Research on the Application of Fuzzy Comprehensive Evaluation in
the Teaching Performance Appraisal of College Teachers
Fuxing Li
1
and Ke Su
2
1
Qilu University of Technology (Shandong Academy of Sciences), China
2
Shandong Mechanical Design & Research Institute, Jinan, China
Keywords: College Teachers, Teaching Performance, Fuzzy Comprehensive Evaluation, Indicator System,
Improvement and Perfection.
Abstract: As the dominant power of teaching activities, college teachers play an important role in the cultivation
system of higher education. In order to judge the realistic value and potential value of their teaching
activities, it is necessary to evaluate their teaching performance. For explicit content in teaching activities,
quantitative methods can be used to carry out objective assessment; for the work content of implicit aspects,
the objective assessment cannot be carried out directly due to the corresponding fuzzy concept. Therefore, a
comprehensive evaluation method based on fuzzy mathematics is proposed. The indicator system including
explicit and implicit contents is established according to the teaching activities of college teachers; the
typical and authoritative assessment subject is determined; the fuzzy operator and weight value are
reasonably determined through analysis and comparison. The final membership is calculated by using the
above determining factors, and the assessment results of each evaluation object are obtained. In addition, the
corresponding perfect and improved measures are put forward in accordance with the information feedback
of the assessment results to achieve the purpose of stimulating teachers' teaching initiative to improve their
performance, so as to provide methods for the implementation of relevant evaluation activities.
1 INTRODUCTION
College teachers serve as a decisive part in the
smooth implementation of teaching activities.
ZHAO (2011) Apart from the required teaching
workload, they also undertake the formulation of
training programs, curriculum construction, students'
innovative practice guiding and other tasks (ZHAO,
2011).In order to evaluate the teaching performance
of teachers while realizing their personal value, and
to reflect the situation that teaching activities or
phenomena satisfy certain explicit or implicit
requirements, colleges and universities carry out
regular assessments of their teaching performance.
GEN (2009) The so-called "teaching performance
evaluation" means that the university extensively
collect the teaching activity information of
individual teachers relying on modern technical
means based on the formulated procedures and
methods, and assess the value and fact of whether
the process and results conform to the teaching
objectives (GEN, 2009). Nevertheless, the explicit
and implicit indicators involved in the evaluation
process will affect the objectivity of the assessment
results. In this regard, the fuzzy comprehensive
evaluation method is adopted in teaching
performance assessment to make full use of teaching
management, teaching transformation and teachers'
professional progress in accordance with the
evaluation results.
2 CURRENT SITUATION OF
TEACHING PERFORMANCE
EVALUATION
In order to make the teaching performance evaluated
objectively, scholars at home and abroad have
studied the evaluation methods from various
viewpoint. CHEN (2017) The representative foreign
evaluation methods include: value-added
assessment, peer assessment, customized teaching
and so on, yet some problems appear in these
methods, such as long cycle and strong subjectivity
(CHEN, 2017).
78
Li, F. and Su, K.
Research on the Application of Fuzzy Comprehensive Evaluation in the Teaching Performance Appraisal of College Teachers.
DOI: 10.5220/0011898600003613
In Proceedings of the 2nd International Conference on New Media Development and Modernized Education (NMDME 2022), pages 78-89
ISBN: 978-989-758-630-9
Copyright
c
2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
Considering the differences of evaluation objects
and the operation difficulty in evaluation method,
Chinese scholar DUAN (2013) proposed the
teaching performance assessment method based on
"BP neural network", and verified the feasibility of
this method in assessment practice (DUAN, DENG,
SHEN, 2013). Given the assessment subject of this
study is mainly students, the final assessment results
are certain restricted, so the scope of the assessment
subject should be extended to supervision experts,
teaching managers, employment units, etc. MA
(2019) built the teaching performance evaluation
indicator system from the aspects of teaching
attitude and teaching content, and adopted the
entropy weight TOPSIS model to realize the
quantitative assessment of teaching performance
(MA, 2019); LIU (2014) put forward the
performance assessment method on the basis of the
extension theory to address the subjective
randomness in the process of qualitative assessment
(LIU, ZHANG, 2014). However, the relevant
assessment factors are limited to teaching and
research papers, teaching workload and other
explicit content, while ignoring the improvement of
students' innovation capability and other implicit
content; In view of the inadequate scientifically in
teaching performance evaluation system and method
that causes the deviation of evaluation results from
actual situation, and then impairs the enthusiasm of
teachers, SUN (2015) came up with an approach of
teaching performance evaluation with "support
vector machine method" (SUN, 2015). However,
when constructing the teaching performance
indicator system, the explicit and implicit
requirements should be considered in an all-around
way.
Moreover, the indicator factors have
corresponding fuzzy concepts in the teaching
performance evaluation of college teachers. To this
end, Liu (2013) proposed the application of fuzzy
theory in the teaching performance evaluation
method, and constructed the corresponding
assessment indicator system (Liu, Zhu, 2013), but
the determination process of weight value is short of
a reasonable basis; Zhao (2013) applied the
hierarchy analysis method to establish the teaching
performance evaluation matrix (Zhao, 2013), yet the
determination of the fuzzy operator lacks rationality,
which weakens the objectivity of the final
assessment results; GAO (2020) put forward the
"principal component analysis method" to evaluate
the teaching performance of teachers, and
reasonably determine the weight value of
assessment indicators, so that ensure the objectivity
of the assessment results to the largest extent (GAO,
LI, SONG, 2020). Given the massive data
calculation and relatively single evaluation subject,
the above methods have poor practicality.
On the basis of the previous researches, this
study establishes a comprehensive evaluation
indicator system to reasonably determine the fuzzy
operators and weight values for the objective
assessment of their teaching performance.
3 OVERVIEW OF FUZZY
COMPREHENSIVE
EVALUATION
The Fuzzy Theory was proposed by American
scholars in the 1960s, and the fuzzy comprehensive
evaluation method is an approach of comprehensive
assessment based on the Fuzzy Theory. With this
method, the qualitative evaluation can be
transformed into quantitative evaluation, which is
suitable for solving various non-deterministic
problems, and for making an objective and
comprehensive evaluation under different factors.
Kember (2006) Since the teaching activities of
college teachers involve a variety of factors with
both implicit and explicit characteristics, some
activities or phenomena even contain certain
ambiguity (Kember, 2006). In this regard, the
evaluation factor set is determined in the teaching
performance evaluation through the analysis of the
evaluation object; The hierarchy analysis method is
applied to assign the weight of each factor involved
in teaching activities, which decompose complex
problems into several constituent components, a
hierarchical structure is formed according to their
dominating and dominated relation, and the relative
importance of each component is identified in the
hierarchy in comparison; Smith(2014)The
investigation and study are conducted to determine
the merits of the factors, so as to obtain the
evaluation value of these factors (Smith, Vinson,
Smith etc., 2014), and calculate the final
membership degree based on the above process, as
shown in Fig.1.
Research on the Application of Fuzzy Comprehensive Evaluation in the Teaching Performance Appraisal of College Teachers
79
Figure 1 Fuzzy comprehensive evaluation flow chart
(1) Factor set: the indicator of fuzzy
comprehensive evaluation, that is, the evaluation
aspects;
(2) Review set: the quality degree of each
evaluation factor, and the result collection of
evaluation grades;
(3) Weight set: the weight value is to measure the
importance of an indicator in the whole assessment
indicator system, and the weight set is a set
composed of each weight value (Butt Babar,
Rehman, 2010). In order to make the fuzzy
calculation process more logical and the assessment
results more objective, the weight value of each
indicator is determined by the authoritative
professors in universities according to their expertise
and experience: based on the estimation of experts,
the final weight value of each indicator is calculated
according to the method in Table 1, and the sum of
each weight value should be 1, as shown in Equation
(1).
Table 1 Weight calculation method of expert estimation
Factors index
Weight
u
1
u
2
… u
n
∑
Experts
Expert 1 a
11
a
12
… a
1n
1
Ex
p
ert 2 a
21
a
22
… a
2n
1
… … … … 1
Ex
p
ert
m
a
m1
a
m2
… a
mn
1
j
m
aij
1
m
1
a
1
m
1
a
2
…
m
1
a
n
1
(a≥0
；
i=1, 2, …n) (1)
(4) Fuzzy relation matrix: the quantitative
processing of qualitative indicators in the teaching
performance of university teachers can be completed
by fuzzy statistics method. the membership degree
of evaluation grade is obtained after the assessment
subject evaluates the qualitative indicator according
to the grade domain, while the membership degree
of each subsystem constitutes the membership set,
and the fuzzy relation matrix of the assessment
indicator is established. The corresponding
mathematical representation is as shown in Equation
(2):
()
mni
n
mn j
nmnn
m
m
r
rrr
rrr
rrr
R
R
R
R
×× =
=
=
...
............
...
...
...
21
22221
11211
2
1
(2)
Where,
()
imii rrr ,,, 21
: the evaluation set of
individual indicator
iu
(i=1,..., n);
mnR ×
: refer to the evaluation set of all
individual indicators.
(5) Single-hierarchy fuzzy evaluation
calculation: the evaluation indicator is divided into
several subsystems according to its characteristics.
LI (2015) The single-hierarchy fuzzy evaluation is
calculated based on the weight set and the fuzzy
relation matrix in each system (
LI, CHEN, 2015). The
corresponding mathematical representation is as
shown in Equation (3):
()
mn
n
mn ij
nmnn
m
m
rA
rrr
rrr
rrr
A
R
R
R
ARAB ×× •=
•=
•=•=
...
............
...
...
...
21
22221
11211
2
1
(3)
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Where, "A" is the weight set of evaluation indicators
at all hierarchies;
"B" means a single-hierarchy evaluation set: it is
calculated by the weight allocation and evaluation
matrix of each factor.
(6) Fuzzy comprehensive evaluation calculation:
the single-hierarchy fuzzy evaluation calculation
results are taken as the relative membership degree
matrix of the previous hierarchy, and the
single-hierarchy fuzzy calculation model is used
again to obtain the membership order of the
assessment object. The corresponding mathematical
representation is as shown in Equation (4):
()
mnij
nnn
bA
RA
RA
RA
A
B
B
B
ΑΒΑC
ו=
•
•
•
•=
•=•=
............
22
11
2
1
(4)
Where, "C" represents the final membership degree
of the assessment indicator: that is, the weight
allocation A of the primary indicator is calculated
from the membership matrix composed of the
single-hierarchy fuzzy evaluation calculation results
of Equation (3).
4 THE APPLICATION OF FUZZY
COMPREHENSIVE
EVALUATION IN TEACHING
PERFORMANCE ASSESSMENT
Most colleges and universities usually adopt the
approaches of students evaluation, supervision team
in lectures, teaching outcomes submission and so on
in evaluation, the focus is only put on classroom
organization, teaching methods, language
expression, research papers, competition awards,
etc., while ignoring the assessment of teaching
effect, such as: Kenneth (2018) the increase of
students' knowledge, enlightenment, innovation
capability, and even problem discovery and solving
ability in work (Kenneth, 2018). In addition, the
growth of students is a gradual and long-term
process, which makes it difficult to generate
immediate effect in teaching activities, and the delay
of such talent training has become a challenge in
teaching performance assessment. Hence, in order to
realize objective teaching performance assessment
results, the evaluation indicator should be
comprehensive, alongside with authoritative
assessment subject as well as reasonable weight
value and fuzzy operator, as shown in Fig. 2.
Figure 2. Teaching performance evaluation process
4.1 Selection of Teaching Performance
Evaluation Subjects
The university teaching performance evaluation
includes both explicit and recessive content,
involving massive indicators interrelated to
evaluation object. Thus, the objective and
comprehensive performance evaluation requires
diversified evaluation subjects consisting of
students, teachers, supervision experts, leaders,
teaching administrators, and employment units to
participate in the "multidimensional evaluation"
system, so as to address the limitations bought by
single subject evaluation.
Based on the teaching quality requirements of
higher education, the university and secondary
colleges randomly inspect and evaluate the
classroom teaching activities of the teachers
Research on the Application of Fuzzy Comprehensive Evaluation in the Teaching Performance Appraisal of College Teachers
81
according to the teaching quality requirements of
higher education, mainly including: teaching
preparation, teaching methods, language expression
and other aspects. Due to the differences in
professional knowledge, the evaluation pays more
attention to the real-time situation, which is unable
to fully recognize the role of the evaluated course in
the curriculum system, thus making the evaluation
limited to superficial teaching, while lack of
profound content of the major and discipline, and
difficult to truly reflect the knowledge absorption
and emotion input of the evaluation object;
Smith(2013)As the object of teaching and the direct
reflection of the teaching effect, students play a
crucial role in the process of teaching performance
evaluation, who are also regarded as an important
information source in the performance evaluation in
terms of teaching attitude, teaching content and
teaching effect (Smith, Jones, Gilbert etc., 2013)
.
Influenced by subjective factors, students may miss
the qualitative description and suggestion of teacher
teaching effect; The teaching performance
evaluation made by teaching administrators puts
more emphasis on the "final results", and the
formulation stress more indicators of completed
teaching outcomes, such as teaching hours, guiding
published papers, competition awards, yet short of
the attention to teaching activities; The ultimate goal
of teaching is to cultivate comprehensive and quality
talents, evaluating the students' actual problem
solving and innovation ability can indirectly reflect
the teaching effect; Teacher self-evaluation refers to
the personal assessment of overall teaching
activities, mainly including: teaching process,
discipline construction, innovative practice training.
College teachers, as a group with strong cognitive
competence, certainly have the ability of
self-assessment and reflection. Hence, teachers'
self-evaluation can fully reflect the actual
performance; Discipline leader, serving as the direct
head of teachers, are familiar with the situation of
teachers' professional competence, discipline
construction, curriculum construction and team
cooperation, which is conducive to the direct
feedback of teachers' teaching performance in
multiple aspects.
4.2 Construction of Teaching
Performance Indicators
In order to make the teaching performance
evaluation of college teachers play a guiding and
all-sided role, it is necessary to construct a scientific
teaching performance evaluation indicator system.
The teaching performance evaluation of university
teachers consists of final evaluation and formative
evaluation, that is, the outcomes led by the teaching
process and the teaching results.
Through the analysis on the teaching
performance evaluation documents of different
universities, questionnaire, survey and interview
methods are adopted to study the relevant indicators
and factors in teachers' teaching performance
evaluation process. The assessment documents and
interviews are mainly from Qilu University of
Technology (Shandong Academy of Sciences),
Shandong Normal University, Shandong University
of Traditional Chinese Medicine and other
universities, with a total of 32 interviewees
including administrators and teachers of different
professional titles; Among the 256 received
questionnaires in 280 distributions, 248 are valid
ones. According to investigation, the teaching
performance assessment of university teachers
chiefly includes the following aspects, (1) one is
explicit content: ① Whether teaching materials
(teaching plan, teaching schedule, internship plan,
graduation design materials, course construction,
examination papers, etc.) are submitted timely and
correctly;② Classroom teaching tasks: the
completion of teaching workload; ③ Guidance of
students' practical teaching, including: competition
awards, patent application, paper publication, etc.;
(2) The other is implicit content: ①Teaching
quality: teaching attitude, teaching methods, teaching
effect, etc.; ② Cultivation of students' innovation
ability, consciousness, etc.; ③ Participation in
teaching research activities: discipline construction,
formulation of talent training program, declaration
of teaching research topics, participation in teaching
transformation, etc.; ④ of Relevant examination
papers: such as the examination paper, standard
scoring procedure, the integrity of invigilation
information;⑤ Creation of teacher ethics. The
explicit evaluation content can be directly assessed
in a quantitative way, but which is improper for
implicit content. In this regard, the objective
evaluation is conducted by transforming the
qualitative content into quantitative assessment
based on the fuzzy comprehensive evaluation
method.
4.3 Determination of the Weight Value
of Teaching Performance
Indicators
In order to carry out objective evaluation of teaching
performance, the weight value of each indicator
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should also be reasonably determined by
authoritative professors with abundant teaching and
management experience, such as, supervision
expert, teaching administrator, Discipline leader and
so on in addition to a comprehensive evaluation
indicator system. According to the established
indicator system, the Delphi method is adopted to
determine the weight allocation of each indicator,
that is, make the evaluation results consistent
through several rounds of anonymous inquiries.
Theoretically, the innovation capability of students
in practice should account for a large proportion, but
given the objective evaluation information of
students' innovation capability from the employment
unit is inaccessible, and the comprehensive quality
of students is the outcome of all teachers' efforts, the
weight value of the corresponding indicator should
not be overly high; Besides, the weight value of
"formative results" in teachers' teaching activities
should not relatively low as they are not the final
form, as shown in Table 2.
Table 2. Work performance evaluation indicators
Primary indicator Secondary indicator Tertiary indicator
Teaching
administrator
Practice teaching U
1
(0.25)
Submit teaching materials
U
11
(0.35)
Complete material submission
U
111
(0.35)
Correct material submission
U
112
(0.35)
Timely material submission
U
113
(
0.30
)
Register examination results
U
12
(0.20)
Test paper conforms to outline
U
121
(0.45)
Accurate score registration
U
122
(0.55)
Guide innovative practice
U
12
(0.45)
Guide participating competitions
U
41
(0.30)
Guide paper publication
U
42
(0.35)
Guide patent application
U
43
(
0.35
)
Student
evaluation
Classroom teaching
U
2
(0.15)
Rigorous teaching attitude
U
21
(0.30)
Plentiful teaching content
U
22
(0.20)
Reasonable teaching method
U
23
(0.30)
Obvious teaching effect
U
24
(
0.20
)
Discipline
leader
Discipline
construction U
3
(0.15)
Major and curriculum
construction
U
31
(0.35)
Premium courses creation
U
311
(0.35)
Professional brand Construction
U
312
(0.35)
Examination database
construction U
313
(0.30)
Team cooperation spirit
U
32
(
0.30
)
Teaching research and
communication
U
33
(0.35)
Research project approval
U
331
(0.35)
Award-winning teaching results
U
332
(0.35)
Classroom teaching
transformation
U
33
(
0.30
)
Supervision
expert
Classroom teaching
U
4
(0.25)
Classroom teaching
U
41
(0.45)
Teaching method
U
411
(0.25)
Language expression
U
412
(0.25)
Classroom atmos
p
here
Research on the Application of Fuzzy Comprehensive Evaluation in the Teaching Performance Appraisal of College Teachers
83
U
413
(0.25)
Classroom interaction
U
414
(
0.25
)
Test paper quality
U
42
(0.30)
Meet syllabus requirements
U
421
(0.35)
Appropriate questions in variety
and quantity
U
422
(0.25)
Moderate difficulty
U
423
(0.25)
Accurate and independent
U
424
(
0.15
)
Standard scoring procedure
U
43
(
0.25
)
Teacher
self-evaluation
Comprehensive
factors U
5
(0.10)
Classroom teaching
U
51
(0.25)
Practice teaching
U
52
(0.25)
Discipline construction
U
53
(0.25)
Teaching research
U
54
(0.25)
Employment
unit
Practical capability
U
6
(0.10)
Problem discovery ability
U
61
(0.35)
Problem solving ability
U
62
(0.35)
Practical innovation ability
U
63
(
0.30
)
The assessment indicators of all the participating
teachers are scored according to the teaching
performance evaluation indicator system in the early
stage, and the assessment subjects based on the
corresponding proportions of lecturers, associate
professors, professors and so on, and the
comprehensive fuzzy assessment list is obtained, as
shown in Table 3.
Table 3. Comprehensive assessment list of teaching performance
Indicator Teacher Zhao Teacher Li Teacher Sun Teacher Wang
Complete material
submission
0.87 0.92 0.85 0.94
Correct material submission 0.82 0.93 0.83 0.85
Timely material submission 0.85 0.78 0.80 0.81
Test paper conforms to
outline
0.86 0.91 0.86 0.92
Accurate score registration 0.85 0.96 0.87 0.90
Guide participating
com
p
etitions
0.89 0.90 0.86 0.83
Guide
p
a
p
er
p
ublication 0.85 0.86 0.80 0.81
Guide patent application 0.76 0.79 0.81 0.73
Rigorous teaching attitude 0.83 0.94 0.82 0.93
Plentiful teaching content 0.81 0.88 0.79 0.87
Reasonable teaching method 0.84 0.89 0.83 0.96
Obvious teaching effect 0.85 0.95 0.81 0.93
Premium courses creation 0.92 0.98 0.92 0.95
Professional brand
Construction
0.87 0.93 0.86 0.89
Examination database
construction
0.97 0.89 0.94 0.96
Team cooperation spirit 0.74 0.77 0.78 0.81
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Research project approval 0.79 0.88 0.75 0.82
Award-winning teaching
results
0.86 0.81 0.87 0.83
Classroom teaching
transformation
0.78 0.79 0.86 0.80
Teaching method 0.88 0.90 0.85 0.83
Language expression 0.85 0.91 0.93 0.89
Classroom atmosphere 0.82 0.88 0.83 0.87
Classroom interaction 0.88 0.93 0.88 0.94
Meet syllabus requirements 0.89 0.87 0.91 0.92
Appropriate questions in
variety and quantity
0.91 0.92 0.88 0.85
Moderate difficulty 0.84 0.89 0.80 0.87
Accurate and independent 0.91 0.86 0.92 0.81
Standard scoring procedures 0.81 0.82 0.91 0.85
Classroom teaching 0.85 0.81 0.78 0.82
Practical teaching 0.96 0.87 0.86 0.91
Discipline construction 0.91 0.94 0.96 0.92
Teaching research 0.94 0.90 0.94 0.90
Problem discovery ability 0.94 0.90 0.95 0.89
Problem solving ability 0.87 0.89 0.84 0.82
Practical innovation ability 0.81 0.87 0.85 0.82
5 THE CALCULATION OF
FUZZY COMPREHENSIVE
EVALUATION
5.1 Determination of Fuzzy Operator
The fuzzy comprehensive evaluation method is
adopted to assess the teaching performance of
university teachers. For sake of the rationality of
evaluation and calculation process, the type of fuzzy
operator should be properly determined. Each pair
of fuzzy operators represents different calculation
methods, and the selection of assessment
information shows certain tendency. Hence, the
analysis is conducted on the information processing
methods of several commonly-used fuzzy operators
regarding reflection of weight role, adoption of R
information, comprehensive degree and other
aspects, so that the optimal operator type containing
overall assessment information is determined, as
shown in Table 4.
Table 4. Characteristics of each fuzzy operator
Characteristics
Fuzzy operator
M(∧, ∨) M(●, ∨)
M(∧, ＋) M(●, ＋)
Reflection of
weight role
Not obvious Obvious Not obvious Obvious
Comprehensive
de
g
ree
Weak Weak Strong Strong
Adoption of R
information
Inadequate Inadequate Relatively adequate Adequate
Type
Prominent main
facto
r
Prominent main
facto
r
Weighted mean Weighted mean
The meaning of each symbol in the fuzzy
operator: "+" means the add operation of ordinary
real numbers; "●" is the multiply operation of
ordinary real numbers; "∧" and "∨" represent
minimum (min) and maximum (max) operations
respectively.
(1) Fuzzy operator M (∧, ∨), the mathematical
model is shown in equation (5). In the process of
fuzzy calculation, only the indicator factors with the
Research on the Application of Fuzzy Comprehensive Evaluation in the Teaching Performance Appraisal of College Teachers
85
largest membership degree
ijd
r
,
and major role are
taken into consideration, while the minor indicators
are not considered, thus excluding the influence of
other factors.
njrab ijdjdjd
m
i
,...,2,1,,,,
1
=
∧∨=
=
(5)
Where:
jda , measures the role of jdu , in
assessment factors;
jdb ,
represents the membership degree of
jdv , to
fuzzy subset
dB ;
=
==
m
i
njrab ijdidjd
1
,...,2,1,,,,
ijd
r
,
means that the assessment object belongs to the
membership degree of the evaluation level
jdv ,
when solely considering
jdu ,
.
(2) Fuzzy operator M (●, ＋) , the mathematical
model is shown in equation (6). The fuzzy operator
is a matrix synthesis in line with the multiplication
and addition arithmetic of ordinary real numbers,
which can balance all indicators in weights, and
fully reflect the information contained by all factors.
=
==
m
i
njrab ijdidjd
1
,...,2,1,,,,
(6)
(3) Fuzzy operator M (●, ∨) , the mathematical
model is shown in equation ⑺. Similar to M (∧, ∨) ,
ida ,
only works to adjust the coefficient, thus the
fuzzy operator also emphasizes the maximum
operation of "∨", which can’t fully reflect the
information of the assessment indicator.
njrab ijdidjd
m
i
,...,2,1,,,,
1
=∨=
=
(7)
Based on the comparison of the information
reflected by each fuzzy operator, the fuzzy operator
M (●, ＋) can clearly present the role of weight A,
and ensure the full exertion of fuzzy relation matrix
R information, so that effectively avoid the loss of
teaching performance assessment information with
relatively strong comprehensive characteristics. The
operator M (●, ＋ ) is finally selected as the
mathematical model of fuzzy calculation to make
sure the rationality of the whole process.
5.2 Determination of the Final
Membership Degree
The evaluation indicator system of teaching
performance is constructed in accordance with
analytic hierarchy process, and each indicator is
divided into several subsystems according to its
attributes. The fuzzy comprehensive evaluation
method is adopted in single-hierarchy calculation of
each subsystem, then the final membership degree is
determined by the calculation results, followed by
the evaluation results of each assessment object. As
shown in Table 2 and Table 3: U11={ U111, U112,
U113}, weight A11={ 0.35, 0.35, 0.30 }. On the
basis of equation (2), the fuzzy relation matrix R11
composed of U11 indicators is constructed:
=
81.080.078.085.0
85.083.093.082.0
94.085.092.087.0
11
R
Amid the U11 subsystem, allocate A11 and fuzzy
relation matrix R11 in the light of the determined
weight, conduct the fuzzy evaluation calculation of
tertiary indicator with fuzzy operator M (●, ＋)
according to Equation (3):
{}
)87.0,83.0,88.0,85.0(
)24.030.033.0,24.029.030.0
,23.033.032.0,26.029.030.0(
)81.030.085.035.094.00.35
,80.030.083.035.085.00.35
,78.030.0
93.035.092.00.35
,85.030.082.035.087.0(0.35
81.080.078.085.0
85.083.093.082.0
94.085.092.087.0
30.0,35.0,35.0
111111
=
++++
++++=
×+×+×
×+×+×
×+×+×
×+×+×=
•=•= RAΒ
According to the same calculation method: B12=
(0.86, 0. 94, 0.87, 0.91) ；B13= (0.84, 0.85, 0.82,
0.75), based on the fuzzy relation matrix constructed
by B11、B12、B13, conduct B1 secondary indicator
fuzzy calculation, the results are as below:
{}
)82.0,83.0,88.0,85.0(
)75.045.091.020.087.00.35
,82.045.087.020.083.00.35
,85.045.094.020.088.00.35
,84.045.086.020.085.0(0.35
75.082.085.084.0
91
.087.094.086.0
87.083.088.085.0
45.0,20.0,35.0111
=
×+×+×
×+×+×
×+×+×
×+×+×=
•=•= RAΒ
With the same fuzzy comprehensive calculation
method, the single-hierarchy calculation results are
obtained respectively as below:
NMDME 2022 - The International Conference on New Media Development and Modernized Education
86
B
1
= (0.85, 0.88, 0.83, 0.82);
B
2
= (0.83, 0.92, 0.82, 0.93);
B
3
= (0.82, 0.85, 0.84, 0.86);
B
4
= (0.86, 0.88, 0.88, 0.87);
B
5
= (0.92, 0. 89, 0.90, 0.90);
B
6
= (0.87, 0.89, 0.88, 0.85).
Taking the calculation results of the
single-hierarchy assessment as the relative
membership degree matrix of the factor set U, the
single-hierarchy fuzzy calculation model is applied
again and calculated according to Equation (4), and
the membership order of the teaching performance
assessment under the overall indicator system is as
follows:
U={ U
1
, U
2
, U
3
, U
4
, U
5
, U
6
}；A={A
1
, A
2
, A
3
, A
4
,
A
5
, A
6
}；B={ B
1
, B
2
, B
3
, B
4,
, B
5
, B
6
}.
()
90.0,88.0,91.0,87.0
85.088.089.087.0
90.090.089.092.0
87.088.088.086.0
86.084.085.082.0
93.082.092.083.0
82.083.088.085.0
}10.0,10.0,25.0,15
.0,15.0,25.0{
6
5
4
3
2
1
=
•=
•=•=
B
B
B
B
B
B
ΑΒΑC
The teaching performance evaluation results of
all teachers are ranked according to the final
membership degree: Teacher Li, Teacher Wang,
Teacher Sun, Teacher Zhao, namely, Teacher Li
obtains the highest teaching performance.
6 THE FORMULATION OF
IMPROVEMENT MEASURES
The teaching performance assessment of university
teachers is the catalyst of higher education reform.
The effective feedback of assessment information to
relevant teachers is the only way to address the
targeted problems appearing in teaching activities.
Hence, colleges and universities should establish a
two-way feedback mechanism inside and outside
school to continuously enhance the teaching
performance.
6.1 Feedback to Assessment Teachers
College teachers, as a group of high intelligence,
usually have higher cognitive competence, whose
work is more driven by internal motivation. Thus,
the feedback from a multi-dimensional perspective
can make teachers have reflection and internal
consciousness, then cope with the problems existing
in their teaching activities, so that realize the
primary function of performance evaluation.
Furthermore, the ultimate purpose of teaching
performance assessment is not ranking, but to build
a scientific and reasonable internal incentive
mechanism and an impartial competition
environment through evaluation, so as to stimulate
teachers' awareness of carrying out teaching
transformation and constantly improve their
teaching performance.
6.2 Improve Formative Evaluation
Content
In addition to final evaluation, the teaching
performance evaluation should also include
formative evaluation. The overall mastery of
teachers' performance and achievements in the
teaching process is crucial to conduct objective
evaluation, and the "teaching archive" will provide
powerful support for the evaluation. The so-called
"teaching archive" refers to the long-term, planned
and purposeful tracking records of teachers' teaching
process and results, as the prototype record of
teachers in teaching activities, it is a information
summary based on multiple evaluation methods
including teachers' self-evaluation, which sums up
the comprehensive materials reflecting teachers'
teaching status and quality. Moreover, the
assessment objects should adhere to the principles of
comprehensiveness, accuracy and authenticity in
establishing teaching archives.
6.3 Establish Tracking Feedback
Mechanism
The major task of college teachers is to impart
scientific knowledge and spiritual wealth into
students' knowledge, skills and morality, and make
them grow into compound talents that realize
individual value while satisfy economic and social
development demands. Hence, students' practical
innovation ability should be involved in the teaching
performance evaluation of college teachers. The
establishment of graduate tracking mechanism can
effectively combine teaching activities with the
needs of economic growth and social progress, in
which the concept of "adaptability" advocated by
higher education is embodied in the teaching
performance assessment, so as to better address the
disconnection between talent training and social
demands.
6.4 Formulate Performance Evaluation
and Incentive Mechanism
The formulation of university teacher teaching
performance evaluation incentive model relies on
Research on the Application of Fuzzy Comprehensive Evaluation in the Teaching Performance Appraisal of College Teachers
87
the recognition of the evaluation system and results.
Accordingly, in addition to a scientific and
reasonable teaching performance evaluation system,
universities are supposed to establish a multilevel
incentive mechanism to stimulate teachers'
enthusiasm and creativity in work, thus both
achieving their goal of personal value and school
expectations, while realizing the benign cycle of
higher teaching level brought by teaching
performance evaluation, as shown in Fig. 3.
Figure.3. Incentive model of teaching performance
evaluation
7 CONCLUSION
In order to obtain objective results in the teaching
performance assessment of college teachers and
further motivate their teaching activities, this paper
puts forward the method based on fuzzy
comprehensive evaluation. Through the analysis on
the factors involved in the teaching activities, the
evaluation indicator system is established with
hierarchy analysis method containing explicit and
implicit content. Besides, the formative evaluation
content in teaching activities and innovation
capability of the students in practice are
incorporated into the evaluation system; The optimal
type of fuzzy operator is determined on the basis of
analysis and comparison, which make the whole
calculation process more rational; The improvement
measures are proposed according to the final
assessment results, aiming to achieve the benign
cycle of higher teaching level and teaching
performance evaluation. Nevertheless, there is a lack
of effective assessment methods for the evaluation
of students' innovation capability in practice, and the
content involved in the formative evaluation calls
for more definition. In this regard, the above
limitations should be taken into consideration in
further research.
Fund projects: Qilu University of Technology
(Shandong Academy of Sciences) General Project of
teaching and Research Project (project number:
2019 YB38)
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