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Validation of course ontology elements for automatic question generation
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Ibrahim Teo, Noor H. and Joy, Mike (2017) Validation of course ontology elements for automatic question generation. EAI Endorsed Transactions on e-Learning, 4 (15). 153392. doi:10.4108/eai.29-11-2017.153392
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WRAP-Validation-course-ontology-automatic-generation-Joy-2017.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution. Download (1087Kb) | Preview |
Official URL: http://dx.doi.org/10.4108/eai.29-11-2017.153392
Abstract
Recent research has led to the emergence of ontology-based question generation and aims to benefit instructors by providing support and intelligent assistance for the automatic generation of questions. However, existing ontologies are not designed mainly for this purpose, and the concern is that an ontology will not be competent enough to act as a semantic source for the question generation process. Therefore, the aim of this work is to validate how well the elements represented in course ontology can be used for the purpose of automatic question generation. In this work, we choose to validate Operating System ontologies and identify related question sources from textbooks on this subject as competency questions. Finally, the result shows that the evaluated ontologies can provide knowledge for generating useful assessment questions. Furthermore, the list of categorized question templates and their variations are generated using a strategy based on the validated ontology.
| Item Type: | Journal Article | |||||||||
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| Subjects: | L Education > LB Theory and practice of education > LB2300 Higher Education Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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| Divisions: | Faculty of Science > Computer Science | |||||||||
| Library of Congress Subject Headings (LCSH): | Operating systems (Computers) -- Web-based instruction, Semantic computing, Internet in education | |||||||||
| Journal or Publication Title: | EAI Endorsed Transactions on e-Learning | |||||||||
| Publisher: | EAI | |||||||||
| ISSN: | 2032-9253 | |||||||||
| Official Date: | 29 November 2017 | |||||||||
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| Volume: | 4 | |||||||||
| Number: | 15 | |||||||||
| Article Number: | 153392 | |||||||||
| DOI: | 10.4108/eai.29-11-2017.153392 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access | |||||||||
| RIOXX Funder/Project Grant: |
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