Research and Practice on the Application of Artificial Intelligence in the Intelligent Teaching Management Platform of Housing Industry under the Perspective of Resource Sharing

Abstract

In recent years, artificial intelligence technology, especially deep learning, has been increasingly widely used in the field of education, and housing industry colleges and universities are facing the problems of dispersed teaching resources and low sharing efficiency. In order to improve the intelligent level of teaching management, the construction of an intelligent teaching management platform based on deep learning has become a key direction for the development of education informatization. This study constructs an intelligent teaching resource sharing platform for the housing industry based on deep learning algorithms, realizes personalized learning path recommendation through the LSTM model, and carries out test question recommendation experiments with A, B, and C students as objects. Methodologically, user behavior and basic information are collected, data cleaning and standardization are used to train the LSTM model, and compared and analyzed with traditional recommendation algorithms such as DT and IRT. The results show that in the test of class A students, the F1 value of this paper's method is 0.8502, and the MAE is only 0.0102; the F1 value of class B students is 0.8571; and the F1 value of class C students is 0.8233, which are all better than other algorithms. The conclusion points out that the platform can effectively improve the accuracy and reasonableness of teaching recommendation, especially for students with different learning styles showing good adaptability and generalization value.