Access to this full-text is provided by Hindawi.
Download available
Content available from Computational Intelligence and Neuroscience
This content is subject to copyright. Terms and conditions apply.
Research Article
Cognitive Computation in Ideological and Political Classroom
Teaching Based on Digital Sensor Technology
Hong Cai
College of Marxism, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia 010000, China
Correspondence should be addressed to Hong Cai; 20120042@stumail.hbu.edu.cn
Received 2 May 2022; Revised 26 June 2022; Accepted 30 June 2022; Published 18 July 2022
Academic Editor: Muhammad Zubair Asghar
Copyright ©2022 Hong Cai. is is an open access article distributed under the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Numerous new ideas and concepts have changed the behavior and value orientation of university students as a result of the internet’s
rising popularity on college campuses. is study performs research on digital sensor technologies in order to enhance the intelligent
effect of ideological and political classroom instruction. In addition, this study combines the fast Fourier transform principle to
enhance digital sensor technology, digital sensor and cognitive computation technology to investigate the ideological and political
classroom teaching process, and the actual situation of the ideological and political teaching to digitally process the ideological and
political teaching process. In addition, this study employs sensor technology to convey data and digital sensor technology to increase
the quality of ideological and political classroom instruction by enhancing the traditional teaching paradigm. In addition, on this
premise, this study conducts a performance evaluation of the system, primarily focusing on the digital effect and the enhancement of
ideological and political teaching quality. In conclusion, this study proves its teaching system through test research. According to the
test results, the intelligent teaching method described in this study has a certain practical effect.
1. Introduction
e ideological and political theory courses of colleges and
universities undertake the important task of ideological and
moral education for college students, and help college
students to establish a correct outlook on the world, life,
values, ethics, and legal system under the guidance of sci-
entific theories. Judging from the current situation inves-
tigation and analysis, the current overall response of college
students to “ideological and political courses” is not ideal.
e current ideological and political education in colleges
and universities in my country is basically the imple-
mentation of a “unilateral policy,” that is, the main method is
indoctrination and narration, which lacks interest, diversity,
and abstraction. As a result of “indoctrination” with un-
interesting and meaningless theories, some college students
with higher education often have clear discrepancies in their
ideological, political, and ethical standards, and beliefs.
Furthermore, these kids’ “main beliefs” are evident, yet their
daily behaviors are aggravating. ere are many reasons for
the lack of vitality and vitality in the teaching of “ideological
and political courses,” and the combination of many factors
has formed the current situation of disconnection between
the teaching and learning of “ideological and political
courses.” erefore, how to make students pay attention to
ideological and political courses, get innovative thinking and
innovative spirit training and training in ideological and
political courses, and make our ideological and political
education receive good results is a topic that every ideo-
logical and political teacher should think about [1].
With the rapid development of educational informati-
zation, colleges and universities, as the forefront of teaching
and research and the main front of student scientific re-
search activities, are also making great strides to achieve the
goal of informatization campus [2]. Among them, infor-
mation-based teaching provides strong support for char-
acteristic teaching in colleges and universities, and it is also
the key to the overall construction of colleges and univer-
sities. It can be seen that the task of optimizing the campus
network topology system structure and accelerating the pace
of building an informationized campus is imminent [3]. e
application of digital sensor technology has enriched the
Hindawi
Computational Intelligence and Neuroscience
Volume 2022, Article ID 8723327, 12 pages
https://doi.org/10.1155/2022/8723327
teaching tools of high school chemistry and integrated the
experimental methods and experimental contents. e ap-
plication of digital sensor technology has also promoted the
change in teachers’ teaching concepts [4]. In the three-di-
mensional teaching goals proposed in the modern education
reform, students must not only learn knowledge and skills,
but also through the learning process, learn scientific
thinking and methods, and acquire emotional attitudes and
values. Moreover, the introduction of digital sensor tech-
nology not only allows students to acquire knowledge, but
also more importantly, through the process of chemical
experiment inquiry, to learn scientific thinking and research
methods, and to enhance students’ practical ability. In ad-
dition, it better embodies the teaching philosophy of
learning as the main body and teaching as the leading factor,
and at the same time stimulates students’ interest in
chemistry learning, cultivates their pragmatic, rigorous, and
scientific attitude, and enhances students’ scientific literacy.
So far, most schools have conducted research studies on
digital sensor technology instruments, but they have not yet
fully utilized the advantages of digital sensor technology.
How to combine digital sensor technology with high school
chemistry experiments and how to combine digital sensor
technology with student experiments will be the focus of the
next research. is study applies digital sensor technology to
ideological and political classroom teaching, constructs a
system functional structure, and verifies the effect of this
teaching method.
is study uses sensor technology to convey data, and
digital sensor technology, with the goal of improving the
quality of ideological and political classroom learning by
enhancing the paradigm of traditional teaching. In addition,
on the basis of this premise, this study does a performance
evaluation of the system, especially concentrating on the
digital effect and the improvement of the quality of ideo-
logical and political instruction. In conclusion, this study
demonstrates that its instructional methodology is sup-
ported by test research. e findings of the tests indicate that
the intelligent teaching strategy that is discussed in this study
does have some effect in the real world.
2. Related Work
As early as the 20th century, foreign developed countries
began to focus on integrating many advanced technologies
into the education of various subjects such as mathematics,
physics, chemistry, and biology, and such as ICT (infor-
mation and communication) and sensor technology. e
integration of computer-centric information and commu-
nication technology and education has become an important
trend in education reform, and it is also a powerful driving
force for education reform in Western countries (including
education goals, content, methods, and forms) [5].
Western schools have invested a lot of money in ICT
research. Literature [6] studied why teachers participate in
the training of information and communication tech-
nology projects, and found that in addition to their in-
terest, it is more important to help their teaching. Lifelong
learning is particularly important in the rapidly
developing modern society. erefore, ICT on-the-job
training conforms to the requirements of the modern
social and cultural environment.
Sensor technology is one of the three key technologies of
acquisition, processing, and dissemination in information
technology, and many countries classify it as a cutting-edge
technology. e United States claims that the world has
entered the sensor era, and Japan ranks sensor technology as
the top ten technologies [7]. Since the 1980s, it has been
widely used in various levels of education in foreign de-
veloped countries. Sensing technology is used in science
teaching and experimental investigation in middle schools in
the United States, Singapore, and some European countries
and regions [8]. Since the development of sensor technology
abroad, the application research in chemical experiments
has become more and more mature, such as carbon dioxide
sensor, dissolved oxygen sensor [9], and so on. Literature
[10] pointed out that self-sustaining research on oxygen
sensors has led to the development of various applications
and different performance characteristics of the sensors. In
order to meet the needs of teachers and students, the United
States has published many books on the application of digital
sensor technology to middle school chemistry experiments,
such as chemistry with computer (31 experiments), ad-
vanced chemistry with vernier (35 experiments), science
with handhelds (experiment-attached CD), and chemistry
with calculators (36 experiments). ese experimental books
show that the development of digital sensor technology in
the United States is relatively mature, and it has a positive
guiding role in the development and use of digital sensor
technology in our country [11].
A digital experiment based on digital sensor technology
is one that employs a computer as a platform to carry out
chemical tests in real time. It incorporates a wide range of
modern scientific and technological breakthroughs, such as
simulation trials, sensor experiments, and multimedia dis-
plays. Because it is still in its early stages of development, the
present name of this technology in our country is not
standardized. e names of the categories of technology are
“sensing technology,” “handheld technology,” and “hand-
held technology.” e names of the secondary device cat-
egories are “digital exploration laboratory,” “digital
information system (abbreviated as DIS),” “handheld lab-
oratory” [12], and so on. Due to the intuitive “digital” feature
of the technology and the important role played by its key
component “sensor,” it is named digital sensor technology.
Digital sensor technology was introduced to our country at
the beginning of this century, and more and more front-line
teachers began to study digital sensor technology. In order to
objectively understand the hotspots and key points of the
research on chemistry experiment teaching in middle
schools in our country, the literature [13] used relevant
software and tools to sort out and analyze the research
results of a large number of existing middle school chemistry
experiment teaching and drawled the hotspot knowledge
map of its research.
Virtual reality technology has been out of the laboratory
in the 1970s, has been used by people in the application
market, and has been unanimously favored by everyone.
2Computational Intelligence and Neuroscience
erefore, individual countries in the world that have
conducted VR research, especially developed countries, have
taken the lead in conducting extensive research and dis-
cussions on related projects. Some schools abroad have used
VR equipment to do some remote teaching activities. Stu-
dents have provided feedback indicating that the impact of
learning can be more concentrated in some classes due to the
immersion that occurs during the process of using VR
equipment. On the other hand, the experience of teaching in
a traditional classroom setting, such as taking notes, needs to
be more technically correct. However, it is understandable
that if it is truly mature and applied, VR will bring break-
through progress for practical operation and experimental
teaching [14].
3. The Principle and Analysis of Fast
Fourier Transform
e angular frequency of the periodic signal x(t) is
ω�2πf �2π/T; the period is T; and its FFT is transformed
into [15] the following:
x(t) � A0+A1cos ωt+B1sin ωt+A2cos 2 ωt
+B2sin 2 ωt+...
�A0+
∞
h�1
Ahcosh ωt+
∞
h�1
Bhsinh ωt.
(1)
In the above formula, A0�1/TT/2
−T/2 f(t)dtrepresents
the DC quantity of the periodic signal, and the coefficients of
the expression after the FFT transformation of the periodic
signal are Ah and Bh.
Ah �2
TT/2
−T/2
f(t)cosh ωtdt, h �1,2,. . .
Bh �2
TT/2
−T/2
f(t)sinh ωtdt, h �1,2,...
(2)
e above formula (1) can be simplified as follows:
x(t) � C0+
∞
h�1
Chcos hωt+φh
.(3)
In the time domain, two consecutive signals are mul-
tiplied, the result of the multiplication is Fourier trans-
formed, which is equal to the Fourier transform of the
respective sequence, and then, the convolution operation is
performed. After the above analysis, the infinite signal xʹ(n)
is DTFT transformed into the following:
X ejw
�DTFT x′
.(4)
In the above formula (3), C0�A0represents the direct
current, Ch��������
A2
h+B2
h
represents the magnitude of the
periodic signal in the hth harmonic amplitude, and φh�
arc tan(Ah/Bh)represents the magnitude of the periodic
x′(n) x′(ejw)
x (n) x (ejw)
DTFT
(a) (b)
(c) (d)
DTFT
Figure 1: Schematic diagram of spectrum leakage.
Computational Intelligence and Neuroscience 3
signal in the h
th
harmonic phase. When we sample the signal,
we can set Nsampling points, and the sampling frequency is
fs. By sampling the periodic signal, the expression of the
signal in the time domain can be obtained, which is [16] the
following:
x(n) � C0+
∞
h�1
Chcos hωn
fs
+φh
,
n�0,1,..., N −1.
(5)
When performing FFT transformation on a periodic
signal, it is necessary to perform transformation analysis not
only in the time domain but also in the frequency domain, so
that the characteristics of the signal can be better under-
stood. If a continuous signal x(t) satisfies the Dirichlet
condition, then
+∞
−∞|x(t)|dt<∞.(6)
en, the Fourier transform FFT of x(t) is as follows:
X(jω) � +∞
−∞x(t)e−jωtdt. (7)
Its inverse Fourier transform (IFFT) is as follows:
x(t) � 1
2π+∞
−∞X(jω)ejωtdt. (8)
Equations (7) and (8) are a set of FFT transformation and
inverse FFT transformation, where the FFT transformation
obtains the signal’s spectral function, and the inverse FFT
transformation obtains the value of the signal at each time t.
When we uniformly sample the signal, what we need is the
value of each point of the signal. By performing a discrete
Fourier transform on an infinitely long signal, we can get
[17] the following:
X(jω) �
+∞
n�−∞
x(n)e−jωn.(9)
e above formula expresses the result obtained by the
DTFT transformation of an infinitely long signal. is is
mainly suitable for theoretical analysis and not suitable
for calculation and analysis on a computer. erefore, we
need a signal of finite length so that it can be applied in
x (K)
0
K0
x (K)
0
K0
(a)
(b)
Figure 2: Schematic diagram of the fence effect.
Optimized design
Modify and adjust
Feedback modification
Testing and evaluation
Add digital resources
Fix platform framework
Graphic design
Selection of resource content
Audience analysis
Environment configuration
Choose a development tool
Frame construction
Digital resource material
processing
Ideological and political digital teaching resources
Figure 3: Technical roadmap for the construction of a digital
resource platform for ideological and political education.
4Computational Intelligence and Neuroscience
practice. We apply the above formula (9) to a transfor-
mation, the variable ω�2πk/Nis brought into it to obtain
the following:
X(k) �
N−1
n�0
x(n)e−j(2π/N), k �0,1,. . . , N −1.(10)
Formula (10) is the discrete Fourier transform DFT of a
signal x(n) of finite length, and its inverse discrete Fourier
transform is as follows:
x(n) � 1
N
N−1
n�0
X(k)ej(2π/N)nk, n �0,1,. . . , N −1.(11)
e above equations (10) and (11) are the DFT and IDFT
of the finite-length signal x(n), where the DFT transform
obtains the discrete spectrum function of the signal. e FFT
algorithm is widely used in signal analysis. is study applies
the FFT algorithm to the time grid signal acquisition to
reduce the error of its measurement.
When performing FFT transformation on a continuous
signal, in actual operation, only a limited-length signal can
be intercepted for analysis. In this process, some errors will
be brought, that is, spectrum leakage and fence effect.
3.1. Spectrum Leakage. Since only a period of time can be
selected for analysis in actual engineering applications, in
essence, the signal is multiplied by a rectangular window
function to obtain a finite-length signal x(n). at is, the
infinite signal xʹ(n) is limited to 0 ≤n≤N−1. e frequency
density function of the rectangular window is [18] as follows:
WRejω
�DTT RN(n)
�sin(ωN/2)
sin(ω/2)e−j(N−1/2)ω.(12)
In the time domain, two consecutive signals are mul-
tiplied, and the result of the multiplication is Fourier
transformed, which is equal to the Fourier transform of the
respective sequence, and then, the convolution operation is
performed. After the above analysis, the infinite signal xʹ(n)
is DTFT transformed into the following:
X ejω
�DTFT x′(n)RN(n)
�1
2ππ
−π
X′e−jθ
WRej(ω−θ)
dθ.
(13)
Figure 1 shows the schematic diagram of frequency
leakage. In Figures 1(a) and 1(b), it can be seen that there is
no leakage of the spectrum when an infinitely long signal is
Human-computer interaction system
Video transmission system
Document Resource System
Remote control system
Automatic simulation system
Real-time interactive system
Learner Teachers, trainers
Learning system Teaching system
Communication and discussion tools
Teaching resource
editing and
production tool
system
Literature, video search
Teaching Evaluation System
Figure 4: e overall model diagram of the digital resource platform for ideological and political classroom teaching.
Computational Intelligence and Neuroscience 5
converted by DTFT. However, in Figures 1(c) and 1(d), it
can be seen that after the infinite signal is truncated, when
the obtained finite signal is subjected to DTFT conversion,
the leakage of the spectrum occurs [19].
3.2. Fence Effect. When using the FFT algorithm to analyze
a signal, the continuous frequency spectrum of the signal
must be discretely sampled at equal intervals. When the
continuous spectral density function X(jω) is uniformly
sampled, X(k) is obtained through discrete Fourier
transform (DFT). Figure 2 shows the schematic diagram of
the fence effect. In the process of signal sampling, ideally
the sampled spectrum is just the desired target spectrum so
that the parameter values of the spectrum can be easily
obtained. However, in actual situations, it is very difficult
for the sampled spectrum to coincide with the target
spectrum. In fact, there will be a certain distance from the
target curve. In this way, many frequency points will be lost
and a fence effect will appear. As shown in Figure 2(a), in an
ideal situation, the sampled spectral line k
p
is just the
desired target spectral line K
0
so that the parameter values
of the K
0
spectral line can be easily obtained. As shown in
Figure 2(b), in the actual situation, the sampled spectral
line k
p
and the desired target spectral line K
0
are not to-
gether, and there is a certain distance. In order to reduce
the fence phenomenon, we can appropriately increase the
number of sampling points, which can reduce the distance
between the sampled spectral lines, make the sampled
spectral lines closer to the target spectral line, and improve
the sampling accuracy [20].
4. Ideological and Political Classroom Teaching
System Based on Digital Sensor Technology
e ideological and political education digital resource
platform’s technical route primarily consists of resource
content selection, audience analysis, environment configu-
ration, development tool configuration, framework con-
struction, and the processing of digital resource material,
graphic design, network addition of materials, testing and
evaluation, modification, optimization, and other 13 tech-
nical links. rough the analysis of the technical route, the
Ideological and political digital resource platform
Teacher teaching Student learning Resource search Online interaction
Teacher teaching
goals
Student learning
goals Site Search Teacher-student
interaction
Teacher Teaching
Plan Self-learning Related websites
Interaction
between students
and students
...... Environmental
creation Link search Leave a message
online
Figure 5: e learning mode of the digital resource platform for ideological and political classroom teaching.
6Computational Intelligence and Neuroscience
system construction resource platform is shown in Figure 3
[21].
A blueprint for the creation of a digital resource platform
for the ideological and political education of students in the
classroom is conceived and developed on the basis of un-
mistakable design principles and concepts. e resource
library system and the support system for the platform are
the primary components of the model. e primary com-
ponents of the support system are the learning system and
the teaching system, both of which encompass various as-
pects of education and scientific research and text resource
library, picture resource library, video resource library,
animation resource library, and resource retrieval system
with the theme of each resource library that are the main
components of the interactive system that make up the
resource library system. Together, these components form a
resource data platform that integrates storage, calling, and
management. ere is a connection between each resource
library and network system, and between the learning
system, teaching system, teaching resource editing system,
and the production system. e back-end management of
the system platform must meet stringent standards if the
digital resource platform for ideological and political edu-
cation in the classroom is to function without hiccups.
Ideological and political classroom teaching digital resource
platform management system includes teaching manage-
ment (teacher management, student management, etc.),
resource library management (text, pictures, video, ani-
mation, data and other resources, network teaching resource
management system, and related personal information
management system), and system management (security
management, performance management, access user per-
sonal information management, fault management, etc.).
e overall model of the digital resource platform for
ideological and political classroom teaching constructed in
this research is as follows (Figure 4).
e learning mode of the digital resource platform for
ideological and political classroom teaching is shown in
Figure 5.
e production and development of the digital resource
platform for ideological and political classroom teaching
mainly include six stages: analysis and topic selection, design
and planning, character resource collection and sorting,
processing and production, platform construction, and
evaluation and modification, as shown in Figure 6.
Audio, video, and video materials are the correct way to
display the correct technical actions with background
sounds and the combination of audio and video. e video
part of the resource platform comes from the TV collection
and self-recorded technical and tactical video pictures,
Analysis and topic selection
Design and planning
Digital resource collection and sorting
Manufacture
Platform construction
Test evaluation correction
Figure 6: e development stage of the digital resource platform
for ideological and political classroom teaching.
Ideological and
political digital
communication
platform
Audience analysis
System framework construction
Platform art design
Digital resource processing and addition
Platform application testing
Platform feedback correction
Create a social account
Figure 7: e design stage of the WeChat platform of digital
resources for ideological and political classroom teaching.
Computational Intelligence and Neuroscience 7
which are self-shooting videos and from the internet.
Among the channel guidance, audio and video digital re-
sources use three storage formats, namely, AVI format,
MPEG format, and streaming media format. e AVI
format is used in the computer system, the MPEG format is
used to separately enjoy larger video materials, and the
streaming media format is used for real-time transmission
and provision of video materials for real-time teaching on
the internet and WeChat platform.
e animation materials of the resource platform are
based on the characteristics of ideological and political
teaching, and the video materials are analyzed and compared
[22, 23]. e use of animation materials can more intuitively
show the changes in ideological and political teaching in a
two-dimensional space. e formats used for animation
materials are GIF format, flash format, AVI animation
format, and FLI/FLC animation format. e development of
ideological and political classroom teaching resource con-
struction network platform and WeChat platform mainly
provide a complete set of network support for ideological
and political teaching. Users upload instructional videos
through the network platform. When the videos of in-
struction have been properly uploaded, any user will be able
to view them, learn from them, and comment on them
Ideological and political digital platform
Education resources
Coaching world
Interactive teaching
My main
Teaching method
Video resource
Teaching plan
Student
Management
Student feedback
Working
arrangements
Teaching
counseling
Teaching feedback
Education
resources
Homework
resources
Role release
Job approval
Figure 8: e framework structure of the WeChat public platform of the digital resource platform for ideological and political classroom
teaching.
8Computational Intelligence and Neuroscience
through the network. Students’ time is saved because the
construction of online teaching resources organizes tech-
nologies, theories, and cutting-edge consultations in detail.
is not only achieves the purpose of allowing students to
learn whenever and wherever they want, but it also makes it
easier for students to quickly learn new skills and master new
knowledge. Teaching information may be more quickly and
easily sent through the network platform and the WeChat
platform, and students can receive personalized instruction
and guidance through one-on-one interactions with their
teachers, as shown in Figure 7.
e framework structure of the WeChat public platform
of the digital resource platform for ideological and political
classroom teaching is shown in Figure 8.
e text material is as follows: it is mainly composed of
textual materials summarized, edited, written, sorted, and
collected from the collected research results related to
ideological and political movements. Picture material is as
follows: it mainly comes from self-photographed, internet,
and ideological and political-related magazine pictures, and
relatively accurate and high-resolution pictures of compe-
titions and exercises. Moreover, according to the needs of
the page, the pictures are processed and organized in a
unified manner by using tools. Video material is as follows: it
is a way of intuitive display of reasonable technical means.
e video part of the WeChat platform of ideological and
political classroom teaching digital resources comes from
the collection of the internet and self-recorded technical and
tactical video pictures.
e client is unique to each user, is used to conduct
front-end functions, and because of its high reaction speed, it
can fully utilize the client PC’s processing resources. e
client can handle a large amount of work before submitting it
to the server. is system’s student terminal primarily
performs the following functions. (1) e student terminal
validates fingerprint data. To begin, the teacher must launch
the teaching assistant system service, and students must
check attendance using the USB-connected fingerprint
collector, log in to the student terminal, and enter the
student ID, password, and fingerprint attendance infor-
mation to gain access to the teaching assistant system.
Following successful authentication, the interface will reveal
student information such as student ID, name, test time, and
other details. When the teacher prepares for the test, he or
she sets up the corresponding test paper, on which the pupils
can answer the questions. e setting status is waiting for the
test when it has been performed. When the status is set to
“start of test,” students can begin answering questions. (2)
Students’ classroom tests. To control the start of the ex-
amination, the teacher configures the test room, students,
and test paper information on the server. After completing
the related subjective and objective questions, students can
submit their responses when the examination begins. If
students come across unclear questions, they can mark them
first and then return to respond once they have completed
the confirmed questions.
e login module is mainly responsible for the func-
tions of student login identity verification and authoriza-
tion confirmation. Students taking the examination must
log in on the student side. Before logging in, first, the
teacher needs to make relevant configurations in the
teacher’s backend, that is, to provide the students with the
login permission for the examination. Second, students
must first enter their fingerprint information into the
teacher’s computer through the fingerprint collector to save
it. e login process is shown in Figure 9.
5. Performance Analysis of Ideological and
Political Classroom Teaching System
Based on Digital Sensor Technology
is study constructs an ideological and political digital
teaching system based on digital sensor technology, and uses
digital sensor technology to improve the traditional teaching
model to improve the quality of ideological and political
classroom teaching. On this basis, this study conducts a
performance test on the system, which mainly analyzes the
Start
Student enters identity information
Verify completeness
Data and content addition
Determine whether
the conditions are
met
Enter the main interface
Yes
Yes
No
No
Figure 9: Login flowchart.
Computational Intelligence and Neuroscience 9
digital effect and the improvement of the quality of ideological
and political education. First, this study evaluates the digital
effect of ideological and political classrooms, and obtains the
results shown in Table 1 and Figure 10.
From the above experimental research, we can see that
the ideological and political digital teaching system con-
structed in this study can reliably transform the ideological
and political classroom teaching into a digital mode.
Afterward, the ideological and political teaching system
based on digital sensor technology is evaluated for teaching
effect, and the results obtained are shown in Table 2 and
Figure 11 below.
From the above experimental research, we can see that
the ideological and political classroom teaching system
based on digital sensor technology constructed in this study
has certain value.
Table 1: Statistical table of evaluation of digital effect of ideological and political classroom.
Number Digitizing Number Digitizing Number Digitizing
1 95.3 28 91.6 55 95.0
2 93.2 29 88.3 56 95.2
3 93.9 30 96.1 57 88.7
4 87.7 31 94.0 58 83.2
5 88.5 32 93.9 59 91.9
6 88.2 33 92.7 60 90.6
7 94.4 34 88.9 61 85.7
8 89.9 35 86.3 62 87.0
9 96.3 36 88.1 63 82.8
10 96.6 37 89.6 64 86.2
11 88.0 38 89.8 65 85.4
12 93.8 39 84.2 66 96.8
13 88.6 40 91.5 67 87.4
14 89.5 41 92.7 68 91.9
15 93.4 42 82.3 69 83.7
16 92.8 43 86.1 70 93.2
17 83.3 44 96.4 71 86.9
18 86.5 45 86.7 72 90.7
19 83.1 46 88.5 73 96.9
20 82.2 47 83.2 74 95.9
21 94.5 48 85.7 75 96.4
22 94.8 49 94.1 76 88.7
23 93.0 50 85.0 77 90.9
24 91.9 51 96.5 78 84.2
25 92.1 52 89.4 79 90.9
26 91.2 53 88.3 80 91.4
27 86.2 54 86.4 81 90.2
70
75
80
85
90
95
100
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81
Digitizing
Figure 10: Statistical diagram of evaluation of digital effect of ideological and political classroom.
10 Computational Intelligence and Neuroscience
6. Conclusions
It is now a problem that needs to be studied and resolved as
quickly as possible. is problem is how to reform the
teaching of ideological and political theory courses that are
offered in colleges and universities so that they can occupy
the position of network ideological and political education
and improve the pertinence and effectiveness of ideological
and political teaching. Based on the findings of the inquiry
and analysis of the existing situation, it appears that the
current response of college students as a whole to “ideo-
logical and political courses” is not the optimal answer. e
ideological and political education that is currently being
provided in the higher education institutions of our nation is
essentially the implementation of a “unilateral policy.” is
means that the primary method of instruction is indoctri-
nation and narration, which is devoid of interest, diversity,
and abstraction. Some college students with higher educa-
tions have clear ideological, political, ethical, and value
contradictions as a result of the “indoctrination” of boring
and empty theories. is is often the result of the “indoc-
trination” of boring and useless theories. In addition, the
“main ideas” that these kids adhere to are unmistakable, yet
the daily actions that they exhibit are exasperating.
Data Availability
e data used to support the findings of this study are in-
cluded within the article.
Conflicts of Interest
e authors declare that there are no conflicts of interest
regarding this work.
References
[1] W. Alhalabi, “Virtual reality systems enhance students’
achievements in engineering education,” Behaviour & In-
formation Technology, vol. 35, no. 11, pp. 919–925, 2016.
[2] M. S. Elbamby, C. Perfecto, M. Bennis, and K. Doppler,
“Toward low-latency and ultra-reliable virtual reality,” IEEE
Network, vol. 32, no. 2, pp. 78–84, 2018.
[3] M. Farshid, J. Paschen, T. Eriksson, and J. Kietzmann, “Go
boldly!” Business Horizons, vol. 61, no. 5, pp. 657–663, 2018.
[4] D. Freeman, S. Reeve, A. Robinson et al., “Virtual reality in the
assessment, understanding, and treatment of mental health
disorders,” Psychological Medicine, vol. 47, no. 14,
pp. 2393–2400, 2017.
[5] M. C. Howard, “A meta-analysis and systematic literature
review of virtual reality rehabilitation programs,” Computers
in Human Behavior, vol. 70, pp. 317–327, 2017.
[6] L. Jensen and F. Konradsen, “A review of the use of virtual
reality head-mounted displays in education and training,”
Education and Information Technologies, vol. 23, no. 4,
pp. 1515–1529, 2018.
[7] H. K. Kim, J. Park, Y. Choi, and M. Choe, “Virtual reality
sickness questionnaire (VRSQ): motion sickness measure-
ment index in a virtual reality environment,” Applied Ergo-
nomics, vol. 69, pp. 66–73, 2018.
[8] E. A. L. Lee and K. W. Wong, “Learning with desktop virtual
reality: low spatial ability learners are more positively af-
fected,” Computers & Education, vol. 79, pp. 49–58, 2014.
[9] G. Makransky, T. S. Terkildsen, and R. E. Mayer, “Adding
immersive virtual reality to a science lab simulation causes
more presence but less learning,” Learning and Instruction,
vol. 60, pp. 225–236, 2019.
85
86
87
88
89
90
91
92
93
94
95
15913 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81
Teaching effect
Figure 11: Statistical diagram of the evaluation of the teaching
effect of the ideological and political classroom system based on
digital sensor technology.
Table 2: Statistical table of the evaluation of the teaching effect of
the ideological and political classroom system based on digital
sensor technology.
Number Teaching
effect Number Teaching
effect Number Teaching
effect
1 89.2 28 91.6 55 88.1
2 93.0 29 90.0 56 88.6
3 91.7 30 92.4 57 93.3
4 90.2 31 90.6 58 92.6
5 92.6 32 92.1 59 90.0
6 88.8 33 93.9 60 91.1
7 89.5 34 91.2 61 93.3
8 89.2 35 92.5 62 92.4
9 90.5 36 92.6 63 88.0
10 93.6 37 88.6 64 93.3
11 92.3 38 90.9 65 88.2
12 90.9 39 89.1 66 92.5
13 89.7 40 93.1 67 92.8
14 92.4 41 92.5 68 88.8
15 88.5 42 90.2 69 91.5
16 91.8 43 93.5 70 90.9
17 89.2 44 91.3 71 89.8
18 89.9 45 91.9 72 89.2
19 92.1 46 91.5 73 93.8
20 92.2 47 93.6 74 91.8
21 88.4 48 89.8 75 93.1
22 92.5 49 88.1 76 92.4
23 89.5 50 92.7 77 90.1
24 93.0 51 91.8 78 90.3
25 93.2 52 92.2 79 88.9
26 91.0 53 94.0 80 88.2
27 89.8 54 89.1 81 93.0
Computational Intelligence and Neuroscience 11
[10] N. Morina, H. Ijntema, K. Meyerbr¨
oker, and
P. M. Emmelkamp, “Can virtual reality exposure therapy
gains be generalized to real-life? A meta-analysis of studies
applying behavioral assessments,” Behaviour Research and
erapy, vol. 74, pp. 18–24, 2015.
[11] M. A. Muhanna, “Virtual reality and the CAVE: taxonomy,
interaction challenges and research directions,” Journal of
King Saud University-Computer and Information Sciences,
vol. 27, no. 3, pp. 344–361, 2015.
[12] X. Pan and A. F. Hamilton, “Why and how to use virtual
reality to study human social interaction: the challenges of
exploring a new research landscape,” British Journal of Psy-
chology, vol. 109, no. 3, pp. 395–417, 2018.
[13] G. Saposnik, L. G. Cohen, M. Mamdani et al., “Efficacy and
safety of non-immersive virtual reality exercising in stroke
rehabilitation (EVREST): a randomised, multicentre, single-
blind, controlled trial,” e Lancet Neurology, vol. 15, no. 10,
pp. 1019–1027, 2016.
[14] M. Serino, K. Cordrey, L. McLaughlin, and R. L. Milanaik,
“Pok´
emon Go and augmented virtual reality games: a cau-
tionary commentary for parents and pediatricians,” Current
Opinion in Pediatrics, vol. 28, no. 5, pp. 673–677, 2016.
[15] D. Shin, “Empathy and embodied experience in virtual en-
vironment: to what extent can virtual reality stimulate em-
pathy and embodied experience?” Computers in Human
Behavior, vol. 78, pp. 64–73, 2018.
[16] J. N. A. Silva, M. Southworth, C. Raptis, and J. Silva,
“Emerging applications of virtual reality in cardiovascular
medicine,” Journal of the American College of Cardiology:
Basic to Translational Science, vol. 3, no. 3, pp. 420–430, 2018.
[17] M. Slater, “Immersion and the illusion of presence in virtual
reality,” British Journal of Psychology, vol. 109, no. 3,
pp. 431–433, 2018.
[18] M. J. Smith, E. J. Ginger, K. Wright et al., “Virtual reality job
interview training in adults with autism spectrum disorder,”
Journal of Autism and Developmental Disorders, vol. 44,
no. 10, pp. 2450–2463, 2014.
[19] L. R. Valmaggia, L. Latif, M. J. Kempton, and M. Rus-Calafell,
“Virtual reality in the psychological treatment for mental
health problems: an systematic review of recent evidence,”
Psychiatry Research, vol. 236, pp. 189–195, 2016.
[20] E. Yiannakopoulou, N. Nikiteas, D. Perrea, and C. Tsigris,
“Virtual reality simulators and training in laparoscopic sur-
gery,” International Journal of Surgery, vol. 13, pp. 60–64,
2015.
[21] R. Yung and C. Khoo-Lattimore, “New realities: a systematic
literature review on virtual reality and augmented reality in
tourism research,” Current Issues in Tourism, vol. 22, no. 17,
pp. 2056–2081, 2019.
[22] Y. Wang, “Analysis on the construction of ideological and
political education system for college students based on
mobile artificial intelligence terminal,” Soft Computing,
vol. 24, no. 11, pp. 8365–8375, 2020.
[23] L. Rong, “Design of ideological and political multimedia
network teaching resources integration system based on
wireless network,” Scientific Programming, vol. 2021, Article
ID 4293771, 15 pages, 2021.
12 Computational Intelligence and Neuroscience
