Managing Individual Learning Plans Across Large Cohorts

An Individual Learning Plan (ILP) — the record of the reasonable adjustments a disabled student needs, whatever a particular institution's paperwork calls it — is easy to manage well for a handful of students and genuinely hard to manage well for two hundred. The underlying legal duty does not scale with cohort size, but the staff time available to discharge it does not scale with cohort size either, and that mismatch is where most of the real difficulty in this area sits: not in whether adjustments are the right thing to do, but in what happens when a workload model was never built to absorb them.

In England, Scotland and Wales, the relevant duty sits in the Equality Act 2010 [1]. Universities, as providers of higher education, must not discriminate against disabled students and must make reasonable adjustments so that a disabled student is not placed at a substantial disadvantage compared with a non-disabled student. Statutory technical guidance from the Equality and Human Rights Commission spells out a detail that matters directly for cohort-scale planning: the duty is anticipatory [2]. An institution is not permitted to wait until an individual student discloses a need and only then start thinking about what to do — it is expected to have anticipated the kinds of adjustment likely to be needed and to have systems, formats and processes already in place. That single feature of the law is why "we'll sort it out case by case as requests come in" is not really a compliant workload strategy at any cohort size, let alone a large one: reactive, one-off accommodation is precisely the anticipatory duty's most common failure mode.

The duty has three limbs: changing a provision, criterion or practice that disadvantages a disabled student (an assessment format, a deadline, an attendance requirement); providing auxiliary aids or services (specialist software, a note-taker, extra time); and addressing physical features of premises. What counts as "reasonable" is assessed against factors including cost, practicability, and the resources available to the institution — which means, awkwardly, that the same adjustment can be reasonable at one institution and arguable at another, and that a large cohort strains "practicability" in ways a small one does not.

Public higher education providers also carry the Public Sector Equality Duty, which requires them to have due regard to eliminating discrimination and advancing equality of opportunity when making decisions — including, in practice, when designing the staffing and administrative processes that support ILPs, not only when responding to individual requests [1].

What Actually Strains at Scale

None of the difficulty is really about the law changing shape as a cohort grows — it is about specific administrative tasks that were designed around individual attention becoming, at volume, a distinct workload category of their own:

  • Per-student coordination. Each ILP typically has to be read and actioned separately by every member of teaching staff who encounters that student — different formats, different deadlines, different exam-room arrangements — and a two-hundred-student cohort can carry dozens of live plans that a lecturer must individually track alongside the rest of their teaching.
  • Consistency across multiple staff. Where several tutors, seminar leaders or markers interact with the same student, ensuring each of them applies the adjustment correctly and consistently is a coordination problem that grows faster than the student count, because it depends on the number of staff-student pairings, not the number of students alone.
  • Review and currency. Adjustments are not static — a plan agreed in year one may need revisiting as a course, an assessment method or a student's circumstances change — and reviewing plans at the same cadence for two hundred students as for twenty requires either more staff time or a different process, not just more effort from the same people.

The Office for Students' 2019 review of disability support across the English higher education sector found wide variation in how consistently this is actually delivered in practice, and flagged digital accessibility in particular — accessible documents, captioned lecture recordings, accessible virtual learning environment content — as an area where provision was frequently inconsistent even where an institution's formal adjustment process looked sound on paper [3]. That gap between the policy and the lived delivery is exactly where a large-cohort workload problem turns into a compliance problem: a reasonable adjustment that exists in a spreadsheet but is not consistently applied by every marker is not, in the sense the Act cares about, actually an adjustment that has been made.

Funding and Support Routes Worth Knowing

The Disabled Students' Allowance (DSA) is a non-repayable, non-means-tested UK government grant that funds specialist equipment, non-medical helper support (such as note-takers or study-skills tutors) and other disability-related study costs for eligible students, following a needs assessment [4]. It matters for the workload question specifically because DSA-funded support — a dedicated note-taker, assistive-technology training, specialist mentoring — moves some of the ongoing support burden away from module tutors and onto funded, individually-assigned specialists, which is one of the few genuine ways cohort-level teaching staff time is protected rather than simply absorbing more adjustment work as numbers rise. It is not a substitute for the institution's own reasonable-adjustment duty, which is unconditional and does not depend on a student having applied for or been awarded DSA.

Managing the Workload Question Honestly

Two things are true at once here, and treating either one as the whole picture misleads staff. First: research on academic workload allocation more broadly — not specific to ILPs, but directly relevant to how that work gets distributed — has found that workload models function better, and staff experience them as fairer, when academics are consulted on their design rather than having a model imposed on them, and when the model is transparent about what it counts [5]. An ILP-heavy module that never shows up as extra allocated hours anywhere in a workload model is a transparency failure, not a workload-management success. Second: workload modelling itself is a genuinely contested exercise — the data institutions report to funders and use internally for planning is widely acknowledged, including by people who run these models, to capture only a partial and sometimes distorted picture of what an adjustment-heavy teaching load actually involves [6]. Neither point offers a shortcut; together they point at the same practical conclusion: treating per-student adjustment coordination as recognised, allocated work — reviewed with the staff who do it, not assumed to be absorbed into "general teaching prep" — is the lever that actually exists, as distinct from a piece of software that makes the underlying workload disappear.

Coordinating administration is the other lever. Centralising who tracks which plan is active, who has been notified, and when a review is due — rather than expecting each individual tutor to independently track their own subset of a two-hundred-student cohort — turns an O(students × staff) coordination problem into something closer to O(students), which is the actual shape of the scaling difficulty described above.

  • Legal Framework in Computing — the wider pattern of statutory duties, including data protection, that apply to systems recording student support needs.

References

  1. Equality Act 2010. https://www.legislation.gov.uk/ukpga/2010/15/contents
  2. Equality and Human Rights Commission (2015). Equality Act 2010 Technical Guidance on Further and Higher Education. https://www.equalityhumanrights.com/sites/default/files/equalityact2010-technicalguidance-feandhe-2015.pdf
  3. Office for Students (2019). Beyond the Bare Minimum: Are Universities and Colleges Doing Enough for Disabled Students? https://www.officeforstudents.org.uk/publications/beyond-the-bare-minimum-are-universities-and-colleges-doing-enough-for-disabled-students/
  4. GOV.UK. Disabled Students' Allowance (DSA). https://www.gov.uk/disabled-students-allowance-dsa
  5. Kenny, J., & Fluck, A. E. (2022). Emerging principles for the allocation of academic work in universities. Higher Education, 83, 1–19. https://pmc.ncbi.nlm.nih.gov/articles/PMC8318840/
  6. Wonkhe (2022). "A beginner's guide to academic workload modelling." https://wonkhe.com/blogs/a-beginners-guide-to-academic-workload-modelling/