Research Method of Maker Education Based on Regression Models

With the rapid development of maker education in China, more and more science and technology enterprises, publishing units, science popularization venues, and educational institutions have been involved in the upsurge of resource development for maker education. Research on the development trend of maker education also shows an upward trend. However, most of the existing studies on trend prediction give the future development trend of maker education in the way of literature statistics and subjective judgment, which makes the prediction results strongly subjective. In order to solve this problem, we drew on the advantages of machine learning in data prediction and proposed a research method for maker education based on regression models. The core idea of the proposed method is to use the characteristics of regression models to predict future maker education without adding subjective factors. Specifically, we built regression models based on the collected historical data, and then predicted future development based on these regression models. In the experiment, we verified the effectiveness of the model based on the research literature on maker education in China from 2013 to 2019.