A better use of qualitative data can inform policy

Data. It's a fact of life for all of us who work in higher education. Data has outgrown the silo of being solely the responsibility of HESA student return officers and has become everybody's problem child.

Data futures, data-driven regulation, improved data capability for all… this is the new rhetoric. But what exactly do we mean when we talk about data?

What's the story, data glory?

In England, the Office for Students (OfS) Data Strategy confirms that the regulator will rely on more than just data returns to understand what providers are doing. Social media is mentioned as a potential source, with details on how this will work in practice to follow.

For now, most HE providers are sticking to what they know - the numbers. Quantitative data in the form of benchmarks, performance indicators and Teaching Excellence Framework (TEF) metrics are recognised ways of categorising providers and students.

But what about the stories and voices that give context to these numbers? Surveys, consultations, interviews and focus groups are rich with qualitative data, and higher education has these in abundance.

The National Student Survey, Postgraduate Taught Experience Survey and even providers' own module evaluation surveys gather student voice data via 'please provide other comments' questions. But what happens to this magical information source? In a lingering echo of Paul Daniels - not a lot.

During a breakout session I ran on Trendspotting at the recent Student Records Officers Conference, I asked how many people analysed the qualitative data available to them. Only a third of delegates raised their hands. Surprising? Maybe not.

A picture tells a thousand words

Analysis of qualitative (word-based) data is common among social science research, dealing as it does with interactions and relationships. However, beyond this subject area it is often deemed to be too challenging to analyse.

Qualitative data inherently lacks structure or categorisation and it can be time consuming to organise such large information sets. There is also a strongly held belief that only statistics are real. Numbers are what can be measured or turned into a metric.

But turn the argument around and the unstructured nature of qualitative data can be its biggest advantage, providing more context and detail than the boundaries of numerical quantitative data ever can.

Joining the dots

Yes, it can be time consuming to analyse free text responses to surveys, consultations or meeting notes, but the wealth of intelligence you identify is invaluable.

At QAA, we value the qualitative data we glean from surveys, consultations, focus groups, reviews and provider liaison meetings.

We analyse these information sources to identify patterns, trends and themes, and use the knowledge we gain to benefit both QAA members and the sector. Qualitative data informs the UK Quality Code for Higher Education and other guidance, and gives quality insights to everything from webinars to case studies and conferences.

Qualitative data intelligence is timely, enabling an agile response to the topics we know are important to our members. We might carry out work in these specific areas of interest or commission bespoke research. We use our insights to deliver relevant and timely data training and help the sector use its own data better.

Picture perfect

In 2019-20, we will be working with members on how to use qualitative data to inform decision-making, approaching data analysis in a way that avoids researcher bias and presents a more accurate idea of what the data is saying.

By effectively analysing the qualitative data available, anyone has the potential to stop their stories getting eclipsed by numbers. If we move to a view of higher education where words and numbers are used together harmoniously, maybe one day we will get the complete picture.