Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/5286
Title: DEVELOPING AN AI-ASSISTED MULTILINGUAL ADAPTIVE LEARNING SYSTEM FOR PERSONALIZED ENGLISH LANGUAGE TEACHING
Authors: Lawrance, Joy Christy
Sambath, Priya
Shiny, Crispine
Vazhangal, Mubashira
Prema, S
Bala B, Kiran
Issue Date: 15-Mar-2024
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: This research focuses on the design and development of an innovative AI -assisted multilingual adaptive learning system tailored for personalized English language instruction. The proposed system leverages artificial intelligence algorithms to provide a dynamic and personalized learning experience that caters to individual proficiency levels, learning styles, and linguistic backgrounds. The system incorporates advanced Natural Language Processing (NLP) techniques to analyze and understand the unique challenges faced by learners from different linguistic backgrounds. By harnessing the power of machine learning, the system adapts its instructional content, pace, and exercises to suit the specific needs of each learner. The AI component facilitates real-time feedback, allowing learners to receive targeted guidance on pronunciation, grammar, and vocabulary usage. The multilingual aspect is achieved through the integration of translation services and language-specific adaptations within the learning modules. The system employs data-driven insights to track learner progress, identify areas of improvement, and continuously refine the personalized learning experience. Through the integration of adaptive learning technologies, the system evolves with each user interaction, enhancing its effectiveness over time. The proposed NLP method outshines its counterparts in terms of flexibility, scoring impressively at 98.12%, signifying its superior adaptability to diverse tasks and data structures.
URI: https://ieeexplore.ieee.org/document/10716887
ISBN: 979-835038436-9
Appears in Collections:4. Conference Paper (12)



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.