Artificial Intelligence and M-Learning in Arabic Countries: Innovations, Trends, and Regional Perspectives
This study addresses the significant knowledge gap in understanding the regional dynamics of artificial intelligence (AI) in education within the Arabic countries. It applied a bibliometric analysis of research published on the Scopus database from 2003 to 2024 to map publication trends, collaborative structure, and emerging research themes. The findings indicate that there has been a significant increase in research output since 2018, with a notable shift from general eLearning applications to specialized AI applications, specifically in mobile learning (M-learning) environments. These applications enhance adaptive, personalized, and resilient educational practices. Key findings include the anticipation of ChatGPT’s prominence in 2024 as a research focus, strong cross-country collaborations, especially with Saudi Arabia, and a growing interest in AI applications in higher education. Additionally, the study highlights the research advancements in AI ethics, natural language processing (NLP) in education, and AI-powered M-learning platforms. The study applied Bradford’s and Lotka’s laws to uncover patterns in journal distribution and author productivity, indicating a concentration of research among a core set of journals and authors. However, challenges remain, including the need for increased international collaboration and addressing ethical considerations in AI implementation. The in-depth study provides useful information for researchers, teachers, and policymakers, focusing on how AI can change M-Learning and the need for culturally aware and morally sound methods for incorporating AI into Arabic school systems.
Authors
- Talal Alasmari (ORCID: https://orcid.org/0000-0002-3330-1980)
Institutions
- University of Jeddah (SA)
Publication Details
- Journal
- International Journal of Interactive Mobile Technologies (iJIM)
- Published
- 2025-03-13
- DOI
- https://doi.org/10.3991/ijim.v19i05.52735
- Citations
- 6
- Primary Topic
- Organizational and Employee Performance
- Type
- article
- Field-Weighted Citation Impact
- 14.89