These are the Education and Skills Funding Agency's measure of the quality of Education and Training courses or Apprenticeships delivered by training providers. QARs are monitored at an Overall and Timely level. Overall is used as the basis for minimum performance levels, whilst Timely monitors how well courses are delivered within the planned duration.
Based on the Overall QAR, these analyse the performance of qualifications by type and determines if the achievement rates meet the thresholds set by the ESFA. Where the sum of leavers for qualification types performing under these thresholds exceed the tolerance level providers fall within scope for intervention.
As the ESFA aims to develop and fair, inclusive and diverse environment in education, learner data is used to identify emerging themes and areas for improvement. Analysing your learner demographic data can help identify these trends but used in isolation may only tell you so much. Integrating local demographic data can help to set and monitor targets for improvement.
The Overall and Timely QARs are concerned with learners achieving in the respective cohort as a proportion of leavers. The Pass Rate looks at the conversion of learners completing aims to those that achieve the learning outcome whereas the Retention Rate looks at completed aim as a proportion of those aims that ended.
Managing and modeling your data effectively can drive business focus and activities. For example, when identifying qualification types that are below Minimum Standards, it is possible to model for the remaining cohort, where the end of year QAR may fall based on current run rates, what achievement rate is required to bring it above Minimum Standards or whether there is sufficient cohort left to do so.
Identifying areas for improvement as in the example above can help drive focus for remedial activities. Once you understand the "what" you also need to understand the "why". Using BI Tools to analyse data with techniques like slicing and dicing can highlight trends in your data which could help prevent these scenarios in the future. For example do some learner groups require additional support or materials.
At Aha Analytics we have a decade of expertise working with learning providers to develop and enhance monitoring of quality standards so that they have a clear understanding
of their current performance, can identify trends quickly and take appropriate action where necessary.
Not only does this help to drive performance but provides a basis for demonstrating the use of data to inform decision making in preparation for an OFSTED inspection.
This includes: