ONLINE GRAMMAR CHECKERS VERSUS SELF-EDITING: AN INVESTIGATION OF ERROR CORRECTION RATES AND WRITING QUALITY

Background and Purpose: In order to compete with native speakers, EFL and ESL students are under more pressure to produce native-like academic papers. This has led to more reliance on online grammar checkers, but these can be ineffective with regards to identifying and giving feedback on particular grammatical forms, phrasing and issues relating to style. Language learners may not be effectively correcting these errors. Hence, this study aims to examine the effectiveness of one online grammar checker, grammarly.com, with that of self-editing. Methodology: This case study employed a descriptive approach to data analysis. 199 essays were collected from undergraduates at four universities in Kyushu, dated from April, 2019 to January, 2020. 99 essays were proofed by an online grammar checker, while 100 essays were self-edited. The English proficiency level of the participants was at the lower to intermediate range (i.e., TOEIC 300 to a TOEIC 500). The online grammar checker Grammarly was utilized by all participants to minimize issues relating to feedback. In the analysis of data, the complexity, accuracy, and fluency (CAF) of the essays was assessed in order to examine the significant changes between the first and other drafts, and the types of errors produced. Findings: Results showed that there were no significant differences found in terms of the methods of editing, although the participants who employed online grammar checkers had better results. It was also shown that there were no significant differences in terms of syntactical complexity with either method of editing. There were fewer errors committed by the participants who self-edited, but there were no significant differences in the edited drafts with regards to errors/100 ratios, error-free clauses, and error-free clause ratios. The study showed marginal differences between the two methods of proofing but indicated that online tools can be useful for identifying certain grammatical errors. Contributions: This paper argues that educators need to work more with EFL learners on the editorial and proofing process, but online grammar checkers may be a useful pedagogical tool to help low-proficient L2 learners. Keywords: Writing quality, editing, online grammar checkers, proofing, syntactical complexity. Cite as: Long, R. (2022). Online grammar checkers versus self-editing: An investigation of error correction rates and writing quality. Journal of Nusantara Studies, 7(1), 441-458. http://dx.doi.org/10.24200/jonus.vol7iss1pp441-458

Exploring the Writing Challenges Faced by M.Phil. and Ph.D. Scholars: A Case

Academic writing plays a pivotal role in developing research proposals. The present study aimed to explore the grammatical errors that M.Phil/PhDs scholars commit in academic writing. The present study employed a qualitative case study designed to explore the challenges in the English language faced by the M.Phil and PhDs scholars. The 20 Ph.D. and 36 M.Phil scholars were selected by busing purposive sampling technique. Data were collected by using two self-developed semi-structured interviews protocol. Thematic analysis approach was employed for data analysis. The findings revealed that all the participants reported that correct use of tenses was a big hurdle that entailed the other grammatical mistakes and reduced the report quality because all the lexical aspects are linked with these mechanics. The study recommended that English language courses be offered to postgraduate, M. Phil and Ph.D. scholars to learn the technical aspects of the language and provide students with online interactive programming.

Inaccuracy within Online Journalism in Indonesia

<em><span>Many scholars have conducted studies on the accuracy of the news media, such as newspaper, television, and magazine, but not online media. In fact, online media is a significant news media in the moment, especially in Indonesia. Online press companies are even the largest press companies in Indonesia compared to newspapers, radio, and television. Therefore, this study is conducted to measure the inaccuracies that occur in news in online news media. Researchers examined 63 online journalistic media that have been administratively and factually verified by the ‘Dewan Pers’ (Press Council). It uses a content analysis method by coding the headlines in Indonesian online journalistic media. This study finds online mass media categories based on the theme segmentation, namely: 1) general, 2) economics, technology, and business, 3) sports, 4) politics, law, and crime, 5) lifestyle and entertainment, and 6) regional. The results of this study indicate that the inaccuracy of news in Indonesian online media is high. Media with economics, technology, and business most often make grammatical errors. This study also finds that speed does not only has an impact on grammatical inaccuracies, but also on unbalanced news reporting, where the imbalance in Indonesian online media news itself is very high.</span></em>

Internet News Headlines: Ontological and Orthological Aspects

The author presents the results of a multidimensional analysis of Internet news headlines based on the headings of the Yandex news aggregator. The issue of the text status of news headlines is considered. When solving this problem, special attention is paid to the formation of correlative paradigms of headings, united by a common denotative meaning. Methods of semantic interaction of heading paradigms based on different types of topic-rhematic deployment are described. It is proved that the paradigms of headings, complementing each other in informational and pragmatic aspects, form the discourse of Internet headings. It is concluded that this way of functioning of headlines enhances their semantic and visual autonomy from the news text, which allows us to consider Internet news headlines as minitext. The frequency methods of lexico-syntactic transformations of the original headings are analyzed, on the basis of which the constituents of paradigms are formed. At the same time, attention is focused on the orthological aspect of Internet headers. The author comes to the conclusion that the focus on the variability and efficiency of headings leads not only to the appearance of lexical and grammatical errors, but also to their replication and consolidation in the mind of the addressee as a result of changes in the structure of cognitive models.

Strategies to Overcome Interlanguage Fossilization by Using Flipped Learning in Pandemic Era

Learning foreign language means learn all aspects of the language, such as language features, sociolinguistics, psycholinguistics, grammar, structure and culture. The different of these aspects from target language and native language will create different form output both of them, that known as the interlanguage. Interlanguage fossilization is common in the process of foreign language learning, which causes foreign language learners not make progress any more. Based on teaching learning process condition, researcher applied the strategies to overcome interlanguage fossilization by using flipped learning in pandemic era. This research focuses on grammatical errors. This study belongs to quantitative method. The study conducted in the pandemic era when the teaching learning process of the students in Padang applied in two shifts both face to face learning and online learning. The research conducted in 3 weeks of learning process. each week consists of two meetings by applying flipped learning Approach. The result of this study showed that there was positive effect of using strategies in flipped learning to overcome their fossilization of target language. The result indicates that almost all of the learners’ grammatical errors could be eliminated step by step and need more process and times.

The Construction of Machine Translation Model and Its Application in English Grammar Error Detection

In order to solve the problems of low accuracy, recall rate, and F1 value of traditional English grammar error detection methods, a new machine translation model is constructed and applied to English grammar error detection. In the encoder-decoder framework, the machine translation model is constructed through the steps of word vector generation, encoder language model construction, decoder language model construction, word alignment, output module, and so on. On this basis, the machine translation model is trained to detect English grammatical errors through dependency analysis and alternative word generation. Experimental results show that the accuracy, recall rate, and F1 value of the proposed method are higher than those of the experimental comparison method for detecting English grammatical errors such as articles, prepositions, nouns, verbs, and subject-verb agreement, indicating that the proposed method is of high practical value.

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.

Communication Strategies Used by Papuan EFL Students

<p class="AbstractText">To fill the absence of research in the context of communication strategies used by Papuan EFL students, this research would present and fill this knowledge gap. This research aimed to determine the types and their reasons of communication strategies used by Papuan EFL students. It applied qualitative study. The researcher used observation and interview as the research instruments. It was found that Papuan EFL employed fillers, code-switching, self-repetition, self-repair, asking for clarification, asking for confirmation, and direct appeal for help. The reasons why Papuan EFL students do those communication strategies because of thinking time, anxiety, nervousness, doubt, worriedness, hesitation, lack of knowledge, lack of vocabulary, grammatical errors, and self-confidence.</p>

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.