A Survey on E-learning Recommendation Systems for Autistic People.

Vijayalaxmi N. Rathod, R.H.Goudar, Anjanabhargavi Kulkarni, G. M. Dhananjaya, Geetabai S. Hukkeri

Research output: Contribution to journalArticlepeer-review

Abstract

Autism, also known as Autism Spectrum Disorder (ASD) or Asperger's syndrome, has an impact on cognition, social relationships, and behavior. Based on these characteristics and their learning interests, e-learning (Electronic Learning) recommendation systems attempt to provide personalized recommendations. This may enhance the learning ability of individuals with ASD. However, some technological challenges limit the ability of the population to use support scenarios and prevent efficient learning. This study tries to review e-learning recommender systems for individuals with ASD. The main identified aspects are 1) lack of design principles while building customized e-learning platforms for those with ASD; 2) technological limitations to developing recommender systems for e-learning, and 3) suggestions that reduce field limitations. The studies additionally discovered that social communication and psychological abilities had the greatest focus of study. A small number of studies mentioned the participant's ASD level, the majority of the articles highlighted the beneficial effects of designing a content-based recommender system specifically for those with ASD.

Original languageEnglish
Pages (from-to)11723-11732
Number of pages10
JournalIEEE Access
Volume12
DOIs
Publication statusPublished - 2024

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Materials Science
  • General Engineering

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