scholarly journals FRAME SEMANTICS METHODOLOGY FOR TEACHING TERMINOLOGY OF SPECIALISED DOMAINS

2022 ◽  
pp. 765
Author(s):  
Oksana Smirnova ◽  
Sigita Rackevičienė ◽  
Liudmila Mockienė
Keyword(s):  
Foreign Languages ◽  
Use Case ◽  
Frame Semantics ◽  
Lexical Database ◽  
Learning Techniques ◽  
Teaching Learning

The article attempts to show how the theory of Frame Semantics and the resources of the lexical database FrameNet can be used for teaching/learning terminology of specialised domains. The article discusses the principles of Frame Semantics and presents a use case of application of the frame-based methodology for developing classification of terminology of the selected financial subdomain for learning/teaching purposes. The use case focuses on terms denoting concepts that compose ‘CAUSE-RISK’ frame which was developed on the basis of several related frames in the FrameNet database. The stages of the use case and its outcomes are described in detail and the benefits of application of the methodology for learning/teaching specialised vocabulary are provided. Hopefully, the provided insights will give ideas to teachers of foreign languages for specific purposes and help to develop effective terminology teaching/learning techniques.

scholarly journals ERRORES GRAMATICALES EN LA EXPRESIÓN ESCRITA DE LOS GRIEGOS APRENDICES DE ELE: ANÁLISIS EN EL NIVEL B1

2019 ◽  
pp. 239
Author(s):  
Eirini Rammou
Keyword(s):  
Foreign Language ◽  
Quantitative Research ◽  
Spanish Language ◽  
Foreign Languages ◽  
Written Expression ◽  
Grammatical Errors ◽  
The Common ◽  
Teaching Learning ◽  
Source Of Information

En este estudio hemos seguido el modelo de Análisis de Errores que constituye una fuente de información importante en el ámbito de la enseñanza-aprendizaje de lenguas extranjeras. El objetivo de este estudio ha sido investigar los errores gramaticales que cometen con más frecuencia los aprendices griegos de español como lengua extranjera en la expresión escrita del nivel B1. Durante el proceso de aprendizaje los alumnos formulan hipótesis mediante la utilización de estrategias y mecanismos psicolingüísticos y por ello nuestro estudio ha profundizado además en la descripción de estas estrategias con el fin de detectar las causas que originan los errores. La clasificación de los errores se ha basado en el criterio lingüístico, descriptivo y etiológico. Los datos obtenidos provienen de producciones escritas reales de los aprendices griegos. Para el análisis hemos aplicado una investigación cuantitativa. En los resultados se proporcionan porcentajes de los errores frecuentes que hemos localizado. Tanto los resultados obtenidos de nuestro análisis e investigación como las conclusiones a las que hemos llegado resultan relevantes para la prevención de errores gramaticales y la optimización de la enseñanza del español a griegos.ABSTRACTIn this study we have followed the model of Error Analysis that constitutes an important source of information in the field of teaching-learning foreign languages. The aim of this study has been to investigate the grammatical errors most frequently made by Greek learners of Spanish as a foreign language (SFL) in the written expression of the B1 level of the Common European Framework of Reference for Languages (CEFR). During the learning process, students formulate hypotheses through the use of strategies and psycholinguistic mechanisms, which is why our study also goes deeper into the description of these strategies in order to detect the causes that originate the errors. The classification of errors is based on linguistic, descriptive and etiological criteria. The data obtained come from real written productions of the Greek students. For the analysis we have applied a quantitative research. Percentages of the frequent errors we have located are given in the results. The results obtained from our analysis and research and also the conclusions we have reached are relevant for the prevention of grammatical errors and the optimization of teaching Spanish language to Greek learners.

scholarly journals TECHNIQUE APPROACHES IN TEACHING FOREIGN LANGUAGE TO STUDENTS OF ECONOMICS

2021 ◽  
Vol 1 (21) ◽  
Author(s):  
Mariia O. Kuts ◽  
Keyword(s):  
Professional Training ◽  
Process Management ◽  
Methodological Approach ◽  
Educational Process ◽  
Foreign Languages ◽  
Educational Goals ◽  
Communicative Interaction ◽  
Economic Area ◽  
Teaching Learning

The article reveals the problem of increasing the efficiency of teaching foreign languages to students of non-linguistic specialties by means of introducing a system of pedagogical teaching technologies into the educational process. It has been determined that pedagogical technologies of teaching are such pedagogical technologies, which are based on modern positions of professional development of a person and aimed at achieving educational goals. In the process of learning foreign languages, they are a way of a phased system of organization of the communicative interaction between a teacher and a student in the conditions of operative feedback between them through the use of specific methods, forms and means of learning. It has been found that the leading class of pedagogical technologies for teaching foreign languages is a communicatively oriented technique – a project technique and an appropriate system of its successive and phased implementation, in which learning emerges as a model of real-world foreign communication. The article provides a classification of pedagogical techniques for teaching foreign languages to students of the economic area of expertise, which can contribute to their more systematic use to improve the efficiency of the educational process in higher education institutions. Among the subspecies of communicative oriented techniques of teaching foreign languages to students of economic specialties the following subcategories have been identified: subjects of educational process management – techniques of teaching, learning, partnership interaction and instrumental techniques; the place in the organization of the educational process – the technique of in-class, out-of-class and independent activities; according to the methodological approach – technique-modernization and technique-transformation and in the terms of implementation – meta-techniques, branch macro techniques, modular-local and micro techniques. The author sees the directions for further research in the development of tools for the implementation of the above techniques in accordance with the characteristics of the professional training of students of economic area of expertise.

A Brief Survey on Text Classification Using Various Machine Learning Techniques

2018 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Padmavathi .S ◽  
M. Chidambaram
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Fixed Number ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Rule Based ◽  
Learning Techniques ◽  
Machine Learning Approach ◽  
Rule Based Approach

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.

SPECIFICS OF TEACHING FOREIGN LANGUAGES FOR PROFESSIONAL COMMUNICATION TO STUDENTS SPECIALIZING IN “LEGAL SUPPORT OF NATIONAL SECURITY”

2020 ◽  
Author(s):  
Анна Владимировна Подстрахова
Keyword(s):  
National Security ◽  
Professional Communication ◽  
Foreign Languages ◽  
Skills Development ◽  
Enhance Efficiency ◽  
Teaching Learning

В статье рассматриваются вопросы формирования у студентов-юристов универсальных компетенций в процессе обучения профессионально-ориентированному иностранному языку. Предлагаются пути оптимизации процесса обучения иностранному языку на примере курса «Иностранный язык в профессиональной сфере» в рамках специальности «Правовое обеспечение национальной безопасности». The paper focuses on the problem of students` universal skills development while teaching foreign languages for professional communication. Ways to enhance efficiency of teaching/learning are proposed and tested among the students specializing in “Legal Support of National Security”.

Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: a review

2021 ◽  
Author(s):  
Hamdi Altaheri ◽  
Ghulam Muhammad ◽  
Mansour Alsulaiman ◽  
Syed Umar Amin ◽  
Ghadir Ali Altuwaijri ◽  
...  
Keyword(s):  
Deep Learning ◽  
Motor Imagery ◽  
Learning Techniques ◽  
Electroencephalogram Eeg

scholarly journals Natural Disasters Intensity Analysis and Classification Based on Multispectral Images Using Multi-Layered Deep Convolutional Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2648
Author(s):  
Muhammad Aamir ◽  
Tariq Ali ◽  
Muhammad Irfan ◽  
Ahmad Shaf ◽  
Muhammad Zeeshan Azam ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Natural Disasters ◽  
Deep Convolutional Neural Network ◽  
Multispectral Images ◽  
Learning Techniques ◽  
Proposed Model ◽  
Disaster Intensity ◽  
And Performance

Natural disasters not only disturb the human ecological system but also destroy the properties and critical infrastructures of human societies and even lead to permanent change in the ecosystem. Disaster can be caused by naturally occurring events such as earthquakes, cyclones, floods, and wildfires. Many deep learning techniques have been applied by various researchers to detect and classify natural disasters to overcome losses in ecosystems, but detection of natural disasters still faces issues due to the complex and imbalanced structures of images. To tackle this problem, we propose a multilayered deep convolutional neural network. The proposed model works in two blocks: Block-I convolutional neural network (B-I CNN), for detection and occurrence of disasters, and Block-II convolutional neural network (B-II CNN), for classification of natural disaster intensity types with different filters and parameters. The model is tested on 4428 natural images and performance is calculated and expressed as different statistical values: sensitivity (SE), 97.54%; specificity (SP), 98.22%; accuracy rate (AR), 99.92%; precision (PRE), 97.79%; and F1-score (F1), 97.97%. The overall accuracy for the whole model is 99.92%, which is competitive and comparable with state-of-the-art algorithms.

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