This research investigated factors influencing the approach of dyslexic higher education students to support in one UK higher education institution. While considering the nature of the population of dyslexic students as a whole, it also looked for potential sub-groups with a view to differentiating support needs and usage.
The research considered data for past dyslexic students of the institution, over nearly a decade, in the context of national data (HESA and UCAS) to establish the nature of the population being investigated. A range of measures were completed by current students of the institution, addressing: aspects of experiences of dyslexia; personality; learning mode preferences; and support use, including DSA Needs Assessment recommendations. These findings, in conjunction with WAIS intelligence test indices scores (where available from
dyslexia assessments), were statistically analysed where appropriate. The research concluded with interviews of selected participants.
The main findings included a trend of late identification of women. Evidence of the impact of dyslexia recognition and support during compulsory schooling was seen in subsequent support use and outcomes. How students attributed outcomes at school was important for self-concept and motivation, although this was not always related to recognition of dyslexia or support. The Perceptual Organisation Index of the WAIS-III test was central to grouping participant cases. Patterns were seen in use of higher education support, relating to age of identification as dyslexic, age when starting the course and
gender.
The implications include the way Learning Mode preference awareness has a role in developing self-awareness and meta-cognitive skill. Study environment requirements are an area of student needs that would benefit from further investigation. Feedback on Needs Assessment recommendations highlights the need for more training opportunities and better ways to introduce students to assistive technology before recommendations were made. Better understanding of support use patterns has implications for support resource
management