Dharmi Kapadia, one of our Data Impact Fellows, explores how teaching students has changed some of her views on data impact.
When we think of data impact, the idea of sharing research beyond academia is brought to mind; we think of sharing research findings with people who our research might affect or benefit.
Data impact has taken on new additional meanings of:
- improving and enriching teaching content,
- enhancing student data analysis skills and
- increasing their confidence to use data outside of the lecture theatre.
This covers everything from being able to critique a statistic they see when they are reading the newspaper to using appropriate statistical analysis in the future jobs that they get.
To me this is an extremely important part of work that comes under the banner of data impact. Future generations of thinkers, scholars, researchers and data analysts need to be equipped with awareness of how research is undertaken with data and how to analyse, interpret and read these data.
As the world becomes increasingly information-oriented, the students of today need to be able to screen, digest and understand large amounts of information, and as a researcher and lecturer, it is my responsibility to make sure my students are using and interpreting data responsibly.
At The University of Manchester, I’m part of the Q-Step Centre. We are one of fifteen universities that have such a centre, funded by The Nuffield Foundation, to develop and deliver quantitative data skills training to students, in order for them to be able to evaluate and analyse data within their discipline.
One of the core principles of the Q-Step Team at Manchester is to introduce numeracy and data analysis skills at an early stage in students’ undergraduate degrees so we can start building their confidence in handling data. This is especially important for students in Sociology, many of whom feel apprehensive about using quantitative data because they think they are ‘bad at maths’ or that the essence of Sociology is to use qualitative methods only.
As you can imagine, it can be a challenge to convince students that they really will be able to use large quantitative survey datasets to conduct their own analyses, and then equip them with the skills to do it! But, this is exactly what I have been able to do with my 1st year undergraduate students.
By the end of the first year, my students have used UK Data Service teaching survey datasets Understanding Society or the Crime Survey for England and Wales, or other survey data such as the British Social Attitudes Survey, to present findings on a research topic of their choice in an oral group presentation, and write a research report using these data.
For students who thought they were rubbish at Maths, and would never dream of using quantitative data, these are massive achievements.
But this isn’t the end of their quantitative data journey.
In the 2nd year, students are able to apply to be a Q-Step intern over the summer at one of our partner organisations; previous organisations have included AudienceNet, the BBC, The Home Office, Greater Manchester City Council and the UK Data Service.
During eight-week placements, students take on a real piece of quantitative data analysis for the organization increasing their data analysis, reporting and visualization skills and providing invaluable research and knowledge to the organization – true mutually beneficial partnerships. A previous UK Data Service Lab post by our summer interns Klara and Rabia showed just how brilliant Manchester Q-Step interns are, the social importance of the work they undertake, and the meticulous level of detail that they work to.
Our 2018 Q-Step interns will be showcasing their work in our Q-Step event this week (14th November): The 39 Q-Steps: stories from data-driven, research-led paid internships.
Once students become interested and excited by the possibilities of using quantitative data for social research, it is our job as their lecturers to keep this interest alive, and help them to keep developing these skills.
After completing a Q-Step internship, many of students want to put their quantitative analysis skills to good use in their third year dissertation projects.
As the Q-Step Lecturer in Sociology, I guide them with finding data, making sure their research questions are answerable with the data that are available, and advise them on analysis methods and appropriate software.
I may be a little biased in favour of my students, but the level of quantitative data analysis skills that they come to me with in the third year, compared to what they knew in first year is simply astonishing!
The Q-Step Centre has a big role to play in developing our students’ skills in data analysis and their confidence in using these skills beyond the classroom. But students’ recognition of the importance of data numeracy and analysis skills in the job market is also a key component of why the Q-Step programme is working well for our students; they know that these skills will be important for them in their future jobs.
For our Sociology students, using quantitative data throughout their degree programmes has changed the way they view Sociology, their potential and the social world.
I’d be confident to say that means I’ve created some real impact by using data with my students.
Dharmi Kapadia is one of the UK Data Service Data Impact Fellows. She is a lecturer in Sociology at The University of Manchester.