Analysis of the Effectiveness Evaluation of College Ideological and Political Course Teaching based on closed Frequent Pattern Mining Algorithm

Authors

  • Heti Li, Jiwei Han, Siyu Chai

Abstract

The construction of a scientific and rational evaluation system of teaching effectiveness is an essential part of the reform of ideological and political theory courses in colleges and universities. At present, there are still some problems in evaluating the effectiveness of ideological and political theory courses in colleges and universities. It is necessary to adhere to the principle of the political, scientific and operable unity in the evaluation and the trinity of knowledge, skills, and values to carry out analysis based on the combination of qualitative and quantitative evaluation. To improve the accuracy of frequent pattern mining in a workflow environment, a new closed frequent pattern mining algorithm is proposed. Firstly, the definition of the dependency matrix is extended, that is, the workflow mining is used to establish dependency support degree matrix that contains direct dependency and overlapping relationship. Subsequently, the CHARM algorithm is extended to perform automatic mining of the closed frequent activity sets based on the support matrix. Finally, the closed frequent item sets are processed to form the final closed frequent pattern. The algorithm has a superior capacity in treating parallel and selective relations to similar algorithms. The evaluation of the effectiveness of ideological and political theory courses should be considered from the multiple dimensions such as the teaching behavior of teachers, the learning behavior of students, the teaching environment, the teaching management, and other dimensions.

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Published

2020-05-10

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Section

Articles