E-Learning Recommender System for Deaf and Hard of Hearing Learners

Title

E-Learning Recommender System for Deaf and Hard of Hearing Learners

Creator

Poly, Anisha; Nizar Banu, P.K.

Description

People with disabilities, including deaf and hard of hearing (DHH), face numerous resources online and need support to choose the right learning materials according to their preferences in communication and learning style. Content recommendation engines may help the DHH learners by suggesting the best possible matching resources to find out the suitable learning materials according to the preferences of learners. Content recommenders that use tag-based clustering techniques reduce the search space by filtering learning objects that match users search keywords at the first level and then present the learning objects with the specified accessibility preferences in terms of communication and learning style in the next level. This chapter presents a detailed study focusing on the tag-based content recommender systems in the e-Learning domain that support learners with sensory impairment, especially DHH learners. 2025 selection and editorial matter, Urmila Shrawankar and Prerna Mishra; individual chapters, the contributors.

Source

Cloud Computing for Smart Education and Collaborative Learning;pp.247-261

Date

01-01-2025

Publisher

CRC Press

Coverage

Poly A., Department of Computer Science, CHRIST (Deemed to be University), Hosur Road, Bengaluru, India; Nizar Banu P.K., Department of Computer Science, CHRIST (Deemed to be University), Hosur Road, Bengaluru, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 978-104031812-6; 978-103274115-4;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1201/9781003472537-22

https://www.scopus.com/pages/publications/105001459797?origin=resultslist