Download PDFOpen PDF in browser

Chatbot in Regional Language

EasyChair Preprint no. 12827

4 pagesDate: March 29, 2024


This paper presents the development and implementation of a Chatbot Application designed to enhance student guidance and motivation. Leveraging the React Native framework for mobile app development and MongoDB for efficient database management, this application offers a versatile and cross-platform solution for students in their educational journey.

Study plan optimization is another significant feature, helping students maximize their time and resources by creating tailored study plans. The application also tracks progress, ensuring students stay on course with their academic goals. Motivation is critical to academic success, and the
chatbot achieves this through a curated repository of inspirational content, including quotes, success stories, and engaging material.

The application goes beyond academic support, assisting students in career guidance, college and scholarship searches, language learning, and facilitating networking opportunities within their chosen fields. Moreover, it adheres to stringent ethical considerations, ensuring data privacy and regulatory compliance. The experiment assesses user interaction with the chatbot, including queries, responses, and feedback. Post-experiment surveys, interviews, and data analysis provide valuable insights into the application’s influence on student motivation and academic performance. These findings have far-reaching implications for the continued development and implementation of technology-driven educational support systems.

In conclusion, this college project report encapsulates the development and potential of the Chatbot Application for Students. By harnessing technology to offer guidance and motivation, it addresses students’ dynamic and evolving needs in their pursuit of education. With a focus on
user-centric design, data privacy, and real-world impact, this project signifies a significant step toward enhancing the student experience.

Keyphrases: AI, Chatbot, NLP

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Abdul Ghani Shaik and Rajesh Reddy Punganuru and Uttej Repaka and Bharath Somepalli and Raithatha Hiren},
  title = {Chatbot in Regional Language},
  howpublished = {EasyChair Preprint no. 12827},

  year = {EasyChair, 2024}}
Download PDFOpen PDF in browser