Reality of Using Artificial Intelligence Applications in Diagnosing Gifted from the Viewpoints of Workers in the Field and Development Proposals

Mohammad, A S, Zhran, Ayman Ramdan, Abdelrhman, Rasha Mohamed, Almalek, Mahra Hamyer and Abo Elnour, Mostafa Mohamed Reality of Using Artificial Intelligence Applications in Diagnosing Gifted from the Viewpoints of Workers in the Field and Development Proposals. Scandinavian Journal of Information Systems, 35 (1).

[thumbnail of 234] Text
234 - Published Version

Download (22kB)

Abstract

The study sought to identify the reality of using artificial intelligence applications to diagnose gifted students, and provide proposals of diagnosis for a sample of (143) workers in the field of special education in the light of artificial intelligence applications, counting on the descriptive analytical approach. Moreover, two questionnaires were constructed for the purposes of the study after verifying their validity and reliability. The findings indicated that the reality of using artificial intelligence applications to diagnose gifted students has miscellaneous problems and needs to be developed based on artificial intelligence applications. The average sample responses to proposals to develop the diagnosis of gifted students in the light of artificial intelligence applications were high. In addition, the findings did not show any statistically significant differences related to each of the work field or work nature.

Affiliation: Skyline University College
SUC Author(s): Mohammad, A S
All Author(s): Mohammad, A S, Zhran, Ayman Ramdan, Abdelrhman, Rasha Mohamed, Almalek, Mahra Hamyer and Abo Elnour, Mostafa Mohamed
Item Type: Article
Uncontrolled Keywords: Artificial Intelligence, Diagnosis of Special Needs, Workers in Special Education
Subjects: A Business and Management > AB Business and Management
B Information Technology > BA Information Systems
B Information Technology > BM Artificial Intelligence
Divisions: Skyline University College > School of IT
Depositing User: Mr Mosys Team
Date Deposited: 25 Dec 2023 14:15
Last Modified: 25 Dec 2023 14:15
URI: https://research.skylineuniversity.ac.ae/id/eprint/683
Publisher URL: http://sjisscandinavian-iris.com/index.php/sjis/ar...
Publisher OA policy:
Related URLs:

    Actions (login required)

    View Item
    View Item
    Statistics for SkyRep ePrint 683 Statistics for this ePrint Item