Paper Title

Formulating SQL Queries from Natural Language Processing for Students Using Mobile Learning

Article Identifiers

Registration ID: IJNRD_200294

Published ID: IJNRD2307102

DOI: https://doi.org/10.5281/zenodo.8150058

Authors

Parth Mody , Maanaav Motiramani , Param Sejpal , Abhitay Shinde

Keywords

Natural Language Processing (NLP), Structured Query Language (SQL), CSV, Tokenization, POS tagging, Chunking, Parsing, Featured context free language, Speech to Text, Mobile Learning, User Experience, Data retrieval.

Abstract

Mobile learning opens new worlds of information and personal development. To enable more personalized learning via mobile devices, several clever approaches should be implemented into mobile-assisted learning systems. This paper examines and explores several systems created with natural language processing (NLP) to extract relevant information from a database by utilizing structured natural language questions as input and SQL queries as output. Natural Language Processing (NLP) tools can be used to evaluate students' flaws throughout the mobile learning assessment process. Furthermore, the approach broadens its use beyond student learning by incorporating CSV data retrieval capabilities. Users, such as placement cell workers dealing with student databases, can perform natural language searches to retrieve useful information from CSV files. The design of the proposed model includes a user interface for submitting English inquiries, followed by NLP modules for analyzing the queries and mapping them to SQL queries. The SQL queries may then be run to obtain the necessary data from the database. It illustrates the power of natural language processing techniques in supporting mobile learning and enhancing data retrieval operations.

How To Cite (APA)

Parth Mody, Maanaav Motiramani, Param Sejpal, & Abhitay Shinde (July-2023). Formulating SQL Queries from Natural Language Processing for Students Using Mobile Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(7), b1-b7. https://doi.org/10.5281/zenodo.8150058

Citation

Issue

Volume 8 Issue 7, July-2023

Pages : b1-b7

Other Publication Details

Paper Reg. ID: IJNRD_200294

Published Paper Id: IJNRD2307102

Downloads: 000121984

Research Area: Science & Technology

Country: Mumbai, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2307102.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307102

Crossref DOI: https://doi.org/10.5281/zenodo.8150058

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper - Volume 10 | Issue 9 | September 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: September 2025

Current Issue: Volume 10 | Issue 9 | September 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 30-Sep-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

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