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: