Improving Innovative Thinking and Practical Ability in Mechanical Design Education——A Research based on Random Forest
Year: 2025
Type: conference-paper
Abstract: The intelligent manufacturing engineering major is a new and applied major. This major belongs to the new engineering education concept. The major encounters opportunities and challenges. The mechanical design course is a foundation course of this major. This course trains intelligent manufacturing professionals. This course follows the design concept of “moral education first, student center, ability training, continuous improvement”. The course adds design experiments for student practice. The experiments help students to improve practical ability. The course has changed assignment forms. It improves student application and innovative ability. It also improves their creativity. The teaching method has been updated. Course design is improved. More teaching resources are added. It helps guide students. The course uses machine learning especially random forest to analyze and improve the student learning data. It makes the evaluation process better. It also gives personal guidance to student. It creates a new evaluation system. That is more valuable information is to evaluate the student learning process. Teaching practice proves that these updates are successful. The course improved the student's ability of mechanical designing skills and the level of student's innovation. The number of students got awards of competition increased 40%. Mechanical design courses of number of projects are growing 300%. It can be used to train many more intelligent manufacturing talents.
Authors: Jiali Kong, Shengtao Li, Enqiang Liang, Minghui Zheng
Institution: Shandong Huayu University of Technology
Language: English
Subfield: Architecture
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4412923462