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Automatic SQL query generation

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Bibliographic Details
Title:	Automatic SQL query generation
Authors:	Arbabifard, Kamyar
Contributors:	Gudivada, Venkat N, Computer Science
Publisher Information:	East Carolina University
Publication Year:	2017
Collection:	East Carolina University: The ScholarShip at ECU
Subject Terms:	Personalized Learning, Question Generation, SQL (Computer program language), MOOCs (Web-based instruction), Educational evaluation
Description:	Automatic generation of questions for learning assessment has been an area of research interest for long. The advent of Massive Open Online Courses (MOOCs) as well as the goal of providing immediate contextualized feedback to enhance student learning has created renewed interest in automatic question generation. This thesis motivates the automatic question generation problem, gives an overview of the current approaches, and describes the proposed novel approach to automatic generation of SQL queries using the notion of grammar graph.
Document Type:	master thesis
File Description:	application/pdf
Language:	English
Relation:	http://hdl.handle.net/10342/6401
Availability:	http://hdl.handle.net/10342/6401
Accession Number:	edsbas.87EF884C
Database:	BASE

Description
Abstract:	Automatic generation of questions for learning assessment has been an area of research interest for long. The advent of Massive Open Online Courses (MOOCs) as well as the goal of providing immediate contextualized feedback to enhance student learning has created renewed interest in automatic question generation. This thesis motivates the automatic question generation problem, gives an overview of the current approaches, and describes the proposed novel approach to automatic generation of SQL queries using the notion of grammar graph.