An Intelligent Assistive System for Autistic Learners

An Intelligent Assistive System for Autistic Learners | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Engineering Reports This is a preprint and has not been peer reviewed. Data may be preliminary. 9 April 2025 V1 Latest version Share on An Intelligent Assistive System for Autistic Learners Authors : Sadia Afrin 0009-0004-6624-5171 [email protected] , Afrin Ahmed , Mehrin Anannya , Samrat Dey , Md. Moshiur Rahman , and Rashed Mazumder Authors Info & Affiliations https://doi.org/10.22541/au.174417331.12382902/v1 Published Engineering Reports Version of record Peer review timeline 328 views 130 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This study presents the design and implementation of an innovative educational assistive system tailored for individuals with Autism Spectrum Disorder (ASD), leveraging eye-tracking technology and machine learning algorithms. The objective is to enhance communication and learning experiences through ocular gaze and fixation-based keyboard selection. Data were collected from 15 children with ASD, generating 320 scanpath images that captured fixation duration and gaze direction during left-right and up-down navigation tasks. Using fixation values and Area of Interest (AOI) analysis, a novel keyboard selection method was developed, distinct from traditional digital keyboards. The proposed system was evaluated using an optimized ensemble model, achieving an accuracy of 83.44%, significantly surpassing baseline models. The results demonstrate improved communication efficiency and usability, validating the system’s ability to facilitate hands-free keyboard control. This assistive system fosters better interaction with parents, teachers, and caregivers, promoting social engagement and enhancing the quality of life for individuals with ASD. Overall, this research underscores the transformative potential of integrating eye-tracking and machine learning in educational tools, paving the way for innovative approaches to support neurodiverse learners. Supplementary Material File (blinded manuscript - copy.docx) Download 631.41 KB Information & Authors Information Version history V1 Version 1 09 April 2025 Peer review timeline Published Engineering Reports Version of Record 12 Nov 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Engineering Reports Keywords assistive technology autism eye-tracking smart board Authors Affiliations Sadia Afrin 0009-0004-6624-5171 [email protected] Jahangirnagar University View all articles by this author Afrin Ahmed Jahangirnagar University View all articles by this author Mehrin Anannya Jahangirnagar University View all articles by this author Samrat Dey Bangladesh Open University View all articles by this author Md. Moshiur Rahman Bangladesh Open University View all articles by this author Rashed Mazumder Jahangirnagar University View all articles by this author Metrics & Citations Metrics Article Usage 328 views 130 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Sadia Afrin, Afrin Ahmed, Mehrin Anannya, et al. An Intelligent Assistive System for Autistic Learners. Authorea . 09 April 2025. DOI: https://doi.org/10.22541/au.174417331.12382902/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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