which is the "semantic gap" in the process of 
information  interpretation.  This  "semantic  gap"  is 
the  problem  existing  in  the  process  of  moral 
education in colleges and universities. 
(3)  Moral  education  educators  do  not  pay 
enough  attention to  information processing and  the 
information technology level is not high 
Although  the  information  technology  develops 
rapidly,  the  information  technology  level  of  moral 
education  educators  in  colleges  and  universities  is 
not  good,  and  they  also  lack  special  information 
technology  ability  training.  In  addition,  moral 
education  educators  in  colleges  and  universities 
have  weak  awareness  of  digitized  information. 
Some moral education educators still use traditional 
information processing methods, such as simple use 
of office software such as word, excel and slide, and 
lack  of  understanding  of  information  technology 
such as big data, data mining and cloud computing. 
In the face of massive moral education information 
resources, many moral education educators can not 
effectively  process  and  use  moral  education 
information resources. 
3  INFORMATION PROCESSING 
MODEL CONSTRUCTION 
3.1  Purpose of Model Building 
The  information  processing  model  constructed  in 
this  study is  to convert  image information  and text 
information  related  to  moral  education  in  colleges 
and  universities  into  data,  and  analyze  the 
dissemination trend of moral education information 
according to the output of data, so as to understand 
which moral education information is more popular 
among  educators  and  educators.  Then  we  should 
consider the current trend of information technology 
of moral  education in colleges  and universities and 
take corresponding measures to avoid the 
marginalization  of  effective  moral  education 
information.  At  the  same  time,  according  to  the 
development  of  moral  education  in  colleges  and 
universities, combined with the current popular new 
media, moral education information will  be pushed 
to  moral  education  educators  and  educated  in  the 
form  of  network  tweets,  audio,  short  videos,  etc., 
and moral education information exchange platform 
will  be  built  to  interact  with  the  majority  of 
educators and educated. In a word, the combination 
of  information  technology  and  moral  education  in 
colleges  and  universities  is  conducive  to  the 
dissemination  and  sharing  of  valuable  moral 
education information. 
3.2  Approach to Model Building 
(1) Data mining 
Under  the  condition  of  information  technology, 
with the help of big data, a large amount of moral 
education  data  information  with  potential 
educational  value  can  be  mined  from  massive 
information. Using key words to carry out data 
mining  can  not  only  search  for  accurate  and 
comprehensive  moral  education  information, 
all-round  display  of  moral  education  related 
information  resources,  but  also  improve  the  speed 
and  efficiency  of  information  acquisition,  so  as  to 
provide an important guarantee for the effectiveness 
of moral education. 
(2) Digitized of text 
Digitized of  text is  to combine text information 
with moral language and convert it into data, so as 
to  solve  comprehension  problems  caused  by  the 
complexity  of  text  expression  through  text 
information  processing.  Digitized  of  text  is  mainly 
to extract the key words and statistical word 
frequency  of  moral  education.  Among  them,  key 
words  are  filtered  out  without  distinction  and 
important  words  are  retained.  Statistical  word 
frequency  is  mainly  to  count  the  frequency  of  a 
word  in  the  keyword  database.  The  type  of 
statistical  graph  can  be  selected  as  needed,  and  its 
purpose  is  to  visualize  the  data.  The  efficient,  fast 
and  accurate  information  data  processing  provides 
technical  support  for the  information  processing  of 
moral education in colleges and universities. 
(3) Image description 
Image description is a combination of computer 
vision  and  natural  language.  Image  description  is 
similar  to  "look  at the picture to talk",  which  is  to 
show  the  content  information  conveyed  by  the 
picture  by  describing  the  picture.  Although  image 
description  is  subjective,  it  is  also  objective  under 
the  condition  of  information  technology.  Using 
information technology to describe pictures can deal 
with  the  problem  of  "semantic  gap"  in  the  process 
of  information  dissemination,  so  as  to  provide 
technical  support  for  the  effect  of  moral  education 
in colleges and universities. 
3.3  Information Processing Model and 
Workflow 
The  traditional  information  transmission  mode  of 
moral  education  is  a  one-way  education  mode  (as