{"title":"Framework for Intervention and Assistance in University Students with Dyslexia","authors":"C. Mejía, R. Fabregat","doi":"10.1109/ICALT.2012.170","DOIUrl":null,"url":null,"abstract":"This paper presents a framework for providing personalized and adapted support to university students with dyslexia in a learning management system (LMS). The components of the framework include tools for: detecting reading difficulties and preferences in the students, assessing cognitive processes involved in their reading, and delivering intervention and assistance tasks according to specific cognitive deficits. This framework is designed considering multimodal interaction mechanisms by means of using different communicative channels (visual, auditory and speech). Additionally, its architecture is formed mainly by: 1) a student model including individual reading profiles, learning styles and cognitive traits, 2) an adaptation engine based on the delivery of learning analytics and adapted recommendations, and 3) tracking tools to measure the performance and satisfaction of users. The framework is proposed to be integrated into a LMS and, to this end, the architecture is supported in web services.","PeriodicalId":268199,"journal":{"name":"International Conference on Advanced Learning Technologies","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Advanced Learning Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALT.2012.170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This paper presents a framework for providing personalized and adapted support to university students with dyslexia in a learning management system (LMS). The components of the framework include tools for: detecting reading difficulties and preferences in the students, assessing cognitive processes involved in their reading, and delivering intervention and assistance tasks according to specific cognitive deficits. This framework is designed considering multimodal interaction mechanisms by means of using different communicative channels (visual, auditory and speech). Additionally, its architecture is formed mainly by: 1) a student model including individual reading profiles, learning styles and cognitive traits, 2) an adaptation engine based on the delivery of learning analytics and adapted recommendations, and 3) tracking tools to measure the performance and satisfaction of users. The framework is proposed to be integrated into a LMS and, to this end, the architecture is supported in web services.