-
Phraseology and National Identity: Teaching Cultural Symbolism of Kazakh Idioms to University Students
This article presents an empirical study of the effectiveness of a training module aimed at teaching Kazakh idioms as cultural-symbolic units in a university course. The theoretical basis is the concept of symbolic competence, according to which phraseology is considered not only as lexical and semantic material but also as a carrier of cultural memory, values, and social norms. The study design is mixed (explanatory sequential mixed-methods) and includes a quasi-experiment (pretest/posttest with a control group) and a qualitative stage (interviews and reflective texts). The study involved 133 students (experimental group n = 67, control n = 66) of the educational program «6B1701 — Training of Teachers of Kazakh Language and Literature» at Zhanibekov University; the module was implemented over 6 weeks (12 lessons of 50 minutes). Quantitative instruments included a phraseological competence test (meaning knowledge, correct context selection, productive use), a national-cultural identity scale, and a cultural awareness/symbolic competence scale. Results showed that, compared with the control group, the experimental group achieved significantly higher gains in the overall idiom competence test score, with the greatest changes observed in the contextual appropriateness and productive use components. Statistically significant increases were also found in the national-cultural identity and cultural awareness scores. Qualitative analysis revealed three key themes: (1) awareness of cultural values through the figurative basis of idioms, (2) rethinking belonging and cultural pride, and (3) difficulties in interpreting symbols without context and cultural commentary. The findings substantiate the pedagogical feasibility of integrating cultural-symbolic interpretation, contextualization, and reflective writing into the teaching of phraseology in higher education and propose a replicable module for the training of future Kazakh language teachers.
-
Topics in Linguistics (2025), 26(1), pp. 92−118 10.17846/topling-2025-0005 The development of research competence in postgraduate foreign language students using project-based methods
This article is aimed at evaluating the effectiveness of developing research competence in postgraduate foreign language students, enhancing their scientific and research skills, enabling independent problem-solving in their professional field, and improving their academic training through project-based methods. Today’s educational paradigm puts students themselves at the centre of the educational process, their needs, characteristics and talents and their development; the need for a teacher to master research competence is obvious. One of the most effective ways to form specialists with creative thinking is to involve postgraduate foreign language students in research activities. With research competence, a specialist is able to actively and productively analyse evidence, and develop and apply new, more efficient algorithms, resources and technologies, instead of being limited to using ready-made, sometimes outdated solutions. The authors of this study highlight that while postgraduate foreign language students understand the concept, goals, and objectives of research, they often lack the motivation and skills required for independent work, information analysis, and research competence development. To address this challenge, research competence must be systematically cultivated from the early stages of postgraduate education.
-
Load Balancing in DCN Servers Through Software Defined Network Machine Learning
In this research paper, we delve into the innovative realm of optimizing load balancing in Data Center Networks (DCNs) by leveraging the capabilities of Software-Defined Networking (SDN) and machine learning algorithms.
Traditional DCN architectures face significant challenges in handling unpredictable traffic patterns, leading to bottlenecks, network congestion, and suboptimal utilization of resources. Our study proposes a novel framework that integrates the flexibility and programmability of SDN with the predictive and analytical prowess of machine learning.
-
Green-oriented automation: AI-driven engineering control technologies for resource efficient solutions
This article is not only about the speed of digital life in human history, also about its second aspect, that is, the existence of Internet users who use online content for the purpose of insulting or degrading, as well as collecting comments written on social networks with obscene words. It is said that simple and automated actions can be implemented using machine learning. Today, the prevalence of negative comments on online content further exacerbates the problem. Cyberbullying is known to be one of the threats posed by online content, which, in turn, puts online users in an emotional state and causes certain psychological damage. We are collecting a database of obscene comments posted on social networks and used by the media in Kazakhstan. Analyzing complaints received from many social networks, we noticed that the number of publications with offensive, that is, derogatory comments in online content is increasing every day. The results of our research using machine learning methods will help not only to study the roots of abusive language posted on social networks, but also to distinguish the types of offensive comments and obtain automated data sets.
-
-
Hate Speech Detection in Social Networks using Machine Learning and Deep Learning Methods
Hate speech on social media platforms like Twitter is a growing concern that poses challenges to maintaining a healthy online environment and fostering constructive communication. Effective detection and monitoring of hate speech are crucial for mitigating its adverse impact on individuals and communities. In this paper, we propose a comprehensive approach for hate speech detection on Twitter using both traditional machine learning and deep learning techniques. Our research encompasses a thorough comparison of these techniques to determine their effectiveness in identifying hate speech on Twitter.
-
Ethnolinguistic aspect of phraseological units сoncerning livestock
If we look at the history, culture, spiritual values of the nation, in close connection with the worldview, that we learn the nature of the national language; we delve into the structure of the language system. One of the main areas of linguistics is the consideration of language, language units together with human factors and human values. In recent years, we have focused on human factors and often spoke about the problem of language, the rational use of linguistic units and understanding language. Special attention is paid to cultural data about the national values, and language is increasingly being studied not only from the point of view of the individual (formal), but also from the point of view of values, conceptualization, and field.
-
Ways of implementing criteria-based assessment in the secondary school of the republic of Kazakhstan
An analysis of domestic and foreign methodological literature shows a great potential for using criteria-based assessment as a means of foreign language teaching. One of the most important recent events in Kazakhstani education was the introduction of the updated curriculum for secondary education. In 2016, a renewed curriculum was adopted in all Kazakhstani secondary schools.
