Question answering is an indispensable link in high school teaching. Through question answering, on the one hand, it can solve students’ learning doubts, on the other hand, it can provide teachers with teaching feedback. However, through the investigation and research, it is found that with the expansion of student size, the effect of question answering in high school is not satisfactory. This paper analyzes the current situation of question answering in high school, and designs an intelligent question answering system for high school teaching based on constructivism learning theory and cognitive structure learning theory. The system, which is the first innovative application in the field of high school teaching, integrates knowledge graph technology and intelligent question answering technology, introduces big data technology. It can solve students’ questions in time and accurately, link the knowledge points related to the questions to help students construct knowledge network graph, and the big data technology is used to analyze the students’ questioning behavior and to predict students’ learning behavior in order to feedback the teaching effect.