Psycho-Emotional State Of Students: Research And Regulation

Semigina, Tetyana; Vysotska, Zoriana; Kyianytsia, Ievgeniia; Shostak, Iryna; Kichuk, Antonina

doi:10.25115/eea.v38i4.4049

Cited by 3 publications

(3 citation statements)

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“…An important aspect in the study of English, in particular communicative competence, is the ability to interact effectively in the educational linguistic process (Semigina et al, 2020). According to Leong and Ahmadi (2017) this is one of the key factors influencing the quality of communication in the acquisition of English speaking skills.…”

Section: Literature Reviewmentioning

confidence: 99%

Social Media Applications as an International Tool for the Development of English-Language Communicative Competencies

Kryvka¹,

Mitchuk²,

Bykova³

et al. 2022

JCT

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The aim of the article is to determine the effectiveness of various international tools designed to develop students’ English-language communicative competencies. Several scientific methods were used: observation, testing, experimental training etc. Statistical processing of the data obtained during pedagogical experiment was carried out, visualization with the use of graphic method is applied. The description and verbal recording of the results of the study confirm its effectiveness. During the research, experimental training was carried out with the use of social media applications for the development of foreign language communicative competence in second-year students of groups G1, G2. Observations and testing of students while developing foreign language communicative competence were carried out while writing e-mails and creating videos for TikTok in English. The educational platforms, programmes, Internet resources were also used in accordance with the goals and topics of training sessions. The practical results prove the advantages of certain social media applications in the acquisition of English-language components of communicative competences (CCC). G1 students demonstrated a standard procedure for acquiring a linguistic, socio-cultural CCC with a “lag” of the regional geography component. In G2 group, the higher levels of CCC were observed in most cases. Mostly positive markers of Communicative Competences were demonstrated at the medium (344.1 points, 69.8% of G1 respondents) and a sufficient level (371.0 points, 75.8% of G2 respondents). Promising “growth points” were identified. The directions concerning further developments of progressive methods are highlighted.

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Section: Literature Reviewmentioning

confidence: 99%

Social Media Applications as an International Tool for the Development of English-Language Communicative Competencies

Kryvka¹,

Mitchuk²,

Bykova³

et al. 2022

JCT

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“…In sectors such as healthcare, marketing, security, and management in hazardous industrial and transportation domains, there's an increasing demand for novel, efficient tools for automatic determination of human psychoemotional states based on vocal characteristics. Automated recognition of psychoemotional states constitutes a pivotal advancement in enhancing human-machine interfaces, enabling the assessment of stress and fatigue levels, and detecting depressive conditions, which could significantly alleviate accumulated fatigue and similar phenomena [1].…”

Section: Introductionmentioning

confidence: 99%

Development of an advanced ai-based model for human psychoemotional state analysis

Ainakulov,

Koshekov,

Savostin

et al. 2023

EEJET

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The research focuses on developing a novel method for the automatic recognition of human psychoemotional states (PES) using deep learning technology. This method is centered on analyzing speech signals to classify distinct emotional states. The primary challenge addressed by this research is to accurately perform multiclass classification of seven human psychoemotional states, namely joy, fear, anger, sadness, disgust, surprise, and a neutral state. Traditional methods have struggled to accurately distinguish these complex emotional nuances in speech. The study successfully developed a model capable of extracting informative features from audio recordings, specifically mel spectrograms and mel-frequency cepstral coefficients. These features were then used to train two deep convolutional neural networks, resulting in a classifier model. The uniqueness of this research lies in its use of a dual-feature approach and the employment of deep convolutional neural networks for classification. This approach has demonstrated high accuracy in emotion recognition, with an accuracy rate of 0.93 in the validation subset. The high accuracy and effectiveness of the model can be attributed to the comprehensive and synergistic use of mel spectrograms and mel-frequency cepstral coefficients, which provide a more nuanced analysis of emotional expressions in speech. The method presented in this research has broad applicability in various domains, including enhancing human-machine interface interactions, implementation in the aviation industry, healthcare, marketing, and other fields where understanding human emotions through speech is crucial

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“…Distance learning of a foreign language for students of higher educational institutions has a number of advantages due to the fact that we are talking about pedagogical interaction with the age group of psychologically mature individuals with relatively formed motivation mechanisms and a defined personal and professional orientation. In the ideal case, the main motivation for non-philological students to learn a foreign language is to meet current educational needs, potential professional needs (solving problem situations in business communication) and personal communication needs (Semigina et al, 2020). However, despite the listed numerous advantages of the age group of HEIs' degree-seeking students, taken into account, as teaching practice shows, the format of distance learning requires constant control over the mechanisms of conscious learning and motivating students to study activities, forasmuch as educational interaction with the teacher becomes possible only through web communication and often not even in real time mode.…”

Section: Introductionmentioning

confidence: 99%

Distance Learning of Foreign Languages for Students of Economic Specialties

2022

JHETP

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The purpose of the present research is a comprehensive analysis of the process and results of distance learning of a foreign language (English) for students of economic specialties. The research methods are as follows: the analysis of modern opportunities for organizing distance learning; study of theoretical and methodological papers on the subject matter; method of experimental teaching of foreign languages with an emphasis on tactics of stimulating the personal and motivational sphere of students' educational activities; development of author's diagnostic models in order to reveal the dynamics of development of knowledge and practical skills in a foreign language of students of economic profile; qualitative and quantitative analysis of empirical data; statistical and mathematical interpretation of results, their functional analysis; method of generalization and abstraction. According to the data obtained, the hypothesis of the research has been confirmed. It lies in the fact that the students with higher indicators of motivation have shown higher results of academic achievements in mastering a foreign language.

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Psycho-Emotional State Of Students: Research And Regulation

Cited by 3 publications

References 0 publications

Social Media Applications as an International Tool for the Development of English-Language Communicative Competencies

Social Media Applications as an International Tool for the Development of English-Language Communicative Competencies

Development of an advanced ai-based model for human psychoemotional state analysis

Distance Learning of Foreign Languages for Students of Economic Specialties

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