Transforming learning through artificial intelligence: Evolution of guided learning systems

Rishi Venkat 1, *, Darshana Suresh 2, Anu Rai 3, Shubham Metha 4 and Dyuti Dave 5

1 Principal Product Manager, Walmart Inc.
2 Independent researcher, Bentonville.
3 Technical Product Manager, Digital Products.
4 Software Engineer II, Enterprise Application, Northwest Bank.
5 Technology Analyst, Consumer banking, Barclays.
 
Review
International Journal of Science and Research Archive, 2024, 13(02), 4334-4340.
Article DOI: 10.30574/ijsra.2024.13.2.2045
Publication history: 
Received 15 September 2024; revised on 12 November 2024; accepted on 16 November 2024
 
Abstract: 
Artificial intelligence powered learning systems are transforming the learning landscape by using advanced algorithms and comprehensive data to deliver a highly personalized and adaptive learning experience. These systems analyze learner behavior, preferences, and outcomes at the macro and micro levels. This allows them to provide tailored content recommendations. adaptive assessment and tailored learning paths. Adaptive systems are those that are able to continuously learn from user interactions and feedback. An AI-powered recommendation system can dynamically adjust recommendations. This ensures that learners receive the most relevant and effective learning resources at all times. These advanced AI models can create personalized content, place interactive learning materials and even simulate a human-led teaching and learning experience. For example, chatbots and AI-powered virtual assistants can engage learners in understanding learner preferences, deciphering learning styles, answering questions and providing real-time feedback. effectively simulating a human teacher. In addition, generative AI can personalize, summarize and modify existing content to customize it based on individual learning capabilities, patterns, preferences, and achievement levels. ensuring that each learner receives a truly customized learning experience as AI continues to evolve.
 
Keywords: 
Artificial Intelligence (AI); Recommended Learning Systems; Personalization; Creative AI; Data-Driven Insights; Adaptive Algorithms; Content creation
 
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0