Connecting Disciplinary and Linguistic Knowledge in Concept-Based Language Instruction

Nowadays, forensic authorship authentication plays a vital role in identifying the number of unknown authors as a result of the world’s rapidly rising internet use. This paper presents two-level learning techniques for authorship authentication. The learning technique is supplied with linguistic knowledge, statistical features, and vocabulary features to enhance its efficiency instead of learning only. The linguistic knowledge is represented through lexical analysis features such as part of speech. In this study, a two-level classifier has been presented to capture the best predictive performance for identifying authorship. The first classifier is based on vocabulary features that detect the frequency with which each author uses certain words. This classifier’s results are fed to the second one which is based on a learning technique. It depends on lexical, statistical and linguistic features. All of the three sets of features describe the author’s writing styles in numerical forms. Through this work, many new features are proposed for identifying the author’s writing style. Although, the proposed new methodology is tested for Arabic writings, it is general and can be applied to any language. According to the used machine learning models, the experiment carried out shows that the trained two-level classifier achieves an accuracy ranging from 94% to 96.16%.

This study investigated the influence of L1 conceptual and linguistic knowledge on Saudi Arabian EFL learners’ comprehension and production of English metaphorical expressions. Guided by the Conceptual Metaphor Theory (CMT), the study employed a four-way typology that differed in the degree of conceptual and linguistic overlap between Arabic and English. Participants completed comprehension and production tasks targeting each metaphor type. Results showed significant differences across types, with higher accuracy for expressions that shared both conceptual and linguistic features across languages. These findings emphasize the impact of L1 conceptual and linguistic knowledge on learners’ comprehension and production of English metaphors and suggest implications for pedagogy and directions for future research.

Natural language processing provides a very significant contribution to various application areas such as multilingual big data, information retrieval, data integration and multilingual web. However, handling linguistic knowledge to develop such lingware applications is a crucial issue, especially for linguistic novice users. To deal with this issue, a "smart" linguistic knowledge management may help the users to understand the meaning, scope and especially the use of related techniques and algorithms. In this paper, (1) we propose a semantic processing of linguistic knowledge based on a multilingual linguistic domain ontology, called LingOnto. Compared to related work, LingOnto does not only handles linguistic data, but also linguistic processing functionalities and linguistic processing features. Besides, it allows, via a reasoning engine, inferring new linguistic knowledge and assisting in the process of proposing lingware applications. This is particularly useful for novice users, but can also provide new perspectives for the expert ones. LingOnto covers the French, English and Arabic languages. (2) We propose also an assisted user friendly ontology visualization tool called LingGraph. It facilitates the interaction with LingOnto. It offers an easy to use interface for users not familiar with ontologies. It is based on a SPARQL pattern-based approach to allow a smart search interaction functionality to visualize only the ontological view corresponding to the user’s needs and preferences. In order to evaluate LingOnto, we apply it to a framework of identifying valid natural language processing pipelines. Finally, we give the results of the carried-out experiments.

The purpose of this study is to see if there is any correlation between linguistic knowledge and writing competence in diagnostic writing assessment. The research data sources were constructed based on two：one is a questionnaire for assessing university students` Korean linguistic knowledge, and the other is a paper examination for evaluating Korean writing competence in diagnostic writing assessment. The statistical data analysis was conducted at two：item and correlation analysis. The findings were that linguistic knowledge, especially syntactic and semantic, has a very strong correlation with rating categories, linguistic and textual features. The present results have some implications for teaching/learning Korean writing. Although the assessment is analytical, the writing education should be holistic, combining linguistic knowledge with categories of text construction.

This study reports on student writing outcomes from a two‐year interdisciplinary collaboration between applied linguists (the authors) and an organizational behavior (OB) professor. We used an ethnographic language‐focused approach to make explicit the linguistic features of the case analysis genre at an American university in the Middle East. We analyzed 33 student case analyses to examine how effectively students applied two heuristics from our scaffolding materials: the semantic wave heuristic for writing analytical paragraphs that move from abstract to concrete and back to abstract knowledge; and the I know, I see, I conclude heuristic for making explicit the logical connections between disciplinary knowledge and case information to produce conclusions. Students integrated the focal linguistic features with varying degrees of effectiveness. Most students met genre expectations by making abstract claims about the case at the beginning and at the end of their analysis paragraphs, integrating OB knowledge with information about the case, thus creating effective waves between disciplinary and case knowledge. However, our analysis reveals differences in the quality of students’ logical reasoning between high‐, mid‐, and low‐rated texts. We discuss how these differences can inform linguistically responsive disciplinary writing instruction.

One subfield of assessment of language proficiency is predicting language proficiency level. This research aims at proposing a computational linguistic model to predict language proficiency level and to explore the general properties of the levels. To this end, we collect the data from Persian learners' textbooks and extract statistical and linguistic features from this text corpus to train 3 classifiers as learners. The performance of the model varies based on the learning algorithm and the feature set(s) used for training the model. For evaluating the models, four standard metrics, namely accuracy, precision, recall, and F-measure are used. Based on the results, the model created by the Random Forest classifier performed the best when statistical features extracted from raw text is used. The Support Vector Machine classifier performed the best by using linguistic features extracted from the corpus annotated automatically. This determines that enriching the model and providing various kinds of information do not guarantee that a classifier (learner) performs the best. To discover the latent teaching methodology of the textbooks, we studied the general performance of the classifiers with respect to the language level and the linguistic knowledge used for creating the model. Based on the obtained results, the amount of extracted features plays an important role during to training a classifier. Furthermore, the average best performance of the classifiers is extending the linguistic knowledge from syntactic patterns at level A to all linguistic information at levels B and C.

This study examined 120 Victorian preservice and inservice teachers' ability to implement evidence-based, early literacy instruction by examining whether teachers possessed positive perceptions of explicit instruction in sound-letter relationships, and a proficient knowledge of language structure. Teachers' confidence in teaching students of known risk for learning difficulties was also investigated. Findings indicated that while teachers report positive perceptions of explicit phonics-based instruction, they generally did not nominate this approach as their predominant early literacy instruction method. School sector also influenced early literacy instruction practices and linguistic knowledge: independent school teachers reported higher linguistic knowledge scores than their Catholic counterparts and were more likely than Catholic or state school teachers to report using phonics-based instruction to teach reading. Inservice and pre-service teachers did not demonstrate adequate knowledge of metalinguistics. Also, the majority of teachers did not report high levels of confidence in their ability to teach reading to diverse student populations.

The paper reports about the development of a Named Entity Recognition (NER) system in Bengali using a tagged Bengali news corpus and the subsequent transliteration of the recognized Bengali Named Entities (NEs) into English. Three different models of the NER have been developed. A semi-supervised learning method has been adopted to develop the first two models, one without linguistic features (Model A) and the other with linguistic features (Model B). The third one (Model C) is based on statistical Hidden Markov Model. A modified joint-source channel model has been used along with a number of alternatives to generate the English transliterations of Bengali NEs and vice-versa. The transliteration models learn the mappings from the bilingual training sets optionally guided by linguistic knowledge in the form of conjuncts and diphthongs in Bengali and their representations in English. The NER system has demonstrated the highest average Recall, Precision and F-Score values of 89.62%, 78.67% and 83.79% respectively in Model C. Evaluation of the proposed transliteration models demonstrated that the modified joint source-channel model performs best in terms of evaluation metrics for person and location names for both Bengali to English (B2E) transliteration and English to Bengali transliteration (E2B). The use of the linguistic knowledge during training of the transliteration models improves performance.

Professional training of students at the University should form the graduate's solid knowledge and ability to quickly master his often changing functional duties. To do this, the basic disci-plines of the engineer should be based on the fundamental disciplines of the first courses, which include, first of all, mathematics and physics. However, mathematical training of University students in the first years has become particularly difficult in recent years. It is known that today school graduates have a low level of exam scores in mathematics, which does not provide adequate assistance to successfully master not only higher mathematics at the University, but also special disciplines. In this regard, currently an urgent task is to study the levels of knowledge of special disciplines by students of technical universities, depending on the level of knowledge of mathematical disciplines. To ensure the quality of teaching mathematics at the University there are methodical systems of organization of level differentiation of training, which takes into account the initial level of pre-University training and corresponding to this level of the program of University mathematical training. However, their implementation is not very successful. The paper proposes a method of evaluation of the study of the connection of mathematical dis-ciplines with General scientific and special disciplines. Their establishment can allow to make necessary adjustments in their study for subsequent sets to the University.

In the system of institutions of professional higher education of engineering profile, physics is a fundamental science that provides a basis for the formation of students' knowledge, skills and abilities of general technical and special disciplines. Physics education should be related to the chosen specialty and be based on specific processes and phenomena that underlie the professional activities of the future professional junior bachelor, and therefore should be aimed at the formation of professional competence. Based on the fact that the course of general physics is the basis of teaching professional and special disciplines, it is important to improve the methodology of teaching physics in institutions of professional higher education. We are convinced that the priority area of preparation of future graduates of professional colleges of engineering is the study of physics and astronomy. However, the implementation of the professional direction of teaching physics in engineering colleges is associated with certain objective difficulties: difficulties in reorienting the teaching of physics to professional orientation, optimizing the amount of educational material with a limited number of hours, the complexity of professionally oriented tasks and others. We are convinced that the purpose of education should not include only the formation of knowledge of the course of physics and astronomy. Physics tools should also be used to form knowledge and activities adequate to the professional activities of a graduate of a professional engineering college. Therefore, it is necessary to form such a didactic model of the subject, which, through integration, will include in the content of the course of physics and astronomy of the profile school also a block of concepts aimed at professional activity. It is important to remember that the professional direction of teaching physics and astronomy should also be realized through practice, namely through the performance of professionally oriented laboratory work and solving professionally oriented problems. The difficulty in solving this type of problem is primarily that students do not have professional concepts related to future activities. Thus, there is a relationship between expanding the conceptual apparatus of technical and special disciplines and understanding the content of professionally oriented tasks.

This paper proposed a spelling error detection and correction using the linguistic features and knowledge resource. The linguistic features mainly come from language model that describes the probability of a sentence. In practice, the formal document with typos is defective and fall short of the specifications, since typos and error hidden in printed document are frequent, rework will cause the waste of paper and ink. This paper proposed an approach that addresses the spelling errors and before printing. In this method, the linguistic features are used in this research to compare and increase a new feature additionally that is a function of Internet search based on knowledge bases. Combining these research manners, this paper expect to achieve the goals of confirming, improving the detection rate of typos, and reducing the waste of resources. Experimental results shows, the proposed method is practicable and efficient for users to detect the typos in the printed documents.

This study compared Korean adult learners’ English speech in dialogic and monologic tasks, measuring 57 college students’ oral proficiency in terms of holistic and analytic grades. The statistical analyses were focused on two questions: 1) how much do the holistic grades of oral proficiency and analytic grades of the four linguistic features function differently across the tasks? and 2) which linguistic feature has the strongest correlation with the holistic grades of English oral proficiency? The study found significant differences between the two tasks in five aspects (English oral proficiency, topic development, fluency, range, and accuracy). It also showed that a monologic task resulted in lower achievements in those five aspects. In the comparison of the correlations with English proficiency, the range reached the top in both tasks, followed by topic development. The study provides some helpful information regarding which types of speech tasks and linguistic features of EFL oral proficiency are more desirable for targeting in teaching and assessment.

The new curriculum was promulgated at the end of 2018. Therefore, there is a need to investigate how teachers perceive the teaching of linguistic knowledge in addition to skills to develop secondary school learners’ communicative competence. The study was carried out during the three months of July, August and October of 2020 in the three provinces of Kien Giang, Ben Tre and Lam Dong with the participation of 120 teachers from 106 secondary schools. Data were collected in the form of group poster presentations for the first two/three periods in the textbooks for the new curriculum and analyzed according to three aspects of form, meaning and use for linguistic knowledge and their sequence. The findings of the study indicate that the teacher participants have a vague idea about teaching the aspects of linguistic knowledge from a learning-centered approach, do not know their sequence of meaning, form and use, and normally follow the activities and their order in the textbook as the only resort available.

This article is devoted to the problem of the development of lingvocultural competence in students in the process of digitalization. The aim of this article is to examine the impact of digitalization on the development of lingvocultural competence, focusing on how digital tools and technologies can enhance the teaching and learning of cultural and linguistic knowledge in an increasingly globalized world. This article employs a mixed-methods approach to explore the development of lingvocultural competence in the context of digitalization. The main research methods are a qualitative analysis of selected case studies performed to illustrate how digital tools and platforms (e.g. online language learning platforms, digital tools for intercultural communication) are currently being used to develop linguistic and cultural competence. Lingvocultural competence, the ability to understand and effectively use language in relation to the cultural values and practices it reflects, is becoming increasingly important in the digital era, where communication transcends national and cultural boundaries. The article analyzes how digital technologies, online learning platforms, and digital communication tools influence the teaching and learning of lingvocultural knowledge. It also examines the challenges and opportunities presented by digitalization in promoting intercultural understanding. Through a review of current digital resources and methodologies, the article provides insight into how educators can leverage these tools to enhance lingvocultural competence among students. The findings suggest that while digitalization offers new avenues for cultural and linguistic exchange, it also requires innovative approaches to ensure effective and culturally sensitive communication in a globalized digital world.

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