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
- Gulnaz Fatma (ORCID: https://orcid.org/0000-0002-2255-5491)
- A. Hepp K.
- M.K. Mohamed Faizal
- J Naga Madhuri (ORCID: https://orcid.org/0000-0002-6941-3378)
- Punit Pathak
- B Sreela
Institutions
- Siddhartha Medical College (IN)
- Auro University (IN)
- Jazan University (SA)
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