# Construction of Cross-Cultural College English Teaching System Based on Computer Simulation Technology

Authors: Jiangshui Xiang
Journal: Security and Communication Networks
 (2022)

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## Abstract

For a long time, college English instruction has emphasised language skills training and information transfer while neglecting to emphasise the development of cross-cultural communication skills. Theoretical study on cross-cultural communication ability, on the other hand, has grown in various dimensions and lacks empirical research methodologies. Meanwhile, in real teaching, a cross-cultural communicative competence training framework that is adequate for Chinese college English teaching practise and has a high degree of recognition and operability has yet to be constructed. This paper uses computer simulation technology to construct the teaching system of college English cross-cultural knowledge. At the same time, this paper proposes a cross-cultural communicative competence training model suitable for Chinese college English teaching based on the Chinese language communication environment and foreign language teaching environment. Finally, this paper constructs a cross-cultural university English teaching system model through computer simulation. Through teaching experiments, we can see that the system constructed in this paper has a certain effect.


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## Body

## 1. Introduction

The most distinctive feature of cross-cultural foreign language teaching is to highlight the humanity of foreign language education. The overall goal of teaching includes not only the language and literature goals of improving learners’ foreign language communication skills but also the social and humanistic goals of improving learners’ cross-cultural communication skills. Improving foreign language communicative competence is the foundation and prerequisite, and an important means to cultivate cross-cultural communicative competence. The cultivation of cross-cultural communicative competence also promotes the improvement of foreign language communicative competence. The four key modules of cross-cultural foreign language instruction contain two significant contents of other culture teaching and cross-cultural communication capacity training, in addition to the two main contents of the conventional target language and target culture teaching. Furthermore, “language awareness” and “cultural awareness” have been included in the language and cultural teaching modules to assist learners in reflecting on their mother tongue and culture while studying the target language and culture [1]. Therefore, the cultivation of cross-cultural communicative competence under the framework of cross-cultural foreign language teaching not only emphasises the extensional ability to communicate with people of different cultures but also puts learners’ relevance and introspective ability to their mother tongue and mother tongue culture in an equally important position [2].Cross-cultural English teaching is a teaching that cultivates students’ understanding of English-speaking countries and their native cultures and enhances their awareness of intercultural communication. It aims to improve students’ ability to control the English language, so that students can use the language appropriately to communicate with foreigners who speak English [3].Cross-cultural English teaching aims to realize the combination of internationalization and localization in the process of communication. It is not only language teaching but also cultural teaching. The ultimate goal of cross-cultural English teaching is to cultivate students’ cross-cultural competence and enhance students’ cross-cultural communication skills, so that they can become a cross-cultural person. What is cross-cultural communicative competence? Many scholars at home and abroad have given definitions. In recent years, discussions on this issue have also been very lively in academic circles. The view of foreign scholars is that intercultural communication ability is the ability to have the same unique activity methods as individuals in a certain environment in order to achieve their personality and goal expectations; cross-cultural communication ability is the ability of individuals or organizations in different cultures and the ability to communicate effectively in the context and emphasises the identity of individuals and organizations with different cultures participating in the communication. Domestic scholar Wen Qiufang divides intercultural communicative competence into communicative competence and intercultural competence. Among them, communicative competence is composed of language competence, pragmatic competence, and strategic competence; cross-cultural competence is composed of cross-cultural sensitivity and tolerance. Cross-cultural communication skills require people or organizations in different cultural environments to have the ability to accurately understand, perceive, express, and evaluate their own culture and the culture of other countries.Both students and instructors share this understanding in conventional teaching philosophy: if you grasp the subject of the test, you may gain high results and fulfil the goal of learning. In English subjects, the content of the test mainly involves vocabulary, grammar, reading, and writing, and as long as these contents are practiced repeatedly, there is no need to spend more time and energy to learn cultural knowledge. In fact, this concept is outdated. With the continuous improvement of people's understanding of globalization, exchanges among countries are also increasing. People are eager to exchange ideas and transfer information. These all require English learning not only to master the language but, more importantly, to understand the complementary relationship between language and culture. Only by mastering the differences between Chinese and Western cultures can we improve cross-cultural communication skills. This is also the original intention and purpose of English teaching in the basic education stage.Based on the above analysis, this paper uses computer simulation technology to construct a cross-cultural college English teaching system and apply it to English teaching practice to improve the effect of cross-cultural college English teaching.


## 2. Related Work

Since the computer was first applied to education in the late 1950s, related applied research has roughly experienced three stages of development. CAI projects are mainly implemented on mainframes, and people have conducted systematic research on these large-scale CAI projects [4]. Microcomputers came out and were widely used in schools. People began to explore microcomputer-assisted education after the CAI paradigm and software on mainframes were extensively translated to microcomputers in the previous stage. Interactive multimedia has made its way into the classroom. The mode and technique of CAI have experienced considerable changes as a result of its potential benefits over prior computers in many respects, as well as the effect of remote communication and the Internet. As a consequence, research into multimedia-assisted education began [5].With the development of computer technology, especially the improvement of the understanding of modern education technology, computer-assisted teaching has been widely used in the teaching of various courses at all levels and has become one of the necessary means to measure the teaching level and teaching quality [6]. In particular, the development of information technology with multimedia and network technology as the core has enabled people’s learning and communication to break the boundaries of time and space in the past and brought new space for the improvement and function of human capabilities. In order to adapt to this development trend, our country has determined to popularize information technology education in primary and secondary schools and strengthen the integration of information technology with other courses [7]. That is, “information technology and curriculum integration” refers to a new type of teaching method that organically combines information technology, information resources, information methods, human resources, and course content in the course of course teaching to jointly complete course teaching tasks [8]. It is a new point of view for the reform of basic education in the 21st century, and it is a new type of teaching that is closely related to and inherited from traditional subject teaching and has a certain relative independence [9]. After more than 20 years of practice and development, the early simple application of computers has developed into the current “information technology and curriculum integration” [10]. Moreover, computers have also become an important method in experimental teaching. Computer simulation courseware is one of the main forms of modern education technology [11]. It is guided by learning theories, such as behavior theory, cognitive theory, and constructivism, and educational theories, such as pedagogy and computer science [12]. Moreover, it is a kind of multimedia software that uses multimedia technology to process graphics, animation, text, etc., to express a certain teaching strategy and teaching content according to a specific teaching goal. In addition, it is an organic combination of teaching content and teaching logic [13]. The introduction of modern teaching methods has always been one of the contents of teaching reform. With the deepening of teaching reform, computer simulation has become increasingly popular with teachers and students due to its large teaching capacity, vivid image, wide teaching time and space, and ease to stimulate teachers’ and students’ interest in teaching [14].There are still many problems or misunderstandings in computer-assisted teaching, such as the limitation of courseware; that is, no matter how good the courseware is, it is generally only suitable for a specific teaching situation [15]. Moreover, the use of CAI weakens the emotional communication between teachers and students. In addition, there are misunderstandings of CAI and the quality of teachers. It is generally believed that the effect of computer-assisted teaching is affected by software, teachers, students, environment, and other factors. Only by handling the relationship between these factors can computer-assisted teaching achieve good results [16]. Throughout the research on computer-assisted teaching, it is found that people have a consensus on the effectiveness of computer-assisted teaching in many aspects, but there are still differences in some aspects. This also shows that computer-assisted teaching is a complex problem that requires us to continue to study in depth [17].


## 3. Computer Simulation Steps

Identifying research challenges and goals, identifying mathematical logic models, gathering and processing data, developing simulation models and programming, simulation results analysis and verification, and so on are some of the computer simulation stages. The computer simulation flowcharts in this paper are all suitable for the step process of the computer simulation program under normal circumstances. For special or concise computer simulation processes, the process steps can be reduced [18].The computer simulation steps are as follows:(1)
Determining research issues and plans:According to the existing conditions and corresponding system requirements, the algorithm determines the goals and tasks of the computer simulation, formulates the overall plan of the computer simulation, and compares the objective function of the simulation results.(2)
Determining the mathematical logic model:First, the algorithm analyzes the mathematical logic relationship between the variables and suitable parameters of each part of the system. Before doing this analysis, it is necessary to clarify the system structure to be simulated and the corresponding evaluation rules and finally establish the model.(3)
Collecting and processing information and data:In the computer simulation module, collecting information and data is a very large workload, and the difficulty of collecting is also very large in the entire simulation. Moreover, it occupies the largest weight and is time-consuming, which often requires the support of a lot of resources. There are two problems in the final result of the collected data. On the one hand, data information may not be collected under special conditions. On the other hand, some data information is obtained, but it is often rarely directly input to the simulation model. In this case, domain experts make a level of estimation and conjecture based on subjective practical experience, and the data obtained in this way is the data information to be collected. The specific computer simulation flowchart is shown in Figure1 [19].Figure 1
Computer simulation flow chart.Next, we need to process the collected data information, that is, to infer an overall distribution of the data information based on the collected data information. The approximate distribution of the data population can be inferred based on the collected data values, or the fit test of the distribution function can be performed [20].


### 3.1. Histogram

The horizontal axis is used to represent the data type, while the vertical axis is used to illustrate the distribution, under usual circumstances. To describe the distribution of data information, several vertical stripes or line segments of varying heights are used to depict the overall situation. In the context of this paper’s study, the histogram approach is equal to the approximation method of probability density. The construction steps of the histogram are as follows [21]:(1)
The data range is divided into intervals with equal width, and the maximum value is marked byc, and the minimum value is marked by d.(2)
The mark is made on the horizontal axis, the intervalc,d is divided into n subintervals, and the group distance of each group is d−c/n.(3)
The frequency of occurrence in each interval is calculated, and the marklii=1,2,…,n is called the frequency. We set(1)fi=lil.Among them,fi is the frequency at which the observation falls on ci−1,ci.(4)
Mark on the vertical axis and arrange them in a row in a rectangular manner.(2)yi=fici−ci−1.In practical applications, if the selected interval is too large, the histogram will appear rough, and the achieved effect is not too ideal. If the distance of the selected interval is too small, the histogram will have glitches, and the data will appear blunt and not smooth. In addition, the collected data are discrete and continuous. The shape of the histogram of the continuous data is very close to the shape of the probability density function pdf curve.After collecting the data information, process the data and use the sample mean and sample variance to estimate the parameters of the hypothetical distribution [22].According to statistical principles, the observed value of a sample of sizen is X1,X2,…,Xn.(3)X¯=∑i=1nXin,whereX¯ represents the sample mean.(4)S2=∑i=1nXi2−nX¯n−1,whereS2 represents the sample variance.


### 3.2. Test of Goodness of Fit

This paper studies the cloud model evaluation method based on computer simulation. In the goodness-of-fit test method, only theχ2-fittest method is introduced, and the process is as follows.The overallX distribution function is Fx, which is the actual distribution function and is unknown. The distribution function of the possible population X that is inferred from the sample value is F∗x, where F∗x represents the theoretical fraction function of X, and then, F∗x is tested.(1)
Then sample values are equally divided into d groups and arranged in order of size. The number of sample points on the i-th interval ti−1,ti is represented by mi, mi/n is the frequency, and a histogram of the frequency is drawn. The distribution function F∗x of X is determined from the histogram, and the distribution of the overall X is estimated according to the histogram.The original assumption is(5)H0:Fx=F∗x,p^i=F∗ti−F∗ti−1.The above formula is mainly to study the degree of difference betweenmi and np^i.(2)
Select Pearson statistics(6)χ2=∑i=1dmi−np^inp^i=−1n∑mi2pi−n.The above formula proves that whenn tends to be infinite, it will be distributed according to χm−r−1(3)
The probability expression of a small probability event (whereα is given) is(7)Pχ2>χα2m−r−1=α.(4)
According to the value ofχ2, the value of χα2m−r−1 is found. The value of χ2 is based on the sample value(5)
Make judgment: if the result is to rejectH0, it must be χ2>χα2m−r−1 (small probability event appears), and if the result is to accept H0, it must be χ2<χα2m−r−1.


### 3.3. Establish Simulation Model and Program Writing

The following formula is used to generate a simulation model of a random variable, and the random variable conforms to a normal distribution. This formula generates suitable random variables based on the inferred probability density function of the data distribution. When writing a program, first of all, we must understand how to transform a mathematical model into a model that can be expressed in computer programming languages. Secondly, we choose a suitable programming language, and finally, we must repeatedly consider the entire program.(8)y=μ+σ2∑k=16ξk−3.


### 3.4. Analysis of Simulation Results

The computer simulation results are produced after a number of computer simulation procedures. To check whether the data information fulfils the real needs, it must be evaluated and tested. In general, hypothesised tests are simulated output data and actual data values. However, under normal circumstances,t-test and F-test methods are used to test whether the simulated data values are significantly different from the actual data values. They are mainly used to estimate the parameters of the hypothetical distribution (sample mean and sample variance are often used).


#### 3.4.1.t-Test Method

The object of thet-test method is the hypothesis of the difference between the sample means of two normal populations.The sample of the normal populationNμ1,σ12 is composed of X1,X2,…,Xn1, and the sample of the normal population Nμ2,σ22 is composed of Y1,Y2,…,Yn2, and they are independent of each other. Among them, X¯ represents the sample mean of the sample of the normal population Nμ1,σ12, Y¯ represents the sample mean of the sample of the normal population Nμ2,σ22, S12 represents the sample variance of the sample of the normal population Nμ1,σ12, and S22 represents the sample variance of the sample of the normal population Nμ2,σ22. Moreover, none of μ1,μ2,σ12,σ22 is known.If we assumeS12=S12, then(9)H0:μ1−μ2=δ,H1:μ1−μ2≠δ,where δ is the rejection domain of an existing constant.(10)t=X¯−Y¯−δSw1/n1+1/n2.The test statistic is to select thet statistic.(11)Sw=n1−1S12+n2−1S22n1+n2−2,X¯−Y¯−δSw1/n1+1/n2≥k.Among them, when the premise is thatH0 is true, the form of the rejection domain of t:tn1+n2−2 is as above. Then, there are(12)PWhenH0is true,rejectH0=Pμ1−μ2=δX¯−Y¯−δSw1/n1+1/n2≥k=α.Thus, we getk:tαn1+n2−2, and finally, we get the rejection domain.(13)t=X¯−Y¯−δSw1/n1+1/n2≥tαn1+n2−2.


#### 3.4.2. F-Test Method

The sample of the normal populationNμ1,σ12 is composed of X1,X2,…,Xn1, and the sample of the normal population Nμ2,σ22 is composed of Y1,Y2,…,Yn2, and they are independent of each other. Among them, X¯ represents the sample mean of the sample of the normal population Nμ1,σ12, Y¯ represents the sample mean of the sample of the normal population Nμ2,σ22, S12 represents the sample variance of the sample of the normal population Nμ1,σ12, and S22 represents the sample variance of the sample of the normal population Nμ2,σ22. Moreover, none of μ1,μ2,σ12,σ22 is known.Now, the hypothesis needs to be tested.(14)H0:σ12≤σ22,H1:σ12>σ22,ES12=σ12≤σ22=ES22 (the premise is that H0 is true), ES12=σ12>σ22=ES22 (the premise is that H1 is true).The observation valueS12/S22 has a tendency to exceed normal (the premise is that H1 is true), so the rejection domain has the following form:(15)S12S22≥k.The constantk is determined in the following way:(16)PwhenAistrue,rejectA=Pσ12≤σ22S12S22≥k≤Pσ12≤σ22S12S22σ12≥kσ22.Because ofσ12/σ22≤1, if we want to control PwhenAistrue,rejectA≤α, we just make(17)Pσ12≤σ22S12S22σ12≥kσ22=α.From the above formula, we get(18)k=Fαn1−1,n2−1.It can be concluded that the rejection domain is(19)F=S12S22≥Fαn1−1,n2−1.


## 3.1. Histogram

The horizontal axis is used to represent the data type, while the vertical axis is used to illustrate the distribution, under usual circumstances. To describe the distribution of data information, several vertical stripes or line segments of varying heights are used to depict the overall situation. In the context of this paper’s study, the histogram approach is equal to the approximation method of probability density. The construction steps of the histogram are as follows [21]:(1)
The data range is divided into intervals with equal width, and the maximum value is marked byc, and the minimum value is marked by d.(2)
The mark is made on the horizontal axis, the intervalc,d is divided into n subintervals, and the group distance of each group is d−c/n.(3)
The frequency of occurrence in each interval is calculated, and the marklii=1,2,…,n is called the frequency. We set(1)fi=lil.Among them,fi is the frequency at which the observation falls on ci−1,ci.(4)
Mark on the vertical axis and arrange them in a row in a rectangular manner.(2)yi=fici−ci−1.In practical applications, if the selected interval is too large, the histogram will appear rough, and the achieved effect is not too ideal. If the distance of the selected interval is too small, the histogram will have glitches, and the data will appear blunt and not smooth. In addition, the collected data are discrete and continuous. The shape of the histogram of the continuous data is very close to the shape of the probability density function pdf curve.After collecting the data information, process the data and use the sample mean and sample variance to estimate the parameters of the hypothetical distribution [22].According to statistical principles, the observed value of a sample of sizen is X1,X2,…,Xn.(3)X¯=∑i=1nXin,whereX¯ represents the sample mean.(4)S2=∑i=1nXi2−nX¯n−1,whereS2 represents the sample variance.


## 3.2. Test of Goodness of Fit

This paper studies the cloud model evaluation method based on computer simulation. In the goodness-of-fit test method, only theχ2-fittest method is introduced, and the process is as follows.The overallX distribution function is Fx, which is the actual distribution function and is unknown. The distribution function of the possible population X that is inferred from the sample value is F∗x, where F∗x represents the theoretical fraction function of X, and then, F∗x is tested.(1)
Then sample values are equally divided into d groups and arranged in order of size. The number of sample points on the i-th interval ti−1,ti is represented by mi, mi/n is the frequency, and a histogram of the frequency is drawn. The distribution function F∗x of X is determined from the histogram, and the distribution of the overall X is estimated according to the histogram.The original assumption is(5)H0:Fx=F∗x,p^i=F∗ti−F∗ti−1.The above formula is mainly to study the degree of difference betweenmi and np^i.(2)
Select Pearson statistics(6)χ2=∑i=1dmi−np^inp^i=−1n∑mi2pi−n.The above formula proves that whenn tends to be infinite, it will be distributed according to χm−r−1(3)
The probability expression of a small probability event (whereα is given) is(7)Pχ2>χα2m−r−1=α.(4)
According to the value ofχ2, the value of χα2m−r−1 is found. The value of χ2 is based on the sample value(5)
Make judgment: if the result is to rejectH0, it must be χ2>χα2m−r−1 (small probability event appears), and if the result is to accept H0, it must be χ2<χα2m−r−1.


## 3.3. Establish Simulation Model and Program Writing

The following formula is used to generate a simulation model of a random variable, and the random variable conforms to a normal distribution. This formula generates suitable random variables based on the inferred probability density function of the data distribution. When writing a program, first of all, we must understand how to transform a mathematical model into a model that can be expressed in computer programming languages. Secondly, we choose a suitable programming language, and finally, we must repeatedly consider the entire program.(8)y=μ+σ2∑k=16ξk−3.


## 3.4. Analysis of Simulation Results

The computer simulation results are produced after a number of computer simulation procedures. To check whether the data information fulfils the real needs, it must be evaluated and tested. In general, hypothesised tests are simulated output data and actual data values. However, under normal circumstances,t-test and F-test methods are used to test whether the simulated data values are significantly different from the actual data values. They are mainly used to estimate the parameters of the hypothetical distribution (sample mean and sample variance are often used).


### 3.4.1.t-Test Method

The object of thet-test method is the hypothesis of the difference between the sample means of two normal populations.The sample of the normal populationNμ1,σ12 is composed of X1,X2,…,Xn1, and the sample of the normal population Nμ2,σ22 is composed of Y1,Y2,…,Yn2, and they are independent of each other. Among them, X¯ represents the sample mean of the sample of the normal population Nμ1,σ12, Y¯ represents the sample mean of the sample of the normal population Nμ2,σ22, S12 represents the sample variance of the sample of the normal population Nμ1,σ12, and S22 represents the sample variance of the sample of the normal population Nμ2,σ22. Moreover, none of μ1,μ2,σ12,σ22 is known.If we assumeS12=S12, then(9)H0:μ1−μ2=δ,H1:μ1−μ2≠δ,where δ is the rejection domain of an existing constant.(10)t=X¯−Y¯−δSw1/n1+1/n2.The test statistic is to select thet statistic.(11)Sw=n1−1S12+n2−1S22n1+n2−2,X¯−Y¯−δSw1/n1+1/n2≥k.Among them, when the premise is thatH0 is true, the form of the rejection domain of t:tn1+n2−2 is as above. Then, there are(12)PWhenH0is true,rejectH0=Pμ1−μ2=δX¯−Y¯−δSw1/n1+1/n2≥k=α.Thus, we getk:tαn1+n2−2, and finally, we get the rejection domain.(13)t=X¯−Y¯−δSw1/n1+1/n2≥tαn1+n2−2.


### 3.4.2. F-Test Method

The sample of the normal populationNμ1,σ12 is composed of X1,X2,…,Xn1, and the sample of the normal population Nμ2,σ22 is composed of Y1,Y2,…,Yn2, and they are independent of each other. Among them, X¯ represents the sample mean of the sample of the normal population Nμ1,σ12, Y¯ represents the sample mean of the sample of the normal population Nμ2,σ22, S12 represents the sample variance of the sample of the normal population Nμ1,σ12, and S22 represents the sample variance of the sample of the normal population Nμ2,σ22. Moreover, none of μ1,μ2,σ12,σ22 is known.Now, the hypothesis needs to be tested.(14)H0:σ12≤σ22,H1:σ12>σ22,ES12=σ12≤σ22=ES22 (the premise is that H0 is true), ES12=σ12>σ22=ES22 (the premise is that H1 is true).The observation valueS12/S22 has a tendency to exceed normal (the premise is that H1 is true), so the rejection domain has the following form:(15)S12S22≥k.The constantk is determined in the following way:(16)PwhenAistrue,rejectA=Pσ12≤σ22S12S22≥k≤Pσ12≤σ22S12S22σ12≥kσ22.Because ofσ12/σ22≤1, if we want to control PwhenAistrue,rejectA≤α, we just make(17)Pσ12≤σ22S12S22σ12≥kσ22=α.From the above formula, we get(18)k=Fαn1−1,n2−1.It can be concluded that the rejection domain is(19)F=S12S22≥Fαn1−1,n2−1.


## 3.4.1.t-Test Method

The object of thet-test method is the hypothesis of the difference between the sample means of two normal populations.The sample of the normal populationNμ1,σ12 is composed of X1,X2,…,Xn1, and the sample of the normal population Nμ2,σ22 is composed of Y1,Y2,…,Yn2, and they are independent of each other. Among them, X¯ represents the sample mean of the sample of the normal population Nμ1,σ12, Y¯ represents the sample mean of the sample of the normal population Nμ2,σ22, S12 represents the sample variance of the sample of the normal population Nμ1,σ12, and S22 represents the sample variance of the sample of the normal population Nμ2,σ22. Moreover, none of μ1,μ2,σ12,σ22 is known.If we assumeS12=S12, then(9)H0:μ1−μ2=δ,H1:μ1−μ2≠δ,where δ is the rejection domain of an existing constant.(10)t=X¯−Y¯−δSw1/n1+1/n2.The test statistic is to select thet statistic.(11)Sw=n1−1S12+n2−1S22n1+n2−2,X¯−Y¯−δSw1/n1+1/n2≥k.Among them, when the premise is thatH0 is true, the form of the rejection domain of t:tn1+n2−2 is as above. Then, there are(12)PWhenH0is true,rejectH0=Pμ1−μ2=δX¯−Y¯−δSw1/n1+1/n2≥k=α.Thus, we getk:tαn1+n2−2, and finally, we get the rejection domain.(13)t=X¯−Y¯−δSw1/n1+1/n2≥tαn1+n2−2.


## 3.4.2. F-Test Method

The sample of the normal populationNμ1,σ12 is composed of X1,X2,…,Xn1, and the sample of the normal population Nμ2,σ22 is composed of Y1,Y2,…,Yn2, and they are independent of each other. Among them, X¯ represents the sample mean of the sample of the normal population Nμ1,σ12, Y¯ represents the sample mean of the sample of the normal population Nμ2,σ22, S12 represents the sample variance of the sample of the normal population Nμ1,σ12, and S22 represents the sample variance of the sample of the normal population Nμ2,σ22. Moreover, none of μ1,μ2,σ12,σ22 is known.Now, the hypothesis needs to be tested.(14)H0:σ12≤σ22,H1:σ12>σ22,ES12=σ12≤σ22=ES22 (the premise is that H0 is true), ES12=σ12>σ22=ES22 (the premise is that H1 is true).The observation valueS12/S22 has a tendency to exceed normal (the premise is that H1 is true), so the rejection domain has the following form:(15)S12S22≥k.The constantk is determined in the following way:(16)PwhenAistrue,rejectA=Pσ12≤σ22S12S22≥k≤Pσ12≤σ22S12S22σ12≥kσ22.Because ofσ12/σ22≤1, if we want to control PwhenAistrue,rejectA≤α, we just make(17)Pσ12≤σ22S12S22σ12≥kσ22=α.From the above formula, we get(18)k=Fαn1−1,n2−1.It can be concluded that the rejection domain is(19)F=S12S22≥Fαn1−1,n2−1.


## 4. Cross-Cultural College English Teaching System Based on Computer Simulation Technology

The English cross-cultural data mining standard process describes a complete data mining cycle, including six stages of business understanding, data understanding, data preparation, data modeling, model evaluation, and deployment, as shown in Figure2.Figure 2
Schematic diagram of the standard process of English cross-cultural data mining.There are many different types of data mining procedures, and there is no good or bad among them, so we simply need to choose one to lead the data mining process. There is some mismatch with the English teaching behavior mining in this study because the cross-industry data mining standard method is more inclined to the description of the commercial area, and the six-step procedure prefers to describe the process of data mining to learners. As a result, this study uses data mining theory to create a technique that fits network teaching behavior mining. The English teaching behavior mining process is shown in Figure3, which is divided into six steps: problem definition, data collection, data preprocessing, behavior data mining, result in expression and evaluation, and English teaching improvement suggestions. These six steps will be described in detail.Figure 3
Mining process of English teaching behavior.With the support of information technology, more and more media provide information interaction functions between students and learning resources, expanding the scope of interaction. Moreover, it transforms the interaction from concrete to abstract, from low-level to high-level to form a teaching interaction level tower, as shown in Figure4.Figure 4
Interactive hierarchy tower of cross-cultural college English teaching.This teaching strategy is derived from the “recent development zone” theory. This theory refers to the distance between the learner’s current level of development to solve problems independently and the potential level of development to solve problems under the guidance of teachers, as shown in Figure5. There is not only teachers’ strategic guidance in scaffolding teaching practise but also a teaching model in which teachers assist students in gradually completing meaning construction, that is, building scaffolding, entering the context, independent exploration, collaborative learning, and effect evaluation. We can only assist pupils to reach their full potential via a progressive teaching method. Teachers continue to give incremental scaffolding assistance for students’ expanded learning and steer students toward the development of higher-level skills, according to the teaching models developed based on the scaffolding teaching technique.Figure 5
Structure diagram of teaching strategy.Figure6 shows the model of English cross-cultural “one, three, five” classroom reform. Its connotation is based on the premise of respecting the status of students as the subject of learning, and it uses modern education information technology as a means and its use of group teaching as the basic form. Moreover, it organizes students’ independent, cooperative, and inquiry-based learning, cultivates the ability of students to learn independently, cooperatively, and practice innovation, and comprehensively improves the quality of students. Among them, “one” refers to the guiding ideology of “make the classroom agile”, which is also the essence of an efficient classroom. “Five” refers to the five teaching strategies of “study plan guidance, microclass learning assistance, cooperative mutual learning, training and testing, and evaluation to promote learning”. These five teaching strategies will not only help the smooth and effective development of the teaching model but will also enrich the form and content of classroom activities and enhance the teaching effect. “Three” refers to the three stages of “autonomous preview, inquiry study, and consolidation exercise” in the teaching process. These three stages, respectively, correspond to the preclass, in-class, and after-class stages, helping students achieve personalized generative learning.Figure 6
“one, three, five” teaching mode.The cloud image of the comprehensive evaluation result is obtained by using the virtual cloud theory and comprehensive cloud algorithm. The generated cloud images and detailed comments are detected by the similarity comparison strategy algorithm. The reference decision information module is the information that provides the decision-maker to make the final evaluation findings and specifics of the evaluation. The overall decision-making module is the decision-maker to make the final decision and save the decision result to the database. The database clearing module means that when the decision-maker needs to reevaluate to input new information or apply the system to another field for evaluation, it needs to clear the data of the previous field evaluation. The specific results are shown in Figure7.Figure 7
Functional structure diagram of the evaluation system.


## 5. Performance Verification of Cross-Cultural College English Teaching System

This paper combines computer simulation technology to construct the cross-cultural college English teaching system and analyzes the structure and function of the system according to the actual needs of the cross-cultural knowledge teaching system. Moreover, this paper verifies the teaching effect of the system constructed in this paper through design experiments. The statistical results are shown in Table1 and Figure 8.Table 1
Statistical table of the evaluation of the teaching effect of the cross-cultural college English teaching system based on computer simulation technology.
NoTeaching effect190.8293.3389.2484.8594.0692.5793.8892.3995.81082.81185.41287.71390.31489.51595.71686.71786.41892.61984.12089.82182.72289.92393.32494.42595.52689.12790.92885.92988.43083.23193.43287.03387.43482.73586.03693.73788.13883.23984.54094.14188.14295.94386.54488.54595.14689.64783.04896.04986.45082.25185.15284.85388.85490.65586.05695.55785.85891.95989.46084.66185.96282.86386.96495.86586.76683.76783.56890.76989.87083.77182.37292.87382.17492.17595.87686.27795.37893.67995.48084.58183.18282.28383.78488.98582.28684.28794.78894.98994.19083.69193.69285.19384.09492.09583.09684.0Figure 8
Statistical diagram of the evaluation of the teaching effect of the cross-cultural college English teaching system based on computer simulation technology.From the above evaluation, it can be seen that the cross-cultural college English teaching system based on computer simulation technology constructed in this paper has good English teaching effects. Therefore, the system constructed in this paper can meet the actual needs of current cross-cultural college English teaching.


## 6. Conclusion

Including the development of intercultural communicative skills as an essential aspect of college English teaching broadens the meaning of college English courses and improves the quality of English instruction. Furthermore, including cross-cultural teaching in college English classes may help to organically integrate the instrumental and humanistic parts of college English classes. Furthermore, by incorporating socialist fundamental principles into college English courses organically, college English may better serve the interests of the nation and society, as well as the needs of students’ personal growth. Based on the collation and review of cross-cultural communicative competence models at home and abroad, starting from the language communicative environment and foreign language teaching environment in my country, this paper proposes a cross-cultural communicative competence training model suitable for college English teaching in my country. Moreover, this paper constructs a cross-cultural college English teaching model through computer simulation. Through teaching experiments, we can see that the system constructed in this paper has certain effects.



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*Source: 6794931-2022-06-03.xml*