Metrics, Data and Reporting

“Data is key to understand the challenge around the employability of WP students in your institution and how they are engaging with you.”

Data Definitions

Understanding the data definitions being used by your organisation and by government and other bodies to identify and define WP groups can be a challenge. This Toolkit contains a Social Mobility and Widening Participation Glossary of Terminology which is as current as we can make it and which we’ll try to keep updated. We hope this will help you and your teams, and maybe your institution to clarify which student groups are being referred to in data being generated and in planning services and conversations within your institution

What data is there?

Working out who does what with which datasets is another challenge. Just keep asking questions until you know what data is collected, who does what with it and why, and what reporting is available. You’ll also factor in the data on students and their activity that you generate through careers, placements, and employer engagement interactions amongst others. One aspect of successful management is how well you use the data you can get access to, to aid your decision-making and work out how your staff and other resources can be applied to optimise impact.

Getting access to data

Challenges and questions raised by Heads of service include:

  • Using the data – understanding and using data dashboards in PowerBI or Tableau
  • Access to analytical resource and ability
  • The APP and understanding OfS data and evaluation templates
  • Flagging WP students in Careers appointments and engagement systems – linking with university student data systems
  • Links to GO Survey data and LEO data

“We are doing more targeted work with final year students and recent graduates based on TEF, APP and Career Registration data.”

“Using data to understand how WP students are performing versus non-WP in graduate outcomes. Identifying data gaps and trends at programme level.”

“Although student data feeds through from our Student Records system, data on POLAR, Indices of Multiple Deprivation (IMD), care leaver and ethnicity isn’t yet available within our Careers system.”

This is a common issue. The ability to pull through WP data from student records systems into careers systems is generally very limited and therefore it can be almost impossible to report on levels of engagement with careers activity by WP indicator. Some careers teams are working with their central IT and Planning departments to merge data from different systems into data ‘dashboards’ which will enable this level of analysis, but some report that getting permission internally to access student data at this level of detail has been a long and difficult process.

“We are working on a project with the University Planning department to develop a live dashboard that will bring together these elements and make the data accessible to colleagues across the University.”

“At our university we are combining Careers Registration data with Careers Engagement and Placement Participation data into a data dashboard, and after a year of lobbying and endless committee papers, we have finally gained permission to combine this with WP student data to be able to review WP-specific data.”

“Analysed TEF data including priorities is shared with the careers team in an easy to digest format from the Planning team. We were able to use this data in department and team planning this year”

Using DLHE/Graduate Outcomes data

At this point (Sept 2019) there is a question about whether the Graduate Outcomes datasets at institutional level will include markers which will enable us to compare outcomes for WP and other students at the level of granularity we’ll need to be able to assess the impact of tailored or targeted initiatives.

“Using WP data to refocus activity and to understand the challenge around engagement from WP students mapped against DLHE outcomes. Will use this going forward with TEF statements.”

In a university with a relatively low proportion of WP students or students from certain groups it can even be difficult to determine significant gaps in attainment or outcomes even at cohort level, and in some small cohorts, very small number shifts can disproportionately skew data.