In order to analyze the intervention effect of integrating mental health knowledge into ideological and political teaching on college students’ employment and entrepreneurship mentality, this paper proposes a study to predict the effect of integrated intervention. This research mainly investigates the ideological and psychological conditions of college students from divorced families through questionnaires, compares and analyzes the classification and statistical results of the survey data between groups and within groups, and analyzes the reasons for the ideological and psychological problems of college students. The experimental results show that 30% of college students from divorced families and college students from non-divorced families responded that they do not feel comfortable in places with many people, and the difference between the groups is not significant. Regarding the concept of entrepreneurship, 64.63% of college students from divorced families in urban areas believe that entrepreneurship is a form of learning and should be encouraged. 63.27% of college students from divorced families in rural areas believe that learning should be the first priority and that a business should not be started. 20.41% of college students from divorced families in rural areas and 25.61% of college students from divorced families in urban areas believe that because entrepreneurship provides economic income, it can reduce the burden on families, but the difference is not obvious. In short, this study can provide reference for the ideological and psychological status of college students from divorced families.
In modern society, the rapid development of the knowledge economy makes education become the core resource of a country’s economic and social modernization development. Under this circumstance, student management has been paid more and more attention by people. This paper aims to study how to use the internet of things technology to study the student management evaluation system. This paper proposes a data mining algorithm based on the internet of things technology and proposes a decision tree method and an association rule algorithm based on the data mining algorithm. The experimental results of this paper show that the student growth rate in 2018 increased from 10% to 33% in 2019 and then from 21% in 2020 to 35% in 2021. It can be seen that with the development of the economy, the enrollment rate is also increasing, and the number of people who can go to college has increased rapidly. This also increases the difficulty of student management, making teachers’ work more arduous, and the complexity of the amount of information leads to a drop in the efficiency of student management. However, the student management evaluation system based on the internet of things technology is beneficial to solving this problem.
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