Data, data everywhere

A welcome publication this week from the British Academy “Count us In” identifies the importance of the ability to understand and interpret data in the 21st Century.

The ubiquity of statistics makes it vital that citizens, scientists and policy makers are fluent with numbers. Data analysis is revolutionising both how we see the world and how we interact with it.

This new report from the British Academy offers a vision of how the UK can rise to the potentially transformational challenge of becoming a data-literate nation.

Within this are two clear messages for a university. Firstly how we make sure that the graduates that we produce are able to work and function in a data literate society, and secondly how we as an organisaton become more data literate.

Universities have traditionally been influenced by the liberal arts – and I will always defend the importance of developing high level critical thinking skills through a liberal education.. Howver, this in  turn has influenced how we might define what is to be a graduate, with a focus on communication, reflection and team working. However, few universities have developed their definition of graduate skills or more recently graduate attributes to explicitly explain how a graduate will be numerate, be able to handle data and be able to make decisions based on proper analysis. More surprising, is that this flies in the face of the skills that we know that employers value. We would have to ask why we have shied away from putting quantitative skills front and centre.

The report from the British Academy envisions:

 a generation of citizens, consumers, students and workers as comfortable with numbers as they are with words, confidently engaging with data in a future driven forward by technological development and a drive for international competitiveness.

and in doing so recognises the need for cultural change at all levels of the education system.

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For UK universities, the key messages in the report are:

  • the need for universities to send signals to school on the importance of quantitative skills
  • the need for it to be normal for science,social science and humanities students
    to have developed significant quantitative skills in school, so that universities can then strengthen their entry requirements.
  • the worry that we dilute the curriculum to reflect the current poor level of quantitative skills of students
  • the bigger worry that the changes in course design may reflect weaknesses in the quantitative and data skills of university teaching staff
  • students graduate with little confidence in these skills, which have a negative effect on the businesses they subsequently work for

In terms of moving forward, the proposals from the report include:

  • universities should review and if necessary redesign the content of social science and humanities degree programmes
  • universities need to signal with more clarity what level of quantitative skills is necessary for each course
  • an increasing need for collaboration between universities and employers to work with the  data now collected and generated by the private sector

As well as the need to develop courses that develop quantitative skills, a university must also be aware of their own workforce’s skills. All staff in university might reasonably be expected to be able to handle data to make decisions – for instance through measuring student engagement as a personal tutor, optimsing a timetabling system, predicting recruitment numbers and workforce planning, benchmarking organisational performance through extenral data sets and league tables. The list goes on.

From the BA report, many more people in the workplace need to be able to handle data fluently.However:

a substantial body of case study research suggests that many employees fail to understand fully the quantitative techniques they are using, and lack the ability to recognise obvious errors in their work.

and

The almost universal investment in technology by private, public and voluntary sector institutions does not negate the need for numerical understanding. Rather, it adds
to it, as people require skills of investigation and interpretation. Nor are quantitative skills deficits confined to less senior employees: it has been estimated that as many as 58 per cent of people in “higher managerial and professional occupations” do not have numeracy skills at GCSE A*–C and above

All of which is worrying, as the report clealry identifies the economic benefits to organisations of being able to use data well.

To improve the situation for companies, the report proposes internal staff development, and engagement by businesses with training providers including FE and HE and taking advantage of apprenticeships.

I hope that this report helps spark more conversation -maybe even a strategic discussion at a committee somewhere –  on the need to improve numeracy, quantitative skills and data analysis.

For a university there are two key main areas to debate:

Firstly, how do we explicitly improve the quantitative skills of all students, and how do we show this  to potential employers that this is the factor that differentiates our graduates?

Secondly, how do we raise the data handling skills of all of our staff – teaching and professional support – to be able to teach and use data in the most effective way for the organisation?

To make a small step forward on this, tomorrow I will be presenting at our “Leading Academics” course on how to use data with the following outcomes:

  • To recognise the importance of using performance data
  • To identify which parts of the performance data set might be a priority for action within own subject area
  • To understand the benefits but also limitations of metrics based approaches

It’s a start.

 

 

 

 

 

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