Availability and utilisation of assistive technologies for education of students with albinism in Federal University Oye Ekiti, Nigeria

Abstract

Purpose This study investigates the extent of availability and utilisation of assistive technologies at Federal University Oye-Ekiti (FUOYE), focusing on students with albinism. Design/methodology/approach The study uses a cross-sectional survey and a quantitative approach. The study includes a diverse population size, comprising 100 students with albinism, 20 lecturers, 20 maintenance staff and ten management staff, totalling 150 staff. A sample of 109 staff was selected using a proportionate sampling technique. The Availability Assistive Technologies Checklist (AATC) and Availability and Utilisation of Assistive Technologies (AUAT) served as instruments. Mean and standard deviation were used to analyse research questions and a t-test was used to analyse hypotheses that guided the study. Findings The analysis highlights that assistive technologies like screen readers, magnification software and speech recognition software are accessible and frequently used, enhancing the educational experience for students with disabilities. However, there are significant gaps in the availability of critical tools such as Braille displays and tactile graphics. The t-test analysis reveals no significant difference between lecturers’ and students’ perceptions of technology utilisation, suggesting a shared awareness of the current state of assistive technologies. Research limitations/implications The study’s limitations include reliance on self-reported data, limited sample size and rapid technological advancements. Future research should adopt mixed-method approaches, expand sample sizes and consider external factors for a detailed understanding of assistive technology utilisation in higher education. Originality/value The study concerning the availability and utilisation of assistive technologies for including students with albinism at Federal University Oye-Ekiti is the first of its kind. It needs to be replicated with mixed methods with an increased sample size.