Understanding transitions in professors’ evaluation: the application of Markov chain

Professors’ evaluations are carried out differently throughout individual universities, but it is an important part of a university internal quality regardless the evaluation system. The institutions with a large number of teaching employees are forced to use quantitative means of evaluation to be able to capture differences between individual science fields. We provide the means of meta-evaluation based on the Markov chain approach that allows to further assess the subjects of evaluation on a long-term basis. The approach is demonstrated on the vast evaluation data gathered in the university in Mexico City. The methodology of using Markov chains is explained on the theoretical level and it is applied to the real data afterwards. Results indicate that the lowest-evaluated professors are more likely to remain within the lowest-evaluated ones over a longer period. This may correspond with professors’ unwillingness to make changes in their courses. Moreover, we provide ample commentary on how the results should be understood. In the end, it occurs that using the Markov chain can even provide a reflection on the evaluation system as such.