Today, as part of my recently acquired role developing Research and Development within the Oxfordshire Teaching Schools Alliance I attended an event on Closing the Gap and how to set up RCTs. Inevitably, given my professional background, my thoughts wandered on to how this would work within a Special School setting and in particular how we would achieve a large enough cohort size to create statistically relevant results. One of the models that was discussed was a ‘honeycomb’ framework of partnership, within which multiple settings delivered the intervention and from which the results were collated. This threw up some interesting discussions around variability and how this can be managed. However, whilst in principle this would be an effective way of increasing cohort sizes for Special school based studies, my concern is that there are significant additional variables in Special schools which may affect the data and therefore the conclusions.
The reason for this is that the structural and operational variance within Special schools seems to me to be greater than in mainstream settings. Part of the reason for this is the freedoms we are allowed in interpreting the curriculum to ensure its accessibility for our students, but also because there is no agreed, or indeed well evidenced, way of structuring Special schools and the provision they offer. The school’s broader philosophy, or sometimes just that of the Head, can often determine the core operational and organisational characteristics of the school in a wide variety of ways. So how would we increase the number of research participants in the ‘honeycomb’ manner, without introducing a multiplicity of variables that could render the comparability of the data meaningless?
What occurred to me, and I have had this thought previously, was that there may be value in setting up a national database of research focused Special schools. Within this you could capture the characteristics of the provision, operational and organisational structures and demographic information in order to find statistically and philosophically comparable schools across the country. Therefore when you were looking for participant schools to build viable cohorts you could begin to isolate certain variables which may affect the outcomes in ways unintended by the study. You could of course also search for areas of research experience or interest allowing schools to better identify those who may be of value approaching.
The following is a list of some of the variables which may be worth considering:
How pupils are grouped – e.g. Age, clinical diagnosis, combinations of multiple grouping approaches
Age range of the pupils
Designation of the school and in turn primary designation of the pupils attending
Number on role
Distribution of pupils by Gender, FSM, LAC, EAL, Ethnicity
Socio-economic characteristics of the school
Residential or Day provision
Way in which subjects are taught – Specialist / Generalist
Location of the school e.g. Unit in a mainstream school, Co-located, stand alone Special School
Now I am sure I have missed some, so let me know what else should be considered and then all we need to do is find a way of building and hosting the database.