Reducing the load – part three: How scale helps teachers save time on data collection and analysis

In our previous blogposts we discussed how great results can be achieved through informed action, which depends on insightful analysis based on accurate data. At Ark, our goal is to minimise the time spent on data collection and analysis, leaving more time for action. We are still on a journey towards achieving this goal, but we believe the following three levers can make a big difference: Technology, Consistency and Scale.

So far, we have focused on how we use Technology and Consistency to minimise workload. This time, we will focus on Scale…
[[{“fid”:”163651″,”view_mode”:”default”,”fields”:{“format”:”default”,”field_file_image_alt_text[und][0][value]”:””,”field_file_image_title_text[und][0][value]”:””,”field_tags[und]”:””},”type”:”media”,”link_text”:null,”attributes”:{“class”:”media-element file-default”}}]]

Scale is obviously one of the main drivers of economic efficiency. Spreading a fixed cost reduces the average cost for everyone involved. This obviously applies to finances (e.g. when procuring systems), but it also applies to workload. The dashboards described in our previous post could, in theory, be built separately by a member of staff at each school – but at what cost? Not only would this undermine the consistency described above, but it would also increase the total workload expended many times over. It’s worth noting that scale efficiencies can be achieved without needing to be part of a multi-academy trust or similar formal network. Leveraging third party systems can achieve similar results, provided you can find one that fully meets your school’s needs without requiring costly adaptation.

Scale also has many other advantages beyond economic efficiency. For example, the reliability of our assessment data significantly increases with sample size. This is one of the reasons we use normative assessments, which are taken by a large, representative sample of students from across the country, to either set our grades or at least calibrate our internal judgements. Another good example of scale in action is comparative judgement, which we use to increase the accuracy and speed of grading assessments like essays and creative writing. Applying a marking rubric to every essay not only takes ages, it is also prone to significant measurement error. Comparative judgement requires teachers to compare two essays at a time and uses the information from all of these decisions to assign a grade to each essay. It takes a fraction of the time and has been shown to be more reliable. You can find out more about the process of comparative judgement here.

[[{“fid”:”169536″,”view_mode”:”default”,”fields”:{“format”:”default”,”field_file_image_alt_text[und][0][value]”:””,”field_file_image_title_text[und][0][value]”:””,”field_tags[und]”:””},”type”:”media”,”link_text”:null,”attributes”:{“class”:”media-element file-default”}}]]

Finally, scale enables comparison across a much broader comparison group than any one school can achieve on its own. If we tell you that a school has a score of 84%, it is impossible to really know whether that is good or not. If we tell you that it is the lowest score among 18 Ark schools, you may assume that it’s not that good. But if we tell you that it is among the top 10% of scores in the country, you may take a different view. These shifts in perspective are essential for our analyses to be truly insightful, but too often they take place over months rather than seconds. We are very fortunate in this country to have a wealth of nationally comparative data at our disposal, but it is often only used as an afterthought. At Ark, we try to embed information about national distributions into everything we can – so that teachers can quickly understand how their data compares not only to other Ark schools, but to similar schools across the country.

[[{“fid”:”163656″,”view_mode”:”default”,”fields”:{“format”:”default”,”field_file_image_alt_text[und][0][value]”:”Rich Davies”,”field_file_image_title_text[und][0][value]”:”Rich Davies”,”field_tags[und]”:””},”type”:”media”,”link_text”:null,”attributes”:{“alt”:”Rich Davies”,”title”:”Rich Davies”,”style”:”height: 100px; width: 100px; float: left; margin-left: 5px; margin-right: 5px;”,”class”:”media-element file-default”}}]]

Rich Davies is Ark’s Head of Data. He splits his time between mining Ark’s data for actionable insights and developing Ark’s in-house data tools, enabling staff across the school network to develop their own data insights. Prior to joining Ark, Rich was a Strategy Consultant at the Boston Consulting Group.

[[{“fid”:”163661″,”view_mode”:”default”,”fields”:{“format”:”default”,”field_file_image_alt_text[und][0][value]”:”Daisy Christodoulou”,”field_file_image_title_text[und][0][value]”:”Daisy Christodoulou”,”field_tags[und]”:””},”type”:”media”,”link_text”:null,”attributes”:{“alt”:”Daisy Christodoulou”,”title”:”Daisy Christodoulou”,”style”:”height: 100px; width: 100px; margin-left: 5px; margin-right: 5px; float: left;”,”class”:”media-element file-default”}}]]Daisy Christodoulou is Head of Assessment at Ark, where she works on assessment reform, replacements for national curriculum levels and readiness for new national exams. Previously, she was Research and Development Manager at Ark. She is the author of Seven Myths about Education and Making Good Progress? The future of Assessment for Learning.