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AI-Driven Personalized Learning and Interview Preparation

Manjula G1Bharath Rajashekar2Tanush Reddy K3Kusuma H4Shankar S5

¹Professor &HOD, Computer Science and Design, Dayananda Sagar Academy of Technology & Management Bengaluru, Karnataka, India. ²,³,⁴,⁵Student, ⁴th Year, B.E Computer Science and Design Dayananda Sagar Academy of Technology & Management Bengaluru, Karnataka, India

Published Online: March-April 2025

Pages: 90-98

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Abstract

The deployment of Artificial Intelligence (AI) in education and training has revolutionized individualized learning and practice interviews. The following paper investigates the ways recent innovations in AI are improving user engagement, responsiveness, and performance. Based on fifteen landmark studies from 2022 to 2024, we present the emerging role of AI-based systems. These adaptive learning systems, smart feedback mechanisms, learning chat bots, and AI-based interview simulators, all play their parts. Current mock interview systems have undergone considerable development. Rather than dry question-and-answer interfaces, they provide interactive experiences. Leveraging technologies such as natural language processing (NLP), machine learning (ML), and computer vision, these platforms test candidates in real time. They analyze emotional indicators, speech patterns, body positioning, and confidence levels. Users get rich, customized feedback that closely resembles actual interview environments. Concurrently, AI-powered learning systems are growing more adaptive. They modify content in response to performance and learning styles of individual students, resulting in improved outcomes and learner engagement.

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