chinese essay checker

chinese essay checker

Developing an Effective Chinese Essay Checker: A Comprehensive Guide

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1. Introduction to Chinese Essay Checkers

Most students often ignore details in the writing process of an essay due to time constraints or they have limited vocabulary; as a result, most students make a lot of grammar mistakes in Chinese essays. However, the school education system in Asia has a big problem: that is the serious reliance on paper to submit homework and be assembled and corrected by the teachers. After checking essays, the teachers need to instruct students and teachers mostly focus classes on how to acquire vibrant vocabulary and sentence patterns but pay less attention to progress in grammar skills. Although the teachers correct a lot of grammar errors with the help of some marking systems and checklists, it is difficult to provide students with an instant and accurate solution. At present, most teachers cannot efficiently and quickly handle the excessive volume of papers submitted by students in a short period of time and are willing to search for solutions by using technologies.

Schoolwork is an essential part of a student’s life. Many students struggle in Chinese essays, particularly in grammar. However, with the use of advanced technology, students can check essays effectively and quickly. This study first reviews some existing essay checkers, with three working principles and critical technologies: (1) grammar-based essay checkers; (2) statistics-based essay checkers; (3) mixed rule- and statistics-based essay checkers, and some recent technologies, namely deep learning and transformer, usually adopted by these essay checkers. Then, the study illustrates the traditional Chinese essay checking procedure with natural language processing methods. After that, the study applies the Grammar-rules-QEC, a prototype for checking the grammar of Chinese essays. In order to enhance the portability of the Grammarules-QEC, the study employs a different method that is fixed-rules-based and machine learning-statistics-based grammatical checker, namely the Chinese Grammar Error Correction, Google Docs, Grammarly, Microsoft Word, Protrek, Viper, with their checking principles or working mechanisms or user interface platforms. Finally, we propose how the functions of the mentioned essay checkers in different formats can be developed.

2. Key Features and Functions of Chinese Essay Checkers

The key features and functions vary among different tools. As we discuss in this guide, there are plenty of works proposed in the recent literature, employing various techniques to fulfill different functions. Since quality and precision of the function are vital to developing an effective Chinese essay checker, in this section, a comprehensive mapping from the main functions to the technical aspect will be applied to discuss and describe the details of the key functions. Various operations may be required to verify the validity of any writing. In this section, we have highlighted ten essential key features of an effective essay checker in Section 2.1, and listed the technical aspects that should be considered for developing or incorporating such functions into an essay checker. In Section 2.2, we discuss the potential impacts on end users for lack of the fine-tuned criteria in the tool.

3. Challenges and Limitations in Developing Chinese Essay Checkers

Machine learning solutions are designed for building an assessment engine with a large number of artifact features have been studied extensively. Rich sets of features including style and content artifacts are not taken into account in most of the existing essay-checking approaches. Almost all existing evaluation methods tend to address focus, syntax, or organization aspects, while lack of solutions for handling sentence integrity issues. In other words, essay assessments using prior work are able to satisfy simplistic criteria efficiently but may fall short when more subtle criteria are required. Due to fewer correction categories defined for easy handling, checking results based on existing dimensions provide insufficient guidance during revision. It is easy to forget that an essay is a group of sentences.

Developing a Chinese essay checker is more challenging than developing an English one due to having character-based input, which increases the size of the input space remarkably. With no standard corpus available in the Chinese essay-checking task, existing results differ tremendously. If such useful resources are constructed and employed properly to count down the issue caused by the gigantic size of the input space, the performance of Chinese essay checkers is expected to boost up. It is known that the demand for computer-assisted language activities has been increasing in recent years. Unlike other domains, the high requirement for both the computational time and resource materials affects its development.

4. Best Practices for Using Chinese Essay Checkers

No tool is perfect; so what theoretical counseling may rely on is what inferences technology may offer with respect to user performance. First, teachers could use Chinese essay checkers to focus on a few highlighted areas, such as cohesion, coherence, topic development, and mechanical errors. Then teachers supplement with feedback that gives positive constructive manners. Second, rather than completely relying on the tools for error diagnosis, teachers could use the errors as clues and engage the students in a more in-depth error correction or language learning activity, such as explaining the possible causes behind the errors, discussing why one error was flagged, and then advising on how to analyze and identify similar errors, and collaboratively identify improvement strategies.

Using Chinese essay checkers can be a time-saving way to scale up Chinese teachers’ activities, making learning gains less vulnerable to limited resources. Here are a few best practices summarized from both literature review and the author’s practical experiences. Teachers may take these as reference points and adjust their use according to the unique learning priorities in their schools.

5. Future Trends and Innovations in Chinese Essay Checking Technology

Too many assessment features may lead to overfitting to specific data. In addition, the consistency of two contradictory scores is the most important requirement of the evaluation system. As there is some potential coherence of the quality features, some sentence-level or discourse-level features may not be assessed independently. Finally, to help learners to achieve correct expression while learning to write essays, the feedback of handwritten composition checking on the electronic dictionary should be given in real time. Little work has been done in this direction.

While the academic community is paying increasing attention to this field, many challenges are presented by the Chinese language and essay checking. As Chinese writing requires a better sense of balance or harmony than English writing, the Chinese language has more criteria and performs more subtle checks than English essay checking. The research of the criteria is the most important and difficult work. Despite many studies on spelling errors, poor word choice, and syntax errors in the Chinese language, further research on supporting structures and enlightening on poor organization and inadequate reasoning in Chinese language writing is needed.

First, tasks such as text classification and automatic summary are closely related to essay checking and can benefit from each other. Far more complex models based on the recent successes in the field can increase the performance of the essay checking system by incorporating more sophisticated features. Additionally, large-scale annotation and data collection for this domain would be extremely beneficial for the field.

In the past two decades, Chinese essay checking technology has seen unprecedented development. Many researchers and developers have devoted significant resources and effort to developing essay checking systems such as WAE and ChineseOpenNLP, as have commercial companies such as Writinglab and EssayJack. We believe this is only the beginning.

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