Research and Design of Automatic Questioning System Based on Question Generation
Didi Shi, Shuying Zhao, Qingting Liu, Yi Zhang · 2024
As an important branch of Artificial Intelligence (AI), Natural Language Processing (NLP) plays an important role in the field of education. Question-driven teaching is a necessary means of all kinds of teaching, and students' learning effect can also be tested through questions. In this paper, according to the demand of a large number of questions in the teaching scene, Question Generation (QG) algorithm in NLP is studied. A QG method based on pretrained language model is proposed. Based on this algorithm, an automatic questioning system is constructed, which can assist teachers to construct question banks and students to carry out reading comprehension. This research mainly introduces the construction and training of the pretraining QG model, the construction of Chinese question generation (CQG) dataset, and the construction of the automatic questioning system for teachers and students.