I find data quite a reassuring part of the research process. Once I get to the data, I feel the hard work is done. Now I can play and see what story the numbers tell me. The hard part is generating the data: putting together questions that are meaningful and most of all that provoke meaningful answers.

In the cross programme session, part of this PGCERT Academic Practice in Art, Design and Communication, I was hoping to learn a lot about how data is used at UAL, how it is collected, what sort of questions are asked, how students are reached and most of all how it is analysed.

I completely appreciate the session is quite brief and not everyone is so keen on data, but perhaps in the attempt on demystifying it, we ended up spending more time on creating poetry about it than on looking at the data itself. Don’t get me wrong I really enjoyed brushing up on the limerick anapaestic tetrameter and learning about haiku.

We were presented some diagrams about attainment at UAL with data shown with different degrees of granularity, but still possibly not granular enough. The bottom line was clear: white students have a higher level of attainment. However, the information we didn’t have was to do with how many students were in each category, what method of evaluation was used to determine how some students were deserving of a 1st or a 2:1 vs others, what age were the students with higher attainment level and so on.

With the information we had was very hard to answer some poignant questions like “what would you do to address the attainment gap?”. All that was possible was to make generic statements, such as:

• Diversifying staff (to reflect student body)
• Student body to be diversified
• Tuition fees to be made more accessible so as to facilitate greater diversification in the student body
• Enforcing a 5-year shift in positions of power

Of course the above points are absolutely sacrosanct, but I understand these are already being worked on. Are they not? Am I being naive in thinking that since I find these points so obvious and so often raised they must be worked on? Let’s assume they are not then and that our suggestions were indeed useful. Still there is much more we can do to get to the core of this problem and bridge this gap.

Is it really that simple? Is it really that under-represented students don’t identify themselves in their tutors and so they struggle to succeed because they don’t feel supported? Have we asked them? Aren’t there any other avenues to these under represented students’ learning that we can explore? Can we do some research on that? Can we perhaps ask some pertinent questions or observe how these students learn or test different techniques and see which has the best results? Is this a patronising approach? Is it even ethical for a white tutor to even think they have the authority to do this. Should this be explored by a tutor of the same minority group as the under-represented students? As I go on writing this blog I feel like I am digging myself into a deeper and deeper hole and instead of finding answers, I find more questions and I feel less entitled to offer suggestions.

How does one earn the right to investigate these matters if one does not belong to the minority they wish to research? Perhaps before starting the research on the effect of different teaching approaches on under-represented students and their learning styles, one could conduct some research on how under-represented students would receive a member of the over-represented group conducting research on them…