We’re working on ways to improve the apprentice experience by capturing and analysing the many kinds of data that can be collected through the apprenticeship journey.
This research is developing alongside our effective learning analytics project. At the core of the learning analytics service is the learning data hub (formerly called the learning records warehouse) where academic and engagement data is collected, stored and processed. We are planning extend the learning data hub to enable data to be gathered from all aspects of the apprenticeship journey. In a previous blog post we listed some of the possible sources that we can gather data from.
By analysing progress of apprenticeships will be able to make timely and appropriate interventions and enhance and improve the apprenticeship journey.
Apprenticeships is a growth area undergoing massive reform, with a government target of three million starts by 2020 and the implementation of the post-16 skills plan. This is a tenfold increase from the current level of 300,000 apprentices.
This increase means for many employers (as well as providers) that having timely and accurate information about their apprentices is critical and to ensure the successful outcome for those apprentices.
There are a range of requirements that employers will need some, are merely information about progress, other aspects will be based on the analysis of various data sets.
These requirements could include:
• Recruitment
• Induction
• Attendance
• Progress
• Topic coverage
• Optional modules choices
• Skills coverage
• Academic plan
• Timetabling
• Resources
• Assessment plan
• EPA Information
• Highlights report
• Risks
• Personal profiles
• Provider profiles
• Subject profiles
Similarly providers may have similar requirements and may wish to bring in data from employers and the apprentices themselves, to combine with their internal data sources.
• Attendance
• Progress
• Topic coverage
• Assessment plan
• Library Usage
• Retention
• Achievement
We can separate out the requirements, from those that are derived direct from the data and those that are dependent on some aspect of processing and analysis.
We also need to consider what data requirements we’re missing but we hope to discover as we start to gather data and feedback.