Revolutionizing e-Learning: Harnessing the Power of Artificial Neural Networks for Personalized Education and Beyond

Artificial Neural Networks (ANNs) have emerged as a transformative technology in e-learning, revolutionizing how educational content is delivered and learners are supported. ANNs, inspired by the human brain, enable machines to learn from data, recognize patterns, and make predictions. In e-learning, ANNs find various applications such as personalized learning, intelligent tutoring, content recommendation, natural language processing, automatic grading, and predictive analytics. By analyzing learner data, ANNs can adapt instructional content, provide real-time guidance, recommend relevant resources, process natural language input, automate grading, and identify at-risk learners. Locating the best-customized learning resources online might be challenging for users and learners. By providing suggestions to users and learners based on their preferences and doing all of this with less time and effort, artificial neural networks significantly impact users’ ability to personalize their learning interests from a huge variety of resources. This study explores the value of employing neural networks in customized e-learning and demonstrates some of its existing uses, along with their advantages and drawbacks.