With the development of history, some folk dances are annihilated and lost in the inheritance. In order to protect and inherit national intangible cultural heritage and promote the construction of advanced socialist culture, this paper uses information fusion technology, combines national aesthetic personality, and refers to multi-factor theory, construction theory, and distillation theory to design and reform the art practice model of folk dance education. The data of dancers’ skeletal joint points are collected by using multiple Kinect sensors, and the Kalman filter algorithm is selected to establish the human skeletal motion model and fuse the data information of each joint point. Taking the hand_right and elbow_right joints as examples, it was found that the mean value of the error between the testers’ joint trajectory and the template movement was reduced from 10mm to 4mm, and the mean value of the error between the joint angle and the template movement was reduced from 90° to 35°. Comparing the dance movement training effects and scores of the experimental group and the control group, it was found that the experimental group kicked the front and side legs an average of 70 times/minute, the middle jump height was improved by 10cm, and the average score was 3.33 points higher. This indicates that the integration of information fusion technology in the art practice of dance education can realize the practical innovation of college folk dance education and improve the comprehensive level of folk dance.