Abstract
Accurate identification of students’ learning modes in online teaching of ideological and political theory courses is helpful to improve students’ concentration in the learning process and enhance the effect of online teaching of ideological and political theory courses. To this end, this paper designed a personal learning pattern recognition model, set the identification criteria for the matching rules of personal learning pattern type and behavior purpose, collected students’ learning data according to the teaching video browsing situation, and analyzed their learning behavior trajectory and the degree of attention in the learning process. By comparing the analysis results with the preset identification criteria, the quantitative identification results of online learning modes of ideological and political courses are obtained. The experimental study shows that the recognition results of the model in this paper are close to the actual online learning types of students in ideological and political courses, and after the application of this model, the test scores of students in ideological and political courses have been significantly improved, which proves that this model has a high promotion value.
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In 2019, Anhui Province Philosophy and Social Science Planning Project “Research on the Construction of Mainstream Ideology Discourse Power in Colleges and Universities in the “Micro-Communication” Era” (project number: AHSKY2019D052).
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Xu, Lt., Wang, Hg. (2021). Design of Personal Learning Model Recognition Model for Online Teaching of Ideological and Political Theory Course. In: Fu, W., Liu, S., Dai, J. (eds) e-Learning, e-Education, and Online Training. eLEOT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-030-84383-0_19
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DOI: https://doi.org/10.1007/978-3-030-84383-0_19
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