Evidence map›Paper›PMID 39001330›Full record

ReviewDiagnostics (Basel, Switzerland)2024

AI-Enhanced Dyscalculia Screening: A Survey of Methods and Applications for Children.

Shashi Bhushan, Sharmila Arunkumar, Taiseer Abdalla Elfadil Eisa, Maged Nasser, Anuj Kumar Singh, Pramod Kumar

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Shashi BhushanDepartment of Computer & Information Sciences, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia.ORCID 0000-0003-0667-9627
Sharmila ArunkumarRaj Kumar Goel Institute of Technology, Ghaziabad 201017, Uttar Pradesh, India.ORCID 0000-0002-9871-3871
Taiseer Abdalla Elfadil EisaDepartment of Information Systems-Girls Section, King Khalid University, Mahayil 62529, Saudi Arabia.
Maged NasserDepartment of Computer & Information Sciences, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia.
Anuj Kumar SinghSchool of Computing Science and Engineering, Galgotias University, Greater Noida 201310, Uttar Pradesh, India.ORCID 0000-0002-2357-7983
Pramod KumarHimalayan School of Science and Technology, Swami Rama Himalayan University, Dehradun 248016, Uttarakhand, India.

Funding

Universiti Teknologi PETRONAS RG2024-1968
6 · The paper itself

Abstract

New forms of interaction made possible by developments in special educational technologies can now help students with dyscalculia. Artificial intelligence (AI) has emerged as a promising tool in recent decades, particularly between 2001 and 2010, offering avenues to enhance the quality of education for individuals with dyscalculia. Therefore, the implementation of AI becomes crucial in addressing the needs of students with dyscalculia. Content analysis techniques were used to examine the literature covering the influence of AI on dyscalculia and its potential to assist instructors in promoting education for individuals with dyscalculia. The study sought to create a foundation for a more inclusive dyscalculia education in the future through in-depth studies. AI integration has had a big impact on educational institutions as well as people who struggle with dyscalculia. This paper highlights the importance of AI in improving the educational outcomes of students affected by dyscalculia.

Indexed as

AI (artificial intelligence)cognitive abilitiesdyscalculiadysgraphiadyslexiaearly interventionlearning disabilitiesmathematical comprehensionneurodevelopmental disordersspecific learning disabilities

Identifiers

PMID39001330
PMCPMC11241753

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.