Quantitative Research in Education Conference, October 2015

flickr photo by blprnt_van http://flickr.com/photos/blprnt/4177112113 shared under a Creative Commons (BY) license

Yes, I know! My research proposal suggests I’m taking a qualitative approach, so why would I be attending a conference focusing on quantitative methods? Well let me return to that shortly.

The conference was arranged by the Sheffield Methods Institute in collaboration with the

School of Education and Applied Quantitative Methods Network at the University of Sheffield. There were two presentations:

  1. ‘Using the Scottish Longitudinal Survey to analyse social inequalities in school subject choice,’ and
  2. ‘A multilevel longitudinal analysis of rich-poor achievement gaps in English schools.’

In the first, Prof Cristina Iannelli from the University of Edinburgh explained how they used the data within the Scottish Longitudinal Study to explore whether the choices students make in their curriculum subjects affect the likelihood of them accessing higher education. In particular the extent to which this is true for students from less privileged social backgrounds. In short, if you have a less advantaged background (neither parent with degree-level education), you’re more likely to follow a curriculum (aged 14 – 18) which disadvantages your chances of going to university. For example, there are some subjects which Russell Group universities demand; if you don’t have them you can’t apply.

In the second talk, Dr George Leckie from the University of Bristol described the multilevel method he used to interrogate the school performance data published by the UK government Department for Education. Seeking to establish whether the data can verify the extent to which ‘schools narrow the performance gaps between the most disadvantaged pupils in their schools and their peers.’ Using the data in their raw state from the school performance figures can be difficult to interpret and/or rather misleading; the multilevel modelling approach makes interpretations more robust and revealing.

Both talks were quite interesting from a meta-perspective. Yes the findings were of interest to anyone in education, including me, however they offered little to inform my study. Where they were much more useful (and now I return to the reason for me attending the conference), were in providing me with an insight into quantitative approaches to educational issues. Though I’m no statistician, perhaps the scientist in me nurtures an affinity for data. In particular I am fascinated by data visualisations and the way that complex numerical information can be displayed in simple, comprehensible, accessible and sometimes even beautiful ways. (See the work of David McCandless for example). I have to confess that although I understood the interpretations today’s speakers were offering of their data, I struggled to understand the statistical techniques they used to achieve their findings. It follows of course then, that I’m not in a position to question their assertions. That must also be the case for many other people too, including those on the bodies who funded the research possibly? Fortunately more capable individuals than me will be assessing their claims through the peer review process when their findings are published. I wonder whether though, because your results are processed using what to the public at large might appear to be smoke and mirrors, presenting your findings might be a tough sell? Given the skill and experience needed to be able to interrogate the data adequately, one wonders to what extent schools manage, given that they lack that expertise.

Takeaways

As I wrote earlier, I can see the allure of a quantitative ontology when you have a readily available source of data that might shed some light on a particular issue of concern, but for me, that’s just the starting point. I found myself asking why it is that Scottish students are disadvantaged by their curriculum choices and why some schools are managing to close the achievement gap between rich and poor, whilst others are not. How did I get here from a science background?!

As I mentioned in an earlier post, this was another opportunity to a) see how researchers go about presenting their findings and b) the pedagogy and process of delivering what amounts to a lecture. I’m minded to think that there’s an actor-network theory study in PowerPoint as an actant and how it translates teachers/lecturers. A future post perhaps?

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