International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
www.irjet.net
AI based Learning System 1Rahul Bansode, 2Pratik Jige, 3Pranav Sali, 4Pradnya Yelkar
B.E. Students Department of Computer Engineering G. V. Acharya Institute of Engineering and Technology, Shelu, Dist-Raigad, Maharashtra, India-410201 ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - This paper presents the E learning Application by
learning and accommodating diverse learner needs. However, the integration of AI in e-learning also raises important considerations around privacy, security, and ethical use of data. As such, it is imperative to implement robust safeguards to protect learner confidentiality and uphold ethical standards in the design and deployment of AI technologies in education. In essence, the marriage of AI and e-learning holds immense promise for revolutionizing education, offering a pathway to more personalized, interactive, and accessible learning experiences.
which users can self-learn the new topics and Languages and grow their knowledge in their fields. Our e-learning system harnesses the power of artificial intelligence (AI) to revolutionize the educational landscape. By integrating AI technologies, our platform offers personalized learning experiences tailored to the unique needs of individual learners. Through sophisticated algorithms, the system analyzes learner behaviors, preferences, and performance data to deliver adaptive content recommendations and assessments. This dynamic approach not only enhances engagement but also optimizes knowledge retention and skill acquisition. Our system fosters interactive learning environments through AIdriven features such as virtual tutors, chatbots, and intelligent feedback mechanisms. These tools facilitate real-time support and guidance, empowering learners to navigate complex concepts and overcome challenges autonomously.
Key Words:
E-learning, Artificial intelligence (AI), Personalized learning, Adaptive content, Intelligent tutoring systems, Natural language processing (NLP).
1.INTRODUCTION In recent years, the convergence of Artificial Intelligence (AI) and e-learning has sparked a remarkable transformation in how we approach education. This fusion of cutting-edge technology and pedagogy promises to reshape traditional learning models, offering a dynamic and personalized educational experience tailored to the needs of individual learners.AI-powered e-learning systems represent a departure from one-size-fits-all approaches, instead harnessing the power of algorithms and data analytics to understand and adapt to each learner's unique profile. By analyzing patterns in learner behavior, preferences, and performance, these systems can intelligently tailor content delivery, assessments, and support mechanisms in real-time. The AI lies not only in its ability to personalize learning but also in its capacity to create engaging and interactive learning environments.
Fig- 1 E learning application Interface
2. LITERATURE SURVEY Our survey covers the integration of Artificial Intelligence (AI) in e-learning platforms, emphasizing personalized learning. We explore how AI techniques like machine learning and natural language processing are used to tailor content, assessments, and support for individual learners. Additionally, we discuss advancements in adaptive learning systems, intelligent tutoring, recommender systems, and deep learning applications in online education. Ethical considerations regarding data privacy and algorithmic transparency are also addressed. This survey aims to provide insights into the current landscape and future directions of AI-driven e-learning.
Virtual tutors, chatbots, and other AI-driven tools leverage natural language processing to provide personalized guidance and support, fostering a sense of collaboration and community in the digital realm. Accessibility is a cornerstone of AI-driven e-learning systems, ensuring that education is inclusive and equitable for all learners. Whether through adaptive content formats, technologies, or personalized feedback, these systems prioritize breaking down barriers to
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