AI and machine learning for adaptive elearning platforms in cybersecurity training for entrepreneurs
This paper explores the application of Artificial Intelligence (AI) and Machine Learning (ML) in adaptive eLearning platforms designed for cybersecurity training, with a focus on entrepreneurs. Due to limited resources and technical expertise, entrepreneurs face unique challenges in protecting their businesses from cyber threats. Traditional training methods often fail to meet their needs, highlighting the importance of AI-driven platforms that offer personalized learning experiences. The paper examines the benefits of AI-powered eLearning systems, including improved engagement, real-time assessments, and adaptation to diverse learning styles. It also addresses emerging trends in AI and ML for cybersecurity education, the integration of adaptive eLearning into entrepreneurial support systems, and the ethical and regulatory implications of AI-driven learning. Finally, recommendations are provided for policymakers and educators to support the growth of AI in cybersecurity training. The findings suggest that AI-powered platforms can offer scalable, effective solutions for entrepreneurs to enhance their cybersecurity skills and protect their digital assets. Keywords: Artificial Intelligence, Machine Learning, Cybersecurity Training, Adaptive eLearning, Entrepreneurs, Personalized Learning.
Authors
- Nurudeen Yemi Hussain
- Adeoye Idowu Afolabi
- Christian Chukwuemeka Ike
- Blessing Austin-Gabriel
Institutions
- Montclair State University (US)
- Lagos State Health Service Commission (NG)
- Texas Southern University (US)
Publication Details
- Journal
- Computer Science & IT Research Journal
- Published
- 2024-12-29
- DOI
- https://doi.org/10.51594/csitrj.v5i12.1787
- Primary Topic
- Impact of AI and Big Data on Business and Society
- Type
- article
- Field-Weighted Citation Impact
- 0.00