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Journal of Quantum Computing
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DOI: 10.32604/jqc.2022.039795

Article

Research on Improving Teaching Quality and Optimizing Teaching Scheme Based on Deep Learning in Chinese Literature Scene

Yali Wang*

Shangqiu Institute of Technology, Shangqiu, 476000, China
*Corresponding Author: Yali Wang. Email: 1350012004@sqgxy.edu.cn
Received: 16 February 2023; Accepted: 27 April 2023; Published: 03 July 2023

Abstract: With the rapid development of society nowadays, this paper begins to study the teaching strategies of promoting students’ deep learning in the Chinese literature scene, and the attitudes and teaching quality of students and teachers when learning Chinese literature. The investigation and analysis show that: (1) For example, the relationship between literary scenes and characters in the famous literary work “Three Kingdoms” is analyzed. The complex character relationships in literature are important to literary scenes and learning. (2) It explains that the suggestions when writing Chinese literary scenes need to be pragmatic, pay attention to modern people’s livelihood, and the author should integrate into the literary scene to create good works. (3) The experiment in this paper investigates the depth of students’ learning of Chinese literature and their learning methods, and discovers methods that can make students learn more deeply.

Keywords: Literary scene; deep learning; teaching strategy

1  Introduction

The contemporary literature research model prevails at the wrong time, and the bias and lag of the data obscure the richness and complexity of literature. Returning to the historical scene and at the same time researchers have accurate historical materials and a historical attitude towards the subject, so that the further development of the discipline can be promoted [1]. South Korea used modern academic methods when studying Chinese literature very early. China’s Lu Xun is a literary peak, and there are many reports on Chinese literature. These reports make the literature of the two countries blend with each other, and the two countries have similar historical backgrounds, and the authors of the two countries can learn from each other [2]. This paper reviews the eliminated literature and research status observed during the same period, and discusses the existing problems. The difference between the two is that contemporaneous observation reflects the timely state of literary obsolescence, while long-term observation reflects the process of literary obsolescence [3]. Opinions are used to develop effective learning strategies. For students (lectures, tutorials, laboratory sessions) are of equal value to their learning. Students’ problems in the biological sciences can be changed through the course [4]. This paper dialectically tests the effect of teaching experiments under the framework of constructivism, and considers the first point that cognitive conflict must have a relatively convincing solution strategy; the second point is that after cognitive conflict occurs, students must be provided with experience. This study is based on two freshmen students, one is the control group and the other is the experimental group [5]. This article shows two methods of translating Chinese literature, free translation and literal translation. Chinese also includes many aspects and has unique charm. Through the principles of translation, we can better understand and lay a good foundation [6]. This article briefly describes the Chinese wartime literature from 1937 to 1949. When the novel could complete the mission of “Saving the Nation”, the works of those who really devoted themselves to the creation only expressed the contradiction and ambiguity of the regulations supporting this cause. This contradiction has a double irony mean. Wartime writers faced a lot of pressure [7]. Literary translation is an important way for Chinese literature to enter the world literature and receive international recognition. This paper takes Mo Yan’s works and translations as examples, analyzes translation and discusses the cultivation of translation talents and cultural communication, so as to expand the influence of Chinese culture [8]. Feng Shicai’s poetry features the adaptation of Chinese poetry to express nostalgia. This is a fusion of two styles of writing. In this way, on the one hand, the culture between the two makes a deep friendship between the two, and on the other hand, due to the existence of the region, the differences between Indonesian Chinese culture and traditional culture are also revealed [9]. This article tells the story of the Chinese drama reform debate caused by magazines in 1918. Critics accuse traditional dramas of seeking self-soothing, misleading melodrama and outdated emotional narrative structures. They argue that old stories and cheap emotional gratification, embodying Confucian morality, distract attention from historical reality and hinder artistic creativity. They call for realistic drama in a tragic mode, trying to break the old narrative procedures and emotional modes and enter the “real” dimension of history. Intellectuals seem to be exploring a new “primitive” form of reality [10]. The rise of the middle class has led to a dramatic increase in the number of young men and women who have the opportunity to attend college. With this growth, college books tend to focus on male students at Oxford or Cambridge. Bogan believes that analyzing lesser-known women’s stories can provide new insights into education, religion, politics, literary culture and gender. The work of Virginia Woolf, Rosamund Lehman, and Vera Brittan, as well as many forgotten authors, are included as case studies and based on their literary and historical contexts. This student novel is not a universal coming-of-age story, but is full of struggles and compromises [11]. In the West African country of Mali, the constitution recognizes fourteen languages as official languages. One of them is French, the language of the former colonial countries, and the remaining 13 are indigenous languages of Africa. These languages are traditionally used for oral communication and narrative, but with the introduction of writing techniques, these languages have been codified and used in creative writing by some writers. This article explores the reasons why the authors chose the language of writing in this multilingual environment. It shows how writers see their role in traditional Malian oral culture. Through the inspection of education and development and other related institutions [12]. This article explores the validity of Andre Lefevre’s hypothesis through a case study of Edgar Allan Poe’s translation in the Turkish literary system. The first part of this paper includes an external analysis of gene-based classifications of ‘metalinguistic’ and ‘sublinguistic’, as well as another category, including social media. Through external analysis, the poetics of Poe and the poetics of the Turkic literary system are discussed, as well as the degree of acceptance of Poe by the system, to determine whether Poe has acquired more classics or reputation. Over the past 90 years, the influence, receptivity and reputation of writers in the Turkic literary system have continued to increase [13]. As a historical manifestation of the Chinese Communist Party’s literary and artistic policy construction during the Yan’an period, the “Speech at the Yan’an Literary and Art Symposium” directly caused the formation of the dialect in the Yan’an literary style. The early Yan’an literature based on intellectual discourse was quickly replaced by dialects with distinctive regional characteristics. The integration of dialect style into official document writing is not out of the author’s conscious pursuit, but has a strong functional color, which not only guarantees the urgent needs of Yan’an in literary and artistic propaganda, encouragement, education, and education. At the same time, he also participated in the construction of the new literary image he aspired to and the party’s major requirements for a new political program for cultural hegemony during the Yan’an period [14]. A research document sheds light on the complexities of Canada’s emerging literary industry. Large cities around the world, including the US, UK, and parts of Europe, have established publishers that offer a lot of scope for local writing skills. In the 1960s, many Canadians saw moving as a necessary step to greater success in writing. This article explores examples of writers fleeing and returning to writers, and what drives the movement. However, as the Canadian literary scene continues to grow and prosper, we are also exploring the current views of these authors to see if the same motivation to leave [15]. The paper uses the artificial intelligence method to carry on the thorough analysis to the literature work creation mentality and the internal literary science logic, has solved the context grammar, the glossary consistency and the logical rationality question on the whole. The experimental results show that it has a good application effect. The analysis time of the adopted method needs to be further improved, especially when the learning model adopts a multi-layer framework. Later, parallel computing is used to coordinate and allocate statistical resources for different deep learning models to reduce the overall execution time.

2  Deep Learning in Literary Scenes

2.1 Adhere to Focusing on “Things” and Pay Attention to the Truth of “My Land and My People”

When writing scenes of non-fiction, it is especially important to emphasize reality, as this is the basic criterion for distinguishing non-fiction from fiction. This forces non-fiction writers to stick to “things” as the main compositional strategy, to be faithful to the facts, and to interpret the world as the truth. The “things” underlined here means that the writer should pay attention to things when setting up the scene, not that the shock of the novel comes from the amazing fact itself. Writers must abandon the fictional literature design mode centered on “people” in the construction of scenes. As Shi Zhanjun said, a good documentary literature should focus on “the truth of the earth”, and a good documentary literature scene should show the true colors of the world. When choosing the theme content of the scene, the documentary literature scene should reflect the basic concept of “people-oriented” socialism with Chinese characteristics. Literature always puts people in the best position, and always puts people first. Zhu Guangqian once wrote in the article “Literature and Life” that when literature is far from people’s reality and only serves as the patent and privilege of a few people, it loses the strength it needs and gradually nourishes and shrinks, forming a shape. The tough non-fiction scene, relying on the power of “My Land My People”, must return to the people and, in the final analysis, tell the story of humanity. He is fictional, meaning fictional things are difficult.

2.2 The Body Really Acts, and the Mind is Really Present

A fundamental quality of the nonfiction literary scene is reliability. To reach the truth, the author needs to act bravely, leave his own small world, and sink into reality through “existence” and “intervention”. Use the existence of the body to ensure the authenticity of the scene content, anduse the existence of the soul to ensure the depth of reality. The so-called physical act, not only requires the author to step out of his own personal research and his little world, but also to spend time in the field, deepening and approaching the forehead line, and bringing events and celebrations into the limelight. Writers need to see, hear, feel, touch and actually participate in the scene and reporting in an immersive way. The presence of the mind means that the author must project his own emotions when communicating with reality through the scenes of the text. Writers need to know how to be kind and respectful to people and lives, and to maintain a high level of humanistic concern for events and individuals. Not only in a scene of social suffering, but also in a scene of the light of humanity, must the presentation of the scene have a comforting power. The non-fiction scene relies on the behavior of the writer, and the best interpretation of this behavior is what Ding Yang calls “wedge” behavior. Writers turn their bodies into a wedge that plugs directly into the muscles of life. It is a way of going beyond imagination, beyond reading, beyond ordinary discourse, and directly into the real world. It is this kind of “cornering” action that is needed to write a documentary scene. Very good non-fiction literature.

2.3 Adhere to Truth and Literature

The nonfiction literary scene follows the principles of nonfiction in content and structure, but is less restricted in texture. After all, art comes from life, but art is better than life. Reality is the soul of non-fictional scenes, but not the basic purpose of scene construction. In the process of writing non-fiction literary scenes, rational and effective use of literary techniques can better guide readers through these seemingly trivial, complex, and boring realities and go deeper into reality. Sincere literary skill is allowed when writing nonfiction literary scenes. Sometimes, literary tricks can actually make a scene more readable. For example, “Zhongzhijun” by Feng Shui, originally written about the boring life of a soldier, but the author cleverly used literary techniques to make the whole work stand out. In the “Coordination and Defense” section, Li Yong was mobilized from the moment he got off the bus. The readers and writers were still puzzled, and the readers’ curiosity was complete until all the cadres were mobilized one after another. The writer was finally fired. After the transfer, readers will follow the author to solve their problems. Feng Junke used the levitation method to build the scenes of his works. This is a great representation of collage in literature and truth. In stage writing, non-fiction can comprehensively use novels, prose, poetry, short stories and other techniques. As long as these techniques do not affect the reader’s judgment of the credibility of the scene, literary devices can participate in reality. A good documentary literature should not only focus on the authenticity of the scene, but also have a strong literary temperament. This is also the development direction that Chinese documentary literature stage writing must follow. While sticking to the truth, it also sticks to literature.

2.4 Deep Learning

Deep learning not only shows the learning process of students, but also allows teachers to understand the nature of the problem and the learning rules of students. In the process of designing and implementing education, “teacher’s educational thought and educational philosophy” clarifying the relationship between deep principles and learning and education is very important for establishing a scientific educational philosophy, and design is useful. Deep thinking is to carry out learning activities that reflect the essence of the subject, pay attention to the learning process, and make deep thinking really happen. Improve educational concepts, ways of thinking and macro principles of education. By cultivating students’ higher thinking ability and problem-solving ability, and creating effective problem situations under the guidance of teachers, students are encouraged to actively participate in the ongoing research on difficult topics. Supports the actual learning process. “Deep learning and surface learning have obvious differences in learning objectives, knowledge presentation methods, learners’ learning status, and communication of learning outcomes.” Deep learning has four aspects. First, educational goals focus on the development of higher thinking, while deep learning reflects the improvement of students’ ability to solve practical problems. Educational goals designed by teachers should focus on cognitive aspects. Thinking style, way of thinking, emotional experience, and field of thought. This aspect has sustained and widespread impact, reflecting basic literacy requirements. And a comprehensive understanding of the educational content, teachers understand the educational content, can better guide students to learn in depth. Teachers determine the unit theme according to the basic content of the subject, pay attention to the internal logic of the unit theme, transform the basic knowledge of the subject, and build a unique and profound understanding of the knowledge for students. Teaching methods focus on student participation and deep thinking. Learning is not a process of passive acceptance by students, but a process of active immersion by students. Guided by unit themes, teachers stimulate students’ cognition, emotion and thought. Participate and trigger ongoing research education activities as a whole through basic tasks. The last is the result of in-depth education. Deep learning not only demonstrates students’ acquisition of superficial knowledge, but also cultivates students’ basic literacy. Teachers provide timely feedback on students’ learning at all stages of practical activities. The characteristics of evaluation teaching are conducive to the establishment of students’ self-consciousness system and the formation of comprehensive ability to solve practical problems. The deep learning means learning process of students proposed in the article. 1. The artificial intelligence model proposed in this paper is applied to literary works to analyze the internal logic. Analyze the functions of different characters and words in literary works from the internal relevance of the works. 2. Through the corresponding logical analysis and in-depth study, it can effectively enhance the depth of readers’ learning of literary works, enable readers to understand the relationship between characters and internal logic in literary works in a deeper level, and adopt literary means and methods for analysis. Therefore, in this paper, there are not only the learning depth of the corresponding literary works, but also the tools to use artificial intelligence models to carry out in-depth logic of literary works.

3  Analysis of Chinese Literature of “Three Kingdoms”

There are many excellent works in the history of Chinese literature that have been passed down to the present. In the literary scene, the relationship between characters is also very important. This chapter mainly introduces the order distribution, network density, modularity, average path length, clustering factor, six indicators of homozygosity and complexity. The internal correlation of each index and its reflection in the social network structure of the three countries.

3.1 Degree Analysis

The degree of a node in a social network refers to the number of all nodes adjacent to that node. The higher the node order, the more connections the node has. In other words, the state of the network nodes is important. A degree distribution is the probability that an arbitrarily chosen node in a social network has degree k [16]. Example: The order distribution of a complete graph consisting of n nodes is as follows: 1 for probability, 0 for others. The degree distribution of a scale-free network follows a power-law distribution there are various power-law distribution phenomena with different properties in nature and social life, so their research has extensive and far-reaching significance. With the help of effective physical and mathematical tools and powerful computing power, scientists have gained a deeper understanding of the nature of power-law distributions. There are various power-law distribution phenomena with different properties in nature and social life, so their research has extensive and far-reaching significance. With the help of effective physical and mathematical tools and powerful computing power, scientists have gained learn more about power-law distributions, which means that the probability of d−k is proportional to some power of k (usually negative). When the degree distribution of the social network satisfies the power-law distribution, it is:

P(k)∼k−r(1)

His meaning is the probability that the randomly selected node has exactly one edge, which is also equal to the ratio of the number of nodes with degree=k in the network to the total number of network nodes. As long as the social network satisfies a power-law distribution, the network is a scale-free network. The average degree vi of all nodes ki in the network is called the average degree of the network, denoted as ⟨k⟩, that is:

<k>=1N∑i=1Nki(2)

3.2 Network Density

Network density is an indicator used to describe the density of interconnections between nodes in a complex network. The meaning of the network density indicator is the ratio of the actual number of bars in the Internet to the upper limit of the number of bars that can be accommodated. The formula for calculating the density of a complex network is:

d(G)=2LN(N−1)(3)

where N is the number of nodes in the network and L is the actual number of edges in the network. d(G)=1 if the network is fully connected, the range of network density values is [0, 1], and d(G)=2 if the network has no edge relationship. However, a network with a density of 1 basically does not exist in the real world, and the maximum density that can be seen in a real network is 0.5. In general, the network density of large networks is lower than that of small networks, and the density of networks of different sizes cannot be directly compared, so the absolute density equation of the network is used to compare the density. The paper points out that network density reflects the concentration of different words in literary works, and the context of different words can be measured by network density. If the vocabulary has a high degree of concentration and has a logical relationship with other vocabulary, it means that there is a correlation between the two vocabularies. When the correlation between different key words establishes a complex network, the network density between different words is used to evaluate the logical relationship and connection degree in literary works. In terms of style, it can reflect the literary characteristics of different works and the author’s literary expression characteristics.

3.3 Modularity

Community detection, which we also call community discovery, can be used to reveal network aggregation behavior. Community detection is actually a way to group networks, where a “community” can be understood as a group of nodes with the same characteristics. In recent years, community detection technology has developed vigorously, mainly thanks to the modular concept in the field of complex networks, so that the quality of community division of the network can be measured by a clear evaluation index. Community collapse during network failure corresponds to different degrees of modularity: the higher the degree of modularity, the more reasonable the corresponding community collapse; the lower the degree of modularity, the more blurred the community division of the corresponding network. The formula for calculating the modularity of a complex network is as follows:

Q=1/(2m)∑ij⁡(Aij−kikj/(2m))δ(Ci,Cj)(4)

Among them, m is the total number of edges in the network, A is the adjacency matrix corresponding to the network, Aij represents that there is a connecting edge between node i and node j, otherwise it means that there is no connecting edge. ki is the degree of node i, ci is the label that node i belongs to a community, and δ(Ci,Cj)=1, if and only if Ci=Cj.

3.4 Average Path Length

The distance between any two nodes in a social network refers to the number of edges of the shortest path connecting these two nodes, and the average distance in a social network is the average distance between all pairs of nodes in the network. The average shortest path length is also the average network distance and represents the degree of isolation between nodes in a social network. Average path length is one of the three most robust measures of network topology, the other two being clustering coefficient and order distribution. The average path length distinguishes easy-to-negotiate networks from complex and inefficient networks, and the shorter the average path length, the better. However, the average path length is only the most probable path length. The network itself can have very remotely connected nodes and many nodes that are adjacent to each other. The average network distance is the average distance between all pairs of nodes, representing a network. The degree of isolation between nodes, i.e., the size of the network. The average shortest path length L of the network can be defined as follows:

L=2(N(N−1))∑i≠j⁡dij(5)

where dij the number of is edges on the shortest path connecting two nodes i and j in the network, and N is the number of nodes in the network.

3.5 Clustering Index

The clustering coefficient of a social network is used to measure the clustering of network nodes. It refers to the ratio of the number of edges between a node and all its adjacent nodes to the maximum possible number of edges between these adjacent nodes. The clustering coefficient of node i can be defined as:

Ci=2eiki(ki−1)=∑j,m⁡aijaimamjki(ki−1)(6)

Among them, ei represents the clustering coefficient of node i, the value of ci is equal to the number of edges adjacent to it, and

ki(ki−1)/2(7)

Represents the maximum number of connected edges. The average clustering coefficient of a social network refers to the average of the clustering coefficients of all nodes in the network, which is defined:

C=<Ci> =1N∑ieV⁡Ci(8)

where N is the number of network nodes, which represents the aggregation trend of nodes in the network and reflects the local characteristics of the social network.

3.6 Homogamy and Heterogamete

In complex networks, you can determine network matching by checking whether network nodes tend to connect to similar nodes. Network matching can be divided into two types: homotype matching and heterotype matching. A network is said to be homozygous if its nodes tend to connect with similar nodes. Otherwise, the network is called a heterojunction [17]. The degree of network uniformity (or non-uniformity) can be characterized by the uniformity coefficient (also known as the Pearson coefficient) r. r>0 means that the entire network is homozygous, and higher-order nodes tend to connect to higher-order nodes. r<0 indicates that each network is heterozygous. r=0 indicates that there is no correlation in the network structure. Among them, the calculation formula of the network matching coefficient is as follows:

r=∑y,zyz(eyz−mymz)σyσz(9)

where eyz represents the ratio of the number of connected edges between nodes with degree y and nodes with degree y in the network to the total number of connected edges:

my=∑yexy(10)

nz=∑zeyz(11)

σy=E(y2)−E2(y)(12)

σz=E(z2)−E2(z)(13)

If it is r<0, it means that the whole network presents heteroassortment; if r>0, it means that the whole network presents homozygosity; if r=0, it means that there is no correlation in the network structure.

3.7 Key Character Scene Mining

In order to discover the protagonists of “Three Kingdoms”, these protagonists act as transportation hubs, and their presence brings many related characters into a huge social network. Computers can only calculate at high speed. Configure a set of algorithms and programs based on existing algorithms, allowing your computer to quickly calculate and get the results you want. Generally speaking, in the face of social networks, it is natural to ask questions such as “who is the most important node in the network?” These issues can be addressed by the centrality measure, which is the most commonly used measure in quantitative network analysis. Compared to the unweight decay method, the weighted lattice decay method is similar to the use of high-resolution microscopy to observe small structures in larger systems. For simplicity, we will assume that all links have a weight of 1, but the link between nodes A and B has a weight of 3. In a real network, such strong links (three times the capacity of other links) mean that a particular node is more important to the core, but that node is traditionally unweight and not explained in the hierarchy calculated by this method at this point. It is placed in the outermost core of ks=1. However, applying the k-kernel decomposition method to the weighted network highlights its practical importance, since node B is assigned to the outer core ks=2 of the far network core.

Definition 1: Degree ki of node i:

ki=∑jneij(14)

where eij=1 indicates that node i and node j are connected, and eij=0 indicates that node i and node j are not connected.

Definition 2: Weight ωij between nodes:

ωij=ki+kj(15)

Definition 3: The weighted degree ki, of node i:

ki,=[kiα(∑j=1k(i)ωij)β]1α+β(16)

where ki is the degree of node i, and ∑j=1k(i)ωij represents the sum of the weights of the edges connected to node i. In this paper, we only discuss the case of α=β=1, i.e., treat the degree of a node and its weight equally, so:

k,=ki∑jkiωij(17)

Since k,(i) is often a decimal in weighted networks, for convenience, we generally discretize it into the closest integer to the decimal, namely:

k,(i)={⌈k,(i)⌉,otherwise⌊k,(i)⌋,k,(i)−⌊k,(i)⌋<0.5(18)

3.8 Deep Neural Networks

The deep neural network [18] is divided into four layers. The first layer is the input layer; the second and third layers are intermediate computational layers, also known as “hidden layers”; and the fourth layer is the output layer. +1 represents the bias value of each layer, hω,b(x) is the output value, which is a function of weight and bias value. This section introduces the forward pass, activation function, loss function, backward pass and some methods to prevent overfitting of neural networks.

The intermediate variables in the computation and storage from the input layer to the output layer in a neural network are called forward pass, and finally calculating the fitting error through the loss function. In the forward pass, the most important process is the weight calculation of neuron nodes. The mathematical model that exists between the input and output of the l th layer is shown in the following formula:

xjl=∑k⁡ωjklykl−1+bjl(19)

yjl=σ(xjl)(20)

Among them, xjl represents the input of the j-th neuron in the lth layer, yjl represents the output of the j-th neuron in the lth layer, and ωjkl represents the k-th neuron in the l−1th layer pointing to the j-th neuron in the lth layer. The weight of each neuron, bjl represents the offset of the j-th neuron in the first layer, and the activation function is σ.

On the whole, the training process of the forward pass is very simple, and it only needs to select the appropriate activation function and loss function to complete.

If the neural network is composed of a stack of linear convolution operations, it cannot form a complex expression space, and it is difficult to extract high semantic information. The main function of the activation function is to make the neuron output through a nonlinear function. The Sigmoid function, also known as the Logistic function, simulates the neuron characteristics of biology. That is, when the accumulated input signal obtained by the neuron exceeds a certain specified value, the neuron is activated, and then in an excited state, otherwise in an inhibitory state.

σ(x)=11+e−x(21)

The paper takes the Romance of the “Three Kingdoms” as the research object. The work has good representativeness, high literary works and high value of literary works. It has high value of literary characteristics analysis and research. “Romance of the Three Kingdoms” has important research value in literary logic and context vocabulary density. Therefore, in terms of topic selection, Romance of the Three Kingdoms is of high literary research value, one of the four masterpieces, the earliest long-chapter historical novel in China, and represents the highest achievement of ancient historical novels. Through the study of the internal logic of the works of Romance of the Three Kingdoms, we can better find the network density and context relationship between different words in literary works.

4  Analysis of Teaching Object Survey Results

4.1 Description of the Experimental Process

The artificial intelligence technique is used to describe the corresponding key semantic analysis methods of literary works. The vector characterization of semantic concepts is carried out by the artificial intelligence technique, and the semantic matrix is generated by the similarity analysis to realize the analysis of internal logical structure features. The specific steps are as follows:

Step1: Extract the corresponding semantic correlation corpus;

Step2: Calculate the concept and semantic association transfer probability model of semantic relational corpus;

Step3: Design appropriate sequence length for full-text matching, calculate the corresponding transfer probability, and form the semantic association network model;

Step4: Artificial intelligence model trains the formed semantic association network to generate semantic concept vector; Each concept vector is classified.

Step5: Merge the semantic concept vector with the least semantic similarity into a new class;

Step6: Recalculate the new class in Step5 to generate new semantic similarity.

Step7: Calculate Step5 and Step6, and finally generate a class. The algorithm ends.

The similarity of lexical semantics in literary works is measured, and the internal logical relevance semantics in the whole literary works form a larger network.

4.2 The Purpose of Students Learning Chinese Literature

The Chinese Literature course in the Department of Sinology is a compulsory course for third-year students. Special attention was paid to the design of this research project. In addition to why Chinese literature is a compulsory course, why students choose the Department of Chinese Literature.

According to the survey results in Fig. 1, “love Chinese culture” is the most common (28%), followed by “curriculum design learning” (26%) and “love Chinese literature” (22%). 8% of the students chose Chinese literature because it would be helpful for their future work, and 8% chose “Other”. From this point of view, the learning goals of students majoring in Chinese literature are relatively clear. 8% of students chose other reasons, but after collecting the survey, I interviewed them in detail. I found that I did not choose this “without a clear purpose”. However, there are other reasons to study, such as improving your Chinese communication skills, satisfying your interests and your overall Chinese fluency. In addition to the reasons for interest in studying Chinese literature, some learners who study Chinese literature also lay the foundation for internships and future jobs. In some unique work environments, knowing Chinese literature can have a positive impact on communication and learning, and can be of great help to learners. In addition, there are many Chinese companies investing in Vietnam at present, and the status of Chinese in Vietnam is constantly improving and their influence is increasing day by day. If you want to be successful in these Chinese-related jobs, you need not only Chinese language ability, but also Chinese language ability and cultural knowledge. Facts have proved that employment is also an important driving force for students to study Chinese literature.

Figure 1: The purpose of students learning Chinese literature

4.3 Learning Validity of Chinese Literature Courses for Students

This part of the survey is the difference between students before and after taking Chinese literature courses, and aims to compare the results of the two learning stages and understand the effect of students’ learning.

The Fig. 2 above shows that no students were familiar with Chinese literature before class. Only 2% of students had a good understanding of Chinese literature. Forty-eight percent (almost half) of the students chose “fair” (about “somewhat familiar”). 36% of students don’t know much, and the remaining 14% don’t know at all. There are several reasons for this result. In particular, the Chinese literature course is specially set up for the advanced Chinese major of the university, giving students the opportunity to systematically master the basic knowledge of Chinese literature and understand the degree of Chinese literature before going to university. Second, students learn and understand Chinese literature, mainly through the translation of Chinese literature into Vietnamese through textbooks. They may know famous Chinese legends, Tang poems and novels, but there is still a big gap between this knowledge and a deep understanding of Chinese literature. After interviewing some students, they themselves found that their understanding of the Chinese literature they were studying was very vague.

Figure 2: Students’ understanding of Chinese literature before class

The graph above shows that after taking the Chinese literature course, “very good” rose from 0% to 2%, and “understanding” rose from 2% to 23%. The chart dropped from 36% to 23%, “I don’t know” dropped from 14% to 9%, but 41% still chose “General”. This is probably because the “general” option is ambiguous and the boundaries are not well defined.

Comparing the data in Figs. 3 and 4, the author found that students’ understanding of Chinese literature changed before and after learning Chinese literature. As the number of students who do not understand decreases and the number of students who understand increases, in the process of learning and learning experience, there is a tendency to understand Chinese literature. However, only 27% of students had a deep understanding of Chinese literature, less than one-third of the total. Due to the unsatisfactory educational effect, there is an urgent need to adjust the educational design of Chinese literature courses so that students have the opportunity to absorb more knowledge.

Figure 3: Students’ understanding of Chinese literature after class

Figure 4: Comparison of students’ foundations in Chinese literature at the two stages

4.4 Student Learning Methods

The author studies the learning methods chosen by the students, and has a preliminary understanding of the students’ learning style trends in this course. This part of the survey includes listening to the teacher’s explanation in the classroom (listening type), watching textbook explanations (self-study type), participating in various extracurricular activities related to Chinese literature (activity type), and using multimedia. Divided into. Software learning (video type), other group discussions (discussion type). Details are as follows in Table 1.

When it comes to the question of what method learners use to study Chinese literature, the data shows that listening to teachers in class has an absolute advantage, with 94.6% of students doing so. Indicates that you are using. Second, through reading relevant textbooks and textbook explanations, 78.4% of students did not understand how teachers asked questions in class. 30.8% used various multimedia and learning software. Participating in group discussions and various activities related to Chinese literature accounted for 78.4%, with a low occupancy rate of 20.4% and 18.2% respectively. 12.5% of the students chose “other methods”. When the authors conducted interviews, what they called “another way” was to read content mostly related to Chinese literature on the Internet.

4.5 Classroom Evaluation Methods to Promote Deep Learning

The focus of my country’s basic education reform has shifted from “literacy” at the beginning to todays “core literacy”, reflecting different learning requirements for students. Students’ core literacy concerns. One of the current six core competencies is “learning to learn”, which requires students to be willing to learn, to explore suitable learning methods, to know when their learning efficiency is the highest, and what to do if they are not in a good state of study How to use scientific learning strategies to improve your efficiency. Learning requirements have changed, and educational evaluation also needs to conform to the trend of the times. Obviously, the focus of today’s educational evaluation has shifted to how students learn, and classroom evaluation should pay more attention to students’ thinking ability.

We propose the following three methods for deep learning of classroom evaluation methods (1) Visualize learning thinking with the help of various tools (2) Use the Socratic method to exercise students’ thinking ability (3) Use formative evaluation to improve knowledge from knowledge The degree of application of the above three methods by students in turning to thinking process is as follows in Fig. 5.

Figure 5: The degree of application of deep learning classroom evaluation methods

We surveyed a class of students on the classroom evaluation methods for deep learning of Chinese literature. Among the survey data, there were 50 people, 10 people liked to use a variety of tools to strengthen deep learning; 23 people liked to use the Socratic Method: 17 people like to use formative evaluation. According to the survey, it can be seen that more people use the Socratic Method when strengthening classroom evaluation in deep learning, which shows that this method is more widely used.

4.6 Guide Students to Self-Evaluate and Reflect During Deep Learning

In the in-depth study of Chinese literature, not only the correct classroom learning methods, but also the students’ self-evaluation and reflection are very important. Chinese literature is not only something that can be learned by teaching, but also Chinese poetry and famous works require readers to experience themselves from the heart. During our investigation and experiment, we found that most students could not really enter deep learning when learning Chinese literature. We conducted investigation and experiment on readers who could not learn in depth, and found three more effective methods (1) Learning goal guidance: For readers, when reading Chinese literature, it may be a little boring without understanding, but when they have certain learning goals, they will increase their interest and gradually enter deep learning. (2) Sharing of evaluation rules (3) Technical guidance for evaluation. All three methods can increase interest in Chinese literature learning and make it easier to enter deep learning. The three methods are favored and the proportion is shown in the Table 2 below.

This is the result of a survey of 100 students. 32 students liked the learning goal guidance, and 68 students did not like it. There are 76 likes and 24 dislikes in the evaluation rules, and 25 likes and 75 dislikes in the evaluation technical guidance. From this survey, we can see that among the students’ self-evaluation and reflection methods in deep learning, the evaluation rules share the largest number of likes, and this method can be further promoted.

4.7 Students’ Recognition of Deep Learning in Literature Teaching

At the end of the experimental investigation, we conducted a survey on the learning status of the students. The survey data in Fig. 6 shows that 40% of the students in the survey can enter deep learning in the Chinese literature scene, and the learning effect is good, and 30% of the students are learning under the current teaching method. The effect is average, and deep learning cannot be carried out immediately, which delays the learning time; there are also a small number of students who cannot enter the deep learning state during learning, which seriously affects the learning efficiency.

Figure 6: Deep learning recognition for Chinese learning scenarios

5  Conclusion

With the progress of the times, this article introduces the effect of learning Chinese literary scenes to promote students’ learning, as well as the main points of writing Chinese literary scenes. The research on the social relations of characters in “Three Kingdoms” further illustrates the importance of Chinese literary scenes to Chinese literature learning. , using the method of weighted decomposition to analyze the characters in literature. A survey of the society shows that students are more inclined to information-based teaching in their learning methods, and literary scenes also play a crucial role in learning. In the current research process, there are still differences in Chinese recognition efficiency and context logic accuracy in the study of literary works. There are differences in the relevance and network density of different words, especially when the literary works are relatively long, the network density is very complex. It is necessary to analyze different chapters of literary works differently so as to enhance readers’ understanding ability. The next step is to analyze and apply the network density between different literary works. When the lexical density of literary works is within a certain range, the complexity of the works is analyzed.

Funding Statement: The authors received no specific funding for this study.

Data Availability: The experimental data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.

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