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Cited by 270Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive LearningAutism Spectrum Disorder Research

The DOI matches its Crossref record; 97 of the 98 references it cites were found in a registry or an index, and 1 are not checked yet.

Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders—A Review

Open access
Barua, Prabal Datta, Vicnesh, Jahmunah, Gururajan, Raj, Oh, Shu Lih, Palmer, Elizabeth, Azizan, Muhammad Mokhzaini, Kadri, Nahrizul Adib, Acharya, U. Rajendra·2022·International Journal of Environmental Research and Public Health
DOI 10.3390/ijerph19031192PMC PMC8835076
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Abstract

Mental disorders (MDs) with onset in childhood or adolescence include neurodevelopmental disorders (NDDs) (intellectual disability and specific learning disabilities, such as dyslexia, attention deficit disorder (ADHD), and autism spectrum disorders (ASD)), as well as a broad range of mental health disorders (MHDs), including anxiety, depressive, stress-related and psychotic disorders. There is a high co-morbidity of NDDs and MHDs. Globally, there have been dramatic increases in the diagnosis of childhood-onset mental disorders, with a 2- to 3-fold rise in prevalence for several MHDs in the US over the past 20 years. Depending on the type of MD, children often grapple with social and communication deficits and difficulties adapting to changes in their environment, which can impact their ability to learn effectively. To improve outcomes for children, it is important to provide timely and effective interventions. This review summarises the range and effectiveness of AI-assisted tools, developed using machine learning models, which have been applied to address learning challenges in students with a range of NDDs. Our review summarises the evidence that AI tools can be successfully used to improve social interaction and supportive education. Based on the limitations of existing AI tools, we provide recommendations for the development of future AI tools with a focus on providing personalised learning for individuals with NDDs.

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Crossref · 10.3390/ijerph19031192

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Figure 1 (a) Normal brain and (b) ADHD brain with smaller volume.
Figure 1 (a) Normal brain and (b) ADHD brain with smaller volume.CC BY · PubMed Central
Figure 2 (a) Large neural adaptation in normal brain and (b) reduced neural adaptation in dyslexic brain.
Figure 2 (a) Large neural adaptation in normal brain and (b) reduced neural adaptation in dyslexic brain.CC BY · PubMed Central
Figure 3 (a) Neurotypical brain and (b) ASD brain with denser neural connections.
Figure 3 (a) Neurotypical brain and (b) ASD brain with denser neural connections.CC BY · PubMed Central
Figure 4 Sequence of steps for training a machine learning model.
Figure 4 Sequence of steps for training a machine learning model.CC BY · PubMed Central
Figure 5 Illustration of the CNN model.
Figure 5 Illustration of the CNN model.CC BY · PubMed Central
Figure 6 Illustration of the LSTM model.
Figure 6 Illustration of the LSTM model.CC BY · PubMed Central
Figure 7 Illustration of the Autoencoder model.
Figure 7 Illustration of the Autoencoder model.CC BY · PubMed Central
Figure 8 Flowchart detailing the use of PRISMA guidelines for selection of relevant articles.
Figure 8 Flowchart detailing the use of PRISMA guidelines for selection of relevant articles.CC BY · PubMed Central
Figure 9 Pie chart representation of assistive tools used to aid in the learning of ADHD, dyslexia and ASD students.
Figure 9 Pie chart representation of assistive tools used to aid in the learning of ADHD, dyslexia and ASD students.CC BY · PubMed Central
Figure 10 Bar graph representation of various assistive tools used to aid in the learning of ADHD, dyslexia and ASD students.
Figure 10 Bar graph representation of various assistive tools used to aid in the learning of ADHD, dyslexia and ASD students.CC BY · PubMed Central
Figure 11 Benefits of using the cloud system in schools for personalised education.
Figure 11 Benefits of using the cloud system in schools for personalised education.CC BY · PubMed Central
Figure 12 Proposed AI-based tool for personalised learning.
Figure 12 Proposed AI-based tool for personalised learning.CC BY · PubMed Central

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Cites

Research works printed but not linked: 6

  1. (2012). Dyslexia. Encyclopedia of Human Behavior, Academic Press. [2nd ed.].
  2. Sharif, H., and Khan, R.A. (2019). A novel framework for automatic detection of Autism: A study on Corpus Callosum and Intracranial Brain Volume. arXiv.
  3. Shukla, 2020, A Comprehensive Study of Audio Visual Aids for Dyslexic Children, IJEET, 11, 211
  4. Rouhi, A., Spitale, M., Catania, F., Cosentino, G., Gelsomini, M., and Garzotto, F. (2019, January 16–20). Emotify: Emotional game for children with autism spectrum disorder based-on machine learning. Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion, Marina del Ray, CA, USA.
  5. Smith, S.W., Bourgeois, D.T., James, L., and Mortati, J. (2021, February 25). The Ethical and Legal Implications of Information Systems; 2021. Available online: https://bus206.pressbooks.com/chapter/chapter-12-the-ethical-and-legal-implications-of-information-systems/.
  6. 2015, The Internet of Things. A New Companion to Digit, Humanit, 2012, 42

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Metadata

Authors
Barua, P. D., Vicnesh, J., Gururajan, R., Oh, S. L., Palmer, E., Azizan, M. M., Kadri, N. A., & Acharya, U. R.
Affiliations
  • University of Technology Sydney (AU)
  • Ngee Ann Polytechnic (SG)
  • University of Southern Queensland (AU)
  • UNSW Sydney (AU)
  • Universiti Sains Islam Malaysia (MY)
  • University of Malaya (MY)
  • Asia University (TW)
Corresponding author
Azizan, Muhammad Mokhzaini
ORCID
Venue
International Journal of Environmental Research and Public Health
Publisher
MDPI AG
Published
2022-01-21
Volume
19
Issue
3
Pages
1192
ISSN
1660-4601 (ISSN-L)
DOI
10.3390/ijerph19031192
PMC
PMC8835076
OpenAlex
W4205370021
Cited by
270
References
97
Citations by year
2026: 70 · 2025: 106 · 2024: 63 · 2023: 23 · 2022: 8
FWCI
6.31
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Environmental Research and Public Health (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
Keywords
artificial intelligence, assistive technology, neurodevelopmental disorders, children with disabilities, personalized learning, autism spectrum disorder, dyslexia, attention deficit hyperactivity disorder, intellectual disability, mental illness, learning difficulties, social interaction, machine learning, educational intervention
MeSH terms
Autism Spectrum Disorder, Adolescent, Anxiety Disorders, Artificial Intelligence, Attention Deficit Disorder with Hyperactivity, Child, Humans, Neurodevelopmental Disorders

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