The development of self-regulated learning (SRL) skills, including the ability to plan, monitor and reflect, is increasingly recognised as essential for academic success in online learning environments. Despite this, most digital learning platforms continue to provide limited feedback, typically focused on task outcomes rather than learning processes. This study investigates the effectiveness of an artificial intelligence-based feedback system integrated into a standard online course platform. The system delivers adaptive, process-oriented feedback by analysing anonymised engagement summaries and short reflective inputs, aiming to promote self-regulated learning strategies without requiring additional instructor involvement or manual input for feedback generation. A quasi-experimental study was conducted with 180 undergraduate students enrolled in a fully online course. Participants were pseudo-randomly assigned by an automated allocation script to an experimental group (n = 90) receiving AI-based adaptive feedback or a control group (n = 90) with standard LMS features. The system employed behavioural indicators (e.g., time-on-task, quiz activity and content engagement) and natural language analysis of reflective entries to generate personalised prompts related to goal-setting (including time management), effort regulation and metacognitive reflection. Data sources included post-course surveys, aggregated system interaction records, academic performance data and open-ended student feedback on the system’s perceived effectiveness and usability. Students who received adaptive feedback exhibited significantly stronger engagement with SRL behaviours, including earlier task initiation, increased use of optional learning resources and greater consistency in study routines. Qualitative responses indicated that participants found the feedback clear, timely, actionable and supportive of their cognitive and motivational processes. In contrast, control group participants primarily relied on grade-based feedback and exhibited fewer strategic adjustments during the course. The findings suggest that a lightweight, AI-driven feedback mechanism can be effectively integrated into online course platforms to support SRL at scale. This study demonstrates how adaptive AI feedback can meaningfully influence academic outcomes, planning behaviour and engagement with feedback in digital learning environments.

Artificial Intelligence (AI) opens up new perspectives for the transformation of distance learning; however, there is still no clearly structured methodological framework for the development of effective AI-based learning platforms. This study proposes the framework model “learning behavior – AI-oriented scenarios”, which aims to identify key pedagogical and technological factors that contribute to effective learning in a digital environment. Based on an analysis of the scientific literature in educational technologies and the use of AI in teaching, the main characteristics of learning behavior are identified: personalized goal setting, adaptive response to feedback, and autonomous engagement. These characteristics correspond to constructivist and experiential approaches to learning. The study examines how intelligent recommendation systems, adaptive content, and AI-based learning behavior analytics contribute to the development of these characteristics and enhance educational outcomes. As an example, a case study is presented on the development of a prototype AI platform for distance learning, whose effectiveness is supported by survey results demonstrating increased student motivation and engagement. The findings address three key research questions and contribute to the theoretical and methodological foundation for integrating AI into the design of distance education.

This review examines scientific and engineering strategies for adapting bituminous and asphalt concrete materials to the highly diverse climates of Central Asia. The region’s sharp gradients—from arid lowlands to cold mountainous zones—expose pavements to thermal fatigue, photo-oxidative aging, freeze–thaw cycles, and wind abrasion. Existing climatic classifications and principles for designing thermally and radiatively resilient pavements are summarized. Special emphasis is placed on linking binder morphology, rheology, and climate-induced transformations in composite bituminous systems. Advanced characterization methods—including dynamic shear rheometry (DSR), multiple stress creep recovery (MSCR), bending beam rheometry (BBR), and linear amplitude sweep (LAS), supported by FTIR, SEM, and AFM—enable quantitative correlations between phase composition, oxidative chemistry, and mechanical performance. The influence of polymeric, nanostructured, and biopolymeric modifiers on stability and durability is critically assessed. The review promotes region-specific material design and the use of integrated accelerated aging protocols (RTFOT, PAV, UV, freeze–thaw) that replicate local climatic stresses. A climatic rheological profile is proposed as a unified framework combining climate mapping with microstructural and rheological data to guide the development of sustainable and durable pavements for Central Asia. Key rheological indicators—complex modulus (G*), non-recoverable creep compliance (Jnr), and the BBR m-value—are incorporated into this profile.

Today, the use of digital technologies and their integration into the education system is of great importance worldwide. In this regard, the President of Kazakhstan's Address in 2023, under the program “Modernization of the Education System,” set the goal of enhancing students' ability to work with new technologies. Therefore, in general education schools, it is crucial to improve students’ knowledge levels and foster their creative abilities through modern technologies while preparing them for informatics Olympiads. On this basis, the role of MOOCs (Massive Open Online Courses) in preparing secondary school students for Olympiads is particularly significant. This article examines the importance, effectiveness, and features of MOOCs in the global educational field. It also discusses the role and structure of MOOCs in the context of modern education, ways to increase their efficiency, and their impact on the learning process. Furthermore, the article analyzes the results of studies by domestic and international researchers aimed at identifying the significance of using MOOCs in the Olympiad preparation process. For the research, a special survey was conducted among school students. The diagnostic survey involved 13 schools in the city of Atyrau. According to the survey results, it was found that using MOOCs is effective for preparing school students for Olympiads and serves as a tool for increasing their interest in learning. Thus, future research aims to determine the importance of MOOC-based teaching in preparing for informatics Olympiads and to conduct further studies in this direction.

The article addresses the pressing issue of STEM teacher preparation in Kazakhstan, highlighting key challenges and proposing a structured approach to improving teacher education. A comprehensive literature review reveals that while effective STEM pedagogical strategies exist, there are still significant barriers to successful implementation. These include insufficient teacher preparedness, the absence of structured curricula or guidelines, a lack of educational resources, and the rigid organizational structure of educational institutions. To address these challenges, the study employs a range of theoretical methods aligned with its research objectives. The methodological foundation is based on a systematic, competency-based, and activity-based approach, integrating principles of constructive alignment, inquiry-based learning, and interdisciplinary education. These frameworks guided the development of the “Physics in STEM” course for future teachers. The course is designed to enhance pedagogical competencies, fostering problem-solving, critical thinking, and interdisciplinary connections. By offering an innovative framework for STEM teacher preparation, the study contributes to advancing Kazakhstan's education system, ensuring that future educators are well-equipped to integrate STEM disciplines effectively in their teaching practices. This research has broader implications for STEM education development, providing valuable insights for curriculum designers, policymakers, and teacher training institutions.

1. In recent years, the integration of technological tools into education has significantly transformed teaching and learning practices. Within the STEM (Science, Technology, Engineering, and Mathe...