Characterizing visual eye tracking differences in students with and without disabilities: An assessment for predicting prescriptive visual accommodative technologies
dc.contributor.author | Thomas, Sharon | |
dc.contributor.author | Freitas, Rui | |
dc.contributor.author | Chan, Anders | |
dc.contributor.author | Colmone, Sabrina | |
dc.contributor.author | Bailey, Stephanie, P. | |
dc.contributor.author | Ramdhari, Ravi, L. | |
dc.contributor.author | McCabe, Katherine | |
dc.contributor.author | Albanese, Nicole | |
dc.contributor.author | Singh, Harnoor | |
dc.date.accessioned | 2018-05-02T18:33:11Z | |
dc.date.accessioned | 2023-06-08T19:28:51Z | |
dc.date.available | 2018-05-02T18:33:11Z | |
dc.date.available | 2023-06-08T19:28:51Z | |
dc.date.issued | 2018-04 | |
dc.identifier.uri | https://soar.suny.edu/handle/1951/70146 | |
dc.description | Continuation of last years study "Validating Visual Eye Tracking Technology to Assess Accommodative Technology for Students with Disabilities in Undergraduate Education" | en_US |
dc.description.abstract | The National Center for Education Statistics (NCES) 2011-2012, reported that 11% of undergraduate students are identified as having a disability. Nearly, 38% of students with disabilities are enrolled in 2-year institutions as compared to 9.8% at 4-year institutions. Students with disabilities require support services some of which are accommodative technologies. However, scant data exist on whether or not such technologies are sensitive to accommodating individual needs, that is tailored to support people with a specific or having multiple disabilities. There are five main categories describing students with disabilities: 1) learning disabilities (LD), 2) emotional/psychiatric conditions (EPC), 3) orthopedic/mobility impairments (EMI), 4) attention deficit/hyperactivity disorders (AD/HD) and 5) health impairments (HI). However, most national data lacks the inclusion of students with multiple disabilities (MD), which while being the most frequent category is by far the most underserved. The aim of the current project was to determine whether assessing student's visual attentional processing abilities (i.e., eye gaze) through a 10-minute Flanker Task could be used as a predictive and prescriptive diagnostic tool to screen students with disabilities that would benefit most from visual accommodative technologies. The research protocol employed a triple blind procedure. The results indicated that visual eye gaze technology is sensitive in detecting individuals with differing disabilities and therefore can be used to further characterize visual trial-by-trial learning differences to simple visual stimuli in populations with LD, EPC, EMI, AD/HD, HI, and MD. Thus, through such evidence based study a “true” prescriptive accommodative technology “match-to-sample” can be provided to students with disabilities to further support their undergraduate education based upon their unique individual needs (SUNY-OW Faculty Development Grant). | en_US |
dc.description.sponsorship | Lilian Park; Stacey DeFelice; Runi Mekherji; Lorenz S. Neuwirth | en_US |
dc.language.iso | en_US | en_US |
dc.rights | Attribution 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
dc.subject | eye gaze | en_US |
dc.subject | visual eye tracking | en_US |
dc.subject | disabilities | en_US |
dc.subject | disability accommodations | en_US |
dc.subject | accommodative technologies | en_US |
dc.title | Characterizing visual eye tracking differences in students with and without disabilities: An assessment for predicting prescriptive visual accommodative technologies | en_US |
dc.type | Learning Object | en_US |
dc.type | Presentation | en_US |
refterms.dateFOA | 2023-06-08T19:28:51Z |
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SUNY Old Westbury Undergraduate Research
Select student presentations from the annual SUNY Undergraduate Research Conference (SURC) and other sponsored undergraduate work.