Construction of a Balanced Development Evaluation Index System
Based on Big Data Analysis and Clustering Extraction Algorithms
Liangbing Gong
Ministry of Public Education & Department of Physical Education, Jiangxi Vocational Technical College of Industry &
Trade. Nanchang, 330038, China
Keywords: Clustering Extraction Algorithm, Balanced Development, Physical Education Assessment.
Abstract: There are unreasonable gaps in educational resources, teaching quality, educational results, etc. between urban
and rural areas, between regions, and among schools at different levels in a region. The balanced growth of
education needs constant decision-making and adjustment, and the assessment activity serves for decision-
making. It can provide information and reflect the reality. As a part of education, school physical education
(PE) should also take balanced development as its value orientation. Assessing the validity of clustering
results is a complex problem. This article puts forward an assessment algorithm of PE based on clustering
extraction algorithm, which provides technical support for the construction of assessment index system of
balanced growth of sports. The experimental results show that the model has high recall and accuracy, and
the accuracy is improved by 19.64% compared with the traditional assessment algorithm. Combining the
fuzzy assessment model with qualitative assessment, the assessment of PE class teaching in universities can
better reflect the situation of the assessd object, realize the unity of fuzziness and accuracy in the assessment
process, and provide a meaningful reference for the construction of the assessment index system of balanced
growth of sports.
1 INTRODUCTION
Promoting social justice is the essential task and core
value of building a harmonious socialist society, and
social justice contains fair contents in different fields
(De-Kun, Memon et al. 2022). Among them,
educational equity is the foundation of the social
equity system. If educational equity can't be realized,
social equity will lose its premise guarantee.
Constantly promoting education equity is an
important task of education in China at present.
Education equity is the foundation and guarantee of
social equity, which is in line with the overall
interests of China society (Liu, 2020). Assessment
comes into being with the growth of human social
activities. In order to manage, a series of assessments
should be conducted. Assessment widely exists in all
fields of social life. Such as the performance appraisal
of teachers' teaching and the appraisal of employees'
working ability (Lee, Lee, et al. 2021). For a long
time, assessment mainly depends on people's
experience, which belongs to the category of
experience assessment. PE assessment is an important
link in PE, which is to make an objective and
scientific judgment on the value of PE process and its
effect based on the acquired PE information (Da-Wei
Chao, et al. 2018). The current general mode of PE
class teaching assessment in universities lags behind,
which has become one of the main obstacles
restricting the reform of PE in universities. The
reform of teaching assessment in PE class is
imperative (Chen, and Yu, 2022). Therefore, it is very
important to construct a new teaching assessment
system with strong operability and in line with the
current growth of PE.
As an integral part of school education, school PE
plays an important role in promoting teenagers'
physical health, cultivating teenagers' good moral
character and will quality, and helping teenagers to
master sports knowledge and skills (Wang, 2019).
Promoting educational equity is the foundation and
premise of realizing social equity. If education,
especially basic compulsory education, can't develop
in a balanced way, the ideal of educational equity can
only be a castle in the air, and social equity is even
more impossible to talk about (Liu, 2021). What and
how to assess PE is directly related to the realization
of PE teaching objectives and the direction and idea
128
Gong, L.
Construction of a Balanced Development Evaluation Index System Based on Big Data Analysis and Clustering Extraction Algorithms.
DOI: 10.5220/0013536700004664
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 1, pages 128-133
ISBN: 978-989-758-763-4
Proceedings Copyright © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

of PE teaching (Han, 2022). The current teaching
assessment model of PE class in universities has
serious deviations from the assessment contents,
objectives and ideas, and there are some problems,
such as narrow assessment contents, single
assessment methods and outdated assessment tools
(Chen, 2018). It's inevitable that there will be major
mistakes in the assessment based on one's knowledge,
experience, wisdom and courage. This is mainly
because the same thing has many attributes and is
influenced by many factors (Kong, and Cao, 2017).
With the deepening of science and technology, the
research object is becoming more and more complex,
and the complex things are difficult to express
accurately. In order to assess things objectively and
fairly, the fuzzy comprehensive assessment method
appears. This article tries to put forward an
assessment algorithm of PE teaching based on
clustering extraction algorithm under the theoretical
framework of educational equity, so as to provide
technical support for the construction of assessment
index system of balanced growth of PE.
2 METHODOLOGY
2.1 Assessment Significance of
Balanced Growth of Sports
The mother of the balanced growth of school PE is
the balanced growth of school education. The
research on the balanced growth of school PE should
belong to the theoretical research of the balanced
growth of school education. The foundation and
guarantee of the balanced growth of school PE is the
balanced growth of school education. Assessment of
the balanced growth of school education and
assessment of the balanced growth of school PE are
both related and subordinate, but also have great
differences. In the field of natural science,
equilibrium or balance is often used to describe the
equal distribution of the basic quantity of a thing or
system state in all parts of a thing. In philosophy and
social sciences, balance is a category that represents
the state of coordinated movement of differences
between things. It is used to describe the state of
mutual connection and restriction between things, and
emphasizes the balance and coordination between the
parts of things or systems. As a subsystem of school
education, school PE should be more specific and
closer to the actual operation (Gao, 2022). The main
particularity of school PE is that it has more abundant
physical activities, while PE activities are mainly
carried out in the basic way. The more open nature of
the course puts forward special requirements for the
growth of the course. Educational equity can't be
understood as the equality of educational
opportunities, but it should also involve the equality
of resources allocation, educational results and
educational environment in the process of education.
The law of material restriction of school PE
development has never been well understood, which
is one of the main reasons why school PE in China
has not been greatly developed so far. Compared with
other components of school education, school PE is
much more restricted by material conditions. The
basic system of PE assessment is shown in Figure 1.
Figure 1: Basic system of PE teaching assessment
The assessment index should objectively reflect
the concept and quantitative expression of a certain
characteristic of the assessment object, which has
both quantitative and qualitative manifestations. The
assessment index can reflect the quantity of the
assessment object and explain a certain characteristic
of the assessment object. Depending on the purpose
of assessment, a series of relatively complete and
interrelated assessment indexes that can
comprehensively and systematically reflect a specific
assessment object are the assessment index system.
The balanced growth of education refers to the
balance between the supply and demand of education
from the social level, the balance of the allocation of
educational resources from the economic level, and
the balance throughout the school education process
from the inside of the education system, including the
balance between different schools in terms of the
allocation of teachers, educational results and
educational assessment (Ou, and Tan, 2017). School
PE assessment is not only the assessment of
education, but also the assessment of sports field, and
the assessment researchers in sports field should have
a certain depth and breadth of relevant theoretical
knowledge in education and sports field. Only by the
perfect combination of the two can the structure of the
assessment index system be clear and the logical
Construction of a Balanced Development Evaluation Index System Based on Big Data Analysis and Clustering Extraction Algorithms
129

relationship of the assessment index system be
scientific and reasonable.
2.2 Assessment Algorithm of PE
Teaching
On the dimension of teachers, the degree of teachers'
research on PE in universities, teachers' self-learning
ability, lesson preparation degree, informatization
degree and self-reflection ability all have important
influences on the teaching quality itself. Besides, in
other dimensions, the richness of teaching resources,
the accuracy of teaching assessment, the adequacy of
information equipment, and the readiness of PE
equipment in universities have important influences
on the teaching quality itself. Because there are many
uncertain and complicated factors in the process of
PE teaching assessment, the assessment method is a
nonlinear problem. The assessment of PE teaching
can be regarded as a nonlinear mapping from input to
output. The assessment model of PE based on neural
network and clustering extraction algorithm is shown
in Figure 2.
Figure 2: PE assessment model
The assessment indexes of PE in universities are
divided into 6 first-class indexes and 10 second-class
indexes. Because the magnitude of each component
is very different, it needs normalization:
minmax
min
II
II
X
−
−
=
(1)
Where
X
is the normalized neural network input
value,
I
is the untreated neural network input value,
and
max
I
is the minimum neural network input value.
In the application of data, it is necessary to further
uphold diversified management measures to
comprehensively promote the application and
management of big data in PE. Teachers can provide
all-round early warning for students with the help of
teaching assessment system, monitor students' PE
learning achievements and learning efficiency in real
time, further improve teachers' classroom design with
the help of big data information, and
comprehensively improve the quality and efficiency
of PE.
In the form of assessment of teaching quality, we
should not only focus on teachers, but also assess the
quality of classroom teaching from the perspective of
the educated (Hu, 2021). The construction of big data
assessment system for PE teaching can not only make
teachers feel the charm and value of big data, but also
play an important role in promoting the quality of PE
teaching. Let an attribute
A
take
v
different values
{}
vi
aaa ,,,
2
…
.
j
S
contains the data sample of
attribute
A
taking
j
a
in the set. If attribute
A
is
selected as the test attribute, let
ij
s
be the number of
samples belonging to
j
C
category in subset
j
S
.
Then the information entropy required to divide the
current sample set by using the attribute
A
can be
calculated as follows:
()
()
mjj
v
j
mjjj
ssI
s
sss
AE ,,
1
1
21
…
+…++
=

=
(2
)
Among them, the
S
sss
mjjj
+…++
21
term is
regarded as the weight of the
j
-th subset, which is
the sum of the samples whose
j
a
values are taken by
the attributes
A
in all subsets divided by the total
number of samples in the set. The information for a
given subset
j
S
is:
()()

=
−=…
m
i
ijijmjjj
ppsssI
1
21
log,,,
(3
)
Among them:
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j
ij
ij
S
s
p =
(4)
The assessment index system is the most critical
part of the whole assessment activity, and it is the
yardstick for the actual operation of the assessment
work. Therefore, whether the assessment can be
carried out reasonably and effectively so as to achieve
the assessment goal depends first on whether the
assessment index system itself is scientific and
reasonable. Only by using a relatively scientific and
reasonable assessment index system can the
assessment results be more accurate and effective.
3 RESULT ANALYSIS AND
DISCUSSION
The assessment index system is the yardstick to
measure the school PE work, so the scientificity of the
assessment index system should be considered in the
process of constructing the assessment index system.
Only the data assessd by the scientific and reasonable
assessment index system can be scientific and
reasonable. The social environment in which school
PE is carried out has a very important influence on
school PE, so the difference of social environment in
which school PE is carried out will inevitably be
reflected in the effect of school PE. For example, the
satisfaction of sports venues and equipment, students'
sports interests, the implementation of PE and other
indicators that involve subjective feelings or cannot
be directly quantified. In the process of teaching
assessment, the application of fuzzy mathematics
assessment model has the advantages of reasonably
quantifying the original assessment indexes which are
difficult to quantify, and displaying the assessment
results in numerical values. Its synthetic operation
method can ensure the integrity of the new
assessment information to the greatest extent, and
make the assessment results more reasonable and fair.
Figure 3 shows teachers' subjective rating data of
different PE assessment methods.
Figure 3: Teachers' subjective rating
Most teachers said that PE assessment based on
data mining can effectively reflect the students'
situation. The assessment index system should be
predictable, that is, the indicators should reflect the
future development direction of school PE, and play
an early warning and guiding role in the growth of
school PE. The fundamental purpose of assessment is
to achieve a balanced growth of school PE, and it is
necessary to find and solve the gaps in the
assessment, so as to promote the growth of school PE.
However, these variables have a certain dependence
on each other, that is, there is often a certain degree
of correlation between them, sometimes even quite
high correlation, which makes the information in the
observed data overlap to some extent.
Big data is introduced into the assessment system
of higher education quality. By collecting, mining and
analyzing the data of the whole teaching process, and
using the results to provide rational basis and
scientific decision-making for the improvement of
higher education quality, the whole process, multi-
level, multi-channel and multi-functional assessment
of higher education quality can be realized. The
framework of the assessment index system of PE in
universities determines the specific content of
teaching assessment. When using big data technology
to construct the assessment system of PE, in the
selection and framework of assessment indicators, we
should not only follow some basic construction
principles, but also strive to form a progressive,
rigorous and orderly hierarchical structure within the
assessment system. To realize the intelligent
innovation of PE with the support of big data,
teachers must learn to use data to analyze and solve
problems. The assessment accuracy results of
different models are shown in Figure 4. The recall
rate of the algorithm is shown in Figure 5.
Construction of a Balanced Development Evaluation Index System Based on Big Data Analysis and Clustering Extraction Algorithms
131

Figure 4: Assessment accuracy results of different models
Figure 5: Recall results of different algorithms
The results show that the model has a high recall
and accuracy, and the accuracy is increased by
19.64% compared with the traditional assessment
algorithm. As for the assessment content of PE
teaching quality, besides referring to the important
data such as students' average PE score, the number
of students' participation and the excellent rate of PE
results as the basic basis for assessment, it is also
necessary to comprehensively examine students'
comprehensive qualities, such as teamwork spirit,
class cohesion and collective sense of honor among
students.
School PE is not only an important part of
education, but also an integral part of PE. Therefore,
the balanced development assessment of school PE is
a comprehensive assessment, which includes not only
the content of educational assessment, but also the
assessment in the field of PE in terms of subject
characteristics. On the whole, the index system
should be able to reflect the four aspects of school PE
resources, school PE process, school PE results and
school PE social environment and the contents of its
sub-indexes, so as to reflect the balanced level and
degree of school PE development. Only in this way
can we comprehensively and objectively assess the
present situation of the balanced growth of school PE.
4 CONCLUSIONS
As an integral part of school education, school PE
plays an important role in promoting teenagers'
physical health, cultivating teenagers' good moral
character and will quality, and helping teenagers to
master sports knowledge and skills. PE assessment is
an important link in PE, which is to make an objective
and scientific judgment on the value of PE process
and its effect based on the acquired PE information.
This article tries to put forward an assessment
algorithm of PE teaching based on clustering
extraction algorithm under the theoretical framework
of educational equity, so as to provide technical
support for the construction of assessment index
system of balanced growth of PE. The results show
that the model has a high recall and accuracy, and the
accuracy is increased by 19.64% compared with the
traditional assessment algorithm. The assessment
results of this algorithm are more in line with the
actual situation and have good practicability. When
there are many assessment indexes, this algorithm is
more superior. What and how to assess PE is directly
related to the realization of PE objectives and the
direction and concept of PE. The ultimate goal of the
assessment index system of balanced growth of
school PE is to adjust and control the weak schools
by government means after the assessment results
come out, so as to ease the contradictions and reflect
social equity and harmonious social development to
the greatest extent.
REFERENCES
De-Kun J, Memon F H. Design of Mobile Intelligent
Evaluation Algorithm in Physical Education Teaching.
Mobile Networks and Applications, vol. 27, no. 2, pp.
527-534, 2022.
Liu Y R. An artificial intelligence and machine vision based
evaluation of physical education teaching. Journal of
Intelligent and Fuzzy Systems, vol. 40, no. 1, pp. 1-11,
2020.
Lee H S, Lee J. Applying Artificial Intelligence in Physical
Education and Future Perspectives. Sustainability, vol.
13, no. 1, pp. 351, 2021.
Da-Wei C, Chao L, Shun W, et al. Research and application
of multimedia digital platform in the teaching of college
physical education course. Journal of Intelligent and
Fuzzy Systems, vol. 34, no. 2, pp. 893-901, 2018.
Chen X K, Yu J. Evaluation Model of Physical Education
Integrated Ideology and Politics Based on Principal
Component Analysis. Mobile Networks and
Applications, vol. 27, no. 3, pp. 1240-1251, 2022.
Wang Y. The automatic evaluation model of physical
education teaching based on two screening algorithms.
INCOFT 2025 - International Conference on Futuristic Technology
132

Journal of Intelligent and Fuzzy Systems, vol. 37, no. 5,
pp. 5945-5953, 2019.
Liu S. Research on the teaching quality evaluation of
physical education with intuitionistic fuzzy TOPSIS
method. Journal of Intelligent and Fuzzy Systems, vol.
40, no. 5, pp. 1-10, 2021.
Han Q. Using neural network for the evaluation of physical
education teaching in universities. Soft Computing, vol.
26, no. 20, pp. 10699-10705, 2022.
Chen Lianxin. Problems and strategies in evaluation of
physical education teaching in primary schools.
Western Quality Education, vol. 4, no. 5, pp. 2, 2018.
Kong Yong, Cao Chengtao. Research on evaluation of
physical education teaching quality based on
comprehensive evaluation method and SVM.
Microcomputer Application, vol. 33, no. 11, pp. 4,
2017.
Gao Peng. Research on physical education teaching quality
evaluation based on the optimized Apriori algorithm.
Modern Scientific Instruments, vol. 39, no. 1, pp. 189-
193, 2022.
Ou Xianliang, Tan Chuanxin. Thoughts on the optimization
way of college physical education teaching evaluation
under the new teaching concept. Contemporary Sports
Science and Technology, vol. 7, no. 3, pp. 2, 2017.
Hu Liwu. Design of Agent-based classification system for
football sports teaching mode. Microcomputer
Application, vol. 37, no. 5, pp. 5, 2021.
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