Automatic Question Generation With Classification Based On Mind Map

Kusuma, Selvia Ferdiana and Siahaan, Daniel Oranova and Fatichah, Chastine and Naufal, Mohammad Farid (2019) Automatic Question Generation With Classification Based On Mind Map. In: 2019 16th International Joint Conference on Computer Science and Software Engineering (JCSSE), 10-12 July 2020, Pattaya, Thailand.

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In Indonesia’s national education system, a question within a national standardized school examination (Ujian Sekolah Berstandar Nasional, USBN) is generated based on a predetermined grid. A predetermined grid is a matrix that contains a set of criteria that all question should abide. Students who would like to take the final school exam usually prepare themselves by learning through the existing predetermined grid then extend their knowledge around the predetermined grid. But extending knowledge around the predetermined grid is not easy because it depends on the student's creativity to associate the material that exists. The contribution of this research is to generate various types of questions that have relevance to the predetermined grid. The dataset that used is learning the material of all grade in 4, 5, and 6 of elementary school science subjects. The question generation process is done by the rule which generated from the mind map. The mind map will help to determine the interrelationship between the learning material. This study uses 50 competencies from the predetermined grid as input to generate questions. The results of question generation are then validated by an expert. Expert state that all inputs used can generate questions according to competence. The experiment result shows that the proposed method can be used to generate questions that are related to the predetermined grid.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Question Generation, Rule-Based, Mind Map, Question Classification
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Engineering > Department of Information Technology
Date Deposited: 14 Dec 2020 02:18
Last Modified: 28 Apr 2021 15:11

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