TCM Data Mining and Quality Evaluation with SAPHRONTM System

2014 ◽  
pp. 215-226
Author(s):  
Jing Yang ◽  
Hua Su ◽  
Guoshun Tang ◽  
Zihan Zheng ◽  
Yue Shen ◽  
...  
Keyword(s):  
Data Mining ◽  
Quality Evaluation

Application of Data Mining Technology in Sports Teaching Quality Evaluation

2014 ◽  
Vol 543-547 ◽  
pp. 4694-4697
Author(s):  
Li Min Zhou
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Scientific Method ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Evaluation Index ◽  
Data Mining Technique ◽  
Mining Technology ◽  
Mining Technique ◽  
Sign System

The unreasonable phenomenon caused by the lack of effective scientific method, The essay attempts to carry on related analysis and research of combining the data mining technique with sport teaching quality evaluation by mining valid sport teaching quality evaluation index sign system, making full use of the decision tree technique to solve the unreasonableness of the sports teaching quality evaluation and putting forward technical method for sports teaching quality evaluation based on the decision tree, aimed at making it fair, just, reasonable and efficient.

Research on Teaching Quality Evaluation Using Data Mining Technique

2014 ◽  
Vol 926-930 ◽  
pp. 4582-4585
Author(s):  
Ai Feng Li ◽  
Ying Hu ◽  
Wen Jing Zhao
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Association Rule ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Data Mining Technique ◽  
Higher Education System ◽  
Potential Factors ◽  
Rule Method ◽  
Using Data

—In this paper, we employ data mining (DM) technique to analyze various potential factors which impact the in-class teaching quality evaluation. Based on an effective dataset, we first exploit association rule method to mine the relationship between the teacher’s attributions, such as title, degree, age, seniority, and load, and the in-class teaching quality evaluation results. Then, we construct the decision tree of course’s attributions to reveal how the course’s attributions, such as property, credit, week hour, and number of students, impact the in-class teaching quality evaluation results. Our mined rules can provide effective guidance to talent development, teaching management, and input of talent in higher education system. Index Terms—data mining, decision tree, association rule, teaching quality evaluation

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