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Transformation Research on the Teaching Mode of Ideological and Political Courses in Colleges and Universities under Big Data Environment

   | 03. Juni 2024

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The application of big data technology in the teaching of ideology and politics courses in colleges and universities can provide strong support for the precise reform and innovation of ideology and politics work. In this paper, we first sort out the status quo and dilemma of the teaching of ideology and politics courses in colleges and universities and analyze the advantages and feasibility of big data technology in the learning of ideology and politics. Then, based on the big data streaming computing Spark framework, a personalized learning service platform for teaching Civics and Politics courses in colleges and universities was established. Aiming at the online learning behavior of students on the platform, the K-mean algorithm is used to select their behavioral characteristics. The personalized recommendation of learning resources for Civics and Political Science courses is implemented based on the learning behavior. Data was utilized to analyze the effectiveness of the personalized learning platform in transforming the teaching of Civics and Political Science courses in colleges and universities using S University as the research object. The study found that the number of focused learners in category 1 of the online learning behavior reached 303, and the teaching of the Civic and Political Science course based on the personalized learning platform helped the students’ will cultivation score increase by 2.49 points and more than 95% of the students recognized the platform. The customized service learning platform for teaching Civics courses established based on big data can realize the innovative transformation of Civics courses in colleges and universities and improve the teaching quality and level of Civics courses in colleges and universities.

eISSN:
2444-8656
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
Volume Open
Fachgebiete der Zeitschrift:
Biologie, andere, Mathematik, Angewandte Mathematik, Allgemeines, Physik