Spelling Mistakes Research Articles

STRATEGIES FOR PRAGMATIC IMPROVEMENT IN THE TRANSLATION OF PUBLIC SIGNS AT ZHAOQING XINGHU NATIONAL PARK FROM THE PERSPECTIVE OF HIGH-QUALITY DEVELOPMENT

As the only national 5A-level tourist attraction in Zhaoqing, the Xinghu National Park serves as a crucial window for cultural dissemination and city branding. This paper systematically analyzes the current state of Chinese-English translations of public signs at this scenic area, identifying issues such as spelling and grammar mistakes, and overly literal translations. These errors reduce the effectiveness of information transmission and weaken cross-cultural communication. To address this, based on the concept of high-quality development, this paper proposes a multi-layered strategy involving translation standardization, cross-cultural adaptation review, and professional training, aiming to enhance the international image and cultural outreach of the Xinghu National Park, and to serve as a reference for other tourist sites. KEYWORDS: Zhaoqing Xinghu National Park, Chinese-English translation, pragmatic failure, cross-cultural communication, translation norms

Students' Difficulties in Spelling Vowels: Case Study

This paper aims to reflect the difficulties students have in spelling the vowels of the Albanian language. The unified spelling of a language, in our case the Albanian language, is an expression of the crystallization of the national literary norm in all the main links of the phonetic, grammatical, word-forming and lexical structure. It reflects the current state and general trends of the development of our literary language. Given that the basic principle of Albanian spelling is the phonetic principle and seeing the constant spelling errors of Albanian speakers in the use of vowels, we conducted research with primary school students in rural areas, to see the most common errors frequency in vowel spelling. Our goal was to see the differences between students whose parents have primary education and those with higher education. Through this research we have also seen the reasons that lead to the impossibility of writing correctly and how the vowels should be written in different words. Our hypothesis is that children of parents with primary education make more mistakes in vowel spelling than children of parents with high education. We have conducted the research through the theoretical, comparative method, distribution of questionnaires and data analysis. The results have shown that parents' education does not affect children's knowledge of spelling. Received: 27 August 2024 / Accepted: 28 October 2024 / Published: 05 November 2024

Pemanfaatan Natural Language Processing Untuk Pengecekan Ejaan Sesuai KBBI

Spelling mistakes in the Indonesian language often occur due to lack of knowledge of spelling rules, the influence of foreign languages, and the use of informal language. This research aims to develop a Natural Language Processing (NLP) based spelling checking system that refers to the Dictionary of Indonesian Language (KBBI). The system is expected to be able to perform automatic spelling verification and correction with high accuracy. The method used is qualitative with an analytic descriptive approach, involving data collection from the KBBI and processing using Python. The research stages include collection, data cleaning, tokenization, and data analysis. The system was trained using a large Indonesian text dataset. The results showed the system achieved a spelling check accuracy of 81.64%, more accurate, easy to use, flexible, and adaptive than conventional systems. The number of words in the text affects the checking time, with longer text taking longer.

APCalign: an R package workflow and app for aligning and updating flora names to the Australian Plant Census

Here we present ‘APCalign’, an R package and accompanying browser-sourced application to align and update scientific names for Australian vascular plants to the most likely currently accepted name in the Australian Plant Census (APC) or a name in the Australian Plant Names Index (APNI). Scientific names are the label assigned to unique taxon concepts by the scientific community, but this common terminology is most useful if a taxon concept is consistently referred to by the same name. These links can be broken because of either spelling mistakes or taxonomic changes. Automated tools are required to resolve taxon lists, aligning and updating long lists of possibly erroneous scientific names to the most likely currently accepted names. It is essential that tools specific to the APC/APNI be developed, because these lists specify an endorsed national-level nomenclature used in government legislation and include the uniquely Australian concept of phrase names, absent in global taxonomic datasets. To align input names to names within the APC or APNI, ‘APCalign’ works progressively through a sequence of checks that combine different permutations of the input name, exact versus fuzzy matches, matches that consider the entire name input versus a subset of words, and character strings that indicate a name can be resolved only to a genus or family. The aligned names are then, when possible, updated to a currently accepted taxon concept within the APC. This package should facilitate all research outputs that require diverse scientific name lists to be merged or outdated lists to be updated.

Using of NLP Methods in Intelligent Educational Systems

For the effective organisation of educational processes supported by relevant intelligent learning systems, it is important to choose the right technologies that would ensure individualisation of learning, adequate perception of learning content, and the so-called “understanding” of texts in Ukrainian provided by students (description of the solution to a task, answers provided in their own words, not selected from the test answer options, questions to the system, etc.), prototyping, constant iteration during natural language text recognition and processing, and maximum reliability and efficiency of learning processes. The purpose of the article is to study and analyse various methods of natural language processing, and the concept of NLP, and to consider common problems and prospects for developing a software product for processing Ukrainian-language text in online courses that support intelligent learning systems based on it. The research methods are the main methodological approaches and technological tools for analysing natural language texts in intelligent educational systems and developing a system for supporting NLP (Natural Language Processing) technology in the linguistic analysis of texts in Ukrainian. Such methods include, in particular: systemic and comparative analyses to identify the features of intelligence and information (with elements of intellectualisation) systems; the method of expert evaluation, which involves the study of literary sources and information resources, interviews and surveys of experts, as well as the processes of developing and testing intelligent and information systems. The novelty of the study is the analysis of modern technologies for the development of online educational process support systems through the organisation of processes of perception of information provided by students in natural language, the results of which can be used in the development of their software product to support the educational process in Ukrainian, ensuring the improvement of learning efficiency through the use of NLP technology in the process of studying the relevant academic content. Conclusions. The paper analyses modern NLP methods. The analysis has led to the selection of tokenisation, normalisation, stemming and lemmatisation methods for use in intelligent learning systems in the linguistic analysis of the so-called “free” communication in the natural (Ukrainian) language of students in the process of studying the educational content of online courses. During the tokenisation of Ukrainian-language texts, we solved such problems as eliminating so-called “merged” tokens, correcting spelling mistakes, identifying common prefixes in compound words and their impact on the semantics of the corresponding lexemes, identifying common prefixes in abbreviations, and bringing words to their normal form. Lemmatisation is especially important for the Ukrainian language (with its large number of cases of nouns, adjectives, word forms, etc.) and it requires the use of specially compiled dictionaries of the subject area under consideration. In these dictionaries, word forms are presented in the forms of lemmas (i.e., nouns are presented in the nominative case).

Membedah Kesalahan Bahasa Indonesia Dalam Caption Dan Komentar di Platform Media Sosial Instagram

This study delves into the usage of Indonesian language on the social media platform Instagram, with a particular focus on identifying and analyzing the prevalent errors and misunderstandings that arise. Employing a descriptive qualitative research methodology, the study examines user-generated comments and captions. The findings reveal that users frequently commit spelling mistakes on basic words, including capitalization, punctuation, and word separation. Additionally, inappropriate word choices and grammatical errors are common among users. Furthermore, the mixing of Indonesian with slang, English, and local dialects contributes to confusion and communication barriers. Overall, the study highlights the suboptimal usage of Indonesian on Instagram, emphasizing the need for enhanced language proficiency and effective communication strategies.

Complexity, Accuracy and Fluency (CAF) oF EFL College Learners’ Writing : The CLIL and Non-CLIL Classes

This study was designed to compare the complexity, accuracy, and fluency of EFL written text in CLIL and Non-CLIL classes. The study enrolled two groups of undergraduate students from the State University of Malang, Indonesia: an experimental CLIL class (N = 50 students; 22 males and 28 females) and a non-CLIL as control class (N = 50 students; 19 males and 31 females). Students' essays were evaluated quantitatively using some aspects of linguistic proficiency, such as complexity, accuracy, and fluency. The errors were classified as syntactic, morphological, lexical, lexicogram, spelling, and punctuation mistakes. The findings indicated that both CLIL and non-CLIL methods produced comparable complexity, accuracy, fluency, syntactic, morphological, lexicogram, and spelling scores in two groups of students. Meanwhile, for complexity and lexical values, the CLIL and Non-CLIL methods produced significantly different average scores, with the application of the non-CLIL method being higher. On the punctuation variable, the CLIL method can significantly improve the assessment. Several possible explanations for the increase in complexity, accuracy, and fluency include a preference for the English standard, the course's assessment criteria, and practice effects. The findings of this study also provide additional pedagogical implications.

Half-baked essays: the embedded use of writing exemplars to encourage active learning for radiography students

This paper discusses the implementation of exemplar essays within an undergraduate first-year diagnostic radiography module to encourage active learning and the development of academic literacies. Nine essays (~400 words each) were provided over six sessions, using lecturer-guided discussion to explore the academic virtues and pitfalls demonstrated alongside assessment criteria. Exemplars were based upon a fictitious baking profession to illicit student interest and eliminate the risk of imitation or plagiarism. The quality of essays varied, with overt examples of common mistakes in spelling, essay structure and selection of appropriate literature. Upon completion of the sessions, and prior to summative assessment, students were surveyed with regard to their opinion of the teaching intervention. Feedback was obtained from 65% of the cohort (n=31/48), who reported an improvement in essay writing confidence. Students found the marking of the essays in class useful and the baking analogy was well received. Not all students found the classroom activities engaging though, with some wishing greater interactivity due to boredom and repetition. Furthermore, there was a slight reduction in pass rates and average marks across the cohort when compared to the previous module delivery. Nevertheless, there was a substantial increase in students attaining marks of 80% or more. This study highlights exemplar essays as a low-tech, low-cost option to increase assessment literacy but accepts the wide diversity in student learning preferences and experience. The efficacy of exemplar essays cannot be guaranteed, and teaching staff must be cognisant of individual student learning needs.

Autocorrect of a Word in a Sentence using Text Feature Analysis with Natural Language Processing

In text editing software, auto-correct is a crucial tool that helps users correct spelling mistakes and improve the grammatical accuracy of their written content. The unique method for auto-correction proposed in this paper combines test feature analysis with natural language processing (NLP). The algorithm makes use of NLP techniques to examine the original sentence's context and spot any potential mistakes. After that, it runs a number of tests to produce correction suggestions for the word in question. This strategy is predicated on the idea that test characteristics like word frequency, word length, and part of speech can be utilized to distinguish between appropriate and inappropriate word patterns. The efficiency of the suggested strategy in correctly correcting words inside a phrase is shown by experimental findings.

Investigating the Effects of Music and Temperature Changes on Heart Function and Human Error

Introduction: Exposure to music and temperature variations can influence physiological state and impact human error. This study aims to investigate the combined and independent effects of music and temperature changes on heart rate (HR) and human error.
 Materials and Methods: This interventional study was conducted on 14 participants (7 men and 7 women) under controlled conditions in 2018. The subjects experienced four types of music (Rock, Rap, Pop, and Iranian traditional music) at the noise pressure level of 75 dB, along with temperatures of 20, 25, and 30 °C independently and in combination, within an acoustic room with controlled temperature conditions. HR and human error rate were measured using a HR meter and a researcher-made text with spelling mistakes, respectively.
 Results: Using SPSS 19, data analysis revealed that exposure to traditional Iranian and rock music in temperatures deviating by 5 °C from 25 °C was associated with increased errors in detecting spelling mistakes (p < 0.05). Interestingly, traditional and rock music did not significantly affect HR across temperatures of 20, 25, and 30 °C (p > 0.05).
 Conclusion: Listening to traditional Iranian and rock music in conditions with approximately 5 °C cooler or warmer than room temperature can have a positive and constructive effect on HR and reduce human error. The use of this type of music has potential implications for optimizing environmental conditions, especially in workplaces where such factors are critical.

Challenges and computer-aided reading strategies in vocabulary enhancement

Early literacy development depends significantly on developing a vocabulary, and computer-aided reading techniques have the potential to improve this process. To maximize their efficacy, grade 1 teachers might encounter particular difficulties when implementing these tactics into their lesson plans. In light of this, the goal of this study is to determine the difficulties that Grade 1 instructors encounter when instructing vocabulary and investigate the possibility of using computer-aided reading procedures to help with these difficulties. The primary goal of the qualitative research for this study was to interview grade 1 teachers about their experiences and anecdotes. Six professional teachers—four from private and four from public schools— participated in the study's interviews. According to the results, the most challenges that first-grade teachers encounter when trying to expand their students' vocabulary include the transition from their native tongue to English, word pronunciation and spelling mistakes, and students' reluctance to learn new vocabulary. The twenty experienced educators use a range of techniques to help students with their vocabulary. These include using the Marungko Method in a multimedia presentation to introduce letter names and sounds, watching phonics and phonemic movies, pronouncing words using YouTube videos and audio-visual presentations, interactive slides, digital flashcards, recordings of the alphabet, and rereading while playing interactive language games to help with retention. The study's outcomes will contribute to the existing literature on vocabulary instruction and computer-aided learning, highlighting the potential of technology in addressing the challenges faced by Grade 1 teachers.

UTAPIS Indonesian Word Error Detection Application: Design and Development

People misspell and incorrectly write Indonesian words without even recognizing it. Poor and incorrect language proficiency is a common cause of word spelling mistakes. Since PT Tribun Digital Online publishes between 600 and 700 articles a day, the U-Tapis website might be of great assistance to journalists in identifying grammatical problems. Three separate cities—Jakarta, Makassar, and Solo—have participated in the testing of the U-tapis website. @ Tribun Digital Online, PT. This department is in charge of using the Flask framework to create the U-tapis website design. This study develops software or applications that are comparatively brief, succinct, and quick using the RAD (Rapid Application Development) technique. In addition to system development methods. The implementation of this method uses the U-tapis Sentence Syntax Error Detection algorithm which functions to detect an algorithm comparing two pieces of data, calculated using a formula called the Jaccard Index to check spelling errors in words. UAT test results produce all the features according to the wishes of the company owner based on the problems faced.

When a song becomes an unusual french grammar test

This work has a set of tasks united by the topic “A grammar test”. The purpose of these tasks is to do a French grammar test by students at the B2 level, who have to correct different errors in an authentic text. The context and the tasks for checking students’ orthographic and grammatical competences, as well as for practicing receptive and productive skills, are based on the lyrics of the song “C’est la faute à l’amour”. The lyrics contain typical spelling and grammar mistakes which are often made by French native speakers. The proposed set of tasks will allow students to test their orthographic and grammar skills and review a significant number of fundamental French rules.

Some Pronunciation-Induced Spelling Errors in Cameroon English

This paper focuses on the spelling mistakes that are idiosyncratically imposed by phonological variation in Cameroon English (henceforth CamE). The paper seeks to establish that, apart from graphology, there is a pronunciation spelling phenomenon where variation in CamE pronunciation conditions writers of English in Cameroon to spell a good number of words differently from what is obtained in Standard British English (Henceforth SBE) and Standard American English (Henceforth SAE). Data for the paper were collected through observation and two spelling tests, a diction spelling test and a multiple-choice spelling test, from sixty junior secondary school students (thirty male and thirty female from age 9 to 17) in GBHS Atiela – Bamenda. The students were from four different forms; Forms 1, 2, 3, 4 and they were chosen because they had not memorised several spellings like students of the upper classes. The school was chosen because it is in the metropolis and has students from diverse backgrounds. The data were analysed qualitatively using Generative Phonology as the theory. The findings reveal that CamE speakers of the secondary level, teachers and students, deviate from native English spelling (SBE and SAE) norms, unconsciously, through phonological processes as substitution, devoicing, analogy, epenthesis, metathesis and CamE-styled homophony. I recommend that a standard variety of pronunciation be adopted and that emphasis be laid on teaching pronunciation in order to curb spelling mistakes since the former is a major generator of the latter and / or a dictionary of CamE should adopt general acceptable spellings that related to Cameroon-derived names and other lexical items denoting cultural uniqueness.

ARABIC SOFT SPELLING CORRECTION WITH T5

Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error injection rate, with a maximum sequence length of 300 characters.

A Determination Regarding the Application of Station Rotation Online Teaching Model in Foreign Language Teaching

Blended learning is currently attracting the interest of many researchers and educators around the world as a new model for organizing the educational process in higher education institutions. Blended learning is understood as a phenomenon where face-to-face learning and teaching experiences are combined with online tasks and activities. This study investigates the effectiveness of online instruction station rotation model (SRM) of blended learning implemented for A2-level students learning Turkish as a foreign language (TFL). The study conducted a mixed method approach where qualitative data was quantified within the usage of ratio analysis. Data was collected from listening and reading skill activities executed by students (n=13) at the online instruction station model and MAXQDA 2020 research program was used to analise each student’s and all students’ performances. As a result it was determined that most of the students gave better answers in true/false and matching activities compared to filling the gap activity. Besides there were found more spelling mistakes in dictation and during expression students apparently have thought in their mother tongue. According to the challenges which students faced during the implementation, this study ends with some implications for future researches to overcome issues of the online instruction model.

The Impact of Adopting an Eclectic Spelling Program on Minimizing KAU Engineering Students’ Spelling Mistakes

The Impact of Adopting an Eclectic Spelling Program on Minimizing KAU Engineering Students’ Spelling Mistakes

Evaluation of Written Expression Skills of Students from Turkish World through Error Analysis

The aim of the research is to evaluate the written expression skills of the students from the Turkish world and communities that are studying at Hoca Ahmet Yesevi International Turkish-Kazakh University by using the error analysis method and to develop a solution proposal for the wrong sources revealed. For this purpose, the composition was printed to evaluate the written expression skills of the students, and negotiations were held so that the wrong sources could be revealed. The results of the research showed that the mistakes most frequently made by Turkish students in written expression studies are spelling and punctuation mistakes and misuse of words. The main causes of these mistakes were determined to be excessive generalizations, not knowing the rule constraints and the main negative transfers. Another category created from student spelling mistakes is mistakes made in word selection. The situation repeated by almost all students in this category is the negative transmission caused by the mother tongue and the incorrect use of words caused by not knowing the rule restrictions. After that, the most repeated mistakes and their causes, respectively, are the unnecessary use of words in sentences due to developing incorrect concepts, excessive generalization and word omissions due to ignorance of rule restrictions, word errors brought from the mother tongue due to negative transmission from the mother tongue, and errors in the use of words that have passed from foreign languages to Turkish.

The Prevalence of Quranic Verses Recitation in Malay Medical Treatment: A Study on Kitab Tib MSS1653 Manuscript

Abstract Al-Quran is known as the best remedy for illnesses. In Malay medical treatment, the recitation of Quranic verses was one of the treatment methods applied by Malay medical practitioners. A lot of Quranic verses were used as a prayer and documented in Malay medical manuscripts produced in the 16th to 20th centuries. Hence, this article attempts to analyse Quranic verses recitation used as a treatment method in Kitab Tib MSS1653 manuscript. This study applied qualitative methodology and library research methods. The data was analysed by using inductive, deductive, and comparative methods to provide a discussion on related objectives. The finding shows that there were 387 Quranic verses from 58 surahs were used as a treatment method discussed in this manuscript. However, there were some spelling errors in Quranic verses writing found in Malay medical manuscripts. Seven types of spelling errors are missing letter hamzah, dots removal in letters, misspelled words, additional letters, missing letters, missing words, and major spelling mistakes.

Improving misspelled word solving for human trafficking detection in online advertising data

<span lang="EN-US">Social media is used by pimps to advertise their businesses for adult services due to easy accessibility. This requires the potentially computational model for law enforcement authorities to facilitate a detection of human trafficking activities. The machine learning (ML) models used to detect these activities mostly rely on text classification and often omit the correction of misspelled words, resulting in the risk of predictions error. Therefore, an improvement data processing approach is one of strategies to enhance an efficiency of human trafficking detection. This paper presents a novel approach to solving spelling mistakes. The approach is designed to select misspelled words, the replace them with the popular words having the same meaning based on an estimation of the probability of words and context used in human trafficking advertisements. The applicability of the proposed approach was demonstrated with the labeled human trafficking dataset using three classification models: k-nearest neighbor (KNN), naive Bayes (NB), and multilayer perceptron (MLP). The achievement of higher accuracy of the model predictions using the proposed method evidences an improved alert on human trafficking outperforming than the others. The proposed approach shows the potential applicability to other datasets and domains from the online advertisements.</span>