Morphofunctional characteristics, including body composition and somatotype components, represent key quantitative indicators of long-term sport-specific physiological adaptation. While these parameters are traditionally analyzed using descriptive statistical methods, their potential for predictive modeling and computational classification remains insufficiently explored. This study develops and evaluates a supervised machine learning framework for classifying sport-specific morphofunctional profiles in male athletes aged 18-21 years engaged in basketball (n = 30), arm wrestling (n = 30), and Shotokan karate-do (n = 30). The dataset included somatotype components (endomorphy, mesomorphy, ectomorphy), body composition indicators (body fat percentage, muscle mass percentage), and basic anthropometric measures (BMI, height, body mass). The classification task was implemented using Random Forest and Support Vector Machine (RBF kernel) algorithms. Model performance was assessed using cross-validation, accuracy, precision, recall, F1-score, and confusion matrix analysis. The results demonstrated that morphofunctional indicators form a discriminative multidimensional feature space, enabling accurate multi-class sport classification. Random Forest achieved higher classification performance (accuracy: 88.2%) compared to Support Vector Machine (82.4%), indicating the presence of non-linear relationships among anthropometric variables. Feature importance analysis identified mesomorphy, muscle mass percentage, and height as the most influential predictors in differentiating sport disciplines. The findings confirm the feasibility of formalizing traditional morphometric diagnostics within a computational framework and support the integration of machine learning methods into sports science. The proposed approach provides a foundation for the development of data-driven decision-support systems in athlete profiling, talent identification, and sport-specific selection.
This study explores the scientific and methodological foundations for integrating gamification and Bloom's taxonomy into secondary computer science education through the development and testing of the BilimQuest e-learning portal. The portal was designed to structure learning tasks according to Bloom's cognitive hierarchy while embedding motivational game elements such as points, badges, and challenges. An experimental study with 312 fifth-grade students from three schools in East Kazakhstan tested whether integrating gamification with Bloom's taxonomy improves motivation, conceptual understanding, and practical skills. Students were divided into an experimental group using BilimQuest and a control group with traditional instruction. The experimental group used BilimQuest during informatics lessons, while the control group followed traditional instruction. The hypothesis was tested using Pearson's chi-square (chi 2) analysis. Results showed significant improvements across all three components. Teachers noted that the platform's analytics supported real-time progress tracking and informed instruction. Based on these findings, it is recommended that gamified digital learning environments be systematically aligned with Bloom's taxonomy to support higher-order cognitive development and formative assessment in secondary education. The study concludes that the deliberate alignment of gamification with Bloom's taxonomy constitutes a robust pedagogical approach for digital learning environments, with both theoretical and practical relevance for digital pedagogy and the professional preparation of future educators.
The growing global demand for health and wellness tourism highlights the importance of the effective use of natural and recreational resources in Kazakhstan’s regions. In this regard, the Kyzylorda region, which possesses significant natural therapeutic resources, offers considerable opportunities for tourism development. The aim of this study is to provide a comprehensive assessment of the potential for health and wellness tourism development in the Kyzylorda region. The research employs literature review, statistical analysis, comparative analysis, natural-resource assessment, SWOT analysis, and a systems approach. The study evaluates the region’s natural therapeutic resources, as well as the condition of sanatorium-resort infrastructure and tourist flow dynamics. The findings demonstrate that the region has substantial potential for health and wellness tourism development; however, its effective utilization is constrained by insufficient infrastructure, limited transport accessibility, shortages of qualified personnel, and weak marketing promotion. Based on the SWOT analysis and international best practices, a conceptual framework for the phased development of a competitive health and wellness tourism product is proposed. The practical significance of the study lies in the development of recommendations aimed at infrastructure modernization, certification of natural therapeutic resources, digital promotion of tourism services, and the sustainable development of the region.
This article examines the process of developing Kazakhstan's tourism brand and the development of a strategy, model, and promotion tools. It examines the theoretical and practical aspects of developing the country's national tourism brand. International tourism branding practices are analyzed, and the work of Kazakhstani scholars on this topic is examined. It is noted that although the global tourism industry is far from perfectly sustainable, sustainable tourism impacts the quality of life of local communities. A SWOT analysis of tourism brand promotion is conducted, highlighting the strengths and weaknesses of Kazakhstan's tourism product, and proposing several options for a basic brand concept. The proposed brand concept is based on the integration of natural diversity, rich history, and culture, emphasizing authenticity and openness. A model for developing the country's tourism brand is proposed, along with brand promotion tools that will increase Kazakhstan's recognition as a tourist destination in key global markets. The development of a KPI matrix for Kazakhstan's tourism brand and a brand implementation roadmap will enable effective promotion of the national brand, increase tourist flows and average tourist spending, implement local initiatives for sustainable growth in the tourism industry, and create a modern digital ecosystem platform for promoting and selling tourism products. Implementing the authors' proposals will engage local communities, boost regional economies, and make them competitive.
This study analyzes the cultural, disciplinary and organizational factors in the use of Artificial Intelligence (AI), and reveals the key role of teachers in the digital transformation of higher education. Respondents are representatives of different professional fields and countries, but the sample examines their participation through the prism of a global interdisciplinary perspective. It is assumed that the affiliation of university teachers to a particular professional field determines their attitudes towards the integration of Artificial Intelligence in teaching. A standardized questionnaire is applied, which includes: demographic information; experience with AI; attitude scales adapted from specific models; resistance to the use of AI; understanding of the potential of AI and understanding the risks of integrating it into the learning process. Data are analyzed using descriptive statistics, ANOVA/MANOVA for group differences, regression analysis and SEM for determinants of the intention to use AI, cluster analysis for user profiling and thematic coding of open-ended responses. Thus, the study contributes to the understanding of the mechanisms through which personal motivation, professional identity and institutional environment interact to shape attitudes towards the use of AI. The results show diverse disciplinary perspectives and reveal the dual nature of the process of integrating AI in higher education: 1) They identify a need for both positive attitude formation and digital skills development; 2) They clarify the determining importance of professional fields - as specific, organizational and cultural contexts in which technologies are introduced. The conclusions practically contribute to the adaptation of higher education to the digital age.
