Bloom’s Classification of Educational Objectives Based on Deep Learning Theory Teaching Design of Nursing Specialty

Through the effective integration of various teaching resources, carry out the teaching design of “basic nursing technology” for the nursing specialty in the information environment based on Bloom’s education objective classification. Select 200 nursing students from two natural classes in the third year of undergraduate nursing major as the research objects with100 students in the experimental group and 100 students in the control group. The experimental group adopted Bloom’s objective classification teaching mode, and the control group adopted the traditional teaching model. They have carried out the teaching intervention to ensure the consistency of teachers, textbook use, teaching hours, and teaching progress between the two groups. The evaluation model of the teaching design results is the RBF neural network. The model improves the convergence ability of the RBF network by dynamically changing the control parameters of the L-M algorithm. RBF realizes the goal of the comprehensive analysis of course teaching effects evaluation and various influencing factors. The results showed that the differences in self-management ability, information ability, cooperation score, and total score of the experimental group were significantly higher than those of the control group, with statistical significance P < 0.01 . The teaching of Bloom’s educational objective model can enhance students’ subjective consciousness and effectively improve their independent learning ability. The learning effect is improved obviously. This paper studies the teaching approaches to improve nursing students’ comprehensive ability and humanistic care quality and provides a reference for deepening nursing undergraduate teaching reform.