“Lockdown engagement” impact on attainment

Staying at home is feeling like the “new normal”. However I know my daughter, like lots of children is missing her friends and teachers. 

We’ve been able to interact regularly with her school, but I am aware that not every child (due to lots of reasons) is so lucky. When all children are able to return to school, will these differing levels of engagement increase the attainment gap.

Markers in the tracker
A number of schools I work with use an Attainment Tracker to follow how their children are achieving from nursery to S3.

Within the document they can compare the attainment of children by different measures such as risk matrix, SIMD.

However, there could be benefit in flagging how much engagement there was during the lockdown. The options could be as simple as,

  • Attended Hub
  • High
  • Medium
  • Low
  • None

By combining this information with your existing data it could highlight any new groups of children that would benefit from additional support. Especially for children transitioning from P7 to S1. 

I love pies, but not pie charts

I was watching BBC Scotland bitesize with my daughter (which we are loving!) and they were explaining “the uses” of a pie chart and I nearly turned the TV off 🙈

Pie charts can look pretty, but in terms of visually communicating information there are so many better ways.

Before you produce any graph, you need to ask yourself what are you trying to tell someone?

Are you wanting to compare two lots of information?

Are you wanting to show that one number is bigger than another?

More often than not, by using a pie chart you end up knowing less about the data then if you had just a table of numbers.

As I said, pie charts can look pretty but if you just want a nice picture I would always prefer an actual pie 🙂

I’m always looking to learn, so if you have an example of a brilliant pie chart I would love to see it.

How confident are you in your data?

Schools seem to be flooded with data: from tests, feedback, teacher assessments…. but does all your data tell the same story.  

If you had to choose two teachers within your school to assess the ability of your pupils, would each child be given the same score by the two teachers? If every child had to give feedback on a lesson would they all have the same view?

Before you start any analysis or taking any actions based on your data, you need to decide how confident are you in the data. Otherwise, no matter how good your analysis is you will just have Rubbish in = Rubbish Out.

Here are some questions that can help you think about your data,

  • How was my data collected? Was it a survey that pupils fill in themselves or did someone ask them questions? Could this have impacted the results?
  • When was it collected? Are there any outside factors that have caused a movement in the data? Could a positive or negative event at home change how a child performs in a test?
  • Who is included in the data? Are you comparing data like for like, e.g. is the increase/decrease in scores due to pupils leaving the school?

Once you are happy with the data you are using, combining data from different sources can be powerful. A number of schools I work with are already doing this. Some look at standardised tests scores with teacher assessments. (Attainment Tracker with NGRT data)

If you would like some support with your data, please get in touch.

“What gets measured gets managed”…..vs. I’m sure everything is fine (!)

I am very blessed to have two beautiful, healthy daughters who keep me very busy! Unsurprisingly a lot of my time is focused on making sure they have everything they need (and everyone else including myself comes after). However, at a recent blood test to check how I was recovering after having my baby, it indicated I was dehydrated (oops!)

After being admitted to hospital twice during my pregnancy due to dehydration I am very aware for drinking plenty! This had never been a concern before having children, so this result was a bit of a surprise.

So I thought I’d measure how much I was actually drinking (instead of guessing) with a labelled water bottle, and oh dear…. I wasn’t doing well!

The first day was fine, I was drinking plenty and everything was great. Day two, not so good! By lunchtime I wasn’t even at the 10am line and it took me all day to finish 1 bottle (oops again!) However if someone had asked me, I would have sworn I had drank the same amount of water on both days.

Without accurately measuring my water intake I would not be properly managing my hydration levels (as I am now, promise doctor!)

In future posts I will cover the need to be aware of possible unintended consequences of ‘what gets measures get managed’ but for now I am off to drink more water and maybe a nice cup of tea 😊

Best practice for analysing data

Over the last 10 years I have seen many principles for analytical best practice. The five that apply regardless of the data you are looking at are,

  1. Rubbish In – Rubbish Out
  2. What gets measured gets managed
  3. The trend is your friend
  4. So what……?
  5. Insight to Action

Over the next few posts I will go into each of these in more detail.