DSpace Repository

Nazarbayev University Repository (NUR) is an institutional electronic archive designed for the long-term preservation, aggregation, and dissemination of scientific research outcomes and intellectual property produced by the Nazarbayev University community and affiliated organizations.

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001. Theses 3318
002. NU Research Publications 11760
003. NU Research Institutes & Centres 586
004. NU Journals & Magazines 285
005. Forums, Conferences & Projects 1332

Recent Submissions

Access status: Open Access ,
Design and Implementation of a Compact Radar-Based System Using Planar Antenna Arrays for IoT applications
(Nazarbayev University School of Engineering and Digital Sciences, 2026-04) Abzhanova, Damilya; Alkenova, Aidana; Zhumadilov, Kairat; Yerkinbekuly, Ali; Hashmi, Mohammad
This capstone project presents the design, development, and implementation of a compact, low-cost Frequency-Modulated Continuous-Wave (FMCW) radar system optimized for Internet of Things (IoT) applications and contactless gesture recognition. To overcome the privacy risks and high computational demands of camera-based systems, a fully localized radio-frequency (RF) transceiver front-end was simulated and fabricated. The hardware chain maintains a highly compact physical footprint and integrates a planar microstrip patch antenna array, a Vivaldi antenna configuration, a Low-Noise Amplifier (LNA), a Power Amplifier (PA), a frequency mixer, and an RF directional coupler. Target reflections captured by the system were processed into raw radar data cubes to extract micro-Doppler signatures, Time-Velocity Profiles, and Range-Doppler Maps (RDMs). To enable intelligent edge-sensing, a Python-based machine learning framework was developed to classify discrete human hand gestures from the micro-Doppler data, achieving a robust classification accuracy of 92% on the test set. The experimental results demonstrate a successful integration of hardware miniaturization and smart signal processing, providing a scalable architecture for future gesture-controlled IoT interfaces.
Access status: Embargo ,
Unpacking English Language Teacher-Tutors’ Emotional Labour: Evidence from Kazakhstan
(Nazarbayev University Graduate School of Education, 2026) Nurmukhambetov, Yernur; Manan, Syed Abdul
Emotional labour has attracted growing attention in language education research, particularly in relation to English language teachers and their well-being. It refers to the regulation of emotions to meet professional expectations in the workplace. Although emotional labour has been widely explored across different educational contexts, little is known about how it is experienced by English language teacher-tutors who juggle teaching in state schools and providing private tutoring in Kazakhstan. To address this gap, this qualitative study investigates the emotional challenges faced by nine English language teacher-tutors in Kazakhstan and the strategies they employ to cope with these demands. The study is guided by Hochschild’s (1983) theoretical framework of emotional labour, with particular attention to surface acting. Data were collected through semi-structured interviews and analyzed thematically. The findings revealed that one of the main motivations for becoming a teacher-tutor was financial benefit. The analysis further showed that emotional labour was shaped by several interconnected factors, including heavy workload, time pressure, organizational pressure, classroom constraints, and surface acting. Participants attributed emotional labor to long commuting between workplaces, intensive schedules with few or no breaks, excessive paperwork, strained relationships with school administration, and experiences of burnout and emotional exhaustion. The study also found that family and peer support played a crucial role in helping teacher-tutors how to manage emotional challenges. In addition, participants relied on boundary-setting and self-regulation strategies to protect their well-being and cope with the pressures of their dual roles. In the end, the study offers practical recommendations for educational stakeholders to reduce the pressures placed on teachers and to create more supportive working conditions for English language teacher-tutors in Kazakhstan.
Access status: Embargo ,
Between Efficacy, Goals and AI: A Mixed-Methods Study of Students’ Generative AI Reliance in an EMI University of Kazakhstan
(Nazarbayev University Graduate School of Education, 2026-04-16) Tileukhan, Dariya; Kerimkulova, Sulushash
Despite the rapid integration of artificial intelligence into Kazakhstan’s higher education sector, the motivational mechanisms underlying students’ dependence on these tools remain underexplored, particularly the roles of academic self-efficacy and goal orientations. This study examines how these factors shape undergraduate students’ reliance on generative AI at an English-medium university in Kazakhstan. Specifically, it explores how different combinations of mastery and performance orientations, together with varying levels of self-efficacy, predict patterns of AI dependence and how students themselves interpret this reliance in their academic lives. A mixed-methods design was employed. Survey data were collected from 55 undergraduate students in the social sciences and humanities, and four semi-structured interviews were conducted to explore the meanings, motivations, and lived experiences underlying AI use. Guided by Goal Orientation Theory (Elliot & McGregor, 2001) and the Academic Self-Efficacy theory (Bandura, 1997), the findings show that academic self-efficacy is the strongest predictor of AI dependence. Students with lower self-efficacy reported significantly higher reliance on AI regardless of their goal orientation. Although the interaction effect between goal orientation and self-efficacy was not statistically significant, descriptive patterns aligned with the predicted hypotheses: mastery-oriented students with high self-efficacy showed the lowest dependence, whereas performance-oriented students with low self-efficacy showed the highest. Interviews further revealed that students use AI not only for efficiency, but also as emotional and linguistic support during moments of academic pressure and self-doubt. Overall, the findings suggest that AI dependence is shaped less by the technology itself and more by the motivational and psychological conditions within which learning occurs, and contextual factors like insufficient institutional support, highlighting the need for institutional initiatives to strengthen academic self-efficacy, foster critical and reflective AI use to prevent erosion of mastery experiences and skills, for instructors to design process-oriented assessments and for policymakers to address the long-term risks of AI reliance.
Access status: Embargo ,
Decolonizing History Education Critical Discourse Analysis of School History Textbooks in Kazakhstan
(Nazarbayev University Graduate School of Education, 2026-04-16) Baimetov, Muzaffar; Kerimkulova, Sulushash
Since independence, the Kazakhstani government has been actively rewriting and republishing history textbooks and redesigning history education programs to help revive the traditions, culture, and identity of the Kazakh population (Deyoung & Balzhan, 1997). However, history textbooks still face ongoing challenges in reassessing Kazakhstan’s historiography, as many historical interpretations remain influenced by soviet narratives (Burkhanov & Sharipova, 2024). The purpose of this study is to critically examine how Kazakhstan’s school history textbooks construct historical narratives with a particular focus on the transformation of colonial and decolonial discourses. Using Norman Fairclough's (2013) three dimensions of Critical Discourse Analysis, the study seeks to investigate how language framing and omissions shape the depiction of Kazakhstan’s past. Additionally, the study seeks to explore the implications of these representations for decolonizing historical knowledge and a more inclusive understanding of national identity in education. Data collected from the secondary school history textbook for Grade 7 (updated in 2025) in Kazakhstan. The findings section covered the analysis with four tables, such as lexical choice, nominalization, active, passive voice, and transitivity. These findings revealed four dominant representational patterns: the Russian Empire as a central imperial authority; the Cossacks as a military social group that served the Russian Empire and as part of a group in the Russian Army in the Kazakhstan region; the Kazakhs positioned as a collective social group; and Kazakh leaders as individualized political actors playing different roles in their opposition to tsarist administration. In addition, these present findings reveal that historical events are processes that seem inevitable and natural. This study will be beneficial for school history textbook studies, history teachers, and textbook writers. The research highlights how language shapes knowledge and identity, offering guidance for more balanced and decolonial revisions. Another one is that the study contributes to the literature on decolonization.
Access status: Open Access ,
PowerBook: A Web Platform for Habit-Building and Competitive Reading
(Nazarbayev University School of Engineering and Digital Sciences, 2026-04-24) Otegenov, Nurdaulet; Bakhtybayev, Nurislam; Aktoreyev, Bekzhan ; Sagyngali, Toktar; Keldibayev, Bektas; Askar Boranbayev
PowerBook is a web platform for building a reading habit through short, head-to-head competitions. Users log how long they read, join competitions that run for a fixed number of days, pick up XP and badges along the way, and - when the competition ends - take part in a gift exchange that pairs the heaviest readers with those who read less. Reading apps usually treat reading as a solo activity; our bet was that a bit of friendly pressure and a live leaderboard would do more for consistency than another streak counter.