This study investigates the application of augmented reality (AR) technology to facilitate collaborative learning in science education. The study involved 30 secondary school students in Kazakhstan, who were divided into an experimental group and a control group. The experimental group utilized an AR platform to facilitate collaborative learning during their science lessons, while the control group received traditional teaching methods. The study aimed to investigate the impact of AR on students’ learning outcomes, communication and collaboration skills, and overall satisfaction with science education. The research design involved pre- and post-tests, as well as a survey of students’ perceptions of the AR experience. The results indicated that the experimental group demonstrated statistically significant improvement in their science test scores compared to the control group. Furthermore, the students in the experimental group reported a high level of engagement and satisfaction with the AR platform, along with enhanced communication and collaboration skills. The study suggests that AR technology has the potential to improve collaborative learning in science education and provides new opportunities for engaging students and enhancing their learning outcomes. The findings have significant implications for educators interested in integrating AR technology into their teaching practices as well as for researchers exploring the use of AR in education. Further research is necessary to investigate the long-term effects of AR on learning outcomes and to determine the most effective methods for incorporating AR technology into science education.

— Augmented Reality is an emerging technology that holds vast potential for being used in pedagogy. The underlying technology of AR is becoming cheaper and ubiquitous every day as smartphones and tablets flood our markets. Numerous AR applications have been designed and developed for Android and IOS platforms to teach STEM subjects. The complexity and scope of such applications ranges from primary education to university education. Such applications have been developed in the developed and developing countries alike, however, there is still a need for such applications in Kazakhstan. This systematic literature review looked at developed Augmented Reality applications for teaching STEM subjects to High School children to develop a pathway for developing indigenous AR applications at the same scale. We identified a lack of standardize assessment tool for measuring success of AR studies. The results of the systematic literature suggest that Kazakhstani developers will need to focus on reducing technostress on children. Otherwise, the intended results may not be achieved as stress is counterproductive.

The object of this study is the analysis of questionnaire data using ontological modeling. The task relates to the fact that conventional methods for processing questionnaire data are often insufficiently effective when working with large volumes of information and do not make it possible to automate many analysis processes. As a result of the study, an ontology was designed that structures and analyzes questionnaire data, which allows for a more accurate identification of hidden relationships between variables. Using these theoretical provisions, an information system for assessing the quality of assimilation of preschool children's competencies was built. 150 children from various preschool organizations were involved in the study as respondents. The data integration method proposed in this paper significantly facilitated the process of data analysis both for a group and for an individual respondent. The key difference of the proposed methodology is the automation of routine data analysis operations based on the ontological structure, which significantly simplifies the processing of large volumes of information. This makes it possible to solve the problem of limitations in conventional analysis methods and makes data analysis more scalable and reproducible. The practical application of the results is possible in marketing for analyzing customer satisfaction, market segmentation, and evaluating the effectiveness of advertising campaigns. In the educational domain, the ontology could be used to evaluate the quality of programs and analyze respondents' opinions, and in sociology – to analyze public opinion and conduct research on social phenomena. Thus, the proposed ontology provides an effective tool for analyzing large volumes of questionnaire data, allowing organizations to make more informed decisions and improve their efficiency

The systematic review uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to explore the development of teacher digital competence (TDC) through various digital technologies. With an emphasis on the technological pedagogical content knowledge (TPACK) framework, the study synthesizes findings from recent peer-reviewed articles to evaluate the integration of technologies such as massive open online courses (MOOCs), serious games, Internet of Things (IoT), and immersive virtual reality (VR) into educational practices. The review highlights the transformative potential of these technologies for enhancing teachers’ pedagogical strategies, fostering digital competence, and addressing gaps in educator training programs. Findings indicate that digital technologies improve immediate teacher competencies and pave the way for more interactive and inclusive learning environments. However, the small number of included studies (n = 10) and other limitations such as short-term study designs and English language only publications highlight the need for future research. The findings offer actionable insights for curriculum design, policy development, and professional training programs to equip educators with the digital competence necessary to thrive in modern educational landscapes.

One of the important elements of the information infrastructure of educational institutions is the information and educational environment. The information and educational environment of preschool education organizations has its own characteristics, which must be taken into account when building a model for managing information processes. The object of study in this work is the information and educational environment for preschool education organizations. The problem to be solved is the need to develop a model for managing data and information processes, which will allow determining the learning outcomes of preschoolers and adjusting individual work with them. The introduction of the developed model allowed to reduce the time spent on adjusting individual work with students by 30 %. These results are explained by the optimization of information processes, as well as improved monitoring of the formation of skills of preschoolers and a reduction in the time for its implementation. When monitoring for each child, 211 indicators are examined. There are 633 indicators per year for three monitoring, in aggregate, per one child. By default, the data is entered into Microsoft Excel and processed manually. However, a large number of entries slows down the processing of Microsoft Excel data and increases the chance of errors. The use of this model will make it possible to carry out calculations automatically, save data and generate reports for each child or group of children. The developed model can be used in information and educational environments for preschool education organizations in order to improve the efficiency of monitoring and managing educational processes

The relevance of this study is predetermined by the lack of models and algorithms for managing the formation of IT competencies in children of senior preschool age in the information and educational environment of a preschool organization. The object of the study is the process of managing the formation of IT competencies in children of senior preschool age. The problem under study is the need to build an effective system for assessing and managing the level of IT competencies, taking into account the uncertainty and subjectivity of assessments, as well as ensuring flexibility and adaptability of the process of developing competencies. The constructed model based on fuzzy logic takes into account the uncertainty of assessments and decomposes competencies into indicators of achievement (low, medium, high levels). The production model of knowledge representation based on fuzzy inference rules enables control adaptability. As a result, recommendations were compiled for assessing and developing competencies taking into account the individual characteristics of children and the educational environment. The approaches and tools proposed in this study help improve the quality of preschool education by providing teachers with effective tools for managing the educational process in the context of digitalization. The essence of the results is to build a model that makes it possible to integrate uncertain and subjective data into the process of assessing IT competencies, providing more accurate and objective assessments. The results could be used in the information and educational environments of preschool organizations, as well as in education systems that introduce modern technologies for assessing and managing competencies