Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging Evidence
Reading is a complex skill that requires accurate word recognition, fluent decoding, and effective comprehension. Children with dyslexia often face challenges in these areas, resulting in ongoing reading difficulties. This study systematically reviews the use of eye-tracking technology to assess dys...
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MDPI AG
2024-11-01
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| Series: | Education Sciences |
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| author | Eugenia I. Toki |
| author_facet | Eugenia I. Toki |
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| description | Reading is a complex skill that requires accurate word recognition, fluent decoding, and effective comprehension. Children with dyslexia often face challenges in these areas, resulting in ongoing reading difficulties. This study systematically reviews the use of eye-tracking technology to assess dyslexia, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The review identifies the specific types of eye-tracking technologies used, examines the cognitive and behavioral abilities assessed (such as reading fluency and attention), and evaluates the primary purposes of these evaluations—screening, assessment, and diagnosis. This study explores key questions, including how eye-tracking outcomes guide intervention strategies and influence educational practices, and assesses the practicality and time efficiency of these evaluations in real-world settings. Furthermore, it considers whether eye-tracking provides a holistic developmental profile or a targeted analysis of specific skills and evaluates the generalizability of eye-tracking results across diverse populations. Gaps in the literature are highlighted, with recommendations proposed to improve eye-tracking’s precision and applicability for early dyslexia intervention. The findings underscore the potential of eye-tracking to enhance diagnostic accuracy through metrics such as fixation counts, saccadic patterns, and processing speed, key indicators that distinguish dyslexic from typical reading behaviors. Additionally, studies show that integrating machine learning with eye-tracking data can enhance classification accuracy, suggesting promising applications for scalable, early dyslexia screening in educational settings. This review provides new insights into the value of eye-tracking technology in identifying dyslexia, emphasizing the need for further research to refine these methods and support their adoption in classrooms and clinics. |
| format | Article |
| id | doaj-art-b114bc31ff8f4e68ae1714997dab4070 |
| institution | OA Journals |
| issn | 2227-7102 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Education Sciences |
| spelling | doaj-art-b114bc31ff8f4e68ae1714997dab40702025-08-20T01:53:45ZengMDPI AGEducation Sciences2227-71022024-11-011411125610.3390/educsci14111256Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging EvidenceEugenia I. Toki0Department of Speech and Language Therapy, University of Ioannina, 45500 Ioannina, GreeceReading is a complex skill that requires accurate word recognition, fluent decoding, and effective comprehension. Children with dyslexia often face challenges in these areas, resulting in ongoing reading difficulties. This study systematically reviews the use of eye-tracking technology to assess dyslexia, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The review identifies the specific types of eye-tracking technologies used, examines the cognitive and behavioral abilities assessed (such as reading fluency and attention), and evaluates the primary purposes of these evaluations—screening, assessment, and diagnosis. This study explores key questions, including how eye-tracking outcomes guide intervention strategies and influence educational practices, and assesses the practicality and time efficiency of these evaluations in real-world settings. Furthermore, it considers whether eye-tracking provides a holistic developmental profile or a targeted analysis of specific skills and evaluates the generalizability of eye-tracking results across diverse populations. Gaps in the literature are highlighted, with recommendations proposed to improve eye-tracking’s precision and applicability for early dyslexia intervention. The findings underscore the potential of eye-tracking to enhance diagnostic accuracy through metrics such as fixation counts, saccadic patterns, and processing speed, key indicators that distinguish dyslexic from typical reading behaviors. Additionally, studies show that integrating machine learning with eye-tracking data can enhance classification accuracy, suggesting promising applications for scalable, early dyslexia screening in educational settings. This review provides new insights into the value of eye-tracking technology in identifying dyslexia, emphasizing the need for further research to refine these methods and support their adoption in classrooms and clinics.https://www.mdpi.com/2227-7102/14/11/1256dyslexiaeye-tracking technologyreading skillsdecodingreading comprehensionvisual processing |
| spellingShingle | Eugenia I. Toki Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging Evidence Education Sciences dyslexia eye-tracking technology reading skills decoding reading comprehension visual processing |
| title | Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging Evidence |
| title_full | Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging Evidence |
| title_fullStr | Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging Evidence |
| title_full_unstemmed | Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging Evidence |
| title_short | Using Eye-Tracking to Assess Dyslexia: A Systematic Review of Emerging Evidence |
| title_sort | using eye tracking to assess dyslexia a systematic review of emerging evidence |
| topic | dyslexia eye-tracking technology reading skills decoding reading comprehension visual processing |
| url | https://www.mdpi.com/2227-7102/14/11/1256 |
| work_keys_str_mv | AT eugeniaitoki usingeyetrackingtoassessdyslexiaasystematicreviewofemergingevidence |