XiaoLibin
Copyright © The Institute of Electronics and Information Engineers(IEIE)
Keywords
Virtual simulation experimental technology, Tourism management, Learning effect, New liberal arts
1. Introduction
China’s education policies are of great importance to the development of new liberal
arts programs and teaching reform in application-oriented universities <note: ambiguous>.
The new arts development group under the Chinese Ministry of Education issued the
Declaration of New Arts Development on November 3, 2020, and proposed a goal of talent
cultivation to satisfy the needs of new applied arts. They also outlined suggestions
for teaching reform and talent cultivation in application-oriented colleges and universities.
Virtual simulation experiment teaching relies on advanced and novel technologies such
as computers, communication and networking, image presentation, virtual reality, human-computer
interaction, and automatic control. Through an established system learning model,
experts conduct experimental learning and inquiry-based teaching based on professional
knowledge and practical phenomena [1]. In recent years, with the rapid popularization and advancement of education informatization,
Chinese colleges and universities have strengthened the development of virtual simulation
experiment teaching projects <note: You should explain what this is> and promoted
the convolutional development <note: ambiguous> of higher education [2].
According to Table 1, there are a total of 401 national virtual simulation experimental teaching projects
in China, and this field of study in Chinese universities has entered a stage of high-quality
development. Virtual simulation experiment teaching has made outstanding contributions
in teaching and research, technology application, talent training, skill training,
service to society, and other aspects. It can effectively make up for the deficiencies
of conventional teaching in the areas of education and pedagogy.
As China develops into a high-quality tourism country, new forms of tourism such as
"internet + tourism" and "smart tourism" are booming. China’s tourism management sector
needs high-quality and interdisciplinary talents. This has set higher requirements
for tourism practice teaching, which is the key to improving the core quality and
practical operation ability of students majoring in tourism management and cultivating
senior tourism management talents. Different from the characteristics of high cost
and high risk of field teaching, virtual simulation technology can enrich the practical
teaching resources in tourism studies and improve the efficiency of practical teaching.
Hence, virtual simulation technology is an inevitable choice for tourism education
[3].
Table 1. National virtual simulation experimental teaching projects of each discipline {\textlessnote: Generally, the introduction should not include tables, so consider removing this>. }
|
Discipline
|
Numbers
|
Discipline
|
Numbers
|
|
Biological sciences
|
35
|
Transportation
|
16
|
|
Machinery
|
44
|
Nuclear engineering
|
13
|
|
Electronic information
|
14
|
Clinical medicine
|
53
|
|
Chemical and pharmaceutical engineering
|
30
|
Pharmacy
|
25
|
|
Education
|
9
|
Journalism and communication
|
10
|
|
Chemistry
|
11
|
Psychology
|
7
|
|
Energy power
|
13
|
Civil
|
13
|
|
Surveying and mapping
|
11
|
Geology
|
11
|
|
Aerospace
|
9
|
Environmental science and engineering
|
11
|
|
Food science and engineering
|
13
|
Plants
|
8
|
|
Animal
|
14
|
Basic medical science
|
17
|
|
Traditional Chinese medicine
|
7
|
Nursing
|
7
|
|
Total
|
401
|
Note: Data from the ministry of education of the People’s Republic of China
2. Literature Review
Virtual simulation technology provides essential support for the development of higher
education informatization and experimental teaching demonstration centers. There is
a lack of real data and a real environment <note: ambiguous> in the process of college
education and teaching, so application-oriented universities integrate intelligent
science, big data technology, and experimental teaching.
Research on virtual simulation in China began in 2000. Zhou Jianghua explored the
design and implementation of virtual simulations of manufacturing systems [4]. The earliest studies on virtual simulation teaching emerged in 2003. Three-dimensional,
solid geometric modeling of a robot can reproduce the whole process of robot movement
[5]. Experimental teaching has been an important topic of virtual simulation technology
research in recent years.
<New paragraph> Taking the practical teaching of biochemical pharmaceutical technology
as an example, scholars have expounded on the problems existing in traditional practical
teaching and discussed how to improve the effectiveness of practical teaching in higher
vocational colleges via virtual simulation technology [6]. Cai Weiguo studied the application of virtual simulation technology in teaching
mechanical engineering experiments [7]. Cao Xuefeng highlighted the advantages of a virtual simulation experiment system
in improving the teaching of pathophysiology experiments. But traditional experiment
teaching still plays an irreplaceable role in enhancing students’ hands-on ability
and on-site demonstration [8].
<New paragraph> Research results show that virtual simulation technology is more widely
applied in the fields of science and engineering, such as mechanical engineering [9], geography [10], electrical automation [11], biomedicine [12], aviation and shipping [13], etc. As one example, a virtual simulation experiment teaching system can guide students
in learning the operation of a task engine system [14]. With the development of other disciplines, virtual simulation technology is also
being progressively adopted in the teaching of liberal arts, economics, management,
and other majors, including logistics management [15], big data, finance, etc. A virtual simulation experimental teaching center of logistics
management in application-oriented universities is designed to meet the diverse needs
of professional teaching, experimentation, scientific research, and academic competition
[16-19].
In light of the new developments in liberal arts, this paper explores the application
of virtual simulation technology in tourism management teaching in application-oriented
universities, which is expected to be of great significance for the cultivation of
excellent management talents in the tourism industry. Students majoring in tourism
management in application-oriented universities were examined in this study. They
were divided into an observation group and a control group. This paper investigates
the effect of virtual simulation technology on tourism practice teaching with experimental
comparative analysis and multivariate statistical analysis methods.
3. Study Design
3.1 Participant and Index Selection
3.1.1 Participants
In this study, students majoring in tourism management from the class of 2019 at an
application-oriented university in China’s Guangxi province were selected as participants.
Students were randomly selected from all tourism management majors at the university,
which can represent the actual learning ability of all students in this major. They
were divided into an observation group (group 1) with 38 students and a control group
(group 2) with 40 students. To ensure that no significant discrepancy existed between
the two groups prior to the experiment, a one-way analysis of variance (ANOVA) in
SPSS23.0 was used to analyze the differences in basic information and learning between
groups.
As presented in Table 2, the average ages of the observation group and the control groups were 21.24 and
21.10 years, respectively. Most of the students in the two groups are from Guangxi
province. There were 10 male students and 28 female students in the observation group
and 12 male students and 28 female students in the control group. There was no significant
difference in terms of gender ratio. Concerning learning ability, the average GPAs
of the two groups were 80.61 and 80.04, respectively. Thus, prior to the implementation
of virtual simulation technology, both groups had almost identical learning levels.
As shown in Table 3, before the experiment, the Sig differences <note: ambiguous; abbreviations should
be defined when they are first mentioned> between the observation group and the control
group in age, place of origin, gender, and academic performance were 0.611, 0.940,
0.908, and 0.545 <note: ambiguous (units and an explanation are needed>, respectively,
all of which were greater than 0.000. This indicates that there was no difference
between the observation group and the control group in any of these aspects. The learning
situation before class for all students in both groups was analyzed. A total of 4
questions were set up in this study. According to the ANOVA results, the Sig differences
of the 4 questions were 0.459, 0.818, 0.318 and 0.633 <note: ambiguous>, respectively,
which were all greater than 0.000. This shows that there was no difference in the
learning basis of the tourism planning course between both groups. Therefore, the
setting of the observation and the control groups fulfills the practical requirements
of comparative research.
Table 2. Descriptive statistics of students’ basic information.
|
|
Observation Group
|
Control group
|
|
The average age
|
|
21.24
|
21.1
|
|
Origin of students
|
In the Guangxi province
|
34
|
36
|
|
Outside the Guangxi province
|
4
|
4
|
|
Gender
|
Male
|
10
|
12
|
|
Female
|
28
|
28
|
|
Study results
|
|
80.61
|
80.04
|
Table 3. One-way ANOVA results of observation group and control group in age, origin of students, gender, and study result before experiment.
|
Indicators and questions
|
Sum of squares
|
df
|
Mean square
|
F
|
Sig.
|
|
Age
|
Between groups
|
0.365
|
1
|
0.365
|
0.26
|
0.611
|
|
Within groups
|
106.468
|
76
|
1.401
|
-
|
-
|
|
Total
|
106.833
|
77
|
-
|
-
|
-
|
|
Origin of students
-
|
Between groups
|
0.001
|
1
|
0.001
|
0.006
|
0.94
|
|
Within groups
|
7.179
|
76
|
0.094
|
-
|
-
|
|
Total
|
7.179
|
77
|
-
|
-
|
-
|
|
Gender
|
Between groups
|
0.003
|
1
|
0.003
|
0.014
|
0.908
|
|
Within groups
|
15.343
|
76
|
0.202
|
-
|
-
|
|
Total
|
15.346
|
77
|
-
|
-
|
-
|
|
Study result
|
Between groups
|
6.19
|
1
|
6.19
|
0.37
|
0.545
|
|
Within groups
|
1271.231
|
76
|
16.727
|
-
|
-
|
|
Total
|
1277.42
|
77
|
-
|
-
|
-
|
3.1.2 Index Selection
Taking students’ self-directed learning ability and the learning effect as indicators,
the effect of virtual simulation technology on tourism management teaching was evaluated.
As one of the indicators, students’ self-directed learning ability was decomposed
into a total of 20 items, including 4 dimensions of learning motivation, planning
and implementation, self-control and interpersonal communication (comprising 6, 6,
4, and 4 items, respectively) [20]. A 5-level Likert evaluation method was used. The higher the score, the better the
self-directed learning ability was.
With reference to the China College Teaching and Learning Survey (CCTL), the learning
effect evaluation scale incorporates a total of 15 items and 3 dimensions (i.e., basic
quality, learning status, and learning discipline) [21]. There are six items for basic quality, six items for learning status, and three
items for learning discipline. Once again, a 5-level Likert evaluation method was
adopted.
3.2 Research Method
3.2.1 Experimental Analysis
The students in the control group were taught by traditional teaching methods, including
theoretical and computer training. The ability of the students in the observation
group and the control group was scored with item tests, and then the values were obtained
in a comparison table through statistical calculation.
For the observation group, virtual simulation technology-based teaching and experiments
were carried out. The teachers selected training items such as field investigation,
field measurement, map making, and UAV operation and determined the training process
for students through virtual simulation for students. The teachers then created a
tourism planning course and introduced cases and pre-class virtual simulation training.
Students entered the virtual simulation laboratory, logged into the system through
their accounts, and practiced training projects (field investigation, field measurement,
map-making, and UAV operation) combined with theoretical content. The system provides
three learning modes: demonstration, practice, and assessment. The teachers then completed
a learning effect evaluation and teaching feedback.
3.2.2 Multivariate Statistical Analysis
SPSS23.0 and ANOVA were adopted to analyze students’ self-directed learning ability
and learning effect in the observation group and the control group. The aim was to
examine whether the application of virtual simulation technology can improve students’
academic performance. By using optimal scale regression analysis, the effect of virtual
simulation technology on students’ learning of tourism planning was explored.
4. Empirical Research
4.1 Comparative Analysis of Student Self-directed Learning Ability
The self-learning abilities of the students in the observation group who had virtual
simulation experiment teaching and the control group who had traditional teaching
were compared. The results are presented in Table 4 and Fig. 1. As can be seen from Fig. 1, before the implementation of virtual simulation experiment teaching, the overall
scores of students’ self-directed learning ability in the observation group and the
control group were 59.61 and 59.80, respectively, with a small gap between them. After
the implementation of the virtual simulation experiment in the classroom, however,
the differences between the two groups in the four aspects of self-directed learning
ability, including learning motivation, planning and implementing, self-control, and
interpersonal communication, were all 0.000 (Sig) <note: ambiguous> (see Table 4), which implied a significant inter-group difference in the overall aspects of self-directed
learning ability among the students. Hence, the virtual simulation experiment had
a substantial impact on every aspect of self-directed learning ability of tourism
planning.
In order to analyze the impact of the virtual simulation experiment on the four aspects
of students' self-directed learning ability in more detail, a comparative analysis
was done on the four aspects of students' self-directed learning ability in the observation
group and the control group, as shown in Fig. 1. The overall level of students’ self-directed learning ability decreased by 0.17
compared with that before the traditional teaching implementation. This indicated
that the traditional teaching method had an adverse impact on students’ self-directed
learning abilities.
Fig. 1. Comparison of the students’ self-directed learning ability between the two groups before and after implementation of virtual simulation experiment teaching.
Table 4. One-way ANOVA results of observation group and control group in students’ self-directed learning ability.
|
-
|
-
|
Sum of squares
|
df
|
Mean square
|
F
|
Sig.
|
|
Students’ self-directed learning ability
|
Between groups
|
3445.041
|
1
|
3445
|
72.2
|
0
|
|
Within groups
|
3626.138
|
76
|
47.71
|
-
|
-
|
|
Total
|
7071.179
|
77
|
-
|
-
|
-
|
|
learning motivation
|
Between groups
|
365.186
|
1
|
365.2
|
56.78
|
0
|
|
Within groups
|
488.763
|
76
|
6.431
|
-
|
-
|
|
Total
|
853.949
|
77
|
-
|
-
|
-
|
|
Plan and implement
|
Between groups
|
338.39
|
1
|
338.4
|
60.04
|
0
|
|
Within groups
|
428.328
|
76
|
5.636
|
-
|
-
|
|
Total
|
766.718
|
77
|
-
|
-
|
-
|
|
Self-control
|
Between groups
|
100.392
|
1
|
100.4
|
29.93
|
0
|
|
Within groups
|
254.954
|
76
|
3.355
|
-
|
-
|
|
Total
|
355.346
|
77
|
-
|
-
|
-
|
|
Interpersonal communication
|
Between groups
|
124.761
|
1
|
124.8
|
47.56
|
0
|
|
Within groups
|
199.354
|
76
|
2.623
|
-
|
-
|
|
Total
|
324.115
|
77
|
-
|
-
|
-
|
<New paragraph> After the virtual simulation experiment teaching, the overall level
of students’ self-directed learning ability was 72.92 (22% higher than before) and
was higher compared to that of the control group. From these four aspects of students'
self-directed learning ability, the application of virtual simulation in experimental
teaching improves students' self-directed learning ability to a certain extent, but
the degree of improvement is different. The application of virtual simulation experiment
teaching has the most prominent effect on improving students’ learning motivation
and interpersonal communication, which increased by 24% and 23.2%, respectively. In
comparison, the increases in the other two aspects were 22.5% and 19%, respectively,
which means that the existing virtual simulation experiment teaching technology was
not comprehensive in improving the students' abilities. It has a focus, which may
be a new breakthrough and possible development direction <note: ambiguous> for virtual
simulation experiments teaching technology for tourism management major in the future.
4.2 Comparative Analysis of Learning Effect
Next, the learning effects of the groups were compared further. The results are shown
in Table 6 and Fig. 2. <note: Generally, paragraphs should be longer than two sentences> According to Fig. 2, before the implementation of virtual simulation experiment teaching, the learning
effects of students in the two groups were 44.21 and 43.60, respectively, with no
significant inter-group difference. Referring to Table 5, after the implementation of the virtual simulation experiment teaching, the differences
in the three aspects of learning effects (basic quality, learning status, and learning
discipline) between the two groups were all 0.000 (Sig) <note: ambiguous>, which implied
a significant inter-group difference. Hence, the virtual simulation experiment had
a substantial impact on every aspect of learning effects in tourism planning.
Fig. 2. Comparison of learning effect between the two groups before and after implementation of virtual simulation experiment teaching.
Table 5. One-way ANOVA results between observation group and control group in learning effect.
|
-
|
-
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
Learning Effect
|
Between Groups
|
1825.598
|
1
|
1825.598
|
101.954
|
.000
|
|
Within Groups
|
1360.863
|
76
|
17.906
|
-
|
-
|
|
Total
|
3186.462
|
77
|
-
|
-
|
-
|
|
Basic Quality
|
Between Groups
|
401.103
|
1
|
401.103
|
116.454
|
.000
|
|
Within Groups
|
261.768
|
76
|
3.444
|
-
|
-
|
|
Total
|
662.872
|
77
|
-
|
-
|
-
|
|
Learning Status
|
Between Groups
|
244.314
|
1
|
244.314
|
42.864
|
.000
|
|
Within Groups
|
433.186
|
76
|
5.700
|
-
|
-
|
|
Total
|
677.500
|
77
|
-
|
-
|
-
|
|
Learning Discipline
|
Between Groups
|
49.969
|
1
|
49.969
|
22.572
|
.000
|
|
Within Groups
|
168.249
|
76
|
2.214
|
-
|
-
|
|
Total
|
218.218
|
77
|
-
|
-
|
-
|
Table 6. Correlation coefficients between virtual simulation experiment teaching and self-directed learning ability.
|
|
|
Correlation coefficients
|
|
Dependent variable
|
Virtual simulation experiment teaching?
|
Standardized coefficients
|
df
|
F
|
Sig.
|
|
|
|
Beta
|
Bootstrap (1000) Estimate of Std. Error
|
|
|
|
|
self-directed learning ability
|
Yes
|
0.698
|
0.041
|
1
|
291.205
|
0
|
|
learning effect
|
Yes
|
0.79
|
0.043
|
2
|
344.136
|
0
|
Upon the implementation of a traditional teaching scheme, the learning effect of the
control group increased by merely 3.30 from 43.60 to 46.90. This indicated that traditional
teaching modes had no significant positive influence on the learning effect. But when
virtual simulation experiment teaching was employed, the learning effect of the observation
group had a substantial increase of 28% than before (i.e., from 44.21 to 56.58). The
application of virtual simulation in experimental teaching improved the three aspects
related to the learning effect to a certain extent, but the degree of improvement
is different.
<New paragraph> The application of virtual simulation experiment teaching brought
about the most prominent effect on improving students’ learning status, with an increase
of 31%. In comparison, the increases in the other two aspects were 26% and 25.2%,
respectively, which means that the existing virtual simulation experiment teaching
technology is not comprehensive in improving the students' ability. It only focuses
on some aspects. Therefore, it leaves a big chance for a new breakthrough and possible
development in virtual simulation experiment teaching technology for the tourism management
specialty in the future.
The research results show that there could be a reform in the virtual simulation classroom.
This could be done by exploring modern education methods based on the classical traditional
classroom teaching mode and enhancing the teaching effect of the course through exploration
and implementation of mixed online and offline teaching modes. The promotion of a
virtual simulation classroom for teaching purposes is consistent with the conclusions
of relevant research [22].
4.3 Optimal Scale Regression Analysis
Self-directed learning ability and learning effects were analyzed by optimal scale
regression. The standard beta coefficient between virtual simulation experiment teaching
and students’ self-directed learning ability was 0.698, and its sig <note: ambiguous>
was 0.000 (Table 6). This indicated that the virtual simulation experiment teaching had a notable positive
impact on the self-directed learning ability of students in the observation group.
It could better help students to carry out project design, project simulation, field
exploration, map design, and other learning tasks in an independent manner.
The standard beta coefficient between the virtual simulation experiment teaching and
learning effect was 0.790 with sig <note: ambiguous> equal to 0.000 (Table 6). This suggested that the virtual simulation experiment teaching had a significant
positive impact on students’ learning in the tourism planning course. The power of
virtual simulation experiment teaching in overcoming the dilemmas in traditional teaching,
such as the lack of practical data and insufficient maneuverability, may account for
this observation. Through virtual simulation technology, the students could explore
tourism resources more comprehensively and classify them more accurately. Specifically,
virtual simulation technology was used to simulate the effect of tourism planning,
plot relevant maps, and strengthen tourism planning and design by means of stereoscopic
visual presentation <note: ambiguous>, thus improving students’ basic quality of tourism
planning and their learning effect.
5. Research Conclusions and Discussion
5.1 Discussion
(1) The reasons why virtual simulation technology can enhance the learning effect
There are three primary reasons why virtual simulation technology can improve the
practical teaching of tourism management in application-oriented universities. Firstly,
virtual simulation technology breaks through the spatial-temporal constraints of conventional
tourism teaching. Virtual simulation technology also aids in guiding students to complete
various experimental projects while improving their ability in process design and
professional practice. Secondly, the practical teaching environment in virtual simulation
experiment teaching is more open, and students can interact directly with various
virtual scenes. This vastly stimulates students’ enthusiasm about their major and
enormously enhances teaching efficiency.
Thirdly, a virtual simulation practice teaching system can be accessed through the
Internet. It is therefore easier to carry out large-scale class experiments while
making them accessible to students and the public. This will encourage students to
learn from their peers and help each other. It will help improve the effectiveness
of tourism practice and teaching.
(2) The need for promoting such a technology and how to improve the virtual technology
in different research regions
The application of virtual simulation technology should give more attention to the
rationality of system design and the efficiency of information collection. In the
application of virtual simulation technology, it is very important to design an efficient
and reasonable information system and strengthen the function and efficiency of collecting
information by software technology. There are obvious differences in the functional
requirements of software systems in different fields, but the same requirements are
needed for information collection and storage. For example, the design of the virtual
simulation classroom information system focuses on the storage of information and
the collection of patient information <note: ambiguous>. It requires both a reasonable
information system to reduce the failure of information storage and efficient information
collection technology to complete and quickly upload the information of students and
teachers to the central system. In the future, with more mature computer and software
technologies, the speed of information collection and the amount of information stored
will be rapidly increased.
(3) How to promote the broad construction of the technology at a higher level
Virtual simulation experiment teaching should to be compatible <note: ambiguous; compatible
with what?> and forward-looking <note: ambiguous>. It can realize the development
of a teaching environment and the sharing of teaching resources among colleges and
universities. Application-oriented universities should build a virtual simulation
experiment teaching platform, integrate different majors and disciplines, and promote
cooperation in virtual simulation experiment teaching among colleges and universities.
This can promote the development and sharing of virtual simulation experiments in
tourism management. Furthermore, universities should encourage students to deeply
engage in the research and development of a virtual simulation experiment so as to
have more practice based on theoretical knowledge in a virtual simulation experiment
and to promote innovation ability in experimental research. This will promote the
diverse development of virtual simulation experiments in tourism management.
5.2 Conclusion
Students majoring in tourism management were divided into an observation group and
a control group, and the effect of virtual simulation technology on tourism practice
teaching in application-oriented universities was investigated. Experimental comparative
analysis and multivariate statistical analysis methods were applied. The results and
suggestions obtained are as follows.
(1) Compared with the traditional teaching method, the virtual simulation experiment
had a substantial impact on every aspect of self-directed learning ability in tourism
planning. With the virtual simulation experiment teaching implemented, the overall
level of students’ self-directed learning ability was 22% higher than before. In terms
of four aspects related to the students' self-directed learning ability, the application
of virtual simulation in experimental teaching improved them to a certain extent,
but the degree of improvement was different. Out of the four aspects, the application
of virtual simulation experiment teaching had the most prominent effect on improving
students’ learning motivation with an increase of 24%.
(2) Compared with the traditional teaching method, the virtual simulation experiment
had a substantial impact on every aspect of learning tourism planning (28% higher
than before). In terms of the three aspects related to the learning effect, the application
of virtual simulation in experimental teaching improved them to a certain extent,
but the degree of improvement was different. The application of virtual simulation
experiment teaching brought about the most prominent effect on improving students’
learning status with an increase of 31%.
(3) The existing virtual simulation experiment teaching technology cannot improve
students' ability in a comprehensive way. Instead, it has a focus, which may be a
new breakthrough <note: ambiguous> and lead to possible development of the virtual
simulation experiment teaching technology in the tourism management specialty in the
future.
ACKNOWLEDGMENTS
This work was supported by the Guangxi Higher Education Undergraduate Teaching
Reform Project, “Exploration and Practice of the Integration of Hotel Management Education
and Innovation and Entrepreneurship Education in Applied Undergraduate Universities
from the Perspective of New Liberal Arts” (Project Number: 2021JGB387); 2021 Project
of Guangxi Education Science Planning: “Study on the Path Optimization of Guangxi
Application-oriented Universities serving Rural Revitalization in the Post-epidemic
Era -- A Case study of Guilin University of Aerospace Technology” (Project Number:
2021C349); Guangxi Higher Education Undergraduate Teaching Reform Project, “Research
and practice on the teaching effect of MooC in applied Universities” (Project Number:
2016JGZ170); University-level Undergraduate Teaching Reform Research Project of Guilin
University of Aerospace Technology, “Research on Hybrid Teaching Reform and Practice
of Hotel Management Major in Applied Undergraduate Based on CDIO Concept” (Project
Number: 2021JB04); and 2020 Teaching Team Construction Project of Guilin University
of Aerospace Technology, “Hotel Management Undergraduate Teaching Team “ (2020JXTD003).
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