Automatically difficulty grading method of "instruction system" question bank based on knowledge tree
Pages 283 - 284
Abstract
The aim of this study is to propose a model, which can automatically grade difficulty for a question from "Instruction System" question bank. The system mainly uses attributes which are employed to be input. A knowledge tree model which was established based on the proper nouns from Chinese "Instruction System" teaching material and a machine learning algorithm are utilized as important parts for classification. The experimental dataset comes from our built "Principles of Computer Organization" online education system, the accuracy result of difficulty classification could be 79.41% which is much higher than the accuracy of random guess 50%.
Index Terms
- Automatically difficulty grading method of "instruction system" question bank based on knowledge tree
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Published In
July 2017
1934 pages
ISBN:9781450349390
DOI:10.1145/3067695
Copyright © 2017 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 15 July 2017
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Funding Sources
- Open Project of the State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences
- Specialized Research Fund for the Doctoral Program of Higher Education of China
- Research Plan in Application Foundation and Advanced Technologies in Tianjin
Conference
GECCO '17
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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%
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