AI-Driven Personalized Learning Systems for Gen Alpha and Beta: Opportunities and Challenges
This research paper explores the potential of AI-driven personalized learning systems for Generation Alpha (born 2010-2024) and Generation Beta (born 2025 onwards). As these digital natives enter educational institutions, there is a growing need for innovative learning approaches that cater to their unique characteristics and expectations. This study examines the opportunities and challenges associated with implementing AI-powered personalized learning systems for these generations. Through a comprehensive literature review and analysis of existing AI-driven educational technologies, we identify key factors that influence the effectiveness of personalized learning for Gen Alpha and Beta. The research also presents a conceptual framework for designing and implementing AI-driven personalized learning systems tailored to these generations’ needs. Our findings highlight the potential benefits of such systems, including improved engagement, enhanced learning outcomes, and the development of crucial 21st-century skills. However, we also discuss challenges such as data privacy concerns, the digital divide, and the need for continuous adaptation of AI algorithms. The paper concludes with recommendations for educators, policymakers, and technology developers to harness the full potential of AI-driven personalized learning for Gen Alpha and Beta while addressing associated challenges.
Authors
- Dharma Raj Ojha
Institutions
- Far-western University (NP)
Publication Details
- Journal
- American Journal of Innovation in Science and Engineering
- Published
- 2025-04-21
- DOI
- https://doi.org/10.54536/ajise.v4i2.4644
- Citations
- 1
- Primary Topic
- Biomedical and Engineering Education
- Type
- article
- Field-Weighted Citation Impact
- 0.67