Accurate recommendation model of mechanical engineering teaching resources for undergraduate students based on big data algorithm

Abstract

With the rapid development of science and technology, the characteristics of comprehensive intersection of modern mechanical disciplines are becoming more and more obvious. Strengthening professional knowledge education, innovative consciousness training, hands-on ability training and comprehensive quality training has become the basic requirement of talent training in mechanical discipline and the core content of contemporary higher education in mechanical discipline. In order to achieve "safe, efficient and high-quality" engineering construction and operation, it is urgent to apply intelligent algorithms to analyze and process engineering big data to provide support for decision-making and planning and design of engineering construction. These demands strongly drive colleges and universities to cultivate talents who understand engineering construction and have intelligent information thinking, which is also the main connotation of engineering professionals training under the background of new engineering. In order to improve students' interest and subjective initiative in learning this course, so that students can deeply understand and master the course knowledge and can learn and use it flexibly in practical engineering, this paper discusses the teaching content and teaching method of mechanical engineering materials course according to the characteristics of safety engineering specialty. The results show that the experimental system has complete functions and good operability and stability.