Abstract
In order to further improve the teaching quality evaluation accuracy of physical education(abbreviated as PE) curriculum in colleges, this study conducts an in-deep research on the overall evaluation of PE teaching effect in colleges from the aspects of teachers’ teaching ability and students’ learning effect based on the hybrid technology of data mining and hidden Markov model. First of all, this study analyzes the development status of the teaching quality evaluation system of PE curriculum in colleges; Secondly, it analyzes the applicability of data mining technology and hidden Markov model to the evaluation of PE teaching quality in colleges, and proposes a mathematical model for evaluating the quality of PE teaching in colleges; Finally, this study carries out a series of experiments on the basis of mathematical models, and analyzes the experimental results in depth. The experimental analysis shows that the model proposed in this paper is helpful to improve the accuracy of PE teaching quality evaluation in colleges. The research results of this study provide a useful exploration for the integration of computing technology and language teaching. At the same time, it provides a reference path and implementation model for improving the teaching of PE for graduates in colleges through machine learning technology.
Highlights
In order to further improve the teaching quality evaluation accuracy of PE curriculum in colleges, this study explores the overall evaluation of PE teaching effect in colleges in depth based on a detailed analysis of the applicability of machine learning technology to improve PE teaching and with references to mining technology and hidden Markov model
Some analyzed the evaluation of the special PE teaching effect in depth, some attempted to use practical methods to guide students to improve their self-evaluation ability, and some analyzed the influence of the composition and feedback mechanism of PE curriculum on the evaluation effect [3,4,5,6,7,8]
In order to improve the performance of PE teaching evaluation algorithm, this article proposes a PE teaching evaluation model based on hybrid technology of data mining and hidden Markov model
Summary
In order to further improve the teaching quality evaluation accuracy of PE curriculum in colleges, this study explores the overall evaluation of PE teaching effect in colleges in depth based on a detailed analysis of the applicability of machine learning technology to improve PE teaching and with references to mining technology and hidden Markov model. More recent research results include the design and optimization of evaluation scales based on the actual needs of PE curriculum teaching [9], and how feedback can be formed through questionnaires to improve teaching [10]. In order to improve the performance of PE teaching evaluation algorithm, this article proposes a PE teaching evaluation model based on hybrid technology of data mining and hidden Markov model. Through the comparison with the previous methods, the advantages of the proposed algorithm in precision and computational efficiency are verified
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