5 DETERMINATION OF WEIGHT
OF PERFORMANCE
EVALUATION SYSTEM
Since the importance of each indicator is different, it
is necessary to assign weight to each indicator. In
this paper, the index system is made into a quantita-
tive evaluation table, which is distributed to front-
line teachers, teaching administrators, teaching aux-
iliary staff, administrative staff and other teaching
related personnel in the way of questionnaire survey,
and the recovered questionnaire data is used as the
basic data to determine the weight of the index.
SPSS software was used for statistical processing of
questionnaire data, combined with AHP and factor
analysis to determine the final weight.
5.1 Questionnaire Survey
In this survey, questionnaires were distributed
through the questionnaire star, with 34 three-level
evaluation indicators as variables and six first-level
indicators as six dimensions, and the importance of
each variable was scored by the five-level system
respectively. A total of 183 questionnaires with valid
data were collected.
5.2 Sample Data Analysis
The data analysis of the sample includes reliability
analysis and validity analysis. This study first car-
ried out reliability analysis (Cronbach's α coeffi-
cient) from the six dimensions of teachers' ethics,
education and teaching ability, scientific research
ability, professional practice ability, external com-
munication ability and professional relearning abil-
ity, and then conducted validity analysis of the
above indicators in order (KMO and Bartley sphere
test). In order to test the validity of the questionnaire
data answers and the rationality of the questionnaire
design.
5.2.1 Sample Reliability Analysis
This paper used SPSS software to analyze the relia-
bility of questionnaire data and sample validity. The
Cronbach 'Salpha coefficients of the six first-level
indicators were all greater than 0.8, indicating the
high reliability of the questionnaire. Then, validity
test was conducted. Since the evaluation indicators
of this paper come from policy interpretation, litera-
ture research and expert interviews, the content is
true and valid, and the content validity meets the
requirements, so the construction validity was main-
ly tested here. After analysis, the KMO of the ques-
tionnaire was 0.907, greater than 0.6, and the Bart-
lett sphericity test showed that P =0.000, less than
0.05, indicating that the data met the condition of
structural validity test by factor analysis. Then factor
information concentration analysis and validity
analysis were carried out, a total of 6 factors were
extracted, and the characteristic root values were all
greater than 1. The variance explanation rate values
of the 6 factors were 14.462%, 14.242%, 13.743%,
10.783%, 6.737%, 5.450%, and the cumulative vari-
ance explanation rate after rotation was 65.417%.
More than 50%. Factor loading coefficient absolute
value is greater than 0.4, the organization discipline
corresponding factor 4, corresponding education
teaching ability factor 2, corresponding factor 6
scientific research ability and professional practice
ability corresponding factor 3, foreign exchange
capacity corresponding factor 1, professional learn-
ing ability corresponding factor 5, factors and re-
search items and consistent with the expected re-
sults, the relation between data effective degrees.
5.3 Selection of Indicator Weight
Determination Method
Because there are three levels of indicators in this
paper, it is suitable to use the analytic hierarchy
process to determine the weight of indicators, but the
analytic hierarchy process has certain subjectivity.
At the same time, there are a large number of indica-
tors in this paper, and dimensionality reduction is
needed in the analysis, which is just suitable for
factor analysis to determine the weight. Therefore,
this paper combines the two methods. The weight of
the first-level index is determined by factor analysis
method, and the weight of the second-level and
third-level indexes is determined by reuse analytic
hierarchy process, which can avoid the defects
caused by a certain method.
5.3.1 Determining the Weight of First-Level
Indicators
According to the variance interpretation rate values
of the six factors and the cumulative variance inter-
pretation rate value after rotation in the sample reli-
ability analysis, the corresponding weights of each
index are shown in Figure 2: