Automated scoring for short answering subjective test in Thai’s language
Khantharat Anekboon · 2018
Natural language processing is widely used in the real life. Natural language understanding is an important part of it to make a machine understands a language. This paper proposes an automated scoring system for a short answering subjective test in Thai’s language. A finite state machine and word2vec are used to create a scoring machine. Many challenge issues to be solved such as problems of Thai’s language, problems of a small number of words appeared in an answer, and problems about flexible of grading. The proposed method able to create an automated scoring machine after there is an exam question. With the proposed technique, there is no need to wait student’s answers for creating a model as many previous works. The experimental result shows that the proposed method gives a score nearly scoring by humans.