Discussion of Online Teaching Strategies for Teaching Elementary Chinese Characters to Foreigners Based on Error Analyses

The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Chinese language learners.Since online teaching is not limited by time and space,its application is widespread.For beginners in the Chinese language,the Chinese characters are both a priority and a challenge.The“Chinese Character Classification,”also known as the“Six Writings,”is the earliest systematic theory of Chinese character structures,and teaching Chinese characters in categories based on the“Chinese Character Classification”is a method that fits the cognition of beginners.In order to teach Chinese characters in a targeted approach,based on the collection and analysis of the common errors of Chinese characters among beginners,(1)this paper proposes that(a)the intuitive method can be applied to teach pictographic characters,indicative characters,and associative compound characters in online teaching;(b)the inductive-deductive method of“basic characters to new characters”can be applied for the teaching of pictophonetic characters and associative compound characters;(c)the learning of character patterns should be approached in a whole-part-whole process,while importance should be attached to the suggestion of the frequency effect with a view to facilitating the online learning of Chinese characters for beginners.The aim of this paper is to provide some practical implications for the online teaching of Chinese characters to foreigners.

Typos Correction in Overseas Chinese Learning Based on Chinese Character Semantic Knowledge Graph

In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunciation, but do not master the semantics of Chinese characters. If they can understand the meaning of Chinese characters and form knowledge groups of the characters with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph (CCSKG). In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104,187 associated edges were finally established for 6752 Chinese characters. Thanks to the development of deep learning, OpenHowNet releases the core data of HowNet and provides useful APIs for calculating the similarity between two words based on sememes. Therefore our method combines the advantages of data-driven and knowledge-driven. The proposed method treats Chinese sentences as subgraphs of the CCSKG and uses graph algorithms to correct Chinese typos and achieve good results. The experimental results show that compared with keras-bert and pycorrector + ernie, our method reduces the false acceptance rate by 38.28% and improves the recall rate by 40.91% in the field of learning Chinese as a foreign language. The CCSKG can help to promote Chinese overseas communication and international education.

A Comparative Analysis of the Origin and Formation Between Chinese Characters and English Alphabets

This research is based on the framework of social constructivism,utilizing the principle of Human Universals as a methodology to compare the similarities and differences between the ideation and formation methods of Chinese characters and English alphabets.Through comparative analysis of the ideation of English letters(pictogramme)and the origin of Chinese characters,known as the"Six Categories Theory,"we discover their alignment in terms of social,traditional,and cultural aspects.This suggests that different ethnic groups share common features in terms of life experience,learning cognitive development,and thinking habits.This study also finds that the origins of English letters and Chinese characters share similar linguistic features in their methods of constructing letters/characters,such as pictographic,ideographic,and semantic characteristics.Exploring these commonalities contributes to promoting learning and communication between Chinese and English characters.Additionally,by focusing on socio-cultural aspects,traditional customs,and cognitive learning,this study aims to break away from the traditional linguistic research approach that solely focuses on language differences.This provides a broader perspective and richer dimensions for Chinese and English language learning,facilitating the development of cross-linguistic and cross-cultural communication.

Redebate on the Value of Chinese Characters

In order to deepen our rational understanding of Chinese characters,it is necessary to reexamine the value of it today.The reason why Chinese characters can keep vital is that it fits the unique thinking mode and aesthetic standards of the Han People.In the meantime,it intervenes in Chinese ontology by improving the resolution ratio of information trans,and objectively performs the function of the fourth element of language.

Research on Handwritten Chinese Character Recognition Based on BP Neural Network

The application of pattern recognition technology enables us to solve various human-computer interaction problems that were difficult to solve before.Handwritten Chinese character recognition,as a hot research object in image pattern recognition,has many applications in people’s daily life,and more and more scholars are beginning to study off-line handwritten Chinese character recognition.This paper mainly studies the recognition of handwritten Chinese characters by BP(Back Propagation)neural network.Establish a handwritten Chinese character recognition model based on BP neural network,and then verify the accuracy and feasibility of the neural network through GUI(Graphical User Interface)model established by Matlab.This paper mainly includes the following aspects:Firstly,the preprocessing process of handwritten Chinese character recognition in this paper is analyzed.Among them,image preprocessing mainly includes six processes:graying,binarization,smoothing and denoising,character segmentation,histogram equalization and normalization.Secondly,through the comparative selection of feature extraction methods for handwritten Chinese characters,and through the comparative analysis of the results of three different feature extraction methods,the most suitable feature extraction method for this paper is found.Finally,it is the application of BP neural network in handwritten Chinese character recognition.The establishment,training process and parameter selection of BP neural network are described in detail.The simulation software platform chosen in this paper is Matlab,and the sample images are used to train BP neural network to verify the feasibility of Chinese character recognition.Design the GUI interface of human-computer interaction based on Matlab,show the process and results of handwritten Chinese character recognition,and analyze the experimental results.

Hand-Written Chinese Characters Identification Input System

The hand-written Chinese characters reorganization input system, introduced by the Shenbi Electronics, Science and Technology Corporation Ltd. in Guangzhou, is made of advancedoverseas computer identification technology. It consists of an input board and identification software.

About Chinese Characters

The Chinese pictographs for 土 tǔ (earth) are "(?)", "(?)" and "(?)", reflecting the Chinese people of remote antiquity’s understanding of earth. They divided it into two layers, upper and subterranean, and used the "二" in "土" to represent both layers, the central "(?)" representing the plants

About Chinese Characters

Some Chinese characters refer to natural phenomena andsubstances, such as "雨" yu (rain), "云" yun (clouds), "雪" xue (snow),"电" dian (lightning) and "雷" lei (thunder). The original form of "雨"was"(?)," in which"(?)" represents the cloud layer, and"(?)"symbolizes rain drops.

About Chinese Characters

“木” mu (wood) has been variously represented as “■ ”“■,” “木 ” and “木 ” throughout history.“ - ” symbolizes branches, “(?) ” a tree trunk, and “(?)” its roots, all three forming a tree. In China, talent is often likened to a tree. There is an old saying, “It takes ten years to grow a tree, but one hundred years to establish a people.” “木” is a component of constructions such as “木材” mucai(timber) “木工” mu gong(woodworker) and “木匠” mujiang (carpenter).

Studying Chinese Characters in a Web-Based Learning Environment: A Case Study of Swedish University Students

This survey study aims to investigate the perceptions learners have of the character-learning strategies they employ when taking a web-based course in Chinese.The seven Likert-scale statements are included in the questionnaire to examine learners’opinions on the three character-learning strategies that are widely used in traditional campus courses.A total of 65 students who completed the beginner level‘Chinese Characters’web-based course at a university in Sweden completed the survey.The results suggest that students in web-based courses consider these three strategies to be just as helpful and effective as campus students;moreover,the more orthodox strategy-rote learning-is found to be the most popular among distance students.Furthermore,findings of this study provide insight into the limitations and advantages associated with a web-based course,and also the possible effect learners’age and gender may have on learning strategy preferences.

A Novel 6G Scalable Blockchain Clustering-Based Computer Vision Character Detection for Mobile Images

6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques.

The Inheritance and Application of Chinese Reverse Contrast Typeface Style

This paper discusses the inheritance and application of Chinese character reverse contrast typeface style.It begins by analyzing the visual features of Western reverse contrast typeface styles,with a focus on Caslon Italian and French Clarendon,providing a Western perspective reference for subsequent Chinese character reverse contrast typeface style designs.The paper then traces the origins of the Chinese reverse contrast style,from the calligraphy style"Lacquer Script"to the earliest printing type"フワンテール形",exploring the historical background and cultural significance of the Chinese reverse contrast style.In the methodology section of Chinese character reverse contrast typeface style design,the discussion is conducted from two dimensions:inheritance and application.In terms of inheritance,through an in-depth analysis of"Lacquer Script"and"フワンテール形"typeface style,the paper summarizes three basic theories for modern Chinese character reverse contrast typeface style design.In the application section,it examines in detail the two most influential recent typeface styles,"Ribaasu"and"Basic Artistic",outlining three directions of application:extreme horizontal stroke variations,exaggerated contrast,and diverse decorative strokes,showcasing new directions and possibilities for Chinese character reverse contrast typeface style design.This paper not only reviews the developmental history of the Chinese character reverse contrast typeface style but also analyzes the design methodology of Chinese character reverse contrast typeface style through specific case studies.

Major achievements in relation to dyslexia in Chinese characters

Objective To review the major achievements in dyslexia in Chinese characters, hoping to give some clues for future studies. Data sources Both Chinese and English language literature search using PUBMED, and original articles published in main Chinese and international journals. Study selection After reviewing the literature, 54 articles were selected that specifically addressed the stated purpose. Results The results of studies about the subtypes, cerebral basis, reading processing model, event-related potential （ERP） and saccadic features between English and Chinese dyslexia are different. Conclusions in the last ten years, great progress has been made in the study of dyslexia in Chinese characters. However, there are still many problems and shortcomings which need to be investigated.

Parallel compact integration in handwritten Chinese character recognition

In this paper, a new parallel compact integration scheme based on multi-layer perceptron (MLP) networks is proposed to solve handwritten Chinese character recognition (HCCR) problems. The idea of metasynthesis is applied to HCCR, and compact MLP network classifier is defined. Human intelligence and computer capabilities are combined together effectively through a procedure of two-step supervised learning. Compared with previous integration schemes, this scheme is characterized with parallel compact structure and better performance. It provides a promising way for applying MLP to large vocabulary classification.

A Form-Correcting System of Chinese Characters Using a Model of Correcting Procedures of Calligraphists

A support system for form-correction of Chinese characters is developedbased upon a generation model SAM, and its feasibility is evaluated. SAMis excelIent as a model for generating Chinese characters, but it is difficult todetermine appropriate parameters because the use of calligraphic knowledge isneeded. By noticing that calligraphic knowledge of calligraphists is includedin their corrective actions, we adopt a strategy to acquire calligraphic knowl-edge by monitoring, recording and analyzing corrective actions of calligraphists,and try to realize an environment under which calligraphists can easily makecorrections to character forms and which can record corrective actions of cal-ligraphists without interfering with them. In this paper, we first construct amodel of correcting procedurcs of calligraphists, which is composed of typicalcorrecting procedures that are acquired by extensively observing their correc-tive actions and interviewing them, and develop a form-correcting system forbrush-written Chinese characters by using the model. Secondly, through actualcorrecting experiments, we demonstrate that parameters within SAM can beeasily corrected at the level of character patterns by our system, and show thatit is effective and easy for calligraphists to be used by evaluating effectivenessof the correcting model, sufficiency of its functions and execution speed.

A Form Evaluation System and Its Data Structure for Brush-Written Chinese Characters

A form evaluation system for brush-written Chinese characters is developed.Calligraphic knowledge used in the system is represented in the form of ruleswith the help of a data structure proposed in this paper. Reflecting the spe-cific hierarchical relations among radicals and strokes of Chinese characters,the proposed data structure is based upon a character model that can generatebrush-written Chinese characters on a computer. Through evaluation experi-ments using the developed system, it is shown that representation of calligraphicknowledge and form evaluation of Chinese characters can be smoothly realizedif the data structure is utilized.

A New Linguistic Decoding Method for Online Handwritten Chinese Character Recognition

This paper presents a new linguistic decoding method for online handwritten Chinese character recognition. The method employs a hybrid language model which combines N-gram and linguistic rules by rule quantification technique. The linguistic decoding algorithm consists of three stages: word lattice construction, the optimal sentence hypothesis search and self-adaptive learning mechanism. The technique has been applied to palmtop computer's online handwritten Chinese character recognition. Samples containing millions of characters were used to test the linguistic decoder. In the open experiment, accuracy rate up to 92% is achieved, and the error rate is reduced by 68%.

A Systematic Review of the Research on Chinese Character Teaching and Learning

Using a thematic analysis methodology,this paper attempts a critical review of published articles on Chinese character teaching and learning in and outside China between 2005 and 2019,highlighting contributions scholars made to the current literature as well as identifying gaps in the research.The analysis reveals that there is a rather large gap in the use of research methodologies between the two sets of articles,with publications in China predominantly adopting non-empirical approaches while most articles published outside China are empirical.Besides,the use of computer-assisted language learning(CALL)in character teaching and learning seems to be a key research topic outside China,while exploring new pedagogical ideas and strategies attracts more interest among scholars in China.The paper concludes with suggestions for future research directions and a call for more diverse research paradigms and mixed-method perspectives.