Paper Info
Title
Quality Of Lod Based Semantically Generated Questions
Abstract
This research aims to automatically generate questions to support history learning. The questions are generated semantically with natural language patterns using Linked Open Data (LOD). The generated questions are designed to reinforce history learning by supporting acquisition of new information and encouraging learners to think about their knowledge. In this paper, we describe an evaluation assessing the capability of the system to generate questions of a quality high enough to support learning. The evaluation had two main results: first, the questions generated by the system cover 87% of the questions generated by humans. Second, we confirmed that the system can generate questions that enhance history thinking of the same quality as human generated questions.
Year
DOI
Venue
2015
10.1007/978-3-319-19773-9_86
ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015
Keywords
Field
DocType
Question generation, Linked open data, Semantic open learning space, Inquiry based learning, Self-directed learning, History learning
Data science,Inquiry-based learning,Computer science,Knowledge management,Linked data,Natural language,Question generation,Autodidacticism
Conference
Volume
ISSN
Citations 
9112
0302-9743
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Corentin Jouault152.40
Kazuhisa Seta22612.94
Yuki Hayashi33811.12