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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | A Comprehensive Survey on Artificial Intelligence Based Knowledge Generation |
| Authors Name: | Althaf M , Arafan Khan P , Sharath A , Rohan Reji Abraham , Alpha Mathew |
| Download E-Certificate: | Download |
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IJRTI_200312
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| Published Paper Id: | IJRTI2502044 |
| Published In: | Volume 10 Issue 2, February-2025 |
| DOI: | |
| Abstract: | This survey explores the role of AI-driven content generation in e-learning, emphasizing its integration, trends, challenges, and future prospects. The study categorizes machine learning approaches, including traditional methods, deep learning, and hybrid models, and evaluates their application in enhancing personalized learning, adaptive assessments, and dynamic content delivery. Unlike conventional e-learning systems that rely on uniform content, AI-powered platforms offer tailored experiences by adapting to individual learners’ strengths, weaknesses, and preferences. This capability improves engagement and outcomes, especially in large-scale online education. Trends such as AI-assisted curriculum development and realtime feedback systems demonstrate the growing adoption of AI in education. However, challenges such as scalability, data quality, and ethical considerations remain significant. Key concerns include biases in AI models, data privacy risks, and the adaptability of AI systems to diverse educational contexts. The study identifies areas requiring further research, particularly in addressing ethical issues, ensuring equitable access, and optimizing AI’s scalability. Despite these challenges, AI-driven systems present transformative potential for automating curriculum design, generating personalized content, and delivering targeted feedback. By leveraging these advancements, e-learning can become more accessible, efficient, and inclusive. This work underscores the need for continued innovation and collaboration in integrating AI into education, ensuring the development of secure, learner-centered systems. Ultimately, this survey highlights AI’s promise to reshape e-learning by addressing existing gaps and enhancing personalized educational experiences globally. |
| Keywords: | AI-driven content generation, e-learning, personalized learning, adaptive assessments, curriculum development, real-time feedback, ethical considerations, data privacy, learner-centered systems, gamification |
| Cite Article: | "A Comprehensive Survey on Artificial Intelligence Based Knowledge Generation", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 2, page no.a414-a418, February-2025, Available :http://www.ijrti.org/papers/IJRTI2502044.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2502044
Registration ID:200312
Published In: Volume 10 Issue 2, February-2025
DOI (Digital Object Identifier):
Page No: a414-a418 Country: Kottayam, Kerala, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2502044 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2502044 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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