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.

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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
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article

AI and machine learning for adaptive elearning platforms in cybersecurity training for entrepreneurs

Nurudeen Yemi Hussain, Adeoye Idowu Afolabi, Christian Chukwuemeka Ike, Blessing Austin-Gabriel
Computer Science & IT Research Journal
Impact of AI and Big Data on Business and Society
article

AI and machine learning for adaptive elearning platforms in cybersecurity training for entrepreneurs

Nurudeen Yemi Hussain, Adeoye Idowu Afolabi, Christian Chukwuemeka Ike, Blessing Austin-Gabriel
article en

Abstract

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.

Computer Science & IT Research JournalVol. 5(12)
Montclair State University (US), Lagos State Health Service Commission (NG), Texas Southern University (US)
Decent work and economic growth
Openalex Percentile: Top 70%
Impact of AI and Big Data on Business and Society
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AI and machine learning for adaptive elearning platforms in cybersecurity training for entrepreneurs — Nurudeen Yemi Hussain, Adeoye Idowu Afolabi, et al. · Computer Science & IT Research Journal (2024) | TGRS Research Map | TGRS