A Model Study on the Exploration and Practice of Digitally Empowered Big Ideology and Politics Courses in the Context of Smart Education

Abstract

Abstract Based on the portrait model, this study collects learner data and outputs the overall portrait and class portrait in this study after K-means clustering analysis. Six-month practice data of precision Civics teaching in a university were collected, from which comparative experiments were carried out to analyze the data of pre-test and post-test of teaching to explore whether precision teaching can significantly improve the learner portrait and the overall learning results. The distribution of questionnaire results and learner satisfaction questionnaires was done to understand the evaluations of lecturers and students on the implementation effect of precision teaching. The results showed that the style tendency of students in a university’s Big Ideology course was visual (72.9% of the total). The optimal cluster analysis for K=4 resulted in the division of student portraits into 4 clusters. Compared to pre-teaching, the students’ performance in Civics and Politics was significantly improved after the teaching, and the potential and hard-working learners made the most progress. And the post-teaching scores were centrally distributed in the range of 40-100 points. More than 70% of students believe that accurate teaching can meet their learning requirements. This paper’s experimental results confirm the effectiveness of precision teaching based on learner profiling.