Moseley, M., Howat, L., McLoughlin, L., Gilling, S. and Lewis, D., 2021. Accessible digital assessments of temporal, spatial or movement concepts for profoundly motor impaired and non-verbal individuals: a pilot study. Disability and Rehabilitation: Assistive Technology, 16 (3), 350-360.
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DOI: 10.1080/17483107.2019.1683240
Abstract
Purpose: Here we present a study of two new Assistive Technology (AT) accessible digital assessments which were developed to address the current paucity of (English) spoken language comprehension assessments accessible to individuals who are both non-verbal and have profound motor impairments. Such individuals may rely heavily upon AT for communication and control. However, many assessments require that responses are given either verbally, by physical pointing or manipulating physical objects. A further problem with many assessments is their reliance upon static images to represent language components involving temporal, spatial or movement concepts. These new assessments aim to address some of these issues. Materials and methods: The assessments were used with 2 young people who are non-verbal and have profound motor impairments (GMFCS level IV/V) and who use eye gaze as their primary method of communication and access. One assessment uses static images and the other short video clips to represent concepts containing temporal, spatial or movement elements. The assessments were carried out with each participant, both before and after an intervention, as part of a larger study. Results: The assessments were accessible using AT (eye gaze) for both participants, although assessment scores varied. The design of the assessments particularly suited one participant who scored near maximum, but they appeared less suitable for the other participant. Conclusions: Making assessments AT accessible removes a barrier to assessing aspects of the spoken language comprehension abilities of some. Video may be a better medium for representing certain concepts within assessments compared with static images.
Item Type: | Article |
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ISSN: | 1748-3107 |
Group: | Faculty of Science & Technology |
ID Code: | 33022 |
Deposited By: | Symplectic RT2 |
Deposited On: | 11 Nov 2019 10:17 |
Last Modified: | 14 Mar 2022 14:18 |
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