Expanding support opportunities for learners with hidden needs

Educators have faced considerable pressure to rapidly adapt methods of teaching in recent years, especially to digitise delivery. Significant steps have also been made to make learning more flexible and personalised by educators dedicated to improving equity, diversity and inclusion (ED&I).

But almost one third of colleges still do not have an ED&I strategy in place, and only 17 percent have one ‘in development’ (AoC, 2021).

We need to accelerate the adoption of ED&I in further education; not only to make it more accessible and inclusive for minority groups, such as those with a disability, but to recognise those who may have hidden learning needs.

Undisclosed shouldn’t mean unsupported

Of the 1.5 million adult learners (19 years old and above) participating in further education/skills in the first three quarters of the 2021/22 academic year, those declaring a learning difficulty and/or disability (LDD) accounted for 17.3 percent (UK Government data, Jan 2022).

But part of the challenge is that many learners do not disclose their LDD or are not even aware that they have one. Cognassist data shows that around 30 percent of learners who complete our digital cognitive assessment are in need of additional support.

This gap means that many learners won’t have an Education, Health and Care Plan (EHCP) in place, making it harder for them to access the support they need to complete their course or apprenticeship programme.

And retention rate is something that the apprenticeship sector in particular is struggling with. Astoundingly, almost half of all apprentices dropped out last year (UK Government data, Jan 2022).

So, there is a distinct need for robust quality assurance measures at every stage of the learner or apprentice journey. As Alex Burghart, MP and former Parliamentary Under Secretary of State for Skills put it in his letter on apprenticeship quality:

“Apprenticeships need to be set up well from the start, with apprentices clear on what to expect and what training and assessment they will get based on a quality initial assessment of their needs, and there are things we can do at each stage of the apprentice journey to support continuation and achievement.”

No learner left behind

Education and apprenticeship providers are now recognising the need for a method to identify individuals with hidden learning needs.

According to Mencap’s Accessible Apprenticeships Report, 96 percent of apprenticeship employers and providers agree that people with LDDs should qualify for adjusted minimum standards based on a cognitive assessment, rather than only relying on EHCPs.

This way, providers can account for learners with both disclosed and undisclosed LDDs.

As part of its LDD quality assurance self assessment framework, Mesma encourages all further education and apprenticeship providers to engage with the five pillars for end-to-end quality learning support.

In addition to mental health screeners and needs assessments, digital cognitive assessments are an integral part of the first pillar: Identify.

Together with comprehensive neurodiversity reports, digital cognitive assessments define an accurate starting point for every learner’s journey. Any needs identified can be discussed with the learner and appropriate reasonable adjustments agreed upon.

Not only this, but from the very beginning everyone has the opportunity to understand their unique cognition and how they process information most effectively.

This approach can be game changing for learners.

It can mean the difference between making it to end-point assessment or dropping out.

A new age of EdTech

Learner dropout represents one of the greatest challenges facing the further education and apprenticeship sectors. So, what if we could predict when someone is more likely to drop out, before it happens?

Cognassist’s initial study with independent training provider, Realise, showed that learning difficulties, identified in a cognitive assessment, were significant risk factors for learners dropping out.

We’re now able to use machine learning to identify correlations in cognitive profiles and learner dropout, offering bespoke predictive modelling around learner dropout within our clients’ cohorts. Ultimately, giving providers the opportunity to proactively support the individual and address the barriers that might have led them to leave their programme early.

This pilot research has been replicated with 851 learners at Multiverse with strong predictive outcomes. We are currently working with academic partners at Newcastle University to expand this research and create intensive support plans and early interventions that will aim to take an evidence-based approach to preventing dropout.

To learn more about this research and for insights into how to build a more neuro-inclusive, quality-focused learner experience, register for our webinar on 4^th October 2022 at 11.30am with the Association of Colleges:

“Best practice tips to support LDD learners from day one and build a more inclusive, quality-focused learner journey”

Register now