The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Demystifying the Dynamic Determinants of Generative Artificial Intelligence (AI) Literacy for Adaptable Sustainable Education: Multistage Structure Equation Remodeling
|
|
Author(s): Manish Dadhich (Sir Padampat Singhania University, India & Lincoln University College, Malaysia), Amiya Bhaumik (Lincoln University College, Malaysia), Kamal Kant Hiran (Sir Padampat Singhania University, India & Lincoln University College, Malaysia)and Midhun Chakkaravarthy (Lincoln University College, Malaysia)
Copyright: 2024
Pages: 14
Source title:
Integrating Generative AI in Education to Achieve Sustainable Development Goals
Source Author(s)/Editor(s): Ruchi Doshi (Universidad Azteca, Mexico), Manish Dadhich (Sir Padampat Singhania University, India), Sandeep Poddar (Lincoln University College, Malaysia)and Kamal Kant Hiran (Sir Padampat Singhania University, India & Lincoln University College, Malaysia)
DOI: 10.4018/979-8-3693-2440-0.ch004
Purchase
|
Abstract
This research aims to demystify the dynamic determinants of generative artificial intelligence (AI) literacy for adaptable sustainable education (ASE) through the application of multistage structural equation modeling (SEM). Utilizing a quantitative approach, a structured questionnaire distributed via Google Forms is employed to gather data from a convenient sample of 260 teachers in higher education. The study unfolds over a specified period, incorporating rigorous data filtering techniques to enhance the reliability of responses. Smart-PLS serves as the primary tool for data analysis, allowing for an in-depth exploration of relationships among variables such as generative AI literacy, digital split, computational intelligence, and cognitive inclusion. Dependent variables include teacher perceptions, technological proficiency, and cognitive inclusion, while independent variables encompass awareness of AI and the perceived usefulness of AI in achieving ASE. The outcomes of this research carry significant policy implications for AI, ICT, and educational professionals, providing insights to shape informed strategies for integrating AI literacy into higher education to meet the goals of adaptable sustainable education.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|