Machine Learning-Based Grammar Error Detection Method in English Composition

The detection of grammatical errors in English composition is an important task in the field of NLP. The main purpose of this task is to check out grammatical errors in English sentences and correct them. Grammatical error detection and correction are important applications in the automatic proofreading of English texts and in the field of English learning aids. With the increasing influence of English on a global scale, a huge breakthrough has been made in the task of detecting English grammatical errors. Based on machine learning, this paper designs a new method for detecting grammatical errors in English composition. First, this paper implements a grammatical error detection model based on Seq2Seq. Second, this paper implements a grammatical error detection and correction scheme based on the Transformer model. The Transformer model performs better than most grammar models. Third, this paper realizes the application of the BERT model in grammar error detection and error correction tasks, and the generalization ability of the model has been significantly enhanced. This solves the problem that the forward and backward cannot be merged when the Transformer trains the language model. Fourth, this paper proposes a method of grammatical error detection and correction in English composition based on a hybrid model. According to specific application scenarios, the corresponding neural network model is used for grammatical error correction. Combine the Seq2Seq structure to encode the input sequence and automate feature engineering. Through the combination of traditional model and deep model, the advantages are complemented to realize grammatical error detection and automatic correction.

The Implementation of Grammatical Error Analysis to Improve Students’ Writing Skill on Recount Text for Students Class X MIA At SMA Tri Dharma Kosgoro Dompu

This study is a classroom action research that focuses on the implementation of grammatical error analysis to improve students’ writing skill on recount text for students. The study conducted at SMA Tri Dharma Kosgoro Class X MIA that consisted of 25 students; 15 male and 10 female. Apart from implementing the grammar error analysis to enhance students’ writing skill, the researcher also identify some errors of students’ writing particularly on grammatical error and analyze some factors of these errors. The implementation of this research was in cycle I that consist of eight meetings. Study shows that the implementation of grammatical error analysis can enhance the students’ understanding in writing recount text. This has been shown by the improvement of student’s score. Moreover, the kinds of the students’ grammatical errors could be classified into seven categories namely errors in verb groups, errors in subject and verb agreement, errors in article, errors in pluralization, errors in conjunction, errors in preposition, and errors in pronoun. The identification of these type of grammatical error is paramount due to these could help students understand some components of grammar that students should master to improve their understanding in writing recount text.

“Makam” nasi: Language interference of a Japanese young learner in Indonesia

In acquiring the second language, children will use their first language knowledge as a base in their attempt of using a new language. This phenomenon is called language interference. This study aimed at identifying specific instances of language interference conducted by a bilingual child during her study in an international school. The subject was a 5-year-old Japanese child who was acquiring Indonesian as her second language. This study was a case study using a descriptive qualitative research method. Data collection was done through observation, interview and note-taking. Furthermore, the data in the form of utterances in Indonesian interfered by Japanese were analyzed descriptively. The results showed that the most common type of language interference that occurred was phonological interference (16 examples), followed by lexical error (4 words) and grammatical error (5 sentences). In short, in this case, Japanese phonological interference with Indonesian pronunciation occurred more frequently than lexical error and grammatical error.

A Comprehensive Survey of Grammatical Error Correction

Grammatical error correction (GEC) is an important application aspect of natural language processing techniques, and GEC system is a kind of very important intelligent system that has long been explored both in academic and industrial communities. The past decade has witnessed significant progress achieved in GEC for the sake of increasing popularity of machine learning and deep learning. However, there is not a survey that untangles the large amount of research works and progress in this field. We present the first survey in GEC for a comprehensive retrospective of the literature in this area. We first give the definition of GEC task and introduce the public datasets and data annotation schema. After that, we discuss six kinds of basic approaches, six commonly applied performance boosting techniques for GEC systems, and three data augmentation methods. Since GEC is typically viewed as a sister task of Machine Translation (MT), we put more emphasis on the statistical machine translation (SMT)-based approaches and neural machine translation (NMT)-based approaches for the sake of their importance. Similarly, some performance-boosting techniques are adapted from MT and are successfully combined with GEC systems for enhancement on the final performance. More importantly, after the introduction of the evaluation in GEC, we make an in-depth analysis based on empirical results in aspects of GEC approaches and GEC systems for a clearer pattern of progress in GEC, where error type analysis and system recapitulation are clearly presented. Finally, we discuss five prospective directions for future GEC researches.

Grammar Mistakes in English Written Academic Discourse

Grammar is an important component of written academic discourse. Knowing the grammatical basis of a sentence avoids grammatical errors. The purpose of the study is to reveal the peculiarities of making grammatical errors in English-language written academic discourse. Results of research. As practice shows, most often in English-language written academic discourse the following grammatical errors occur: errors that occur in the process of matching the subject and predicate in a sentence; errors that occur when using the right time in verbs and / or adverbs; errors that occur in the use of articles. The reasons for non-compliance with the requirements for the use of articles are: the use of the noun "author (s)" without the specified article; use of the specified article "the" without grounds; frequent neglect of the inability to use a computable noun in the singular without an article. Regarding the incorrect use of prepositions, in the phrase "practical research is aimed at the system" the preposition "at" should be used instead of the preposition "to". A grammatical error, which consists in using the adjective "own" without a possessive pronoun, occurs in the following phrases: "the search for directions of own activity", "formation of own strategy of activity". Grammatical error related to non-compliance with the requirements for the use of specific and temporal forms of the verb: in today's conditions, in order to solve personal problems, some people use illegal acts. There are cases when in the translation of the English text instead of the noun complex definitions or a number of such definitions are used. An example of incorrect construction of a sentence structure is the expression of a predicate in a sentence in the passive form of a verb. A compound noun is not used in English. In English, the error is quite common when the infinitive is used after the verb "allow". Also a grammatical error is the frequent use of the noun "readiness" in articles of psychological and pedagogical direction. According to the results of the research, the peculiarities of grammatical errors in the English-language written academic discourse are revealed; features of English-language written academic discourse in the context of the analysis of the programs of educational disciplines developed by the leading institutions of higher education of Ukraine are considered; the parameters according to which the evaluation of academic written texts is carried out are revealed; features of English-language academic writing are analyzed. It is noted that as an option to avoid grammatical errors in English written academic discourse, you need to use modern information technology, including programs to check English academic writing for grammatical errors. Based on the results obtained during the study, the prospects for further research are seen in a comprehensive study of the features of English-language academic discourse.