The Office for Students started to provide updates of the general student numbers at providers under their regulatory control. This covers both traditional higher education providers as well as further education colleges and alternative providers.
The data is available here: https://www.officeforstudents.org.uk/data-and-analysis/student-number-data/get-the-current-student-numbers-data/
The visualising HE team decided to give it a crack as it is a simple data set and it provided a genuine whole sector view of data.
This as it turned out was not as straightforward as we had hoped. The simplicity of the data set made it challenging to find the interesting story within the data.
This gave us an opportunity to try out different approaches and pushing both technical and design skills to try and come up with something that is interesting.
Each member of the team outlines below what they have produced and what they have gained from the process.
Dave – Size and shape over the last 2 years
I struggled to find an interesting narrative at first then as I looked at the changes between the years I noticed that although the numbers for further education colleges were smaller than the changes in higher education the proportions of the total was much more dramatic.
Once I found this I decided that I would create a visual that stepped through the data to draw out this interesting element. The long form story telling nature of the visualisation focusing on bar charts hopefully works well.
Jennie – Simple student numbers reporting
My visualisation simply looks at reporting student numbers at different levels, allowing the user to select a higher education provider and compare how the proportion of students at different levels compares with other institutions. Student numbers on the right-hand side of the chart are provided for context and both 18/19 and 17/18 figures can be shown.
This analysis focuses on higher education institutions. Unsurprisingly at the majority of these institutions 100% of students are taking level 6 or above qualifications, however I feel as though it is more interesting to look at the institutions which offer levels 4 and 5 qualifications. For example, on average only 1.5% of students across all university institutions are studying for level 5 qualifications, however almost 30% of University College Birmingham students are at level 5.
Whilst the dashboard isn’t too complicated, it nicely uses sets, set actions and animations to reorder the main chart based on the proportion of students at the level selected. The stacked bars also sort dynamically, with the selected level always at the end of the bar to allow easy comparison between universities.
James – student population comparison
When I began exploring the data in Tableau I was struck by the size of some of the institutions. That gave me the idea to try to find out how many large institutions it takes to match the populations of the remaining institutions. I decided that two stacked bars next to each other could show this.
The data cover both Further and Higher Education institutions and different education levels. So I built the workbook to allow you to make comparisons within and between them. The most striking finding is that when looking at all levels combined for 18/19, it takes only the top 3 Higher Education institutions to match the population size of all the Further Education institutions.
Building the workbook required me to solve some technical challenges. To make the stacked bars gain or lose institutions I made some plus or minus buttons. Clicking these triggers a parameter action increasing or decreasing the number in the parameter by one. The number of institutions in the right stacked bar is based on the rank of the sum of the students at that institution. If the rank is less than or equal to the value in the parameter then that institution appears on the right hand side (and disappears from the left hand side where appropriate).
To make the buttons I put institution on columns in a sheet in Tableau and put index() on detail in the marks card. I then filtered to only leave the institutions with an index() one above and one below the current value in the parameter. When you click a button the parameter is updated and the button sheet is filtered to the institutions above and below that rank.