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How can data-viz help improve student outcomes?

12th April 2018 | Sarah Cull

Start with a question

Data analytics and visualisation should always start with a question that you want answering...

  • What technologies are useful in my school and when should I be using them?
  • What teaching methods work best in my classes and on which students?
  • What time of the day should I be setting exams to get the best results for my students?
  • How is my seating plan affecting attainment?
  • Does attendance correlate with poor behaviour?
At Vizi, we believe having the answers to these sorts of questions, at your fingertips, in real-time, delivered simply and automatically can help shape your own teaching methods and a student’s path through education.

So, how is this made possible? Having evidence in the form of data is a great start, and with a decent MIS or tracking system you can build up lots of nice data. It is often interpreting the data that is the tricky and time consuming bit!

Enter Data Viz

It is easy to create a muddle of data spread across various teachers, captured in various formats. This is very often the case in schools, and the job of manipulating this data into something comprehensible can occupy a significant amount of teacher time.

Enter data visualisation! Data visualisation, or ‘data viz’ as it is commonly referred to on social media, is a practice that has existed for years and years. Remember formatting those old excel graphs, making them 3D, throwing in the odd patterned background…. But it has really gained prominence over the past decade, riding on the wave of big data. Big data being companies, organisations and public bodies suddenly having these vast troves of data with potentially fascinating insights hidden away. Data viz acts as a window into that data. A way of simplifying data into something manageable and meaningful. Good data visualisation should always allow a user to quickly understand a dataset and most importantly, it should allow you to quickly answer those pressing questions you’ve had stored up!

Data viz in schools?

Educational institutions and especially schools haven't really reaped the benefits of data viz, especially at an individual teacher level. This is partly down to the data usually being isolated by individual teacher and the data that is collected school wide often lacks the depth required to draw meaningful conclusions. And the fact that data visualisation suites can often be rather pricey! We hope that Vizi can begin to change this! So, let's go through some of the virtues of using data viz to interpret your educational data.

How can data viz help to interpret educational data?

We are visual!

Humans are a visual species, we are adapted to spot trends and patterns. Even now, human pattern spotting abilities outmatch those of computers in many fields. Simply, visualising data in a bar chart, column chart, scatter plot etc. makes it far easier to pick up patterns in your data. Compare finding a pattern in a well formatted line graph to finding one in a spreadsheet of your raw data, the difference would obviously be rather stark. Having a long list of marks for your students can feel like a good start, but just by visualising that as a line graph over time, you will immediately start to see the trends in your data - are we improving over time? What events have caused spikes or drops in our performance?

Let's go further and take our list of student marks and split it for males and females - so we have to trend lines over time. By doing this, we may see different patterns emerge from the two cohorts - our male students might have reacted well to the introduction of tablets in the classroom. Female students might always outperform male students in the morning, but this might level out as the day goes on… Interesting ey!? Well collected data is always glistening with potential insights and being able to quickly split data sets into different segments can help to reveal them.

It is also worth considering what are the best visualisations to recognise particular patterns and display certain types of data. We touched on our brain’s ability to interpret visuals in a previous blog post; like using visuals that rely on position and length, avoiding those that rely on area (pie charts!) or volume. Take a look.

Speed of retention

Using good data visualisation allows you to understand and retain information quickly. Why spend time looking through individual mark sheets when you can see everything in one place in the form of simple visualisations.

We can then combine multiple visualisations in a dashboard. Most data viz is displayed in dashboards, which are simply collections of visualisations. They are designed so that you can quickly and easily view all of your marks, grades and general information in one place. So you might have a dashboard that shows the average attainment grade for a group, the trend of that grade overtime and the distribution of the grade for that group! All the visualisations relate to one another, but give different tidbits of information relating to a cohort.

Understand and retain information

It is far easier to comprehend and remember a shape or picture than it is a muddle of data points. By looking at your data as a well presented visualisation you begin to much more quickly understand what you are looking at - whether that be a simple upward trend in the performance of a cohort of students over time, or more a more complex visualisation showing you the outliers in attendance of lessons by the time of the day.

Being able to quickly draw these conclusions is not only useful for the simple fact you have gained new information but it also saves a lot of time! You can trawl through data for hours and find something that could have been revealed in seconds with a good visualisation.

When recalling information, whether that be for an assembly, an inspection, parents evening, having that information stored in your brain as a shape or image makes the recolation come a lot faster and more accurately.

Data interrogation

Being able to quickly ask questions of your data, add filters and apply different parameters means one visualisation or dashboard can tell lots of different stories.

Let's take an example; say you have a dashboard for your Year 7 students with a bar chart showing each 1) subject’s average attainment, another showing 2) average attainment by student and one showing 3) attainment for each assessment. I click on the bar for mathematics and my data is filtered for mathematics, now I just see the average attainment for mathematics on my students bar chart. And it goes on. I click on a student that I am interested in and this filters the other graphs for that student. So I am left with an average grade for mathematics for the student and a list of assessment for Mathematics, all in a matter of seconds. I am able to drill down into the data, through my different visualisations, to get the answer I am looking for - how a single student is doing in Mathematics, for a specific assessment.

Introducing new parameters to your data

Looking at your data with new parameters and from different perspectives can reveal interesting insights. It is easy to look at performance in a set or form, against a student’s immediate peers. But can you take that same data and look at performance by topic? Or perhaps add more off the wall parameters - the school meals the students have eaten that day… Does that have a discernible effect on performance. If the data is there, data viz allows you to quickly understand the effects of particular parameters.

To take another example, it may be that you conventionally look at your data over the past term and maybe look at the weekly performance of a student - you may even see a nice friendly uptick as performance is steadily increasing. But can we look at that data through a different lense. Instead of plotting performance against week, plot it against time of day. Or day of the week. It may be that overall performance is increasing, but that the student is always performing better in the morning. Or works best in the middle of the week.

Anomaly identification

Anomalies are defined as an incidence or occurrence when the actual result under a given set of assumptions is different from the expected result. This could be a student outperforming their target or a cohort of students underperforming. Anolmolies can also exist over different spans of time - not just for a single data point, i.e. one exam result.

This is where data visualisation can come up trumps. If an anomalous result occurs over a month or a term, you might not notice it when you are recording your marks. But creating a line graph that shows that group, year group or student against a target or their peers can clearly alert you to outliers.

Pre-empting change

Seasonal, termly, by topic. Patterns start to emerge across time. Forecasting is a tricky art and you can apply lots of complex mathematical principles to predict the future. But seeing your data over time on a line graph simply allows you to see patterns emerging. There may be a lul in performance or attendance prior to a half term. Or you may notice a cohort of students struggles immediately before an important exam.

Explain complex ideas and convincing people

Telling a story is far easier if you have graphics to explain the journey you are taking someone on. Having evidence in general to back up an argument or make a point is of course handy. But having a clear and compelling visualisation that paints a picture is very persuasive and unambiguous.


Using data viz relies on having good data in the first place - consistent, organised and connected. Data viz is the icing on top that helps to unlock the hidden messages in your data.

There are lots of fantastic data visualisation products out there. Tableau, PowerBI, Lookr, Mode… to name but a few. At Vizi we hope to have captured all the power of data visualisation whilst tailoring it exactly to education and schools. That is, automatically creating these meaningful visualisations without the toil of trying to create them yourself! Get in touch if you would like to find out more!

Thanks for reading. Mike

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