This page was updated in October 2018 to reflect progress made in developing this strand of work.
Higher Education Learning Gain Analysis (HELGA) is a strand of the learning gain programme which investigates the potential for using existing data on the student experience to identify what it tells us about learning gain. This seeks to explore whether administrative data can provide a low burden approach to a proxy measure for learning gain.
About the strand
Our work is exploring two statistical modelling techniques:
- The first methodology can account for observable characteristics such as gender and ethnicity.
- The second methodology seeks to account for unobservable characteristics such as a students’ preference for a particular region.
The models use data from the start of a student’s higher education journey and compare it with data collected at the end of their undergraduate experience.
Development of this work
The Learning Gain Expert Group is made up of specialists in the area of measurement of educational progress who contribute to the development of this work. The Group advises on various aspects of both methodologies, including discussing the most appropriate outcome measures, data sources and technical aspects of the modelling techniques.
We are continuing to work with our Learning Gain Expert Group to test and validate both methodologies. Our initial findings of this strand of activity will be presented alongside outputs from the learning gain pilot projects and National Mixed Methodology Learning Gain project (NMMLGP) in spring 2019 to inform the next stage of the learning gain programme.