Abstract
Under the premise of active in the field of machine learning, this paper takes online teaching system of ideological and Political education as an example to study machine learning and machine teaching system. In order to specifically understand the current situation of the construction and application of machine teaching based on supervised teaching of ideological and political theory courses in local colleges and universities, this experiment first conducted a statistical analysis of the learning results of the surveyed classes in two semesters from March 2020 to December 2020. The experimental data show that there is a positive interaction between teachers and students. Most students use the interactive communication mode of machines, while a small number of students use real-time interactive discussions with teachers. The experimental results show that the excellent rate of ABC classes in the first semester is 80%, 82% and 90%, respectively, through the machine-supervised teaching mode. Therefore, supervised machine learning can greatly help students improve their academic performance. In the future, we should further explore the application of other personalized and extensible machine learning methods in quality education.
Highlights
For a machine delivery system, the course provider and the course learner themselves cannot intervene
In order to deeply understand the application of machine teaching in ideological and political theory course in colleges and universities, the experiment further investigated the work in a local college
Investigation project mainly includes: the local construction of ideological and political theory course teaching machine based on the main network platform, to participate in major colleges and universities, the platform of ideological and political theory courses, course has opened all the machine teaching mode, students participate in the course, course platform to create a pattern, etc
Summary
For a machine delivery system, the course provider and the course learner themselves cannot intervene. Traditional algorithms extract specific data based on surveys and other methods, and use fixed algorithms to analyze users and projects [1, 2]. Grzegorz et al believe that machine learning is the focus of artificial intelligence and the fundamental way to make computers intelligent It is established on the basis of cognitive discipline and so on, and learning can imitate the learning mechanism of human beings through mathematical modeling, so as to obtain the learning model oriented to specific functions, so as to autonomously learn and study the general learning theories and algorithms [6]. The function of machine learning to predict results has made it widely used, such as data mining, computer vision, natural language processing, etc. [9, 10]
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