Academic progress in learners with profound intellectual disabilities: analysis of a Routes for Learning dataset

Martin, P, Thorpe, P, Ware, J, Goldbart, J ORCID: https://orcid.org/0000-0003-1290-7833, Denovan, A, Dagnall, N ORCID: https://orcid.org/0000-0003-0657-7604 and Bradshaw, J (2025) Academic progress in learners with profound intellectual disabilities: analysis of a Routes for Learning dataset. European Journal of Special Needs Education. pp. 1-18. ISSN 0885-6257

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Abstract

Routes for Learning (RfL) is a Welsh-English assessment tool designed to provide formative and summative assessment for learners with Profound and Multiple Learning Disabilities (PMLD). The assessment uses a ‘Routemap’ consisting of 43 approximately developmentally ordered ‘boxes’ (assessable competencies, such as contingency awareness) with no assumption of linear progress.) This study uses data from RfL to examine learners’ trajectories and progress over time. The data came from a special school which had assessed learners annually over 13 years. Routemap boxes were ordered by averaging over individual learner trajectories and comparing this with the partial ordering of boxes implicit in the Routemap. Distributions of the number of boxes gained by a single learner in a year were derived. The probability of a learner gaining at least one box in a year was calculated. Analysis of the order in which individual learners achieved Routemap Boxes was largely consistent with the partial ordering of the Routemap. Progress was demonstrated across all age groups, in almost all learners. RfL can demonstrate both progress and regression. The value of longitudinal electronically recorded data is highlighted. The time taken to achieve boxes and sequence followed shows some variation among learners, supporting the appropriateness of the non-linear model of progress adopted by RfL.