AI Driven Technological Drift in Interactive Learning

Abstract

AI and ML technology are changing how people learn in both education and professional growth. Our approach integrates AI-driven study schedules, resume tracking, student performance analysis, and discussion facilitation to create an inclusive atmosphere. Students are able to maximize their learning experiences with the AI-Integrated Study Plan module, which customizes study programs based on user data analysis.. The Resume Tracker module, in a similar vein, uses machine learning algorithms to process resumes and connect candidates with jobs, thus streamlining the application process. Personalized support is provided via the Student Performance Analysis module, which predicts performance trends using machine learning techniques. By using AI-powered content recommendation and intelligent moderation, the Discussion Forum module also promotes collaborative learning. Through providing tailored assistance, encouraging involvement, and enabling ongoing growth, our project aims to revolutionize education and equip learners for success in the modern, fast-paced world. Our goal is to provide students with the tools and resources they need to succeed in a world that is becoming more competitive and dynamic, enabling them to reach their full potential and make valuable contributions to society.

Authors and Affiliations

K Gopala Reddy, J Vishala SubbaLakshmi, P Phani Sivani, S Kiran Kumar

Keywords

Related Articles

The Role of Forces in Engineering Applications: Friction, Gravity, and Tension-A Review

The role of forces in engineering applications: friction, gravity, and tension. Friction, gravity, and tension are forces commonly used in engineering. It is important to be able to identify each type of force acting on...

Federated – Ensemble Learning (FEL) Techniques on Healthcare Data Privacy: A Review

In the realm of healthcare, protecting patient privacy by harnessing extensive medical data for enhanced clinical outcomes presents a significant challenge. Federated learning (FL) offers a promising solution by enabling...

Benefits and Difficulties of Student-Generative Artificial Intelligence Collaboration in Programming Learning: An Empirical Case Study

Conversational generative artificial intelligence Gen AI is sometimes viewed as a two-edged sword that could result in learning that is only superficial. We created and implemented a programming course that emphasizes st...

A study on Modular Construction for Industrial Buildings

Modular Construction is a type of pre-engineered, prefabricated construction that primarily uses fabrication of lightweight steel sections and plates to create modular units in a workshop, which are then transported to t...

A New Encrypted Secret Message Embedding in Audio by using LSB Based Stenography with AES

This work explores the use of steganography to embed textual information into audio files. The proposed method encodes text by mapping its binary representation into the least significant bits (LSBs) of the audio data. D...

Download PDF file
  • EP ID EP747891
  • DOI https://doi.org/10.46501/IJMTST1009012
  • Views 41
  • Downloads 0

How To Cite

K Gopala Reddy, J Vishala SubbaLakshmi, P Phani Sivani, S Kiran Kumar (2024). AI Driven Technological Drift in Interactive Learning. International Journal for Modern Trends in Science and Technology, 10(9), -. https://europub.co.uk./articles/-A-747891