Advisor | Gudivada, Venkat N | |
Author | Houshvand, Salar | |
Date Accessioned | 2020-12-18T16:00:46Z | |
Date Available | 2021-12-01T09:01:53Z | |
Date Created | 2020-12 | |
Date of Issue | 2020-11-17 | |
xmlui.metadata.dc.date.submitted | December 2020 | |
Identifier (URI) | http://hdl.handle.net/10342/8814 | |
Description | Automated question generation is critical for realizing personalized learning. Also, learning research shows that answering questions is a more effective method than rereading the textbook multiple times. However, creating different types of questions is intellectually challenging and time-intensive. Therefore, it emphasizes a necessity for an automated way to generate questions and evaluate them. In this research after analyzing the existing approaches to automated question generation, we conclude that most of the current systems use natural language process techniques to extract questions from the text, therefore, other topics such as mathematics are lacking an automated question generation system that could help learners to assess their knowledge.In this research we present a novel framework that automatically generates unlimited numbers of questions for different topics in discrete mathematics. We created multiple algorithms for various questions in four main topics using Python. Our final product is presented as an application programming interface (API) using Flask library, which makes it easy to gain access and use this system in any future developments. Finally, we discuss the potential extensions that can be added to our framework as future contributions. The repository for this framework is freely available at https://github.com/SalarHoushvand/discrete-math-restfulAPI. | |
Mimetype | application/pdf | |
Language | en | |
Publisher | East Carolina University | |
Subject | API | |
Subject | Auto Question Generation | |
Subject | Flask | |
Library of Congress Subject Headings | Discrete mathematics | |
Library of Congress Subject Headings | Individualized instruction | |
Library of Congress Subject Headings | Python (Computer program language) | |
Title | A FRAMEWORK FOR AUTOMATICALLY GENERATING QUESTIONS FOR TOPICS IN DISCRETE MATHEMATICS | |
Type | Master's Thesis | |
xmlui.metadata.dc.date.updated | 2020-12-18T14:31:26Z | |
Department | Computer Science | |
xmlui.metadata.dc.degree.name | M.S. | |
xmlui.metadata.dc.degree.level | Masters | |
xmlui.metadata.dc.degree.discipline | MS-Software Engineering | |
xmlui.metadata.dc.degree.grantor | East Carolina University | |
xmlui.metadata.dc.degree.department | Computer Science | |
xmlui.metadata.dc.access.option | Open Access | |
xmlui.metadata.dc.embargo.lift | 2021-12-01 | |
xmlui.metadata.dc.type.material | text | |