. My choice was Comic Sans. Yes, Comic Sans, because I was going for a fun artistic / informal look. Little did I know that there was something about Comic Sans… When I asked for some feedback on the way my dashboard was coming together, I got mixed reactions. I particularly like the contrast in Dave and Stephen’s comments:

Comic Sans & Fonts

After doing some reading on the internet and quite a few lengthy discussions with friends and colleagues at work, I decided that though I see nothing wrong in using Comic Sans for my dashboard (especially, since I am not saying: ‘Danger, Danger, the world is about to collapse’ … or something in those lines), I decided to change it. Simply because I didn’t want the font to distract from its overall purpose.

What did I learn?

  1. How to build a Sankey
  2. How to build an hour glass visualisation
  3. How to crop an image in GIMP (and add transparency to it)
  4. There is something about Comic Sans…
  5. How to use A LOT of containers (with very few of them floating!)

What are my personal challenges for the next viz?

  • Don’t use a long-form dashboard
  • Produce a dashboard with a non-black background

Thank you for reading and I hope you enjoy exploring the dashboard!


Inflow & Outflow (6)