The mastery of knowledge points by students is not only an important indicator of their academic performance but also a crucial avenue for personalized learning. Based on an analysis of the current state of high school chemistry teaching in China, this study integrates a precision teaching platform as a data support for instruction and proposes a precision teaching model grounded in educational big data. Through the excavation of student test scores, we accurately analyze each student's knowledge mastery based on their exam performance, enabling personalized learning. Furthermore, by analyzing test scores, we achieve precision teaching by precisely assessing each student's knowledge mastery. We take two classes in the first year of high school in a school in Guizhou as experimental subjects. With one class as the experimental group and the other class as the control group, the experimental group used the platform technology to carry out precise teaching in chemistry exercise classes and the control group carried out traditional lecture teaching, and the results of the experiment were subsequently processed and analysed by collecting and analysing the results of the two chemistry exams of the two classes. Finally, it was found that the use of big data in education for precision teaching can address the problems and needs of teachers who are unable to meet the differences in the levels of students at different levels of instruction. This provides a new perspective for chemistry exercise review classes, optimizing teaching effectiveness and enhancing the efficiency of both teaching and learning.
