A Differentiated Learning Environment in Domain Model for Learning Disabled Learners

Autor/inn/en	Thapliyal, Monika; Ahuja, Neelu Jyothi; Shankar, Achyut; Cheng, Xiaochun; Kumar, Manoj
Titel	A Differentiated Learning Environment in Domain Model for Learning Disabled Learners
Quelle	In: Journal of Computing in Higher Education, 34 (2022) 1, S.60-82 (23 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Ahuja, Neelu Jyothi) ORCID (Cheng, Xiaochun) ORCID (Kumar, Manoj)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1042-1726
DOI	10.1007/s12528-021-09278-y
Schlagwörter	Individualized Instruction; Intelligent Tutoring Systems; Students with Disabilities; Learning Disabilities; Children; Models; Learning Strategies; Case Method (Teaching Technique); Game Based Learning; Educational Environment; Special Needs Students; Student Centered Learning + Suchen Sie Ihr Suchwort? Individualisierender Unterricht; Intelligentes Tutorsystem; Student; Students; Disability; Disabilities; Schüler; Schülerin; Studentin; Behinderung; Learning handicap; Lernbehinderung; Child; Kind; Kinder; Analogiemodell; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Case method; Fallmethode; Lernumgebung; Pädagogische Umwelt; Schulumwelt; Sonderpädagogischer Förderbedarf; Group work; Student-entered learning; Student-centred learning; Student centred learning; Schülerorientierter Unterricht; Schülerzentrierter Unterricht; Gruppenarbeit
Abstract	This paper presents the ontological design and implementation of the differentiated learning environment in the domain model of an intelligent tutoring system for children with specific learning disabilities. It addresses the learners need for differentiated instruction in a preferential learning environment. The proposed model helps to identify the most affected learning domains and related multiple-criteria's which effects the learners. The learning resources and problems diagnosis questionnaires are organized and used with various learning strategies to create various learning environments such as case-based learning environment, game-based learning environment, practice-based learning environment and visual-based learning environment. Different techniques can define a set of rules to decide the most preferred learning environment. Here, multiple criteria decision analysis approach map the information, learning resources and learning environments to create a differentiated learning environment for the learning disabled. The contribution of proposed model is to reduce the gap between learner and learning habits with special needs. Our model is implemented as domain model of an intelligent tutoring system to develop learner-centric learning environment. In the designed intelligent tutoring system (ITS), the differentiated learning environment domain model is further evaluated and validated by a set of fuzzy rules. The pilot test result shows that proposed model enables an ITS to improve the implementation of appropriate learning strategies with high accuracy and sensitivity for both learning and non-learning-disabled users. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01