scholarly journals Evaluation of Physical Education Teaching Quality in Colleges Based on the Hybrid Technology of Data Mining and Hidden Markov Model

2020 ◽  
Vol 15 (01) ◽  
pp. 4 ◽  
Author(s):  
Yuansheng Zeng
Keyword(s):  
Data Mining ◽  
Physical Education ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Hidden Markov ◽  
Teaching Quality ◽  
Learning Technology ◽  
Hybrid Technology

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.

scholarly journals Research on the Evaluation Index System and the Grey Clustering Analysis Model of Teaching Quality of Physical Education in Higher Education

2015 ◽  
Vol 10 (8) ◽  
pp. 59 ◽  
Author(s):  
Baoquan Wu
Keyword(s):  
Physical Education ◽  
Clustering Analysis ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Colleges And Universities ◽  
Evaluation Index System ◽  
Analysis Model ◽  
Grey Clustering

Teaching quality evaluation of physical education usually involves multiple influence factors with grey and uncertain information. This brings about limitations to effective evaluation of teaching quality of physical education in colleges and universities. Thus, this paper draws merits from previous research and proposes a teaching quality evaluation system and model of physical education in colleges and universities. First, based on real situations, grey categories of evaluation state for physical education teaching quality are established. The definite weighted functions of grey category of evaluation state are confirmed. Specific steps of the teaching quality evaluation model based on grey clustering analysis are accounted for. Finally, a case study is introduced to verify the model. This model enlightens a new way to evaluate teaching quality of physical education in colleges and universities.

Research on the teaching quality evaluation of physical education with intuitionistic fuzzy TOPSIS method

2021 ◽  
Vol 40 (5) ◽  
pp. 9227-9236 ◽  
Author(s):  
Shulin Liu
Keyword(s):  
Physical Education ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Distance Measures ◽  
Topsis Method ◽  
High Quality ◽  
Intuitionistic Fuzzy ◽  
Quality Evaluation System ◽  
Intuitionistic Fuzzy Topsis

Under the background of the national fitness craze, the demand space for social sports professionals is constantly expanding. However, according to the author’s investigation, the overall situation shows that the number of high-quality social sports professionals in Chinese colleges and universities is relatively small. Among them, the unsound teaching quality evaluation system of social sports major is one of the important reasons affecting the cultivation of high-quality talents, so it is imperative to construct a sound teaching quality evaluation system of social sports major. At the same time, the perfect social physical education teaching quality evaluation system is an important basis for teachers’ teaching job evaluation and strengthening teachers’ management. And it is frequently considered as a multi-attribute group decision-making (MAGDM) issue. Thus, a novel MAGDM method is needed to tackle it. Depending on the conventional TOPSIS method and intuitionistic fuzzy sets (IFSs), this essay designs a novel intuitive distance based IF-TOPSIS method for teaching quality evaluation of physical education. First of all, a related literature review is conducted. What’s more, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria are decided objectively by utilizing CRITIC method. Afterwards, relying on novel distance measures between IFNs, the conventional TOPSIS method is extended to the intuitionistic fuzzy environment to calculate assessment score of each alternative. Eventually, an application about teaching quality evaluation of physical education and some comparative analysis have been given. The results think that the designed method is useful for teaching quality evaluation of physical education.

scholarly journals A Weekly Load Data Mining Approach Based on Hidden Markov Model

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 34609-34619 ◽  
Author(s):  
Shixiang Lu ◽  
Guoying Lin ◽  
Hanlin Liu ◽  
Chengjin Ye ◽  
Huakun Que ◽  
...  
Keyword(s):  
Data Mining ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Data Mining Approach

Predicting translation behaviorsby using Hidden Markov Model

2020 ◽  
Vol 3 (1) ◽  
pp. 76-99 ◽  
Author(s):  
Sheng Lu ◽  
Michael Carl ◽  
Xinyue Yao ◽  
Wenchao Su
Keyword(s):  
Machine Learning ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Prediction Accuracy ◽  
Hidden Markov ◽  
Process Research ◽  
Target Language ◽  
Learning Technology ◽  
Translation Process ◽  
Activity Unit

Abstract The translation process can be studied as sequences of activity units. The application of machine learning technology offers researchers new possibilities in the study of the translation process. This research project developed a program, activity unit predictor, using the Hidden Markov Model. The program takes in duration, translation phase, target language and fixation as the input and produces an activity unit type as the output. The highest prediction accuracy reached is 61%. As one of the first endeavors, the program demonstrates strong potential of applying machine learning in translation process research.

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