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Application of Python Programming Methods in the Constructing of Effective Teaching Criteria

The aim of this study was to explore the evaluation methods of university teachers’effective teaching criteria with python programming. The evaluation criteria of 539 university teachers was carried out with a python programming Bayesian discriminant function. The results showed that: 1. The structure of  effective teaching criteria for evaluation university teaching were student factors, teacher factors, teaching contents, teaching media, teaching environment, teaching evaluation and feedback evaluation process. 2. The overall evaluation of teachers' effective teaching and its sub dimensions were at the medium level. It showed that the teaching quality of  the teachers need to be improved in general. 3. The teaching quality in the major of science and engineering was significantly higher than that of liberal arts and medicine, and no significant difference between liberal arts and medicine was found. This may partly be attributed to the nature of different subjects. 4.The higher the teacher's professional title was, the better the teaching quality was found. It suggested that the evaluation criteria of effective teaching about university teachers should take into account the teachers’ qualities such as experience, knowledge, which were embedded in the term of “title”.