Using Destination Data to Widen Opportunities for Young People

Destination data is any information that is collected on students’ destinations after they leave secondary school. This may include institutions they later go on to attend, what courses and subjects they go on to study, and their subsequent future employer.

Schools, local authorities, or other bodies may collect information through self-reporting by students, follow-up surveys, or by linking together administrative data on the same individuals at different points in time.

The data is used to understand the opportunities that a school has offered its past students so that changes can be made to improve opportunities for future students.

The North East Local Enterprise Partnership (LEP)

The North East Local Enterprise Partnership [1] is a private, public and education sector partnership. They are supported by a small executive team that provides collaborative leadership to champion the growth and development of the North East economy.

Skill and careers education: The North East LEP work with the 176 secondary schools in the region, securing destination data to ensure that:

• Individuals, regardless of age or employment status have an understanding of the employment opportunities available in the North East and the pathways to access them.

• Employers have strong links with education and training providers leading to responsive provision that meets local needs.

• All partners understand the importance of skills in improving productivity and living standards, with a commitment to delivering good working environments for residents.

Opportunity North East (ONE Vision)

The ONE Vision Delivery Plan [2] is a £24 million, Department for Education funded project to improve educational outcomes across the North East. It is managed by the North East LEP.

It involves the use and interpretation of school data to inform interventions from the school level up to local authority level; widening opportunities for young people by informing the priorities of the North East LEP for their skills and careers education provisions.

The North East LEP was tasked by the Department for Education to identify the key challenges that exist across the region. They found five:

Challenge 1: Too few children continue to make good progress from primary to secondary

Challenge 2: A need to unlock the potential of key secondary schools in the North East

Challenge 3: Some schools struggle to recruit, retain and develop great teachers

Challenge 4: Too few young people find a pathway to a good career

Challenge 5: Too few young people progress to higher education, particularly into top tier universities

Challenge 4 became a particular focus of the project. The North East is the region with the lowest percentage of young people in sustained education, employment or training after Key Stages 4 and 5.

Using Destination Data

To help young people in the area find career pathways, the North East LEP knew that they had to use destination data to paint a picture of what was going wrong.

However, the existing destination data was not robust enough. There were time lags in the data, as well as a lack of validity and comparability of interim data sets. The data sets were not valid due to the gaps in the student profiles. Destinations profiles could not be compared against each other to identify trends, as some students had not been tracked as thoroughly as others.

They needed a solution, to develop a mechanism for live data collection that can be applied to an academic improvement cycle that improves career prospects for future students.

How the New Model Works

The ONE Vision plan runs as follows:

The assessment information is inputted by careers advisors and school staff. The data is collected through interviews, tutor time and sessions with young people who have previously left school.

In the project pilot, there were 840 young people involved over 2 years.  The analysis is conducted through a termly cycle of interventions repeating the process of interviews, data collection, and student-level interventions.

Students are tracked starting from Year 10, through to their GCSE’s and are assessed into their sustained destinations.

The new data model has shown a 60% increase in quality destination data including knowledge on:

Future career plans among SEND students have increased by 90%, showing that the new model has been highly effective at signposting options to young people.

Year 10 students are now starting to form a vision of the sector they might want to work in, 94% of students at this age now have sector aspirations.

Most importantly, 95% of students on the programme now have a post-16 plan.

Collaborative Approach

The model gathered data on the sectors that students were most interested in pursuing careers in after they had left formal education. The team were then able to present this data to industry and talk to them about how they could better encourage students to take an interest.

Careers in clean energy and logistics are particularly under-desired by students. The North East LEP prioritise clean energy in the region and they are planning to create up to 10,000 jobs in the sector as part of their strategic economic plan. Yet, there is very little interest in this sector among the future workforce as seen above.

Despite this concern, it is useful for the North East LEP to have this knowledge so they can devise ways to incentivise and inspire young people to take up an interest in specific career destinations that are underrepresented.

Key Takeaways

Overall, quality destinations data can motivate both students and employers to develop plans that set young people up on robust career paths and prepare them for the future.

The North East LEP has demonstrated how to transform a rusty destinations data model, into one that has proven successful in improving students future outcomes. The key factors for success that are shown in their work and can be applied to any destinations data model are:

• A collaborative investment into the model from students, teachers, career advisors and external employers to ensure no gaps in the student’s destinations profile

• Implementing a standardised schedule of analysis. For example, termly checks on the progress and efficiency of the model

• Maintaining a strong relationship with industry as part of the data model. This bridges the gap between the student’s career aspirations and sector-specific opportunities.

[1] The North East Local Enterprise Partnership

[2] Opportunity North East Delivery Plan 2019-2022