# Research on Multimedia Technology-Assisted College English Grammar Teaching

Authors: Huarui Xu; Yun Yao
Journal: Wireless Communications and Mobile Computing
 (2022)

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## Abstract

The English Curriculum Standard for Compulsory Education lists the specific requirements for the integration of English discipline and information technology to optimize the presentation of education. For college students’ English teaching, the most appropriate and effective way is to widely apply multimedia courses to English teaching. Using the rich multimedia knowledge of multimedia courses to expand students’ oral English and teaching skills, widen the reading path of reading and writing, multimedia tutoring teaching can concretize and visualize abstract knowledge well, and rich multimedia knowledge can facilitate students’ learning and play an important role in understanding knowledge. This paper focuses on multimedia technology-assisted college English grammar teaching. The multimedia technology is analyzed by using the multimedia data hashing algorithm with semantic fusion. Then, the application of multimedia teaching materials in teaching and traditional teaching methods is experimented. By comparing their learning effects, the author draws a conclusion that multimedia technology has been applied in English grammar teaching to a certain extent, and the present situation of its application is relatively good. Most of them have an encouraging attitude, especially in improving students’ learning attitude and increasing their interest in learning. Due to the limitations of awareness and conditions, the extent and progress of the integration of information technology and disciplines have lagged behind relatively, and there are many difficulties in the application of multimedia course materials; there are certain difficulties in integrating multimedia course materials and English subjects.


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## Body

## 1. Introduction

The purpose of this paper is to explore the practical application of multimedia technology in teaching, explore the application rules and characteristics of multimedia technology, give full play to the advantages of multimedia, make multimedia better serve classroom teaching, and improve teaching effect [1]. The purpose of this study is to evaluate the usability of multimedia software applications. The results show that the software applications have high global usability, and this kind of software can improve the quality of life of family caregivers and their coping ability [2]. This paper is a summary of the research and application of multimedia in China in 1998. Understanding its development will facilitate researchers to consult reference materials and help editors to compile journals and authors to write papers [3]. This paper is one of a series of reports on multimedia research and application in China in 2003. The research results show that multimedia technology and digital earth are the development trends in the world for a long time [4]. This paper describes a suite of multimedia tools for filmless radiology to create multimedia radiology reports with text, images, and sound annotations. The collection of client and server controls the acquisition and processing of multimedia information [5]. The purpose of this paper is to discuss the characteristics of multimedia technology and foreign language teaching and the application of multimedia technology in language teaching and try to find out the related technical problems [6]. This paper studies the cultivation of college students’ autonomous learning ability, and the results show that strategy training plays an important role in enriching students’ metacognitive knowledge and promoting the establishment of learners’ autonomous learning ability. The development of metacognitive achievement and academic achievement also has high synergistic efficiency [7]. This paper focuses on and attempts to demonstrate that English should be taught as a foreign language in China after 50 years of university education reform. Therefore, reading and writing should be the most important [8]. On the basis of analyzing the present situation of college English teaching in China, this paper points out that college English teaching in China is entering a critical stage of historical transformation, which requires studying individualized teaching and learning requirements and reflecting on the Chinese college English teaching system [9]. This paper discusses the role of language input in college English teaching through theoretical research and empirical research and points out that with the application of modern teaching theories and teaching methods, traditional language teaching methods should not be completely abandoned [10]. The concept of autonomous learning belongs to the category of educational philosophy. This paper discusses the possibility of autonomous learning in Chinese college students’ English learning from two aspects: principle and action. Teachers and educational authorities should also be responsible for the development of autonomous learning, just as learners should learn to be responsible for their own learning [11]. This paper further analyzes the background and definition of Ele and holds that the development direction of CET is academic English, not ELEE, and the course is an elective course in college English teaching, which should not be regarded as the mainstream or even the direction of college English teaching [12]. Grammar teaching traditionally provides learners with the opportunity to produce specific grammatical structures. This paper discusses another grammar teaching method: the method based on explanatory input, and discusses the basic principle of this method and the principle of designing explanatory tasks in grammar teaching [13]. This paper reviews the research on how to best teach grammar from four theoretical motivation teaching options. In view of the difficulty in drawing clear conclusions based on this research, based on the difference between teachers’ practical knowledge and technical knowledge, some possibilities for teachers to use the information provided by them in teaching are considered [14]. This paper outlines a TD strategy, through which teachers check their theories in grammar teaching and the materials to assist teachers in implementing this strategy. The role of formal teaching itself has always been the focus of debate, and more than 20 years’ research has failed to give clear grammar guidelines [15].


## 2. Definition of Multimedia-Related Concepts

### 2.1. Multimedia Technology

Multimedia technology is a kind of computer technology that can collect, store, process, or integrate multimedia information such as text, graphics, images, sounds, animations, and videos. It can use computer to process external media data and print it out in the combination of images, texts, sounds, animations, videos, etc., so as to realize multipurpose dynamic performance effects. Multimedia technology has the characteristics of integration, interactivity, real-time, and convenient data use.


### 2.2. Multimedia-Assisted Instruction

Multimedia-assisted instruction means that in the learning process, according to the characteristics of learning objectives, teaching contents, and learning objects, we choose and use multimedia wisely, combine with traditional teaching methods organically, participate in the whole teaching process and deal with it together, and then use multimedia information to influence students. A reasonable structure of educational process, in order to achieve the best learning effect, can provide a better role for multimedia technology in teaching and at the same time ensure that students get more abundant physical knowledge and broaden their horizons.


### 2.3. English Classroom Teaching

Teaching is a process of knowledge, knowledge transfer, and specific cognitive activities, which is the whole process of teachers imparting knowledge and skills to students. English classroom teaching means that with the help of classroom teaching, students systematically master the basic vocabulary and language needed by English graduate students and understand the practical application of these English knowledge and strive to cultivate students’ oral expression ability and language learning ability, as well as the ability to solve problems through communication in daily life by using English communication.


### 2.4. Multimedia-Assisted English Classroom Teaching

With the wide application of multimedia technology, information technology characterized by multimedia and intelligence has exerted great influence on traditional curriculum concept, curriculum content, and curriculum implementation. As a teaching method, multimedia technology is integrated into English classroom teaching and becomes an integral part of the curriculum, which makes English teaching resources integrate into the classroom and integrate with each other, optimizes English classroom teaching, and enhances the influence of English language teaching.


### 2.5. The Role of Multimedia Technology in Assisting English Teaching

Compared with the traditional English classroom, English teaching in the application of multimedia technology is livelier and interesting, which can change the stereotype of monotonous and boring in the traditional language learning classroom. Multimedia can realize both pictures and texts, audio and video; through video and pictures, students’ interest and thirst for knowledge are stimulated. Multimedia can also simulate virtual reality and create classroom teaching situations, which brings many advantages to English classroom teaching. It has a special application to English classroom teaching. Multimedia technology has excellent processing ability to sounds and images. With this unique characteristic, it can be from abstract to concrete, from static to dynamic microprocess macrosimulation, to microprocessing macroscene, as well as boring life changes. Thus, the problem that knowledge is too abstract in traditional education is solved, and the abstract knowledge content is transformed into vivid and realistic concrete forms of virtual scenes, which are presented to students so that students can understand and relax more easily.


## 2.1. Multimedia Technology

Multimedia technology is a kind of computer technology that can collect, store, process, or integrate multimedia information such as text, graphics, images, sounds, animations, and videos. It can use computer to process external media data and print it out in the combination of images, texts, sounds, animations, videos, etc., so as to realize multipurpose dynamic performance effects. Multimedia technology has the characteristics of integration, interactivity, real-time, and convenient data use.


## 2.2. Multimedia-Assisted Instruction

Multimedia-assisted instruction means that in the learning process, according to the characteristics of learning objectives, teaching contents, and learning objects, we choose and use multimedia wisely, combine with traditional teaching methods organically, participate in the whole teaching process and deal with it together, and then use multimedia information to influence students. A reasonable structure of educational process, in order to achieve the best learning effect, can provide a better role for multimedia technology in teaching and at the same time ensure that students get more abundant physical knowledge and broaden their horizons.


## 2.3. English Classroom Teaching

Teaching is a process of knowledge, knowledge transfer, and specific cognitive activities, which is the whole process of teachers imparting knowledge and skills to students. English classroom teaching means that with the help of classroom teaching, students systematically master the basic vocabulary and language needed by English graduate students and understand the practical application of these English knowledge and strive to cultivate students’ oral expression ability and language learning ability, as well as the ability to solve problems through communication in daily life by using English communication.


## 2.4. Multimedia-Assisted English Classroom Teaching

With the wide application of multimedia technology, information technology characterized by multimedia and intelligence has exerted great influence on traditional curriculum concept, curriculum content, and curriculum implementation. As a teaching method, multimedia technology is integrated into English classroom teaching and becomes an integral part of the curriculum, which makes English teaching resources integrate into the classroom and integrate with each other, optimizes English classroom teaching, and enhances the influence of English language teaching.


## 2.5. The Role of Multimedia Technology in Assisting English Teaching

Compared with the traditional English classroom, English teaching in the application of multimedia technology is livelier and interesting, which can change the stereotype of monotonous and boring in the traditional language learning classroom. Multimedia can realize both pictures and texts, audio and video; through video and pictures, students’ interest and thirst for knowledge are stimulated. Multimedia can also simulate virtual reality and create classroom teaching situations, which brings many advantages to English classroom teaching. It has a special application to English classroom teaching. Multimedia technology has excellent processing ability to sounds and images. With this unique characteristic, it can be from abstract to concrete, from static to dynamic microprocess macrosimulation, to microprocessing macroscene, as well as boring life changes. Thus, the problem that knowledge is too abstract in traditional education is solved, and the abstract knowledge content is transformed into vivid and realistic concrete forms of virtual scenes, which are presented to students so that students can understand and relax more easily.


## 3. Multimedia Data Hashing Algorithm Based on Semantic Integration

### 3.1. Hash Algorithm for Cross-Modal Retrieval

It is assumed that the multimedia data training seto=oii=1n contains n groups of multimedia data training samples. For the sake of simplicity, this paper defaults to considering two modal data of image [16] and text for each set of multimedia data, and the method proposed in this paper can be extended to multimedia data containing more modal features in theory. For each multimedia data sample oi=xi1,xi2,yi, xi1∈Rd1 is the i-th image feature vector, xi2∈Rd2 is the i-th text feature vector, d1,d2 is the dimension of image and text features, respectively, yi=0,1c is the corresponding category label, and c is the total number of semantic categories. Image mode and text mode attribute matrix are X1=xi1i=1n∈Rd1×n and X2=xi2i=1n∈Rd2×n, and the category label matrix is Y=yii=1n∈Rc×n. The purpose of discrete latent semantic cross-modal hashing algorithm [17] is to learn two modal-specific hash functions for image modality and text modality, project heterogeneous data features into a common Hamming space, and generate hash code B=b1,b2,⋯,bn∈−1,1r×n for skip level search. The formula representation of the two algorithms fX1:Rd1⟶0,1r and fX2:Rd2⟶0,1r, where r is the length of the hash code [18].


### 3.2. Representation Learning of Subsurface Space

Assuming two matricesX1 and X2, the p vector can be obtained such as formula (1) is obtained by Gaussian kernel function [19]. Gauss kernel function, also known as radial basis function, is a commonly used kernel function. It can map finite dimensional data to high-dimensional space, and the Gauss kernel function is a monotonic function of the Euclidean distance of two vectors.
(1)φxi=expxi−a12ε,⋯,expxi−ap2ε.whereaij=1p is P anchor points randomly selected from the training set and ε is Gaussian kernel parameter. Learn latent semantic representations of image modalities and text modalities separately using common matrix factors, it can be reduced to
(2)minU1φx1−A1F2+φx2−U2A2F2.φX1∈Rp×n and φX2∈Rp×n are Gaussian kernel projections of image and text feature matrices, respectively, A1∈Rk×n and A2∈Rk×n are latent semantic representations of image and text modes, respectively, U1∈Rp×k and U2∈Rp×k are basis matrices of image and text modes, respectively, and K is the dimension of latent semantic representation.


### 3.3. Discriminative Hash Learning

The DLSCMH algorithm learns two pattern-specific hash functions [20], maps the latent semantic representations of two heterogeneous patterns to a common Hamming space, and generates a binary hash code for that state. The image and text modality attributes corresponding to each multimedia data sample oi describe the same semantic class and theoretically have the same binary hash code B. DLSCMH algorithm uses a unified binary hash code matrix bi to construct the correlation between heterogeneous modes, which effectively reduces the semantic gap between heterogeneous modes. The hash functions of the two modes are expressed as
(3)f1A1:Rd1⟶−1,1r,f1A2:Rd2⟶−1,1r,(4)f1A1=sgnW1A1,f2A2=sgnW2A2.sgn⋅ is a symbolic function that converts continuous data to binary form; W1∈Rr×k and W2∈Rr×k are projection matrices corresponding to two modes, respectively. Learn the unified binary hash code and the loss function of hash function as
(5)minW1,W2,BB−w1F2+B−w2F2s.t.A∈−1,1r×nAccording to formula (5), the hash code learned from the intrinsic features of the data contains only very limited semantics, since the process is independent of semantic tags. The DLSCMH algorithm improves the semantic expression ability of unified binary hash code by using the rich semantics in explicit class tags. In theory, the closer hash codes are in the same class, the better and vice versa. In this case, the courses taken can simply be classified according to their class ID. Based on the above analysis, the DLSCMH algorithm [21] constructs a term that enhances the discriminant ability, as shown in formula (6). The category label yi corresponding to each multimedia data sample is directly regressed to the corresponding binary hash code bi; the specific mathematical form of which is
(6)minbi,Q∑i=1nbi−QyiF2s.t.bi∈−1,1rwhereQ∈Rr×c is the semantic transfer matrix. The formula generates a unified binary hash for each data sample from the by the semantic transformation matrix Qyi. The matrix form of formula (6) is expressed as
(7)minB,QB−QYF2s.t.bi∈−1,1r×nNext, the unified binary hash code matrixB can be obtained by a simple sgn⋅ function [22]. In addition, this strategy of direct regression of supervised category labels can well support discrete hash optimization. Combined with the above calculations, the objective function of the DLSCMH algorithm is as follows:
(8)minU1,U2,A1,A2,W1,W2,Q,B∑m=12φXm−UmAmF2s.t.B∈−1,1r×nwhereβ and δ are the correlation parameters and y the regularization parameter.


### 3.4. Discrete Algorithm Optimization

The discrete constraints of binary arithmetic cause problems with NP-hard; the existing hash methods adopt the “relaxation + rounding” hash optimization strategy. Firstly, the discrete constraint of binary hash code is simply relaxed, then the continuous solution is solved, and finally the continuous solution is thresholding to approximate binary code [23]. Although this “relaxation + rounding” hash optimization strategy can easily solve hash codes, it will lead to large quantization errors and limit the retrieval accuracy. In contrast, DLSCMH algorithm proposes an iterative discrete hash optimization strategy to update binary hash codes directly and efficiently. Each optimization step adopts the strategy of fixing other variables and optimizing one variable. The specific solution process is as follows.Step 1.
Fix the other variables and update the latent semantic representation of the two modes to(9)minA1φx1−U12+βB−W1F2,(10)minA2φx2−U22+βB−w22.
Constraints, mathematical terms, in mathematical programming the constraints on decision schemes often appear in the form of inequalities or equations. In economic problems, the objective function often has to find the maximum value (or minimum value) under certain constraints, and they contain the variables used to represent the decision-making scheme, to impose a limited range on the decision-making scheme. If the derivative of objective function formula (8) with respect to A1 and A2 is 0, formulas (11) and (12) can be obtained
(11)A1=U1+w1−1U2+w2,(12)A2=U2+w1−1U1+B.Step 2.
Fixing other variables, semantic transformation matrixQ, and obtaining
(13)minU1φX1−U1A1F2+γU1F2,(14)minU2φX2−U2A2F2+γU2F2,(15)minQδB−QYF2+γQF2.
The solution results are(16)U1=φX1A1TA1A1T+γI−1,(17)U2=φx2AT+γB,(18)Q=δBYTδYYT+γI−1.Step 3.
Fix other variables, updateW1 and W2, and get
(19)minW1βB−W1A1F2+γW1F2,(20)minW2βB−W2A2F2+γW2F2,
whereI is the identity matrix.Step 4.
Fix other variables and update unity binary, which is expressed as(21)minBβB−W1A1F2+B−W2A2F2+δB−QYF2s.t.B∈−1,1r×n
It can be rewritten as(22)minBβTrBT−A1TW1TB−w1+βTrBT−w2+δTrBT−YTQTB−QYs.t.B∈−1,1r×n
Since is a constant, the above formula can be converted into(23)minB−TrA1+β2∈−1,1r×n.
Finally, the unified binary hash code can be solved as follows, such as(24)B=sgnw1+β2+YQ.
By equation (26), all bits of the binary hash code can be learned at one time from the solution. Binary code is obtained by sgn⋅ function. The iterative discrete hash optimization strategy proposed by the DLSCMH algorithm avoids quantization error and significantly accelerates the whole training process.


### 3.5. Hash Function Learning and Extended Sample Coding

Once the latent semantic representationAm and projection matrix Wm of the image and text patterns are obtained, the hash function is defined as fmAm=sgmWmAm. Using the new query example, hash codes can be generated using prebuilt hash functions. In a modal condenser search scenario, query examples typically contain only one modality that retrieves the database from another modality. To generate binary hash codes for query samples, a latent semantic representation of the query samples must be obtained, and a modality-specific hash function generates binary hash codes. In query example x~1 or x~2, the latent semantic representation is captured in the form of matrix factors, as in
(25)mina~mx~m−Uma~mF2,m=1,2.Among them,Um is from offline training. The hash code b~ associated with the latent spatial semantic representation can be obtained by the hash function b~=sgnW1a~1 or b~=sgnW2a~2 of the corresponding modal.


### 3.6. Convergence Analysis and Complexity Analysis of Algorithm

At each stage of iterative optimization, a strategy is built to link other variables together and optimize one variable to ensure that the objective function is convex with respect to the variable. Therefore, each step of optimizing the DLSCMH algorithm results in a smaller or constant value of the objective function (8); i.e., each update of the binary code monotonically decreases the value of the objective function. In theory, after many iterations, the algorithm reaches a stable value, which can be considered as effective convergence. The complexity of the DLSCMH algorithm is related to nonlinear embedding [24] and iterative discrete optimization. The time complexity of nonlinear immersion is Onkdm, where n is the number of training samples and k is the number of anchors. Discrete hash optimization is achieved through iteration, and the computational complexity of this process is Oiterd1n+d2n+d1r+d2r+rn, where iter is the number of iterations and r is the length of the hash code. Assuming n≫dm>r, the iterative discrete hash optimization process is linearly related to the number of learning samples n. Learning latent semantic representations is a linear process with time complexity On. The calculation of the hash function solves a linear problem with time complexity. This indicates DL. During out-of-sample coding, the generation of spreading codes for new query samples can be done in the F-complexity domain.


### 3.7. Discussion on Multiple Modal Conditions

In theory, the DLSCMH algorithm extended from two modes to more modes. The general function is shown in(26)minUm,Am,Wm,Q∑mφXm−UmAmF2s.t.B∈−1,1r×nAs with these two patterns, it is necessary to learn the latent semantic representation of each pattern and reflect it into a common Hamming space using a state-specific hash function [25]. Diverse hash searches are possible by learning binary hash codes and hash functions using separate hash optimization methods similar to the previous one. The optimal solution for each variable is expressed as follows. The optimal solution of Um is
(27)Um=φXmAmTAmAmT+γI−1.The optimal solution ofQ is
(28)Q=δBYTδYYT+γI−1.The optimal solution ofWm is
(29)Wm=βBAmTβAmTAmT+γI−1.The optimal solution ofB is
(30)B=sgnβ∑mWmAm+δYQ.


## 3.1. Hash Algorithm for Cross-Modal Retrieval

It is assumed that the multimedia data training seto=oii=1n contains n groups of multimedia data training samples. For the sake of simplicity, this paper defaults to considering two modal data of image [16] and text for each set of multimedia data, and the method proposed in this paper can be extended to multimedia data containing more modal features in theory. For each multimedia data sample oi=xi1,xi2,yi, xi1∈Rd1 is the i-th image feature vector, xi2∈Rd2 is the i-th text feature vector, d1,d2 is the dimension of image and text features, respectively, yi=0,1c is the corresponding category label, and c is the total number of semantic categories. Image mode and text mode attribute matrix are X1=xi1i=1n∈Rd1×n and X2=xi2i=1n∈Rd2×n, and the category label matrix is Y=yii=1n∈Rc×n. The purpose of discrete latent semantic cross-modal hashing algorithm [17] is to learn two modal-specific hash functions for image modality and text modality, project heterogeneous data features into a common Hamming space, and generate hash code B=b1,b2,⋯,bn∈−1,1r×n for skip level search. The formula representation of the two algorithms fX1:Rd1⟶0,1r and fX2:Rd2⟶0,1r, where r is the length of the hash code [18].


## 3.2. Representation Learning of Subsurface Space

Assuming two matricesX1 and X2, the p vector can be obtained such as formula (1) is obtained by Gaussian kernel function [19]. Gauss kernel function, also known as radial basis function, is a commonly used kernel function. It can map finite dimensional data to high-dimensional space, and the Gauss kernel function is a monotonic function of the Euclidean distance of two vectors.
(1)φxi=expxi−a12ε,⋯,expxi−ap2ε.whereaij=1p is P anchor points randomly selected from the training set and ε is Gaussian kernel parameter. Learn latent semantic representations of image modalities and text modalities separately using common matrix factors, it can be reduced to
(2)minU1φx1−A1F2+φx2−U2A2F2.φX1∈Rp×n and φX2∈Rp×n are Gaussian kernel projections of image and text feature matrices, respectively, A1∈Rk×n and A2∈Rk×n are latent semantic representations of image and text modes, respectively, U1∈Rp×k and U2∈Rp×k are basis matrices of image and text modes, respectively, and K is the dimension of latent semantic representation.


## 3.3. Discriminative Hash Learning

The DLSCMH algorithm learns two pattern-specific hash functions [20], maps the latent semantic representations of two heterogeneous patterns to a common Hamming space, and generates a binary hash code for that state. The image and text modality attributes corresponding to each multimedia data sample oi describe the same semantic class and theoretically have the same binary hash code B. DLSCMH algorithm uses a unified binary hash code matrix bi to construct the correlation between heterogeneous modes, which effectively reduces the semantic gap between heterogeneous modes. The hash functions of the two modes are expressed as
(3)f1A1:Rd1⟶−1,1r,f1A2:Rd2⟶−1,1r,(4)f1A1=sgnW1A1,f2A2=sgnW2A2.sgn⋅ is a symbolic function that converts continuous data to binary form; W1∈Rr×k and W2∈Rr×k are projection matrices corresponding to two modes, respectively. Learn the unified binary hash code and the loss function of hash function as
(5)minW1,W2,BB−w1F2+B−w2F2s.t.A∈−1,1r×nAccording to formula (5), the hash code learned from the intrinsic features of the data contains only very limited semantics, since the process is independent of semantic tags. The DLSCMH algorithm improves the semantic expression ability of unified binary hash code by using the rich semantics in explicit class tags. In theory, the closer hash codes are in the same class, the better and vice versa. In this case, the courses taken can simply be classified according to their class ID. Based on the above analysis, the DLSCMH algorithm [21] constructs a term that enhances the discriminant ability, as shown in formula (6). The category label yi corresponding to each multimedia data sample is directly regressed to the corresponding binary hash code bi; the specific mathematical form of which is
(6)minbi,Q∑i=1nbi−QyiF2s.t.bi∈−1,1rwhereQ∈Rr×c is the semantic transfer matrix. The formula generates a unified binary hash for each data sample from the by the semantic transformation matrix Qyi. The matrix form of formula (6) is expressed as
(7)minB,QB−QYF2s.t.bi∈−1,1r×nNext, the unified binary hash code matrixB can be obtained by a simple sgn⋅ function [22]. In addition, this strategy of direct regression of supervised category labels can well support discrete hash optimization. Combined with the above calculations, the objective function of the DLSCMH algorithm is as follows:
(8)minU1,U2,A1,A2,W1,W2,Q,B∑m=12φXm−UmAmF2s.t.B∈−1,1r×nwhereβ and δ are the correlation parameters and y the regularization parameter.


## 3.4. Discrete Algorithm Optimization

The discrete constraints of binary arithmetic cause problems with NP-hard; the existing hash methods adopt the “relaxation + rounding” hash optimization strategy. Firstly, the discrete constraint of binary hash code is simply relaxed, then the continuous solution is solved, and finally the continuous solution is thresholding to approximate binary code [23]. Although this “relaxation + rounding” hash optimization strategy can easily solve hash codes, it will lead to large quantization errors and limit the retrieval accuracy. In contrast, DLSCMH algorithm proposes an iterative discrete hash optimization strategy to update binary hash codes directly and efficiently. Each optimization step adopts the strategy of fixing other variables and optimizing one variable. The specific solution process is as follows.Step 1.
Fix the other variables and update the latent semantic representation of the two modes to(9)minA1φx1−U12+βB−W1F2,(10)minA2φx2−U22+βB−w22.
Constraints, mathematical terms, in mathematical programming the constraints on decision schemes often appear in the form of inequalities or equations. In economic problems, the objective function often has to find the maximum value (or minimum value) under certain constraints, and they contain the variables used to represent the decision-making scheme, to impose a limited range on the decision-making scheme. If the derivative of objective function formula (8) with respect to A1 and A2 is 0, formulas (11) and (12) can be obtained
(11)A1=U1+w1−1U2+w2,(12)A2=U2+w1−1U1+B.Step 2.
Fixing other variables, semantic transformation matrixQ, and obtaining
(13)minU1φX1−U1A1F2+γU1F2,(14)minU2φX2−U2A2F2+γU2F2,(15)minQδB−QYF2+γQF2.
The solution results are(16)U1=φX1A1TA1A1T+γI−1,(17)U2=φx2AT+γB,(18)Q=δBYTδYYT+γI−1.Step 3.
Fix other variables, updateW1 and W2, and get
(19)minW1βB−W1A1F2+γW1F2,(20)minW2βB−W2A2F2+γW2F2,
whereI is the identity matrix.Step 4.
Fix other variables and update unity binary, which is expressed as(21)minBβB−W1A1F2+B−W2A2F2+δB−QYF2s.t.B∈−1,1r×n
It can be rewritten as(22)minBβTrBT−A1TW1TB−w1+βTrBT−w2+δTrBT−YTQTB−QYs.t.B∈−1,1r×n
Since is a constant, the above formula can be converted into(23)minB−TrA1+β2∈−1,1r×n.
Finally, the unified binary hash code can be solved as follows, such as(24)B=sgnw1+β2+YQ.
By equation (26), all bits of the binary hash code can be learned at one time from the solution. Binary code is obtained by sgn⋅ function. The iterative discrete hash optimization strategy proposed by the DLSCMH algorithm avoids quantization error and significantly accelerates the whole training process.


## 3.5. Hash Function Learning and Extended Sample Coding

Once the latent semantic representationAm and projection matrix Wm of the image and text patterns are obtained, the hash function is defined as fmAm=sgmWmAm. Using the new query example, hash codes can be generated using prebuilt hash functions. In a modal condenser search scenario, query examples typically contain only one modality that retrieves the database from another modality. To generate binary hash codes for query samples, a latent semantic representation of the query samples must be obtained, and a modality-specific hash function generates binary hash codes. In query example x~1 or x~2, the latent semantic representation is captured in the form of matrix factors, as in
(25)mina~mx~m−Uma~mF2,m=1,2.Among them,Um is from offline training. The hash code b~ associated with the latent spatial semantic representation can be obtained by the hash function b~=sgnW1a~1 or b~=sgnW2a~2 of the corresponding modal.


## 3.6. Convergence Analysis and Complexity Analysis of Algorithm

At each stage of iterative optimization, a strategy is built to link other variables together and optimize one variable to ensure that the objective function is convex with respect to the variable. Therefore, each step of optimizing the DLSCMH algorithm results in a smaller or constant value of the objective function (8); i.e., each update of the binary code monotonically decreases the value of the objective function. In theory, after many iterations, the algorithm reaches a stable value, which can be considered as effective convergence. The complexity of the DLSCMH algorithm is related to nonlinear embedding [24] and iterative discrete optimization. The time complexity of nonlinear immersion is Onkdm, where n is the number of training samples and k is the number of anchors. Discrete hash optimization is achieved through iteration, and the computational complexity of this process is Oiterd1n+d2n+d1r+d2r+rn, where iter is the number of iterations and r is the length of the hash code. Assuming n≫dm>r, the iterative discrete hash optimization process is linearly related to the number of learning samples n. Learning latent semantic representations is a linear process with time complexity On. The calculation of the hash function solves a linear problem with time complexity. This indicates DL. During out-of-sample coding, the generation of spreading codes for new query samples can be done in the F-complexity domain.


## 3.7. Discussion on Multiple Modal Conditions

In theory, the DLSCMH algorithm extended from two modes to more modes. The general function is shown in(26)minUm,Am,Wm,Q∑mφXm−UmAmF2s.t.B∈−1,1r×nAs with these two patterns, it is necessary to learn the latent semantic representation of each pattern and reflect it into a common Hamming space using a state-specific hash function [25]. Diverse hash searches are possible by learning binary hash codes and hash functions using separate hash optimization methods similar to the previous one. The optimal solution for each variable is expressed as follows. The optimal solution of Um is
(27)Um=φXmAmTAmAmT+γI−1.The optimal solution ofQ is
(28)Q=δBYTδYYT+γI−1.The optimal solution ofWm is
(29)Wm=βBAmTβAmTAmT+γI−1.The optimal solution ofB is
(30)B=sgnβ∑mWmAm+δYQ.


## 4. Experimental Results and Analysis

### 4.1. Experimental Data Collection

Multimodal English classroom teaching enables teachers to make use of multimedia curriculum materials and other resources to better create a real learning situation, provide students with various sensory stimuli such as sight, hearing, and touch, and truly act as students. In this study, 48 senior high school English teachers were selected from the first and second grades of senior high school, and they were investigated. Eight local teachers were selected for interviews, which were observed six times in 12 grades from grade one to grade three in two months. The observational research mainly focuses on two aspects: on the one hand, teachers’ use of multimedia materials in teaching, on the other hand, the influence of students’ classroom learning.


### 4.2. Present Situation and Management of Teachers’ Multimedia Course Application

In the computerization of English teaching, the design, development, and teaching application of multimedia teaching materials are important ways and forms of computer training. In English classroom teaching, most teachers have taken the application of multimedia teaching materials as a traditional teaching method. The specific survey data of this study (or multimedia course materials applied to English classroom teaching) are shown in Figure1.Figure 1
Teachers’ use of multimedia courseware.The results in Figure1 show that most (92%) English teachers consider and apply multimedia education courses when designing and implementing education. Many teachers say that multimedia courses are often used for teaching their own courses, and their vocational training is inseparable from supporting multimedia courses.The survey results also confirm that English teachers have understood the importance of multimedia courses. The survey asked: “I think multimedia courses play an inestimable role in today’s English grammar education,” as shown in Figure2.Figure 2
Teachers’ understanding of the importance of multimedia courseware.As shown in the figure, 77% of English teachers recognize the important role of multimedia textbooks in English teaching, but different teachers often have different views on the role of multimedia textbooks in classroom teaching. From this point of view, this paper studies the role of English teachers’ multimedia curriculum programs in terms of questions (the purpose of applying teachers’ multimedia curriculum programs). The specific data results are shown in Figure3.Figure 3
The purpose of applying multimedia courseware in classroom teaching.The results in Figure3 show that more than 90% of teachers use multimedia curriculum programs to present information, 66.7% use multimedia curriculum programs to create classroom teaching situations, and 52.1% use multimedia education courses in classroom teaching. Classroom is mainly to attract students. In the study, we also examine the application of multimedia courses in teachers’ English classroom teaching, as shown in Table 1.Table 1
Specific application of multimedia courseware in English classroom teaching.
App linkFrequencyProportionIntroduce newConformity50%Sen practiceConformity75%Situ converGeneral conformity50%Assign tasksConformity75%OthersGeneral conformity45.80%As shown in Table1, the most widely used multimedia course materials in English teaching are sentence exercises and situational discussions. Among them, sentence practice is an important starting point for using multimedia course materials in English subjects. It is precisely because language learning requires a lot of “listening and reading,” so it is necessary to use the voice and video information in multimedia textbooks as tools and support to complete the classroom.


### 4.3. Multimedia Application Data Analysis

This study also examined the multimedia curriculum production tools commonly used by educators, which are described in more detail in Table2.Table 2
Multimedia courseware making and auxiliary tools commonly used in English subjects.
Making toolFrequencyProportionPPTConformity91.70%FlashNonconformity79.20%PSNonconformity58.40%FocuskyNonconformity94.60%The actual survey results show that rural English teachers manage the best and use the most widely PPT; among the respondents; the auxiliary tools in teaching material production, such as image editing software, video editing software, and audio editing software, are relatively few in application. As for the range of other “new” tools that can be used to make multimedia courses, the tools chosen by English teachers in rural middle schools are relatively simple, and PPT is less selected except for the rest of the multimedia production platform courses. Practical management is not particularly ideal when it comes to managing production tools, and most teachers do not have enough control over software—many people do not know how to apply it. This study also examines the sources of multimedia curriculum programs used by teachers in the classroom, and the exact results of the study are shown in Figure4.Figure 4
Source of multimedia courseware.The results in Figure4 show that only 17% of teachers’ course materials can be completed independently. This also shows that some English teachers have some problems in multimedia production and design. At the same time, the teacher survey also focuses on the specific difficulties and problems in the production and application of multimedia curriculum programs for English teachers: “What difficulties have English teachers encountered in the production and practical application of multimedia curriculum programs,” as shown in Table 3.Table 3
Common problems in the making and application of multimedia courseware commonly used in English subjects.
ProblemOptionsProportionPoor techConformity65.40%Nowhere to learnConformity95.80%Lack of materialsConformity93.80%No processingGeneral conformity95.80%Unable to expressNonconformity68.80%Unable to mergeConformity83.30%Poor effectGeneral conformity75%The ratios in Table3 represent the frequency share of common problems in the production and application of commonly used multimedia courses in English subjects among teachers; and each share is measured with a separate population as a sample, so the proportions are different from each other related. It can be seen from Table 3 that the main problems in the production of multimedia training programs are “poor production technology,” “inability to learn from others,” “lack of materials,” “no processing,” and so on. This is the biggest problem of multimedia courses produced by English teachers. In other words, apart from the lack of technical control over the textbook production software (PPT), the related technology and the ability to process multimedia materials are also the fundamental bottlenecks that restrict teachers’ ability to produce multimedia courses. In recent years, systematic training has become an effective means to improve teachers’ information application level, and the training for all teachers, including English teachers, in the production and application of multimedia teaching materials has also increased. In fact, the exact results of the impact study of this training are shown in Figure 5.Figure 5
Training of English teachers in making and applying multimedia courseware.Figure5 shows that most of the teachers interviewed have received training in making and applying multimedia courses. Among these teachers, basic application (83%) receives the most, but other software training, such as image processing and video editing, only accounts for 50%, and this training is still mainly for young teachers. The vertical axis in Figure 5 represents the percentage of training in the production and application of multimedia course materials in the total population of each age group. A longitudinal comparison shows that the proportion of young teachers who have been trained is higher and that the content of the training is more extensive.


### 4.4. Application Effect of Multimedia Courseware

As a matter of fact, students have the most say in the effect of the application of English multimedia curriculum software, and students’ feelings about the effect of teachers’ use of multimedia curriculum programs in teaching are relatively objective. In fact, one of the most important issues in teaching and learning supported by multimedia courses is the frequency of use, and its production level is constantly improving. The educational impact of multimedia curriculum projects is often reflected in the form of rewards, IT integrated courses, and open courses. In this experiment, we also studied these situations, and the exact results of the study are shown in Table4 and Figure 6.Table 4
Teaching awards of teachers’ multimedia courseware and related evaluation courses.
SpeciesHaveNoneMultimedia91.70%8.30%Integrating lesson examples22.90%6.30%Original14.60%10.40%Others39.60%60.40%Figure 6
Award-winning level of teachers’ informatization.As can be seen from the table, 91.7% of teachers have won similar awards in multimedia teaching materials; 22.9% of teachers won similar awards in the information technology integration course through multimedia teaching materials; 14.6% of teachers received similar awards from original sources.Figure6 shows that 70.8% of teachers have won district and provincial teaching materials for comparable computerized achievements, 22.9% of teachers have won district and provincial teaching awards for integrating teaching examples, and 33.3% of teachers have won district and provincial teaching materials. Among the original resources for teachers to receive provincial and municipal awards, 68.8% of teachers received district and provincial awards, 22.9% received provincial and municipal awards, and 2.1% received national awards. Although some achievements have been made in the application of multimedia curriculum, there is still much room for improvement. This study collected the opinions and suggestions of educators on improving multimedia curriculum, and the exact results are shown in Figure 7.Figure 7
What can be improved in the application of multimedia courseware.Figure7 shows that most teachers believe that the application of multimedia courseware in current English vocational education to further improve the learning effect still needs a certain amount of latitude. As for teachers, 38% of teachers believe that multimedia course materials can further integrate the teaching content of English subjects, which corresponds to the educational needs of course material production and application. Among them, teachers hope to have richer media expression (23%) and artistic beauty of curriculum materials (12%), which is a hope and need for the improvement of technology and art. Of course, more teachers are in favor of it. Curriculum program can be more convenient and agile. After all, the simplicity and efficiency of teaching application and design are the factors that directly affect the application effect of curriculum program.


## 4.1. Experimental Data Collection

Multimodal English classroom teaching enables teachers to make use of multimedia curriculum materials and other resources to better create a real learning situation, provide students with various sensory stimuli such as sight, hearing, and touch, and truly act as students. In this study, 48 senior high school English teachers were selected from the first and second grades of senior high school, and they were investigated. Eight local teachers were selected for interviews, which were observed six times in 12 grades from grade one to grade three in two months. The observational research mainly focuses on two aspects: on the one hand, teachers’ use of multimedia materials in teaching, on the other hand, the influence of students’ classroom learning.


## 4.2. Present Situation and Management of Teachers’ Multimedia Course Application

In the computerization of English teaching, the design, development, and teaching application of multimedia teaching materials are important ways and forms of computer training. In English classroom teaching, most teachers have taken the application of multimedia teaching materials as a traditional teaching method. The specific survey data of this study (or multimedia course materials applied to English classroom teaching) are shown in Figure1.Figure 1
Teachers’ use of multimedia courseware.The results in Figure1 show that most (92%) English teachers consider and apply multimedia education courses when designing and implementing education. Many teachers say that multimedia courses are often used for teaching their own courses, and their vocational training is inseparable from supporting multimedia courses.The survey results also confirm that English teachers have understood the importance of multimedia courses. The survey asked: “I think multimedia courses play an inestimable role in today’s English grammar education,” as shown in Figure2.Figure 2
Teachers’ understanding of the importance of multimedia courseware.As shown in the figure, 77% of English teachers recognize the important role of multimedia textbooks in English teaching, but different teachers often have different views on the role of multimedia textbooks in classroom teaching. From this point of view, this paper studies the role of English teachers’ multimedia curriculum programs in terms of questions (the purpose of applying teachers’ multimedia curriculum programs). The specific data results are shown in Figure3.Figure 3
The purpose of applying multimedia courseware in classroom teaching.The results in Figure3 show that more than 90% of teachers use multimedia curriculum programs to present information, 66.7% use multimedia curriculum programs to create classroom teaching situations, and 52.1% use multimedia education courses in classroom teaching. Classroom is mainly to attract students. In the study, we also examine the application of multimedia courses in teachers’ English classroom teaching, as shown in Table 1.Table 1
Specific application of multimedia courseware in English classroom teaching.
App linkFrequencyProportionIntroduce newConformity50%Sen practiceConformity75%Situ converGeneral conformity50%Assign tasksConformity75%OthersGeneral conformity45.80%As shown in Table1, the most widely used multimedia course materials in English teaching are sentence exercises and situational discussions. Among them, sentence practice is an important starting point for using multimedia course materials in English subjects. It is precisely because language learning requires a lot of “listening and reading,” so it is necessary to use the voice and video information in multimedia textbooks as tools and support to complete the classroom.


## 4.3. Multimedia Application Data Analysis

This study also examined the multimedia curriculum production tools commonly used by educators, which are described in more detail in Table2.Table 2
Multimedia courseware making and auxiliary tools commonly used in English subjects.
Making toolFrequencyProportionPPTConformity91.70%FlashNonconformity79.20%PSNonconformity58.40%FocuskyNonconformity94.60%The actual survey results show that rural English teachers manage the best and use the most widely PPT; among the respondents; the auxiliary tools in teaching material production, such as image editing software, video editing software, and audio editing software, are relatively few in application. As for the range of other “new” tools that can be used to make multimedia courses, the tools chosen by English teachers in rural middle schools are relatively simple, and PPT is less selected except for the rest of the multimedia production platform courses. Practical management is not particularly ideal when it comes to managing production tools, and most teachers do not have enough control over software—many people do not know how to apply it. This study also examines the sources of multimedia curriculum programs used by teachers in the classroom, and the exact results of the study are shown in Figure4.Figure 4
Source of multimedia courseware.The results in Figure4 show that only 17% of teachers’ course materials can be completed independently. This also shows that some English teachers have some problems in multimedia production and design. At the same time, the teacher survey also focuses on the specific difficulties and problems in the production and application of multimedia curriculum programs for English teachers: “What difficulties have English teachers encountered in the production and practical application of multimedia curriculum programs,” as shown in Table 3.Table 3
Common problems in the making and application of multimedia courseware commonly used in English subjects.
ProblemOptionsProportionPoor techConformity65.40%Nowhere to learnConformity95.80%Lack of materialsConformity93.80%No processingGeneral conformity95.80%Unable to expressNonconformity68.80%Unable to mergeConformity83.30%Poor effectGeneral conformity75%The ratios in Table3 represent the frequency share of common problems in the production and application of commonly used multimedia courses in English subjects among teachers; and each share is measured with a separate population as a sample, so the proportions are different from each other related. It can be seen from Table 3 that the main problems in the production of multimedia training programs are “poor production technology,” “inability to learn from others,” “lack of materials,” “no processing,” and so on. This is the biggest problem of multimedia courses produced by English teachers. In other words, apart from the lack of technical control over the textbook production software (PPT), the related technology and the ability to process multimedia materials are also the fundamental bottlenecks that restrict teachers’ ability to produce multimedia courses. In recent years, systematic training has become an effective means to improve teachers’ information application level, and the training for all teachers, including English teachers, in the production and application of multimedia teaching materials has also increased. In fact, the exact results of the impact study of this training are shown in Figure 5.Figure 5
Training of English teachers in making and applying multimedia courseware.Figure5 shows that most of the teachers interviewed have received training in making and applying multimedia courses. Among these teachers, basic application (83%) receives the most, but other software training, such as image processing and video editing, only accounts for 50%, and this training is still mainly for young teachers. The vertical axis in Figure 5 represents the percentage of training in the production and application of multimedia course materials in the total population of each age group. A longitudinal comparison shows that the proportion of young teachers who have been trained is higher and that the content of the training is more extensive.


## 4.4. Application Effect of Multimedia Courseware

As a matter of fact, students have the most say in the effect of the application of English multimedia curriculum software, and students’ feelings about the effect of teachers’ use of multimedia curriculum programs in teaching are relatively objective. In fact, one of the most important issues in teaching and learning supported by multimedia courses is the frequency of use, and its production level is constantly improving. The educational impact of multimedia curriculum projects is often reflected in the form of rewards, IT integrated courses, and open courses. In this experiment, we also studied these situations, and the exact results of the study are shown in Table4 and Figure 6.Table 4
Teaching awards of teachers’ multimedia courseware and related evaluation courses.
SpeciesHaveNoneMultimedia91.70%8.30%Integrating lesson examples22.90%6.30%Original14.60%10.40%Others39.60%60.40%Figure 6
Award-winning level of teachers’ informatization.As can be seen from the table, 91.7% of teachers have won similar awards in multimedia teaching materials; 22.9% of teachers won similar awards in the information technology integration course through multimedia teaching materials; 14.6% of teachers received similar awards from original sources.Figure6 shows that 70.8% of teachers have won district and provincial teaching materials for comparable computerized achievements, 22.9% of teachers have won district and provincial teaching awards for integrating teaching examples, and 33.3% of teachers have won district and provincial teaching materials. Among the original resources for teachers to receive provincial and municipal awards, 68.8% of teachers received district and provincial awards, 22.9% received provincial and municipal awards, and 2.1% received national awards. Although some achievements have been made in the application of multimedia curriculum, there is still much room for improvement. This study collected the opinions and suggestions of educators on improving multimedia curriculum, and the exact results are shown in Figure 7.Figure 7
What can be improved in the application of multimedia courseware.Figure7 shows that most teachers believe that the application of multimedia courseware in current English vocational education to further improve the learning effect still needs a certain amount of latitude. As for teachers, 38% of teachers believe that multimedia course materials can further integrate the teaching content of English subjects, which corresponds to the educational needs of course material production and application. Among them, teachers hope to have richer media expression (23%) and artistic beauty of curriculum materials (12%), which is a hope and need for the improvement of technology and art. Of course, more teachers are in favor of it. Curriculum program can be more convenient and agile. After all, the simplicity and efficiency of teaching application and design are the factors that directly affect the application effect of curriculum program.


## 5. Concluding Remarks

With the passage of time, multimedia technology has been used in English teaching to a certain extent. The application situation is generally good, and multimedia equipment can basically meet the educational needs, but there are still some problems in teachers’ English ability, mastery of multimedia and information technology, and effectiveness of multimedia courses. Multimedia software is a classroom teaching aid based on textbooks and higher than textbooks. It can not only help teachers explain but also make it easier for students to learn, embrace, and relearn. At the same time, it also expands the teaching content, making the teaching content deeper, wider, more comprehensive, and more systematic. Teachers’ lectures are boring. Multimedia can combine multimedia information such as words, images, audio, and video into one, stimulate students’ senses in multiple directions, overcome the abstract and boring shortcomings of traditional education, and make the educational content more vivid and intuitive. First, the content of the survey and interview is not comprehensive enough, and the persuasiveness of the study is still somewhat insufficient and may not fully reflect the difficulties that exist in the application of multimedia course materials to English subjects. The use of multimedia in any education is inevitably influenced by other factors, which are not considered in this study. The number of classes observed by the observation method is too small, and the representativeness of the observed classes is not strong.



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*Source: 7534153-2022-08-17.xml*