The HEAT Service has engaged the influential Behavioural Insights Team (BIT) to conduct research on the impact of Campus Visits on the propensity for the most disadvantaged outreach participants recorded on the HEAT database to enrol in Higher Education.
The HEAT Research Group and the HEAT Steering Group have approved a proposal by BIT to further explore this perceived link using causal tree analysis. The origin of this commission is a desire to triangulate the initial findings of the HEAT Service Analysis Team that seem to show that attendance at a Campus Visit increases the propensity of the most disadvantaged participants recorded on the HEAT database to enrol in Higher Education.
We recognise that the definition of ‘Campus Visit’ may be subject to variation across our membership and, as such, we will be asking each HEAT Lead to complete a review of their post-Aimhigher activities to help us identify correctly what should be included. Each HEAT Lead will be sent a file of their activities and will be asked to review that file against a set of questions. The HEAT Service Team will review for inclusion all the historic Aimhigher activities that HEAT holds. We aim to place your data on the File Store by the 12th January 2018. HEAT Leads will receive an email with instructions on how to access their institution’s file and how to return it to the central team. We ask Leads to complete the checking by Friday 26th January 2018.
BIT proposes the use of a causal tree analysis model to look at our data, dissecting it into a logical, tree-structured hierarchy to identify which actions or conditions (causal factors) were necessary and sufficient for a given consequence to occur. In this instance, actions may be (for example) attendance at more than one Campus Visit and conditions may be (for example) that an outreach participant lives in a POLAR quintile 1 or 2 postcode. We are testing the theory that attendance at a Campus Visit is necessary and sufficient for us to expect an increased likelihood of HE enrolment for our most disadvantaged cohort.
An advantage of this type of analysis is that, by its very nature, a causal tree considers actions and conditions both independently and in conjunction with each other. A by-product of this analysis will be a further exploration of how we define ‘disadvantage’. We have asked BIT to include each of the attainment and societal disadvantage factors that HEAT uses in the methodology of its ‘HEAT Groups’, thereby affording us the opportunity to finalise their combination and construction.
Please use the following link for a clear and more detailed explanation of causal tree analysis.