Character-based Language Research Articles

ARABIC LANGUAGE LEARNING BASED ON CHARACTER EDUCATION

This article explores the integration of character education into Arabic language learning in Indonesian education. Character education, foundational in Indonesian education, has gained renewed attention due to societal moral crises, prompting a closer examination of its implementation. The research employs library research methodology, focusing on literature related to Arabic language learning and character education. It identifies methods and approaches for integrating character education into Arabic language learning, emphasizing the significance of Arabic as the language of the Quran and Hadith, fundamental texts in Islam containing guidance on character formation. The article discusses the nature of Arabic language learning, goals, learning systems, and character education concepts, highlighting essential character traits and values. Strategies for character education and methods for fostering character development in students are explored. Moreover, the article outlines character-based Arabic language learning activities, from planning to evaluation stages, underscoring the role of teaching materials and educators as role models. Ultimately, it concludes that integrating character education into Arabic language learning can contribute significantly to the holistic development of learners, instilling moral values and ethical principles derived from Islamic teachings.

A search tool based on language modelling developed for The Index of Middle English Prose

Non-standardised early vernaculars present a problem for search tools due to the high degree of variation. The challenge lies in the variation found in orthography, syntax, and lexicon between titles, incipits, and explicits in manuscript copies of the same work. Traditional search methods relying on exact string matching or regular expressions fail to address these variations comprehensively. This project presents a web-based search tool specifically designed to handle linguistic and textual variation. The software is made available as a part of the Index of Middle English Prose (IMEP). The search tool addresses the issue of variation by utilizing a database of incipits and explicits, character-based n-gram language models (LMs) built with the Stanford Research Institute Language Modelling (SRILM) toolkit, and a fuzzy search script (IMEP: FSS) written in Python. The tool optimizes for recall, retrieving multiple potential matches for a search string, without attempting to identify the ‘correct’ one. The search process involves looking up exact matches in the database while simultaneously using the fuzzy search script to evaluate the incipits and explicits against a model of the search string, followed by a match of the search string against models of the incipits and explicits. This two-step process shortens the processing time, which would otherwise be unreasonably long, because while using SRILM to match the search string against each incipit or explicit in the IMEP for precision could be time-consuming, running a first step where all texts are matched against a single LM built from the search string allows for faster processing. A web application, built using Django and Docker, combines the results of the direct database lookup and the fuzzy search script, presenting them as a list with exact matches followed by fuzzy matches ordered by increasing model perplexity. The tool is made available Open Access and can be adapted to other datasets.

Ara--CANINE: Character-Based Pre-Trained Language Model for Arabic Language Understanding

Recent advancements in the field of natural language processing have markedly enhanced the capability of machines to comprehend human language. However, as language models progress, they require continuous architectural enhancements and different approaches to text processing. One significant challenge stems from the rich diversity of languages, each characterized by its distinctive grammar resulting in a decreased accuracy of language models for specific languages, especially for low-resource languages. This limitation is exacerbated by the reliance of existing NLP models on rigid tokenization methods, rendering them susceptible to issues with previously unseen or infrequent words. Additionally, models based on word and subword tokenization are vulnerable to minor typographical errors, whether they occur naturally or result from adversarial misspellings. To address these challenges, this paper presents the utilization of a recently proposed free-tokenization method, such as Cannine, to enhance the comprehension of natural language. Specifically, we employ this method to develop an Arabic-free tokenization language model. In this research, we will precisely evaluate our model’s performance across a range of eight tasks using Arabic Language Understanding Evaluation (ALUE) benchmark. Furthermore, we will conduct a comparative analysis, pitting our free-tokenization model against existing Arabic language models that rely on sub-word tokenization. By making our pre-training and fine-tuning models accessible to the Arabic NLP community, we aim to facilitate the replication of our experiments and contribute to the advancement of Arabic language processing capabilities. To further support reproducibility and open-source collaboration, the complete source code and model checkpoints will be made publicly available on our Huggingface1 . In conclusion, the results of our study will demonstrate that the free-tokenization approach exhibits comparable performance to established Arabic language models that utilize sub-word tokenization techniques. Notably, in certain tasks, our model surpasses the performance of some of these existing models. This evidence underscores the efficacy of free-tokenization in processing the Arabic language, particularly in specific linguistic contexts.

The Presentation of the Pictogrammic “Self” and Persona

This article focuses on the history of emoji. From the identifiable smiley face from the 1960s and 1970s to the computer and early Internet culture of using emoticons, it describes how this form of communication filled certain gaps in our structure of conveying sentiment and feeling and works at the construction of a constructed persona of the self in contemporary culture. Connected to this study is the historical connection to pictograms and character-based languages; in that analysis and its linguistic emphasis, the article concludes with the possibility that the development of emoji helps us understand how language and its rearticulation in “text” and “image” has worked to produce collective and common meanings. Research into the differences in written languages – from alphanumeric structures to hieroglyphs and character-based systems – is integrated into positioning emoji and their collective meaning systems. The article concludes with a comprehensive reading of how emoji – in its massive migration and integration from its Japanese imagistic origins to its now routine play in across a myriad of cultures - constructs a strategic form of communicationthat conveys a tactical expression of self and our persona in and through digital culture.

A search tool based on language modelling developed for The Index of Middle English Prose.

Non-standardised early vernaculars present a problem for search tools due to the high degree of variation. The challenge lies in the variation found in orthography, syntax, and lexicon between titles, incipits, and explicits in manuscript copies of the same work. Traditional search methods relying on exact string matching or regular expressions fail to address these variations comprehensively. This project presents a web-based search tool specifically designed to handle linguistic and textual variation. The software is made available as a part of the Index of Middle English Prose (IMEP). The search tool addresses the issue of variation by utilizing a database of incipits and explicits, character-based n-gram language models (LMs) built with the Stanford Research Institute Language Modelling (SRILM) toolkit, and a fuzzy search script (IMEP: FSS) written in Python. The tool optimizes for recall, retrieving multiple potential matches for a search string, without attempting to identify the 'correct' one. The search process involves looking up exact matches in the database while simultaneously using the fuzzy search script to evaluate the incipits and explicits against a model of the search string, followed by a match of the search string against models of the incipits and explicits. This two-step process shortens the processing time, which would otherwise be unreasonably long, because while using SRILM to match the search string against each incipit or explicit in the IMEP for precision could be time-consuming, running a first step where all texts are matched against a single LM built from the search string allows for faster processing. A web application, built using Django and Docker, combines the results of the direct database lookup and the fuzzy search script, presenting them as a list with exact matches followed by fuzzy matches ordered by increasing model perplexity. The tool is made available Open Access and can be adapted to other datasets.

PEMBELAJARAN MATA KULIAH BAHASA INDONESIA BERBASIS KARAKTER UNTUK MENDUKUNG IMPLEMENTASI KURIKULUM MERDEKA DI PERGURUAN TINGGI

The purpose of this study is to determine the implementation of character education integration into Indonesian language lectures based on the independent curriculum and also to find out the obstacles and problems in the implementation of character education integration in Indonesian language lectures based on the independent curriculum. the research in this journal is descriptive qualitative research. Descriptive qualitative research is a research procedure that produces descriptive data from people and behavior observed in the form of written or spoken language. The research was conducted on STTI Bontang students majoring in mechanical engineering and chemical engineering semester 2, using data collection interviews via google from.1. Description of Research Results Based on the results of interview research on STTI Bontang semester 2 students and mataram university, the research results are: What are the obstacles in character-based Indonesian language learning that are not running properly. the obstacles are still from students who are active when learning Indonesian language courses to liven up the interactive classroom atmosphere and the Implementation of the Merdeka Curriculum even though it has been running smoothly in the past few months, there are still several obstacles such as, among others, lack of experience with learning independence, limited references and uneven access to learning, time management. The concept of learning Indonesian language courses in supporting an independent curriculum in higher education has the concept of how students have a deeper character to participate in supporting an independent curriculum and during the lecture process students are taught, more active and effective in lectures. Thus students are expected to support an independent curriculum in higher education. The independent study program is implemented by giving freedom to educational institutions, including students, to identify topics, interests and desire to learn. They are also free to determine the learning methods that suit their needs. Merdeka Belajar - The Independent Campus Policy aims at the "Right to Study for Three Semesters Outside the Study Program" program to improve the ability of graduates, both soft skills and hard skills, to be better prepared and adaptive to the needs of the times, to train graduates to become outstanding national leaders in the future, the concept of independent learning is the latest policy in the field of education.

Improving named entity correctness of abstractive summarization by generative negative sampling

The problem of factual incorrectness in machine-generated abstractive summarization has received widespread attention in the past few years. Although large-scale neural models show excellent capability in generating fluent and coherent summaries, they still struggle with factual inconsistency, in which the named entity incorrectness is the most frequent and notable one, especially for the character-based languages, such as Chinese. Since abstractive summaries are mostly generated character by character in Chinese, the problem of hallucinated entities is more severe than that of other word-based languages. In this paper, we propose CC-Gens, a novel approach for Correctness Checking based on a Generative negative sampling strategy. Considering that the problem is due to the uncertain nature of the language generation process, we leverage fine-tuned generative language models, i.e., UniLMv2 and mT5, to generate summaries with incorrect entities, thereby constructing a synthetic binary classification dataset for the factuality discriminative model. We propose three strategies: Entity Sampling, Sequence Sampling, and Cloze Sampling, to generate summaries with incorrect entities. With such strategies, the negative samples are much more similar in nature to the output of the neural summarization model. We then train a BERT-based discriminator to identify factually incorrect machine-generated summaries with entity errors based on these generative negative samples. We further propose a novel PU learning algorithm to improve the performance of our approach by iteratively training the discriminator to select high confident negative samples from the unlabeled model generated summaries to replace the former artificially constructed ones. By generating multiple candidate summaries and selecting the one with the highest factual correctness score among them, our approach can significantly reduce the probability that an output summary contains factual errors. According to a comprehensive evaluation, the CC-Gens we proposed outperforms previous works in identifying faithless summaries as well as providing faithful ones.

What Does Doodling do in Chinese tasks: measuring the difference between Chinese and English with expected outcomes

Previous studies have demonstrated that different types of doodling, a way of passing time to release boredom, have either positive or negative influences on one's ability to concentrate and memory. However, previous studies are limited to alphabetic languages, such as English, whereas character-based languages, such as Chinese, are underrepresented to a great extent. Therefore, the current study attempts to extend the extant research by considering the effects of two types of doodling on attention and recall during Chinese tasks and their difference between Chinese and English. In the present experiment, a total of 200 participants, including 100 individuals whose mother language is Chinese and English respectively, are randomly allocated to one of three conditions (structured doodling, unstructured doodling, and control). The concentration and recall performance of participants are measured by writing down the names and places during and after listening to a mundane telephone message. The results suggest that although structured doodling aids concentration in Chinese, the assistance is less than that in English.

Literacy-based tex books to improve the character and language competence of elementary students

The purpose of this study was to produce and determine the feasibility, practicality, and legibility of reading literacy-based textbooks using the type of research and development of the 4D model. The research instruments were arranged based on the level of research needs, namely material expert validation, product validation, and linguist validation. The results of the product feasibility assessment by validation experts obtained 95.8% media validation, 95% material validation, and 91.96% language validation. The product readability rating obtained 89.83%, supported by 90.75% language literacy story questions and 89% character-based language story test results. The findings of this study indicate that reading literacy-based textbooks can attract students' attention and are interactive, the presentation of the content supported by pictures and various color compositions can attract reading interest and stimulate critical thinking skills. So as to help students have the literacy skills needed at this time.

No evidence of a positive effect of learning Chinese language as an L2 on spatial ability

Spatial ability (SA) was shown to be a robust predictor of success in various educational contexts, including STEM. Thus, ways to improve SA are of interest to educational psychology. There is some evidence that SA might be improved via learning character-based language, e.g. Chinese as a second language (CSL), however, the existing research is quite limited. The study aims to investigate an effect of CSL learning on SA in schoolchildren from Year 2 to Year 7. Current study employs a sample of Russian schoolchildren (N = 283), who learnt: English only, English and Spanish; or English and Chinese. Participants completed Raven’s progressive matrices and Mental rotation task at the age of 8 and again at the age of 14. Our data showed negligible group differences in the initial SA level at Year 2 (before learning second language). Similar negligible differences were found at Year 7. Regression analysis showed that SA was predicted by intelligence (Raven’s) and gender but not language learnt at both ages. This pattern of results indicates that learning a Chinese as a second language is unlikely to affect SA. Further research is needed to investigate whether other factors, such as length, intensity and context of learning, moderate this link.

Record linkage for character-based surnames: Evidence from chinese exclusion

This paper proposes a novel pre-processing technique to improve record linkage for historical Chinese populations. Current matching approaches are relatively ineffective due to Chinese-specific naming conventions and enumeration errors. This paper develops a three-step process that both triples the match rate over baseline and improves match accuracy. The procedures developed in this paper can be applied in part or in full to other sources of historical data, and/or modified for use with other character-based languages such as Japanese. More broadly, this approach suggests the promise of language-specific linkage procedures to boost match rates for ethnic minority groups.

Eye movement pattern of reading Chinese Classics

Abstract This article explores the use of eye movement technology in studying the reading pattern of Chinese classical text. Written in a character-based ancient language, Classical Chinese or wenyanwen, the Chinese classics are known to be difficult to apprehend for most contemporary readers. In this study, a new character-oriented eye movement technology, Region of Interest in Reading (ROIR), was invented to detect readers’ attention allocation in reading. Based on ROIRs, first fixation duration, gaze duration, and total fixation duration were formulated to discuss readers’ cognitive processes and reading patterns when reading Classical Chinese text. The empirical study was conducted using Tao Te Ching (道德经) as the reading material. The study provides foundational technology for the construction of Chinese-oriented eye movement control model, and the findings also shed light on the teaching of Chinese Classics.

Computational authorship analysis of the homeric poems

Natural language modeling is used to predict or generate the next word or character of modern languages. Furthermore, statistical character-based language models have been found useful in authorship attribution analyses by studying the linguistic proximity of excerpts unknown to the model. In prior work, we modeled Homeric language and provided empirical findings regarding the authorship nature of the 48 Iliad and Odyssey books. Following this line of work, and considering the current philological views and trends, we break down the two poems further into smaller portions. By employing language modeling we identify outlying passages, indicating reduced linguistic affinity with the main body of the two works and, by extension, potentially different authorship. Our results show that some of the passages isolated as outliers by the language models were also identified as such by human researchers. We further test our methodology and models on texts of similar language and genre created by other authors, namely Hesiod’s “Theogony” and “Work and Days”.

Use of ‘I-Do’ methodology in integrating moral characters into the development of ELT materials for transactional speaking skills

This study is aimed at improving the quality of teaching English at the university level by aligning the students’ needs and the expectations of the lecturers (a needs analysis) with moral values in developing moral character-based English language teaching materials. Development research method is used to carry out this research by employing the ‘I-DO’ methodology which contains three distinct phases namely; 1). The input phase which is passed by a needs analysis involving 60 participants (55 students and 10 lectures). The participants were purposively selected. Questionnaires were used to collect the data which were analyzed by using descriptive approach. 2). The development Phase which is passed by formulating goals and objectives based on the information gathered from the needs analysis. 3) The output phase which is completed by making lesson plans, and producing prototype of the moral value-based teaching materials. This research has built one prototype of a well-developed ELT material for transactional speaking skill. We believe that our findings on the use of ‘I-DO’ methodology could have a profound impact on the way ELT materials is developed in language program.

Stylistics of Nida Ilahi and Its Implications in Character Learning

Nowadays, character learning occupies an important position. There are many studies related to this and the Qur’āncan be a solution in the offer of language and character studies. This study aimed to reveal the way of conveying God (stylistics) to mankind contained in the Qur’ān. A qualitative approach was used with narrative inquiry. The data collection technique was done by analyzing the text of the document which was Al-Maidah verse 90 and 105, also An-Nisa verse 43, which was then analyzed for the data trustworthiness, consistency of research data, the possibility for generalization, neutrality, in a grounded theory research. The results of this study found 3 ways of conveying God to humans in the form of prohibitions or orders, the three appeals are as follows: first, in conveying the order, it is carried out in stages; secondly, the substance conveyed in the message is chosen which is very essential and basic; third, the context chosen is adjusted to the understanding of the aspect. The way God calls His servants with different contexts and appeals can be analyzed so that it is finally adopted as a way of conveying moral messages and character in learning. The results of this study can add to the scientific treasures in character-based language learning.

Adaptive Semiparametric Language Models

AbstractWe present a language model that combines a large parametric neural network (i.e., a transformer) with a non-parametric episodic memory component in an integrated architecture. Our model uses extended short-term context by caching local hidden states—similar to transformer-XL—and global long-term memory by retrieving a set of nearest neighbor tokens at each timestep. We design a gating function to adaptively combine multiple information sources to make a prediction. This mechanism allows the model to use either local context, short-term memory, or long-term memory (or any combination of them) on an ad hoc basis depending on the context. Experiments on word-based and character-based language modeling datasets demonstrate the efficacy of our proposed method compared to strong baselines.

Examining the extent of trademark squatting of NBA athlete names in China

ABSTRACT Research question The development of effective brand protection strategies requires an understanding of the potential threats that brands face from illegal actions. Trademark squatting of transliterated names belonging to well-known celebrities and athletes is perceived by the international business community to be a serious problem in China. Translations are words that have been converted from alphabetic languages into words in character-based languages. As such, the purpose of this study was to examine the phenomena of trademark squatting of foreign athletes’ names and whether that phenomena poses a significant threat to foreign athletes due to the appropriation and bad-faith registration of their transliterated names. Methods A qualitative research approach was employed to detect indicators for both (a) trademark squatting and (b) good faith registrations, which were then applied to trademark registrations for names that matched the transliterations for well-known NBA athletes and the business records for those who registered the marks. Results and Findings 210 registrations (38%) of transliterated names belonging to 55 (57%) of the 96 NBA players included in the study were deemed to include strong indicators of trademark squatting. Implications The prevalence of trademark squatting in China involving the transliterated names of foreign athletes warrants proactive measures by athletes and those who protect and manage their brands. Athletes who compete in contests that are broadcast within China run the risk of losing the rights to their transliterated names to squatters if transliterations are not developed and registered by the athlete.

How Do Educationally At-Risk Men and Women Differ in Their Essay-Writing Processes?

This study examined differences in the composition processes used by educationally at-risk males and females who wrote essays as part of a high-school equivalency examination. Over 30,000 individuals were assessed, each taking one of 12 forms of the examination’s language arts writing subtest in 23 US states. Writing processes were inferred using features extracted from keystroke logs and aggregated into seven composite indicators. Results showed that females earned higher essay and total language arts writing composite scores than did males, but only by trivial amounts. More pertinent was that, after controlling for language arts writing composite score, age, and essay prompt, all seven process indicators showed nontrivial, statistically significant differences, the most notable being for indicators related to fluency and different aspects of editing. The study’s findings are consistent in important ways with those from other investigations of school-age students and adults, and with results from both online and paper-based writing tasks. Implications are offered for conducting similar research for individuals composing in character-based languages like Chinese.

Difficult name, cold man: Chinese names, gender stereotypicality and trustworthiness.

Names can play an important role in forming first impressions. While much of the literature has demonstrated how alphabet-based names influence impression formation, little is known about how character-based names (e.g., Chinese names) affect interpersonal trust. Across six studies, we demonstrated that a difficult-to-recognise Chinese name with less frequently used characters activated masculine perception, which in turn decreased trust in the name holder. The masculine inferences from difficult names were replicated across within-subjects (Study 1a and 1b) and between-subjects judgements and maintained irrespective of normative knowledge about difficult names as male names (Study 1c). The mediation of gender stereotypicality was manifested in both measured spontaneous gender inference (Study 2a and Study 2b) and manipulated gender information (Study 2c). The effects of recognisability on masculine and trust perceptions were independent of pronunciationability (Study 2b). This research extends previous research by revealing the implications of character-based names and pictographic language on the feeling-as-information theory, also in terms of interpersonal contexts.

The Neural Correlates of Spoken Sentence Comprehension in the Chinese Language: An fMRI Study.

PurposeEveryday social communication emphasizes speech comprehension. To date, most neurobiological models regarding auditory semantic processing are based on alphabetic languages, where the character-based languages such as Chinese are largely underrepresented. Thus, the current study attempted to investigate the neural network of speech comprehension specifically for the Chinese language.MethodsTwenty-two native Mandarin Chinese speakers were imaged while performing a passive listening task of forward and backward sentences. Sentences were used as task stimuli, as sentences compared with words were more frequently utilized in daily speech comprehension.ResultsOur results suggested that spoken Chinese sentence comprehension may involve a neural network comprising the left middle temporal gyrus, the left anterior temporal lobe, and the bilateral posterior superior temporal lobes. The occipitotemporal visual cortex was not found to be significantly involved with the sentence-level network of spoken Chinese comprehension, as bottom-up visualization process from homophones to visual forms may be less needed due to the availability of top–down contextual controls in sentence processing. In addition, no significant functional connectivity was observed, likely obscured by the low cognitive demand of the task conditions. Limitations and future directions were discussed.ConclusionThe current Chinese network seems to largely resemble the auditory semantic network for alphabetic languages but with features specific to Chinese. While the left inferior parietal lobule in the dorsal stream may have little involvement in the listening comprehension of Chinese sentences, the ventral neural stream via the temporal cortex appears to be more emphasized. The current findings deepen our understanding of how the semantic nature of spoken Chinese sentences influences the neural mechanism engaged.