People with Autism Spectrum Disorder experience difficulties with reading comprehension and information processing, which affect their school performance, employability and social inclusion. The main goal of this work is to investigate new ways to evaluate and improve text and web accessibility for adults with autism. The first stage of this research involved using eye-tracking technology and comprehension testing to collect data from a group of participants with autism and a control group of participants without autism. This series of studies resulted in the development of the ASD corpus, which is the first multimodal corpus of text and gaze data obtained from participants with and without autism. We modelled text complexity and sentence complexity using sets of features matched to the reading difficulties people with autism experience. For document-level classification we trained a readability classifier on a generic corpus with known readability levels (easy, medium and difficult) and then used the ASD corpus to evaluate with unseen user-assessed data. For sentence-level classification, we used for the first time gaze data and comprehension testing to define a gold standard of easy and difficult sentences, which we then used as training and evaluation sets for sentence-level classification. The results showed that both classifiers outperformed other measures of complexity and were more accurate predictors of the comprehension of people with autism. We conducted a series of experiments evaluating easy-to-read documents for people with cognitive disabilities. Easy-to-read documents are written in an accessible way, following specific writing guidelines and containing both text and images. We focused mainly on the image component of these documents, a topic which has been significantly under-studied compared to the text component; we were also motivated by the fact that people with autism are very strong visual thinkers and that therefore image insertion could be a way to use their strengths in visual thinking to compensate for their difficulties in reading. We investigated the effects images in text have on attention, comprehension, memorisation and user preferences in people with autism (all of these phenomena were investigated both objectively and subjectively). The results of these experiments were synthesised in a set of guidelines for improving text accessibility for people with autism. Finally, we evaluated the accessibility of web pages with different levels of visual complexity. We provide evidence of existing barriers to finding relevant information on web pages that people with autism face and we explore their subjective experiences with searching the web through survey questions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:704339 |
| Date | January 2016 |
| Creators | Yaneva, Victoria |
| Publisher | University of Wolverhampton |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2436/620390 |
Page generated in 0.0019 seconds