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Automatic SQL query generation

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Bibliographische Detailangaben
Titel:	Automatic SQL query generation
Autoren:	Arbabifard, Kamyar
Weitere Verfasser:	Gudivada, Venkat N, Computer Science
Verlagsinformationen:	East Carolina University
Publikationsjahr:	2017
Bestand:	East Carolina University: The ScholarShip at ECU
Schlagwörter:	Personalized Learning, Question Generation, SQL (Computer program language), MOOCs (Web-based instruction), Educational evaluation
Beschreibung:	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.
Publikationsart:	master thesis
Dateibeschreibung:	application/pdf
Sprache:	English
Relation:	http://hdl.handle.net/10342/6401
Verfügbarkeit:	http://hdl.handle.net/10342/6401
Dokumentencode:	edsbas.87EF884C
Datenbank:	BASE

Beschreibung
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.