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The Impact of Mental Health Awareness on Leadership and Employee Engagement
(SDU University, 2026) Kalmaganbet Sh.
Employee mental health has grown to becoming a more critical issue for organizations who want to create a healthier and more productive workplace for their employees. This study looks at the effects of mental health training in organizations on employee engagement, and investigates the mediating effects of organizational leadership support and the psychological safety climate, and the moderating effect of organizational trust. Based on the Job Demands–Resources (JD-R) model, the study suggests that mental health awareness is an organizational resource that can positively affect the employee's engagement both directly and indirectly. The data were obtained using a structured survey, and analyzed using the analysis methods of Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that there is a positive relationship between mental health awareness in the organization and employee engagement. In addition, the role mental health awareness plays in leadership support and psychological safety partially mediates the link between mental health awareness and employee engagement. The results also reveal that organizational trust further enhances the positive connection between mental health awareness and employee engagement. Further analysis showed variations in strength of some relationships by generation. This study builds on a growing body of literature on workplace mental health by pointing to the value of cultivating mental health awareness, practices of supportive leadership, psychological safety, and organizational trust. The findings offer implications for organizations aiming to foster healthy workplaces and enhance employee engagement.
Moduli of smoothness and growth properties of Hartley transform
(SDU University, 2026) Ozbek U.
This study analyzes how the moduli of smoothness of functions influence the behavior of their Hartley transforms. While harmonic analysis has historically centered on the Fourier transform, the Hartley transform offers a computationally efficient, real-valued alternative for processing real data. The analysis establishes key results, including variants of the Riemann–Lebesgue lemma adapted to the Hartley transform context, the Parseval identity, and the proof of the Hausdorff–Young inequality applicable in Euclidean spaces. By employing the symmetric difference operator, we derive weighted estimates that link the smoothness properties of a function, measured by higher-order moduli of smoothness, to the decay rates of its Hartley transform. Additionally, the investigation extends to Hartley series on the torus, where conditions for convergence and decay of coefficients are formulated through the corresponding moduli of smoothness..
Improving the methodology of distance learning mathematics for students in grades 5-6
(SDU University, 2026) Yegeubekov Y.
This study investigates the effectiveness of distance learning mathematics instruction for sixth-grade students through the use of video-based lessons and interactive digital tools. The research employed a quasi-experimental pretest–posttest design involving two sixth-grade classes in a private school in Kazakhstan, with one experimental group and one control group. The intervention included teacher-created instructional videos, Wayground and Kahoot activities, and structured online learning tasks. Data were collected through pre-tests and post-tests measuring students’ academic achievement in mathematics. The findings showed significant improvement in both groups after the intervention. The experimental group demonstrated higher engagement and positive learning outcomes, the difference between the groups was statistically significant. The results suggest that digital tools and video-based instruction can support student engagement and enhance the effectiveness of distance mathematics learning.
The Impact of Gamified Learning Strategies on Student Achievement in Algebra and the Fundamentals of Analysis
(SDU University, 2026) Gubasheva A.
This study examined the impact of gamified learning strategies on Grade 10 students’ achievement in Algebra and the Fundamentals of Analysis and explored students’ perceptions of the gamified learning experience. A quantitative quasiexperimental design was used with 58 tenth-grade students from one school in Kazakhstan, including 29 students in the experimental group and 29 students in the control group. The intervention focused on derivative-based topics, including critical points, extrema, monotonicity, intervals of increase and decrease, and maximum and minimum values. A 25-item multiple-choice achievement test was administered before and after the intervention to measure students’ achievement. Students’ perceptions were measured using the GAMEFULQUEST questionnaire, which was completed by the experimental group after the intervention. The results showed that both groups improved from pre-test to post-test; however, the experimental group demonstrated greater improvement. The experimental group’s mean score increased from 10.28 to 17.52, while the control group’s mean score increased from 10.52 to 12.59. The posttest comparison showed a statistically significant difference in favor of the experimental group, t(56) = 5.27, p < .001, with a large effect size, Cohen’s d = 1.38. GAMEFULQUEST results indicated generally positive perceptions of the gamified learning experience, especially in the dimensions of Accomplishment and Guidance. The findings suggest that gamified learning strategies can support student achievement and create a positive learning experience in upper-secondary mathematics classrooms.
Collaborative Multi-Agent Chatbot Framework for Intelligent Tutoring and Feedback
(SDU University, 2026) Myrzaliyeva Zh.
Intelligent Tutoring Systems (ITS) seek to deliver a personalized approach akin to one-on-one human tutoring. The advent of large language models (LLMs) makes it possible to create conversational tutoring systems at a reasonable scale. Nevertheless, despite some recent advances, single-agent LLM-based tutoring still suffers from problems such as inaccuracies, varying quality of the pedagogical content, and low self-correction ability. In this dissertation, a Collaborative Multi-Agent Chatbot Framework (CMACF) for ITS and assessments is presented and evaluated. The system includes three agents: Tutor Agent, which generates adaptive explanations; Feedback Agent, which detects and corrects any potential misunderstandings; and Verifier Agent, which validates and optimizes responses prior to their delivery to the learner during Java programming lessons. For testing, the framework was used to perform 40 different Java tasks in the following domains: loops, conditionals, arrays, object-oriented programming, exceptions, and typecasting. A comparison between three frameworks was conducted based on three scenarios: single-agent system (SA), multi-agent system without verification (MA-NV), and the proposed multi-agentsystem with verification (MAV). The criteria applied included correctness, clarity, pedagogy, actionability, and consistency of responses. It can be concluded that the proposed model resulted in the best scores (4.52 points) and surpassed both the single-agent solution (4.165) and the multi-agent solution without verification (4.215). In addition, 25% of generated responses were subject to changes due to the verification component and improved task completion rate from 17.5% to 52.5%. Although the response generation time of MA-V (11.1 seconds) exceeded the single-agent solution (3.66 seconds), its quality is sufficient for intelligent tutoring purposes.