Creating an AI English Tutor With Personalized Content and Dynamic Lessons

Designing an AI English tutor entails using an elaborate approach of achieving an intelligent tutor that makes teaching and learning of the English language more effective. This project starts out with the development of clear goals and scope and knowing the subject clients for the right message to pass. Among this preliminary investigation, the educational tools already in use are first examined and the learning theories are incorporated into the design of the AI tutor. NLP and personalization algorithms are used in these models to make the content more dynamic and to also give real time feedback. Workshops feature lessons with content arranged in increasing order of complexity, elements of conversation practice and the use of games as well. For the sake of putting emphasis on the use, the interface is designed to be flexible and easy to use to provide learners with their use preferences and aims. Beta-testing, as well as usability-testing is done to ensure the refinement of the system for deployment. The AI tutor is then deployed on selected platforms with appropriate marketing to the target market. By doing so the AI English tutor can continue to remain optimally effective, interest and relevant to the learners’ needs inasmuch as the language learning process is concerned which will enhance learning comprehensiveness in the process. Notably, the AI tutor achieves an accuracy rate of 98% which id implemented by python, surpassing the performance of existing methods and setting a new benchmark in language learning technology.

Authors

Institutions

Publication Details

Published
2024-12-20
DOI
https://doi.org/10.1109/icaiqsa64000.2024.10882220
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Creating an AI English Tutor With Personalized Content and Dynamic Lessons

Gulnaz Fatma, A. Hepp K., M.K. Mohamed Faizal, J Naga Madhuri et al.
Intelligent Tutoring Systems and Adaptive Learning
article

Creating an AI English Tutor With Personalized Content and Dynamic Lessons

Gulnaz Fatma, A. Hepp K., M.K. Mohamed Faizal, J Naga Madhuri, Punit Pathak, B Sreela
article en

Abstract

Designing an AI English tutor entails using an elaborate approach of achieving an intelligent tutor that makes teaching and learning of the English language more effective. This project starts out with the development of clear goals and scope and knowing the subject clients for the right message to pass. Among this preliminary investigation, the educational tools already in use are first examined and the learning theories are incorporated into the design of the AI tutor. NLP and personalization algorithms are used in these models to make the content more dynamic and to also give real time feedback. Workshops feature lessons with content arranged in increasing order of complexity, elements of conversation practice and the use of games as well. For the sake of putting emphasis on the use, the interface is designed to be flexible and easy to use to provide learners with their use preferences and aims. Beta-testing, as well as usability-testing is done to ensure the refinement of the system for deployment. The AI tutor is then deployed on selected platforms with appropriate marketing to the target market. By doing so the AI English tutor can continue to remain optimally effective, interest and relevant to the learners’ needs inasmuch as the language learning process is concerned which will enhance learning comprehensiveness in the process. Notably, the AI tutor achieves an accuracy rate of 98% which id implemented by python, surpassing the performance of existing methods and setting a new benchmark in language learning technology.

Siddhartha Medical College (IN), Auro University (IN), Jazan University (SA)
Quality Education
Openalex Percentile: Top 75%
Intelligent Tutoring Systems and Adaptive Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.