Innovative Learning Assistance Through the Multiverse AI Educator Using Natural Language Processing

Objectives: To develop an AI-powered chatbot utilizing NLP techniques for personalized learning, efficient academic support, and seamless college navigation using English as the primary communication medium. Methods: The study employed BERTSUM and Pegasus for text summarization, with SVM and Random Forest for college website navigation. An automated email-based problem-reporting mechanism was implemented to address students’ concerns. Data simulation was conducted to evaluate the performance metrics of these algorithms. Findings: The Multiverse AI Educator enhanced learning by simplifying academic concepts through summarization models, achieving over 85% accuracy in delivering concise explanations. Navigation assistance efficiently directed users to college resources with an 88% success rate in locating relevant sections. The problem-reporting system streamlined communication with college authorities, reducing response times by 50%. These functionalities demonstrate the AI's capacity to foster interactive learning and improve accessibility in educational settings. The findings align with existing AI-driven educational tools while introducing novel integration of problem reporting. Novelty: Integration of NLP with AI-driven academic assistance and automated issue reporting in a single platform using supervised learning. Keywords: Artificial Intelligence, Machine Learning, ChatBot, BERTSUM, Pegasus, Wav2Vec, DeepSpeech, Natural Language Processing