The Teaching Pattern of Law Majors Using Artificial Intelligence and Deep Neural Network Under Educational Psychology - Xuan, Di; Zhu, Delong; Xu, Wenhai (Frontiers in Psychology, 2021)
With the increasing attention to the cultivation of legal talents, a new teaching model has been explored through Artificial Intelligence (AI) technology under educational psychology, which focuses on improving students' learning initiative, teaching methods, and teaching quality. Firstly, the application of AI and Deep Neural Network (DNN) algorithms are reviewed in education, the advantages and disadvantages of traditional learning material recommendation algorithms are summarized. Then, a personalized learning material recommendation algorithm is put forward based on DNN, together with an adaptive learning system based on DNN. Finally, the traditional User-based Collaborative Filtering (UserCF) model and Lifelong Topic Modeling (LTM) algorithm are introduced as the control group to verify the performance of the proposed recommendation system. The results show that the best learning rate of model training is 0.0001, the best Dropout value is 0.5, and the best batch size is 32. The proposed personalized learning resource recommendation method based on Deep Learning (DL) still has good stability under various training data scales; The recommended students' personalized test questions are moderately difficult; It is easier to recommend materials according to the students' acquisition of knowledge points and the practicability of the recommended test questions; Personalized learning materials recommendation algorithm based on AI can timely feedback students' needs, thereby improving the effect of classroom teaching. Through the combination of AI and DL algorithms in teaching design, students can complete targeted personalized learning assignments, which is of great significance to cultivate high-level legal professionals.