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THE EFFECT OF GEOGEBRA ON ACADEMIC PERFORMANCE OF HIGH SCHOOL STUDENTS IN GEOMETRY LEARNING
(SDU University, 2026) Abdualiyeva G.
This study investigates the effect of integrating GeoGebra into geometry instruction on students’ academic performance at the high school level. The research was conducted among students in 10-th grade from “125 High School” in Kyzylorda city. The primary purpose of the study was to examine whether the use of dynamic geometry software GeoGebra contributes to improved learning outcomes in geometry. A quasi-experimental research design with pre-test and post-test measures was adopted. The participants included 35 students, who were assigned to experimental and control groups. The findings revealed that students who learned geometry through GeoGebra showed greater improvement in geometric understanding and higher post-test scores than those in the control groups. These results suggest that GeoGebra facilitates deeper comprehension of geometric concepts and supports active student engagement in the learning process. Overall, the study demonstrates that the integration of digital tools such as GeoGebra can effectively enhance geometry learning and represents a valuable auxiliary tool to traditional instructional approaches in mathematics education.
The Effect of Artificial Intelligence on Secondary School Students' Self-Learning of Fractions
(SDU University, 2026) Salamatkyzy M.
This study examines the effect of an artificial intelligence-based intelligent tutoring system (MATHOS AI) on academic achievement in fractions and selfregulated learning among Grade 5 secondary school students. The research design includes an achievement test and a questionnaire measuring self-regulated learning (MSLQ). The study involved two groups: the control group received traditional instruction, while the experimental group was taught using the MATHOS AI platform. The study aimed to analyze the differences between the experimental and control groups in understanding fractions and developing selfregulated learning. The primary focus of the research was to measure students' academic achievement and the development of their metacognitive skills. The results of the study demonstrate that instruction based on MATHOS AI has a positive effect on both academic achievement in fractions and the development of self-regulated learning among students. These findings confirm the importance of implementing intelligent tutoring systems, such as MATHOS AI, in mathematics education programs in Kazakhstani schools.
Numerical Methods for HJB Equations in Option Pricing with Greek Sensitivities
(SDU University, 2026) Berikbayev K.
Usually, optimal control problems in financial mathematics are solved by maximizing profit and using the Hamilton-Jacobi-Bellman equation. This leads to nonlinear PDE, the solution of which is based on numerical methods. In this paper, we use the method described in the article by Christara and Wu: second-order finite differences on a non-uniform grid. However, instead of the long position discussed there, we study the short position. Therefore, here too we use the same time step, calculated using the Crank-Nicolson-Rannacher method, and we employ an iterative solver with a penalty term. The nonuniform grid puts more nodes near the strike price. This is important for keeping second-order convergence when the straddle payoff is not smooth. Rannacher smoothing at the first time steps helps remove unwanted oscillations from the kink in the initial condition. The nonlinear penalty-like term comes from the optimal control in the stock borrowing fee model. We solve it at each time step with a Newton-type iterative algorithm that uses two stopping criteria. Our numerical tests show secondorder convergence for the short position. The results agree with the benchmarks of Forsyth and Labahn and also Christara and Wu. The main result of this work is the numerical calculation of the Greeks for this nonlinear HJB model: Delta, Gamma, and Theta. As far as we know, there is no other full numerical study of the Greeks for the short position using finite differences on HJB problems. This is the main applied result of our work.
The Role of Adapted English Course Books in Vocabulary Enhancement of Intercultural Communicative Competence
(SDU University, 2026) Baktybayeva A.
In light of globalization and growing needs for intercultural communication, English language teaching (ELT) has moved away from focusing exclusively on linguistic competence to also focusing on developing intercultural communicative competence (ICC). Vocabulary plays a significant role in this, as vocabulary is one of the major means of expressing and interpreting cultural meaning. Additionally, adapted English coursebooks are becoming more widely utilized in a growing number of educational contexts around the world, including Kazakhstan, to ensure that what is being learned is relevant to the learner and that it is accessible. The purpose of this research is to examine how adapted English textbooks assist students with their vocabulary acquisition and thereby help them to develop their intercultural communicative competence. Qualitative research methods were used to conduct this study and the data were gathered from semi-structured interviews conducted with instructors of the English language. A thematic analysis of the data was conducted to find common themes in the responses from the instructors regarding their experiences, perceptions, and practices in their classrooms. The report serves as a contribution to knowledge of the literature concerning the adaptation of coursebooks for use in Kazakhstan and also shows how vocabulary learning and intercultural competence are connected.
The Impact of Remote Work on Employee Well-Being in Small and Medium-Sized Enterprises
(SDU University, 2026) Sakhipkereyeva A.
In the post-pandemic period, the remote work format was transformed from an emergency measure into a stable component of modern labor relations. Despite the obvious advantages in the form of flexibility and autonomy, the transition to remote management creates specific challenges for small and medium-sized enterprises (SMEs), which traditionally operate in conditions of limited financial, technological and human resources. This dissertation is devoted to the analysis of the impact of remote work on the well-being of SME employees, with a special focus on such parameters as mental health, job satisfaction, quality of organizational support and productivity. The theoretical foundation of the research is based on the synthesis of the theory of self-determination and the model of "requirements and resources in work" (JD-R model). The empirical part was performed within the framework of the quantitative paradigm: data collection was carried out through a survey of SME employees in Kazakhstan, and subsequent verification of hypotheses was carried out using the structural modeling method (PLS-SEM) in the SmartPLS 4 software environment. The results of the study demonstrate that the well-being of staff in a remote format is determined not so much by the availability of digital tools as by the quality of "soft" management factors: clarity of communications, regularity of feedback from management, emotional support and respect for the boundaries between professional and personal life. The author concludes that remote work becomes a driver of productivity in the SME sector only if it is administered as a human-centered organizational practice, and not as a purely technical solution for changing the workplace location.