Using the Fine Grade tool in Connect

Using the Fine Grade tool in Connect

This article and video show you how to get the best out of using fine grades as in year monitoring point uploads. Note that you have to switch the fine grade option on in Connect Data and add the specific notation that you use for each of stretch, secure and at risk. 



If you have added fine grades data to a monitoring point in Connect, these will automatically show in your subject value added pages in the student tab as shown below.



Subject staff will be able to perform the usual ‘What If’ analysis to these fine grades – so for example, how do I move my Chemistry department in this school from an Alps grade 5 to a grade 3?

Click and drag/drop the left hand box on the thermometer to a grade 3. The pop up tells me that I require 30 students on average to improve by 1 grade to reach my aspirational Alps grade.



We would turn on the ‘What If’ toggle to model which students I might work with to improve their grades and the resultant impact on my Alps grade. 
Fine Grades gives you more flexibility - what you might now do is to look at your fine grades in the ‘What If’ column on the right hand side of the page and target those students who are in the ‘Stretch’ group. In this example – the students who are on a + fine grade.

In the example below, we have targeted the + fine grades and ‘stretched’ the students to the grade above. If we ‘stretch’ 30 or more + grades, then we have reached our aspirational subject target.



You can see that you could model the opposite – in other words, now many ‘at risk’ grades would cause the Alps grade to drop if these students were to just miss the grade. The ‘What If’ tool can be used to model worse case scenarios too. These ‘at risk’ students would then be key for a different type of intervention by subject staff.

 



Combining the fine grade scenarios

Navigate to the Fine Grades tab. 

Clicking on the tab brings you to a modelling tool which allows you to use sliders to identify what might happen to your Alps Subject Grade if a given percentage of students are ‘stretched’ to a higher grade, or if a given percentage of ‘at risk’ students drop to the grade below.


In this example, we have modelled several cumulative scenarios.

  • The original overall grade for the subject is Alps 5. This is shown in the box on the left hand side of the thermometer.
  • Based on previous experience with predictions in this department, I might judge that realistically they can ‘stretch’ 30% of students in this category to the higher grade. Note that my slider now reads 30% for this group.
  • Again, in the past the department have also been able to ‘Secure’ a certain percentage of students in the middle category, therefore we slide the thermometer to 20% likely to go up.
  • Unfortunately, 10% of all students in the ‘At risk’ group have dropped to the lower grade in previous years, and so reluctantly we slide this bottom thermometer to 10%. This indicates that these students will not achieve that grade.

The cumulative effect of these changes means that the department are perhaps more likely to achieve an Alps grade 4 as shown by the right hand box on the thermometer.

 



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