This study aimed to describe the profile of professional collaboration among students in teacher-education programmes and to examine whether readiness for further collaboration is associated with prior experience. The work was conducted within a university grant of Abai Kazakh National Pedagogical University and implemented as a descriptive–comparative study based on a posttest cross-sectional snapshot with no baseline measurement. Data were collected via Google Forms from 91 students of the Department of Primary Education (Years 1–4). The questionnaire covered collaboration experience (yes/no), frequency of participation in joint projects, perceived value of collaboration (1–5), perceived impact on the learning experience, readiness to participate in joint research/projects in the future (1–5), and open-ended questions on motivations, barriers, and expected university support. Prior collaboration experience was reported by 40.7% of respondents; participation was predominantly irregular (48.4% “never”, 44.0% “rarely”). Perceived value was high (M = 4.05, SD = 1.15; Me = 4), and most respondents reported a positive contribution to their learning experience (75.8%). Readiness for future participation was moderately high (levels 4–5: 52.7%). A Mann–Whitney test indicated higher readiness among students with prior collaboration experience (U = 1288, p = 0.016, r = 0.29). Thematic grouping of open-ended responses showed that knowledge sharing and mutual support were the dominant motivations, while organisational/time and communication barriers were most frequently mentioned; the most commonly requested support measures included regular joint events and support for student communities. Findings are interpreted as a descriptive snapshot rather than causal evidence. The results may inform the design of facilitated collaboration formats and subsequent monitoring of student readiness.

The trajectory of digital progress in Kazakhstan has highlighted several challenges within the primary education system. A critical component of developing digital design skills (DDS) lies in the impact of innovative educational technologies on these skills. Despite the potential of such technologies to enhance DDS and engage students in digital literacy, the existing literature falls short in exploring this area comprehensively. The study aims to examine students’ DDS and examines how innovative educational learning technology affects these skills. This study used a quantitative research approach to measure innovative educational learning technology’s impact on primary school students’ DDS. The experiment involved 120 participants and uncovered several key insights. The deficiency in DDS and lack of motivation revealed by the study called for systematic changes in how digital literacy is taught. These changes included restructuring curricula, enhanced teacher training, access to digital resources, and more engaging, practical learning environments. The study demonstrated substantial improvements in students’ DDS following the introduction and testing of the author’s academic program with the experimental group (EG) participants. The findings from this study can serve as a foundation for developing strategies to enhance DDS in primary school and provide a methodological basis for adapting educational programs to support DDS development.

This study examined whether supervised peer mentoring was associated with adaptation trajectories among first-year repatriate students and explored programme-record patterns that could help interpret the observed quantitative trajectories. A longitudinal quasi-experimental mixed-methods design was used with 400 students: 204 in the mentoring condition and 196 in a delayed-access comparison condition. Academic adaptation, perceived social support, and acculturative stress were assessed at three time points during the 2024–2025 academic year. Quantitative data were analysed using three-level linear mixed-effects models with academic-group random intercepts, covariate adjustment, and CR2 cluster-robust sensitivity analyses. By T3, the mentoring condition showed more favourable changes in academic adaptation (Hedges’ g = 0.39), perceived social support (g = 0.29), and acculturative stress (g = −0.35). Qualitative analysis of 222 mentor reports, supervision records, and de-identified case summaries identified recurrent documentary patterns involving procedural clarification, lower-threshold help-seeking, and supported social participation. It also identified low-engagement cases, unresolved institutional barriers, mentor-dependence risks, and procedural gains without broader social integration. These findings support supervised mentoring as a feasible adjunct to usual university services. Because allocation was non-random and institutional translation was not directly measured, the results should be interpreted as programme-associated differences and theoretically informed process interpretations rather than as causal or mediation evidence.

The trajectory of digital progress in Kazakhstan has highlighted several challenges within the primary education system. A critical component of developing digital design skills (DDS) lies in the impact of innovative educational technologies on these skills. Despite the potential of such technologies to enhance DDS and engage students in digital literacy, the existing literature falls short in exploring this area comprehensively. The study aims to examine students’ DDS and examines how innovative educational learning technology affects these skills. This study used a quantitative research approach to measure innovative educational learning technology's impact on primary school students’ DDS. The experiment involved 120 participants and uncovered several key insights. The deficiency in DDS and lack of motivation revealed by the study called for systematic changes in how digital literacy is taught. These changes included restructuring curricula, enhanced teacher training, access to digital resources, and more engaging, practical learning environments. The study demonstrated substantial improvements in students’ DDS following the introduction and testing of the author's academic program with the experimental group (EG) participants. The findings from this study can serve as a foundation for developing strategies to enhance DDS in primary school and provide a methodological basis for adapting educational programs to support DDS development.

The school period is critical for developing health‐related knowledge, attitudes and behaviours. However, evidence on primary school students' perceptions of school‐based health‐preserving practices and engagement with health‐related educational content remains limited in Kazakhstan. This cross‐sectional survey of 1750 primary school students aged 6–12 years in Kazakhstan assessed perceived health awareness, attitudes, perceived cognitive impact and health‐related learning engagement. Psychometric properties were evaluated using reliability and factor analyses, and associations were examined using correlation, regression and cross‐sectional path analyses. The hypothesized four‐factor model showed strong incremental and residual fit (CFI = 0.972, TLI = 0.964, SRMR = 0.034), although RMSEA was elevated (0.087) and discriminant separation was incomplete for selected domains. Health‐related learning engagement was positively associated with perceived health awareness, attitudes and perceived cognitive impact, with the multivariable model explaining 60.6% of its variance ( R ² = 0.606, p < 0.001). Language of instruction and grade level were also associated with engagement through direct and indirect statistical pathways. Overall, the findings support a four‐dimensional framework of closely related health‐related perceptions and educational engagement among primary school students. The instrument assesses self‐reported perceptions and engagement rather than objective health knowledge or actual health behaviours, warranting cautious interpretation and further validation.

The article explains the theoretical analysis of the fundamentals of artificial intelligence and the structural and substantive features of the preparation of future primary education teachers for the use of artificial intelligence. The effective functions of using artificial intelligence tools reflect the learning needs of students, the study of learning style, the regulation of objective characteristics in testing knowledge, and the creation of a digital environment. The main features of the motivational, cognitive, design-practical, and reflexive components of training future primary education teachers to use artificial intelligence elements at high, medium, and low levels are outlined. The motivational component here is characterized by the interest of the future primary education teacher in the elements of artificial intelligence, the desire for its application and awareness of its importance, and the presence of a positive attitude towards digital technologies. The article defines the depth, scope of understanding, and level of cognition of cognitive AI. The design and practical component explains that the professional activities of future teachers are not limited to teaching, but consist in the integrity of organizational, analytical, design, evaluation, and management activities along with teaching. The reflexive component states that in order for any type of activity it requires experience, critical evaluation of the result, identification of shortcomings and difficulties, and finding ways to prevent it.The empirical section analyzes the overall level of training of future primary education teachers to use artificial intelligence elements at the detection stage. In accordance with the components of training future primary education teachers to use artificial intelligence elements as diagnostic methods, a summary of author’s questionnaires, tests, practical and reflective tasks is given. In order to verify the statistical uniformity of the initial training levels of the experimental and control groups, the Pearson criterion χ2 was used at the determination stage.