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A study on the reform of college English education inspired by the cultural differences between China and the United States

Publicado en línea: 14 Nov 2022
Volumen & Edición: AHEAD OF PRINT
Páginas: -
Recibido: 15 May 2022
Aceptado: 30 Jun 2022
Detalles de la revista
License
Formato
Revista
eISSN
2444-8656
Primera edición
01 Jan 2016
Calendario de la edición
2 veces al año
Idiomas
Inglés
Introduction

In English education and teaching in colleges and universities, cross-cultural education can enable students to better understand the differences between Chinese and American cultures, such as the differences in social customs, values and morality between Chinese and American cultures [1]. Only by guiding students to correctly understand the cultural differences between China and the United States through cross-cultural education and teaching can students better master the essence of English culture [2]. In the primary stage of English learning, teachers generally pay more attention to the learning of English language knowledge due to various pressures of entering a higher school, thus ignoring culture teaching, which is lack of comprehensive English learning.

A previous study [3] states that colleges and students should not only use normal class time to study but also make full use of external leisure time to study hard and constantly accumulate and master Chinese culture, so as to make better use of and spread Chinese culture. Another study [4] believes that understanding and adjusting the differences between Chinese and Western cultures in teaching is one of the effective means of teaching quality. This article expounds the differences between China and the West, analyses its reasons, introduces the differences between Chinese and Western education and teaching modes and puts forward some suggestions to eliminate the differences between China and the West. One other study [5] from the perspective of micro-class, combined with modern teaching methods, created a diversified classroom teaching model suitable for business education and carried out educational reform. It is helpful to broaden students’ vision and expand and optimise the allocation of school resources. An upgraded classroom model can also better promote students’ enthusiastic participation, cultivate students’ learning enthusiasm and provide a high-quality platform for cultivating all-round talents suitable for market demand and professional skills. A previous study [6] takes the educational concept of the new curriculum as the basic guiding concept, fully invests in the process of educational practice, constantly develops and innovates, explores educational methods more suitable for the characteristics of modern society, further improves the effect of classroom teaching and realises the efficient education of high school teaching. Yet another study [7] integrates multimodal teaching strategies to diversify listening teaching modes in colleges and universities, which is helpful to cultivate students’ subjective initiative and multimodal cognitive ability. This article expounds the connotation of the multimodal theory, analyses the current situation of college listening teaching mode under the multimodal environment and puts forward the way of reform. A previous study [8] analyses the problems existing in the current high-school English teaching and puts forward a feasible teaching reform scheme under the background of big data, so that the English writing ability can be realised under the background of real modernisation.

College English teaching is in the deep water of information reform, and the teaching reform strategy has become the focus of research. This article proposes a study on the reform of college English education inspired by the cultural differences between China and the United States. First, we aim to understand the cultural differences between China and the United States and analyse the background and current situation of college English information teaching, aiming at the existing problems; establish a matrix factor model to obtain the characteristic values of cultural differences; predict the efficiency of the development trend of college English education reform according to the VaR identification model; strive to give full play to the role of information-based teaching ideas and means and improve the quality of English teaching in higher vocational colleges.

The current situation of college English education inspired by the cultural differences between China and the United States

Campus culture is not only reflected in the core competitiveness, levels and characteristics of students but also in the campus after the social economy has developed to a certain level [9]. With the continuous development of today's society, the exchanges between China and the United States are increasing, and the cultural exchanges and collisions are constantly formed. The campus cultures of China and the West gradually show their fascinating charm and very strong vitality in the exchanges and collisions [10]. However, there are some cultural differences between the two sides. This article makes an in-depth discussion on the differences between Chinese and American campus culture, investigates the reasons and analyses their advantages on this basis, so as to promote the development direction of China's education in the future.

Let students understand the living habits and customs of American society and the law of language action, which will help students better master the key points of knowledge in English learning [11]. First, in terms of privacy, Chinese people do not shy away from personal conditions such as age and work, while Americans believe that such inquiries involve personal privacy. Second, Americans are rigorous. Chinese people are often used to forgiving each other's small mistakes and giving each other a chance. Chinese people do not like to look directly into each other's eyes in daily communication, thinking it will be very uncomfortable, while Americans think it is one of the ways of equal communication [12]. In China, the folk custom of hospitality has been almost well known all over the world. Once the Chinese are the host, they are bound to entertain the guests warmly and say some polite words. Compared with Americans, they are more straightforward and would not be too polite to each other. Therefore, in the cross-cultural English education and teaching between China and the United States in colleges and universities, we need to help students understand the connotation knowledge and differences of Chinese and American cultural backgrounds, and understand the obstacles caused by Chinese and American cultural differences in students’ learning, so that students can better understand the connotation of English teaching culture [13].

First of all, Chinese and American civilisations have endowed human beings with different cultures in different regional environments. When praised by others, Chinese people prefer to answer in a modest way, while Americans will accept and thank them directly. It can be seen that the Chinese believe that modesty and prudence are important, while the Americans believe that their expression is true and respectful, resulting in differences in values on the same issue [14]. Second, in English teaching, teachers’ praise to students often makes students feel shy, and then teachers will say some words of encouragement and warning, while American students will accept it calmly and show sincere confidence.

Collectivism is widely respected in China, while Americans advocate individualism and sense of independence and put personal interests first, which is completely opposite to the concept of Chinese collectivism, which is to worry about the world first and enjoy the world later [15]. Chinese people always believe that many people have great power, but Americans advocate personal supremacy [16]. In the face of these problems caused by the differences in morality and values, college students will eventually be hindered by obstacles in English cross-cultural learning. If they cannot treat the differences equally and objectively, they will eventually be unable to acquire the essence of English culture under the background of the obstacles of cultural differences between China and the United States.

At present, college education still adopts the traditional way of education and does not pay attention to the grammar, key points of knowledge, English words and technical application of basic knowledge and relative English. Higher education has carried out many reforms and innovations, but it has not changed the shortcomings of higher education from the source. Some students continue to study after entering the era from kindergartens to primary and secondary schools, middle schools, ordinary high schools and colleges and spend a lot of time learning and training, but in the final application, the result is not ideal [17]. In public places and workplaces, learning cannot be integrated with daily life.

In today's globalisation, the use of English has become very common. The utilisation rate of various countries is also very large, so the education work of colleges and universities should make rapid progress and cultivate professional talents [18]. The connection between ordinary high-school education and social development can be smoother in the future application. In classroom teaching, we should cultivate professional talents in an all-round way and cultivate students’ quality. The systematisation of higher education is the final goal of colleges and universities and the overall goal of continuous pursuit of perfection.

Model establishment
Matrix-valued factor model

Set up Xt(t = 1,2, ⋯,T) represents the time series of matrix values, where Xt is representative of the p1 × p2 dimension matrix [19], and the formula is as follows: Xt=[xt,11xt,1p2xt,p11xt,p1P2] {X_t} = \left[{\matrix {{{x_{t,11}}} & \cdots & {{x_{t,1{p_2}}}} \cr \vdots & \ddots & \vdots \cr {{x_{t,{p_1}1}}} & \cdots & {{x_{t,{p_1}{P_2}}}} \cr}} \right] If Xt represents the covariance matrix of a positive definite symmetry, so that p1 = p2 = n and implement decomposition, and the formula is as follows: Xt=LtLt {X_t} = {L_t}{L_t} where Lt is the triangular matrix [20] after decomposition is described, which is modelled by the using matrix-valued factor method. The formula is as follows: Lt=RFtC'+Et {L_t} = R{F_t}{C^{'}} + {E_t} Among them, Ft expresses k1 × k2 (k1,k2n) a dimensional potential factor matrix, R expresses n × k1 a pre-dimensional load matrix, C expresses n × k2 a post-dimensional load matrix and Et represents a difference matrix. Set up k1 = n and R is n dimensional unit matrix, and the model becomes Lt = FtC + Et. On this basis, in the matrix Lt, every column is Ft. The linear combination of the overall column vectors can be known as the matrix C. As column load matrix [21]. Similarly, the matrix R is a row load matrix.

Keep the row and column load matrix unchanged, and the factor matrix after dimension reduction Ft. Use the VAR mode to implement modelling and prediction, so that vec(·) vectorisation operator lag p order, and the formula is as follows: vec(Ft+1)=p=1pΦF,tp+1vec(Ftp+1)+et+1 vec\left({{F_{t + 1}}} \right) = \sum\limits_{p = 1}^p {\Phi _{F,t - p + 1}}vec\left({{F_{t - p + 1}}} \right) + {e_{t + 1}} ΦF is the k1k2 × k1k2 dimensional coefficient matrix and e is the cultural difference vector [22]. It can be concluded that the prediction matrix-valued factor model is as follows: X^t+1=L^t+1L^t+1'=RF^t+1C'CF^t+1'R' {\hat X_{t + 1}} = {\hat L_{t + 1}}\hat L_{t + 1}^{'} = R{\hat F_{t + 1}}{C^{'}}C\hat F_{t + 1}^{'}{R^{'}} According to the VAR-LASSO model, the realised covariance matrix can be modelled: vec(Xt)=p=1pΦV,tpvec(Xtp)+et vec\left({{X_t}} \right) = \sum\limits_{p = 1}^p {\Phi _{V,t - p}}vec\left({{X_{t - p}}} \right) + {e_t} It is assumed that the decomposition of the predictable matrix-valued factor model and the lag order of VAR-LASSO are 1, and the number of different elements in the covariance matrix is n(n + 1)/2; therefore, ΦV is the representative [n(n+1)2×n(n+1)2] \left[{{{n(n + 1)} \over 2} \times {{n(n + 1)} \over 2}} \right] dimensional coefficient matrix and et is the representative error vector [23]. The VAR model without considering the shrinkage algorithm ΦV. The number of parameters to be estimated is [n(n + 1)/2]2. However, in the matrix-valued factor model, the high-dimensional covariance matrix to be estimated can be described by the low-dimensional factor matrix, and C Matrix, R Matrix, ΦF. The total number of matrix parameters to be estimated is ΦF. Therefore, the matrix-valued coefficient model can effectively reduce the matrix dimension and greatly reduce the number of prediction parameters [24].

Covariance matrix

Lack of interest is one of the main reasons why students’ English performance is not ideal. In order to enable students to learn English well, students should first have a strong interest in this kind of English [25]. In the teaching strategy, we should implement the teaching concept of ‘teachers leading students’ and adopt a variety of practice strategies to stimulate students’ interest in learning [26]. Teachers should give flexible guidance, choose the best teaching methods, encourage students to actively participate in the classroom and improve the teaching effect.

Using the construction method of the realised covariance matrix [27], for the reform of college English education, it is assumed that the number of courses in the whole day is m, students interested in English courses p, English classroom performance i and English classroom performance j between test scores t. The realised covariance of days is given by the following formula: RCOVijt(m)=k=1m(pitkpitk1)(pjtkpjtk1) RCOV_{ijt}^{(m)} = \sum\limits_{k = 1}^m \left({{p_{itk}} - {p_{itk - 1}}} \right)\left({{p_{jtk}} - {p_{jtk - 1}}} \right) After obtaining the realised covariance, you can build n realised covariance matrix of dimension. According to the structure of the existing covariance matrix, the realised variances are sorted in order, and all the realised covariance matrices can be obtained [28]. The expression is as follows: RCOVt=[RCOV11tRCOV1ntRCOVn1tRCOVnnt] RCOV_{t} = \left[{\matrix {{RCOV_{{11t}}} & \cdots & {RCOV_{{1nt}}} \cr \vdots & \ddots & \vdots \cr {RCOV_{{n1t}}} & \cdots & {RCOV_{{nnt}}} \cr}} \right] According to the realised covariance, the structural model that can accurately reflect the essential characteristics of the entity is obtained for the formal description and reasoning of the entity.

Reform path of college English education

The reform of college English education mainly includes three aspects: subject information, curriculum learning management and educational information. The subject information is mainly composed of student information, curriculum information and teacher information [29]. Curriculum learning management is mainly composed of students’ classroom expression, students’ homework expression and students’ expression. Teaching information is mainly composed of teachers’ experience information, teachers’ observation information and teachers’ intuition information. The guiding method of education mode is shown in Figure 1.

Fig. 1

Guiding method of teaching model

Cross-cultural awareness and improvement of teaching quality

The cultivation of English intercultural communicative competence should be emphasised in teachers’ teaching process. Therefore, a high level of cross-cultural English and correct values are necessary for every teacher [30]. On this basis, teachers should constantly strengthen their knowledge of anthropology and geography. It can make teachers more quickly and effectively understand the process of the formation and development of Chinese and American culture and the differences between Chinese and American cultures and expand teachers’ cross-cultural vision [31]. Second, teachers should strengthen the cultivation and establishment of cultural awareness, improve their mastery of professional skills and constantly strengthen and learn cross-cultural education and psychology.

In classroom teaching, teachers should actively guide students’ learning, stimulate students’ diversified appreciation ability, establish correct values for them, make them face the differences and obstacles between Chinese and Western English cultures and help students form an objective and fair cultural awareness system [32]. Teachers should combine language and culture closely with English teaching, guide students to experience the differences between Chinese and Western cultures and ensure the realisation of the purpose of cross-cultural communication.

As one of the subjects of teaching, teachers should constantly enrich their English language knowledge, teaching theory and thought; timely grasp the development trend of educational theory of the times; choose reasonable teaching methods [33]; learn from the successful teaching experience in history, actively adapt to the corresponding teaching reform work; push through the old and adopt a people-oriented way to find teaching methods suitable for students to learn English cross-cultural knowledge, so as to improve the teaching effect.

Guide students to form a cross-cultural learning attitude

In teaching, teachers should correctly treat the cultural differences between China and the United States and guide students to analyse them from an objective and fair perspective [34]. First, colleges and universities should increase the investment in hardware facilities and build a good multimedia equipment environment. In classroom teaching, teachers can use the Internet to ‘learn and check’, use the Internet to search the relevant teaching cultural background in a short time, give students a comprehensive explanation, construct a sound Chinese and American cultural database and update it in time and provide the latest journals, magazines and documents, enabling students to learn the most cutting-edge knowledge of American culture [35]. Second, the teaching curriculum should be rich and diversified. Rich and diverse English courses can make students feel the culture of different levels and backgrounds, and the range of culture students will receive will be broader. Teachers should encourage students to develop the concepts of equality and language equality. In the research, teachers should overcome prejudice and eliminate the restrictions starting from their own values [36]. In education, teachers should provide students with more opportunities for learning strategies and training strategies.

In the development of college English education and teaching, we should pay attention to the infiltration of cross-cultural education, and it is very important to show it in the cultural connotation [37]. Teachers should actively adopt new teaching methods; infiltrate cross-cultural education into the teaching of reading, grammar and oral English; and establish new English learning ideas for students by expanding the scope of English learning. At the same time, teachers can transform the existing teaching mode, make students play a role in English cross-culture and stimulate students’ interest in English learning. In the setting of English teaching content, we need to get rid of the influence of stereotyped thinking. We should introduce the rich content of cross-cultural awareness and look at the problem from a global perspective. The world is an organic whole. American English culture is only a part of it. Teachers should help and guide students to understand the formation of English culture in various countries and the West, establish an open learning attitude for them and encourage students to take English as a tool to understand the world, so as to establish a standard and correct English cross-cultural learning attitude for students.

Construction of identification model

In view of the problems in the process of college English teaching, how to find and eliminate the possible adverse effects as soon as possible is the focus of this article. Using the powerful data analysis and processing ability of discriminant model, we can provide scientific means and basis for the prediction of actual teaching effect.

Set up n represents the covariance matrix dimension so that any U1 and U2 all n × n dimensional invertible matrix, decomposed Lt. The matrix can be represented by the matrix-valued factor model as follows: Lt=RU1U11FtU2U21C'+Et {L_t} = R{U_1}U_1^ {- 1}{F_t}{U_2}U_2^ {- 1}{C^{'}} + {E_t} It is not difficult to see that the of the model may encounter identification problems. Although the C matrix and R matrix are difficult to identify, the R matrix and C column space of the matrix M(R) and M(C) are uniquely certain [38]. Adopt QR decomposition treatment R matrix and C matrix, and the formula is as follows: R=Q1W1 R = {Q_1}{W_1} C=Q2W2 C = {Q_2}{W_2} Qm is a representative pm × km dimensional column orthogonal matrix, Wm is the representative km × km dimensional upper triangular matrix m = 1,2 and Q1 and Q2 are frontal space. M (Q1), M (Q2), M (R) and M (C) are equivalent, and the estimated R matrix and C column space of the matrix are transformed into an estimate Q1 and Q2 column space, and the formula is as follows: Zt=W1FtW2' {Z_t} = {W_1}{F_t}W_2^{'} Then the matrix-valued factor model is transformed into Lt=Q1ZtQ2'+Et {L_t} = {Q_1}{Z_t}Q_2^{'} + {E_t} Take lt,j, Rj, Cj, Qm,j, ɛm, j separately as Lt, R, C, Qm, Et the first j column will Rk' R_k^{'} , Ck' C_k^{'} , Qm,k' Q_{m,k}^{'} , separately as R, C, Qm on line k of, the expression is: lt,j=RFtCj+εt,j=Q1ZtQ2,j+εt,j {l_{t,j}} = R{F_t}{C_j} + {\varepsilon _{t,j}} = {Q_1}{Z_t}{Q_{2,j}} + {\varepsilon _{t,j}} Set h to represent a positive integer step size. For i j = 1,2,3, ⋯,n, it is defined as Ω. Ωzq,ij(h)=1Tht=1Thcov(ZtQ2,i,Zt+hQ2,j) {\Omega _{zq,ij}}(h) = {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} \mathop {\rm cov}\left({{Z_t}{Q_{2,i}},{Z_{t + h}}{Q_{2,j}}} \right) Ωl,ij(h)=1Tht=1Thcov(lt,i,lt+h,j) {\Omega _{l,ij}}(h) = {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} \mathop {\rm cov}\left({{l_{t,i}},{l_{t + h,j}}} \right) Ωl,ij(h)=Q1Ωzq,ij(h)Q1' {\Omega _{l,ij}}(h) = {Q_1}{\Omega _{zq,ij}}(h)Q_1^{'} Set h = h0, defined as: M=h=1h0i=1nj=1nΩl,ij(h)Ωl,ij'(h) M = \sum\limits_{h = 1}^{{h_0}} \sum\limits_{i = 1}^n \sum\limits_{j = 1}^n {\Omega _{l,ij}}(h)\Omega _{l,ij}^{'}(h) M=Q1(h=1h0i=1nj=1nΩzq,ij(h)Ωzq,ij'(h))Q1' M = {Q_1}\left({\sum\limits_{h = 1}^{{h_0}} \sum\limits_{i = 1}^n \sum\limits_{j = 1}^n {\Omega _{zq,ij}}(h)\Omega _{zq,ij}^{'}(h)} \right)Q_1^{'} It can be seen that each column M in Q1 is a linear combination of the whole column. Therefore, M(M) = M(Q1) is estimated according to the eigenvector of the observed value of rotating M samples. The expression of M(Q1) is as follows: Ω^l,ij(h)=1Tht=1Thlt,ilt+h,j' {\hat \Omega _{l,ij}}(h) = {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} {l_{t,i}}l_{t + h,j}^{'} M^=h=1h0i=1nj=1nΩ^l,ij(h)Ω^l,ij'(h) \hat M = \sum\limits_{h = 1}^{{h_0}} \sum\limits_{i = 1}^n \sum\limits_{j = 1}^n {\hat \Omega _{l,ij}}(h)\hat \Omega _{l,ij}^{'}(h) Implement cultural difference feature decomposition for M^ \hat M and take the former k1 eigenvectors corresponding to the maximum eigenvalues q^1,,q^k1 {\hat q_1}, \cdots,{\hat q_{{k_1}}} get Q^1={q^1,,q^k1} {\hat Q_1} = \left\{{{{\hat q}_1}, \cdots , {{\hat q}_{{k_1}}}} \right\} hold Lt transpose processing and get Q^2 {\hat Q_2} .

According to k1, the determination method recorded λ^1λ^2λ^n {\hat \lambda _1}{\hat \lambda _2} \cdots {\hat \lambda _n} is M^ \hat M . Then the formula is as follows: k1=argmin1in/2λ^i+1λ^i {k_1} = \arg \mathop {\min}\limits_{1in/2} {{{{\hat \lambda}_{i + 1}}} \over {{{\hat \lambda}_i}}} Z^t=Q^1'LtQ^2 {\hat Z_t} = \hat Q_1^{'}{L_t}{\hat Q_2}

The vectorisation operation of Z^t {\hat Z_t} is implemented, and the VAR identification model is constructed to obtain Z^t {\hat Z_t} . L^t+1=Q^1Z^t+1Q^2' {\hat L_{t + 1}} = {\hat Q_1}{\hat Z_{t + 1}}\hat Q_2^{'} where L^t+1 {\hat L_{t + 1}} represents the decomposed triangular matrix. The non-zero elements of the upper triangle are errors, so L^t+1 {\hat L_{t + 1}} elements in the l^t+1,ij {\hat l_{t + 1,ij}} threshold function can be obtained L^t+1*={l^t+1,ij*}n×n \hat L_{t + 1}^* = {\left\{{\hat l_{t + 1,ij}^*} \right\}_{n \times n}} : l^t+1,ij*={l^t+1,ijij0i<j \hat l_{t + 1,ij}^* = \left\{{\matrix {{{{\hat l}_{t + 1,ij}}} & {ij} \cr 0 & {i < j} \cr}} \right. To sum up, the predicted realised covariance matrix is as follows: X^t+1=L^t+1*L^t+1* {\hat X_{t + 1}} = \hat L_{t + 1}^*\hat L_{t + 1}^* The following formula is obtained through processing: Ω^s,ij(h)=1Tht=1ThRFtCiCj'Ft+h'R' {\hat \Omega _{s,ij}}(h) = {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} R{F_t}{C_i}C_j^{'}F_{t + h}^{'}{R^{'}} Ω^sε,ij(h)=1Tht=1ThRFtCiεt+h,j' {\hat \Omega _{s\varepsilon,ij}}(h) = {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} R{F_t}{C_i}\varepsilon _{t + h,j}^{'} Ω^εs,ij(h)=1Tht=1Thεt,iCj'Ft+h'R' {\hat \Omega _{\varepsilon s,ij}}(h) = {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} {\varepsilon _{t,i}}C_j^{'}F_{t + h}^{'}{R^{'}} Ω^ε,ij(h)=1Tht=1Thεt,iεt+h,j' {\hat \Omega _{\varepsilon,ij}}(h) = {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} {\varepsilon _{t,i}}\varepsilon _{t + h,j}^{'} Available: Ω^l,ij(h)=1Tht=1Thlt,ilt+h,j'=1Tht=1Th(RFtCj+εt,j)(RFt+hCj+εt+h,j)=Ω^s,ij(h)+Ω^sε,ij(h)+Ω^εs,ij(h)+Ω^ε,ij(h) \matrix {{{{\hat \Omega}_{l,ij}}(h)} \hfill & {= {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} {l_{t,i}}l_{t + h,j}^{'}} \hfill \cr {} \hfill & {= {1 \over {T - h}}\sum\limits_{t = 1}^{T - h} \left({R{F_t}{C_j} + {\varepsilon _{t,j}}} \right)\left({R{F_{t + h}}{C_j} + {\varepsilon _{t + h,j}}} \right)} \hfill \cr {} \hfill & {= {{\hat \Omega}_{s,ij}}(h) + {{\hat \Omega}_{s\varepsilon,ij}}(h) + {{\hat \Omega}_{\varepsilon s,ij}}(h) + {{\hat \Omega}_{\varepsilon,ij}}(h)} \hfill \cr} About the n decomposition matrix of dimensional realised covariance matrix L. Using the Davydov inequality, the sample covariance space Ω^l,ij(h) {\hat \Omega _{l,ij}}(h) . The convergence rate of estimation error is as follows: i=1nj=1nΩ^l,ij(h)Ωl,ij(h)224i=1nj=1n(Ω^s,ij(h)Ωs,ij(h)22+Ω^sε,ij(h)22+Ω^εs,ij(h)22+Ω^ε,ij(h)22)=Op(n4T1) \matrix {{\sum\limits_{i = 1}^n \sum\limits_{j = 1}^n \parallel {{\hat \Omega}_{l,ij}}(h) - {\Omega _{l,ij}}(h)\parallel _2^24\sum\limits_{i = 1}^n \sum\limits_{j = 1}^n \left({\parallel {{\hat \Omega}_{s,ij}}(h) - {\Omega _{s,ij}}(h)\parallel _2^2 + \parallel {{\hat \Omega}_{s\varepsilon,ij}}(h)\parallel _2^2} \right.} \hfill \cr {\left. {+ \parallel {{\hat \Omega}_{\varepsilon s,ij}}(h)\parallel _2^2 + \parallel {{\hat \Omega}_{\varepsilon,ij}}(h)\parallel _2^2} \right) = {O_p}\left({{n^4}{T^ {- 1}}} \right)} \hfill \cr}

Experimental analysis

In the research process, a total of 26 items were prepared by the questionnaire survey, including three fields: structured data of research subject information, semi-structured data of research process learning management and unstructured data of educational information research [39]. A questionnaire survey was conducted on 400 students in a university in a city. Through the questionnaire survey, the current situation, achievements and existing problems of students’ learning process were objectively reflected. According to the model designed in this study, suggestions on the mode of higher education were put forward.

The parameters under investigation adopt the Richter scale of 5 (1 = very poor, 2 = difference, 3 = normal, 4 = good, 5 = very good) [40] because the variable is level 2. Relevant research shows that the teaching mode of colleges and universities involves 27 variables, and the description of some variables is shown in Table 1. Among them, the variable allocation shows the level 5 index without ‘*’ subjective quantitative standard in the highest, maximum and best decline files.

Description of some research variables

Research content Variable type Variable name Variable assignment

Predict behaviour Dependent variable Learning behaviour Bad = 0, good = 1
Subject information Student information Score <5 points
Average study time <1 h
Optimistic state <2 articles
Believability <2 articles
Course information Degree of interest <2 articles
Time investment <3 days
Acceptance <3 days
Amount of knowledge <3 days
Faculty information Teacher rank 5, 4, 3, 2, 1
Students’ love 5, 4, 3, 2, 1
Communicate with students 5, 4, 3, 2, 1
Teacher status 5, 4, 3, 2, 1

There are 26 difference features set in the questionnaire. According to the basic norms of row and column sampling, the number of features m selected in the difference feature column is about sqrt (m), M is the total number of features and sqrt (m) is the root mean square function. This experiment M = 5 is suitable. Figure 2 shows the test results of classifying factors and classification errors under different m values.

Fig. 2

Classification error relationship under different m values

According to the M obtained from the aforementioned experiment, the top five variables are taken to predict the learning behaviour of high-school education model.

The analysis in Figure 2 shows that if M = 5 and the factor is 40, the effect is very good. This parameter is used in subsequent experiments; 361 valid sample data collected were tested.

In order to verify the accuracy of this prediction model, this study predicts the development trend of college English teaching reform with the methods of literature 3, literature 4 and literature 5. Two groups of validation were conducted for 361 questionnaire data, including 230 training sets and 122 test sets. The measured results are shown in Table 2.

Prediction results of the development trend of college English education reform

Method Training set (%) Test set (%) Comprehensive (%)

Paper method 99.44 99.25 99.20
Literature 3 methods 86.25 77.33 79.40
Literature 4 methods 81.10 70.65 82.54
Literature 5 methods 89.90 88.44 81.15

The results show that the accuracy of the reform method proposed in this article is as high as 99.20%. It has good adaptability, discrimination and generalisation ability for college English teaching path, which is obviously better than those of the other three methods. Then it analyses the English performance after the reform, as shown in Figure 3.

Fig. 3

Comparison of results after proofreading in English class

It can be seen from Figure 3 that after the reform, students’ English scores are on the rise, and the number of students whose test scores reach the pass rate is high. Therefore, the teaching model of college English reform inspired by the cultural differences between China and the United States is feasible.

Conclusion

From the perspective of cultural differences between China and the United States, this study focusses on the reform of college English education. Through 361 survey data, five different features can be extracted, with an accuracy of 99.20%, which verifies the feasibility and effectiveness of this scheme. In the process of English teaching in colleges and universities, we should pay attention to the strengthening of the cross-cultural education theory, actively establish correct values for students to understand the differences between Chinese and Western cultures, give full play to the important role of cross-cultural education in college English teaching and lay the foundation for building comprehensive quality English talents.

Fig. 1

Guiding method of teaching model
Guiding method of teaching model

Fig. 2

Classification error relationship under different m values
Classification error relationship under different m values

Fig. 3

Comparison of results after proofreading in English class
Comparison of results after proofreading in English class

Prediction results of the development trend of college English education reform

Method Training set (%) Test set (%) Comprehensive (%)

Paper method 99.44 99.25 99.20
Literature 3 methods 86.25 77.33 79.40
Literature 4 methods 81.10 70.65 82.54
Literature 5 methods 89.90 88.44 81.15

Description of some research variables

Research content Variable type Variable name Variable assignment

Predict behaviour Dependent variable Learning behaviour Bad = 0, good = 1
Subject information Student information Score <5 points
Average study time <1 h
Optimistic state <2 articles
Believability <2 articles
Course information Degree of interest <2 articles
Time investment <3 days
Acceptance <3 days
Amount of knowledge <3 days
Faculty information Teacher rank 5, 4, 3, 2, 1
Students’ love 5, 4, 3, 2, 1
Communicate with students 5, 4, 3, 2, 1
Teacher status 5, 4, 3, 2, 1

Bing, Wang. “The College English Teaching Reform Based on MOOC.” English Language Teaching. (2017). BingWang “The College English Teaching Reform Based on MOOC.” English Language Teaching 2017 10.5539/elt.v10n2p19 Search in Google Scholar

Yu, Shuti; Guo, Jianli. “Real-time Online Education of College English Based on Cloud Computing.” IOP Conference Series: Materials Science and Engineering. (2020). YuShuti GuoJianli “Real-time Online Education of College English Based on Cloud Computing.” IOP Conference Series: Materials Science and Engineering 2020 10.1088/1757-899X/750/1/012217 Search in Google Scholar

He Mengying. “A study on the current situation of” Chinese Cultural Aphasia “in College English education in China.” Campus English (2017):20. MengyingHe “A study on the current situation of” Chinese Cultural Aphasia “in College English education in China.” Campus English 2017 20 Search in Google Scholar

Duan Wei “A study on eliminating cultural differences between China and the West in English teaching.” Campus English (2020):4–5. WeiDuan “A study on eliminating cultural differences between China and the West in English teaching.” Campus English 2020 4 5 Search in Google Scholar

Niu Xuejian “Research on business English teaching reform in Colleges and universities from the perspective of micro class.” Campus English (2019):27–27. XuejianNiu “Research on business English teaching reform in Colleges and universities from the perspective of micro class.” Campus English 2019 27 27 Search in Google Scholar

Ye Mingchun “Research on efficient English classroom teaching in Senior High School under the new curriculum reform.” Campus English (2017):89. MingchunYe “Research on efficient English classroom teaching in Senior High School under the new curriculum reform.” Campus English 2017 89 Search in Google Scholar

Zhang Lichao, Wang Lihong “Research on the reform of College English Listening Teaching Model in a multimodal environment.” Campus English (2019):56–56. LichaoZhang LihongWang “Research on the reform of College English Listening Teaching Model in a multimodal environment.” Campus English 2019 56 56 Search in Google Scholar

Cen Haixia “Research on the reform of English Writing Teaching in senior high school in the context of big data.” Campus English (2017):120. HaixiaCen “Research on the reform of English Writing Teaching in senior high school in the context of big data.” Campus English 2017 120 Search in Google Scholar

Kasey Buckles, Andreas Hagemann, Ofer Malamud, Melinda Morrill, Abigail Wozniak. “The effect of college education on mortality.” Journal of Health Economics. (2016):99–99. BucklesKasey HagemannAndreas MalamudOfer MorrillMelinda WozniakAbigail “The effect of college education on mortality.” Journal of Health Economics 2016 99 99 10.1016/j.jhealeco.2016.08.00227723470 Search in Google Scholar

Suo, Jia; Hou, Xiuying. “A Study on the Motivational Strategies in College English Flipped Classroom.” English Language Teaching. (2017). SuoJia HouXiuying “A Study on the Motivational Strategies in College English Flipped Classroom.” English Language Teaching 2017 10.5539/elt.v10n5p62 Search in Google Scholar

Li, Jing. “Environmental education in China's College English context: A pilot study.” International Research in Geographical and Environmental Education. (2013):139–154. LiJing “Environmental education in China's College English context: A pilot study.” International Research in Geographical and Environmental Education 2013 139 154 10.1080/10382046.2013.779124 Search in Google Scholar

Wang, Bin. “Empirical Study on the Computer-aided College English Translation Teaching.” International Journal of Emerging Technologies in Learning (iJET). (2016) WangBin “Empirical Study on the Computer-aided College English Translation Teaching.” International Journal of Emerging Technologies in Learning (iJET) 2016 10.3991/ijet.v11i12.6012 Search in Google Scholar

Sun Mao-hua, Li Yuan-gang, He Bing. “Study on a Quality Evaluation Method for College English Classroom Teaching.” Future Internet. (2017):41 Mao-huaSun Yuan-gangLi BingHe “Study on a Quality Evaluation Method for College English Classroom Teaching.” Future Internet 2017 41 10.3390/fi9030041 Search in Google Scholar

Yi, Le-Xiang. “A Tentative Exploration on the Use of Multi-media in College English Education.” AASRI Procedia. (2012):282–286. YiLe-Xiang “A Tentative Exploration on the Use of Multi-media in College English Education.” AASRI Procedia 2012 282 286 10.1016/j.aasri.2012.06.043 Search in Google Scholar

Yi, Le-Xiang. “A Tentative Exploration on the Use of Multi-media in College English Education.” AASRI Procedia. (2012). YiLe-Xiang “A Tentative Exploration on the Use of Multi-media in College English Education.” AASRI Procedia 2012 10.1016/j.aasri.2012.06.043 Search in Google Scholar

Zhai, Qiang. “The New Era College Education Reform and Development Trend of Exploration.” Advanced Materials Research. (2014). ZhaiQiang “The New Era College Education Reform and Development Trend of Exploration.” Advanced Materials Research 2014 10.4028/www.scientific.net/AMR.1044-1045.1680 Search in Google Scholar

Liu Xin-hong. “The Construction of College English Teaching Model Based on Blended Learning.” PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL I. (2009):773 – 777. Xin-hongLiu “The Construction of College English Teaching Model Based on Blended Learning.” PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL I 2009 773 777 10.1109/ETCS.2009.177 Search in Google Scholar

Wang Qiao, Jiang Xiao-qin. “Empirical study on reform model of college English teaching model based on computer and big data.” 2018 10TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA). (2018):412 – 415. QiaoWang Xiao-qinJiang “Empirical study on reform model of college English teaching model based on computer and big data.” 2018 10TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA) 2018 412 415 10.1109/ICMTMA.2018.00107 Search in Google Scholar

Zhou, Yaping. “Reflection on the Computer and Network-based College English Teaching Model From the Perspective of Learning Styles.” World Journal of English Language. (2011). ZhouYaping “Reflection on the Computer and Network-based College English Teaching Model From the Perspective of Learning Styles.” World Journal of English Language 2011 10.5430/wjel.v1n2p30 Search in Google Scholar

Zhang Y, Qian T, Tang W. Buildings-to-distribution-network integration considering power transformer loading capability and distribution network reconfiguration[J]. Energy, 2022, 244. ZhangY QianT TangW Buildings-to-distribution-network integration considering power transformer loading capability and distribution network reconfiguration[J] Energy 2022 244 10.1016/j.energy.2022.123104 Search in Google Scholar

T. Qian, Xingyu Chen, Yanli Xin, W. H. Tang*, Lixiao Wang. Resilient Decentralized Optimization of Chance Constrained Electricity-gas Systems over Lossy Communication Networks [J]. Energy, 2022, 239, 122158. QianT. ChenXingyu XinYanli Tang*W. H. WangLixiao Resilient Decentralized Optimization of Chance Constrained Electricity-gas Systems over Lossy Communication Networks [J] Energy 2022 239 122158 10.1016/j.energy.2021.122158 Search in Google Scholar

Baining Zhao, Tong Qian*, Wenhu Tang, Qiheng, Liang. A Data-enhanced Distributionally Robust Optimization Method for Economic Dispatch of Integrated Electricity and Natural Gas Systems with Wind Uncertainty[J] Energy, 2022, Energy, 2022: 123113. ZhaoBaining Qian*Tong TangWenhu QihengLiang A Data-enhanced Distributionally Robust Optimization Method for Economic Dispatch of Integrated Electricity and Natural Gas Systems with Wind Uncertainty[J] Energy 2022 Energy, 2022: 123113 10.1016/j.energy.2022.123113 Search in Google Scholar

T. Qian, Y. Liu, W. H Zhang, W. H. Tang*, M. Shahidehpour. Event-Triggered Updating Method in Centralized and Distributed Secondary Controls for Islanded Microgrid Restoration[J]. IEEE Transactions on Smart Gird, 2020, 11(2): 1387–1395. QianT. LiuY. ZhangW. H Tang*W. H. ShahidehpourM. Event-Triggered Updating Method in Centralized and Distributed Secondary Controls for Islanded Microgrid Restoration[J] IEEE Transactions on Smart Gird 2020 11 2 1387 1395 10.1109/TSG.2019.2937366 Search in Google Scholar

Zhang, Dan, Wang, Xiaoying. “The Effects of the CALL Model on College English Reading Teaching.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING. (2017):24 – 34. ZhangDan WangXiaoying “The Effects of the CALL Model on College English Reading Teaching.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2017 24 34 10.3991/ijet.v12i12.7954 Search in Google Scholar

Wen, Jianlan, Wu, Wei. “Multi-Interactive Teaching Model of College English in Computer Information Technology Environment.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING. (2017):79 – 90. WenJianlan WuWei “Multi-Interactive Teaching Model of College English in Computer Information Technology Environment.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2017 79 90 10.3991/ijet.v12i12.7956 Search in Google Scholar

Wang, Baojian, Wang, Jing, Hu, Guoqiang. “College English Classroom Teaching Evaluation Based on Particle Swarm Optimization – Extreme Learning Machine Model.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING. (2017):82 – 97. WangBaojian WangJing HuGuoqiang “College English Classroom Teaching Evaluation Based on Particle Swarm Optimization – Extreme Learning Machine Model.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2017 82 97 10.3991/ijet.v12i05.6782 Search in Google Scholar

Xu, Meng; Lv, Kang; Bi, Xinwen. “Computer Network Assisted Teaching of College English Reading.” International Journal of Emerging Technologies in Learning (iJET). (2016). XuMeng LvKang BiXinwen “Computer Network Assisted Teaching of College English Reading.” International Journal of Emerging Technologies in Learning (iJET) 2016 10.3991/ijet.v11i08.6048 Search in Google Scholar

Li Zhiyu, Hu Muhui, Zou Hongying. “Internet-Assisted College English Teaching in China.” IERI Procedia. (2012):623–629. ZhiyuLi MuhuiHu HongyingZou “Internet-Assisted College English Teaching in China.” IERI Procedia 2012 623 629 10.1016/j.ieri.2012.06.144 Search in Google Scholar

Zhiyu, Li, Muhui, Hu, Hongying, Zou. “Internet-Assisted College English Teaching in China.” IERI Procedia. (2012):623–629. ZhiyuLi MuhuiHu HongyingZou “Internet-Assisted College English Teaching in China.” IERI Procedia 2012 623 629 10.1016/j.ieri.2012.06.144 Search in Google Scholar

Ma, Bing-jun. “Application of Visual Simulation Technology in College English Teaching.” International Journal of Emerging Technologies in Learning (iJET). (2016). MaBing-jun “Application of Visual Simulation Technology in College English Teaching.” International Journal of Emerging Technologies in Learning (iJET) 2016 10.3991/ijet.v11i11.6243 Search in Google Scholar

Zhang, Xin, Bi, Jingxuan. “Design of a College English Mobile Learning System Based on CAD Model.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING. (2018):139 – 149. ZhangXin BiJingxuan “Design of a College English Mobile Learning System Based on CAD Model.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2018 139 149 10.3991/ijet.v13i04.8477 Search in Google Scholar

Levin, Orna, Avidov-Ungar, Orit. “Students’ views on the use of ClassBoost in a teachers’ education college.” JOURNAL OF COMPUTER ASSISTED LEARNING. (2018):816 – 827. LevinOrna Avidov-UngarOrit “Students’ views on the use of ClassBoost in a teachers’ education college.” JOURNAL OF COMPUTER ASSISTED LEARNING 2018 816 827 10.1111/jcal.12290 Search in Google Scholar

Zhang, Dan, Wang, Xiaoying. “The Effects of the CALL Model on College English Reading Teaching.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING. (2017):24 – 34. ZhangDan WangXiaoying “The Effects of the CALL Model on College English Reading Teaching.” INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2017 24 34 10.3991/ijet.v12i12.7954 Search in Google Scholar

Ma Hongwei. “The Study on College Physical Education based on Quantity Model.” Energy Procedia. (2012):1345–1350. HongweiMa “The Study on College Physical Education based on Quantity Model.” Energy Procedia 2012 1345 1350 10.1016/j.egypro.2012.02.250 Search in Google Scholar

Gardiner, Christie. “College cops: a study of education and policing in California.” Policing: An International Journal of Police Strategies & Management. (2015):648–663. GardinerChristie “College cops: a study of education and policing in California.” Policing: An International Journal of Police Strategies & Management 2015 648 663 10.1108/PIJPSM-02-2015-0015 Search in Google Scholar

Mironov, V. V. “On the Reform of Russian Education.” RUSSIAN EDUCATION AND SOCIETY. (2013):3 – 63. MironovV. V “On the Reform of Russian Education.” RUSSIAN EDUCATION AND SOCIETY 2013 3 63 10.2753/RES1060-9393551201 Search in Google Scholar

Shuo Guan. “Network Education and New Ideas for the Reform of College Physical Education.” Procedia Engineering. (2012):3562–3566. GuanShuo “Network Education and New Ideas for the Reform of College Physical Education.” Procedia Engineering 2012 3562 3566 10.1016/j.proeng.2012.01.531 Search in Google Scholar

Kozlova, Olga, Astafurova, Tatyana, Vishnevetskaya, Natalya, Cindori, S., Larouk, O., Malushko, E. Yu., Rebrina, L.N., Shamne, N.L. “Model of Teaching English at Architectural University.” SHS Web of Conferences. (2018). KozlovaOlga AstafurovaTatyana VishnevetskayaNatalya CindoriS. LaroukO. MalushkoE. Yu. RebrinaL.N. ShamneN.L. “Model of Teaching English at Architectural University.” SHS Web of Conferences 2018 10.1051/shsconf/20185001089 Search in Google Scholar

Hu, Yu. “Study on Multimedia Education System of Technological College.” Advanced Materials Research. (2013). HuYu “Study on Multimedia Education System of Technological College.” Advanced Materials Research 2013 10.4028/www.scientific.net/AMR.694-697.3700 Search in Google Scholar

Liu, Yan Hong, Liu, Ze Quan. “A Corpus-Based Study of College English Coursebooks.” Advanced Materials Research. (2011):1990–1993. LiuYan Hong LiuZe Quan “A Corpus-Based Study of College English Coursebooks.” Advanced Materials Research 2011 1990 1993 10.1007/978-3-642-21411-0_67 Search in Google Scholar

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