The current stage of Kazakhstan’s development is characterized by the formation of a digital economy. One of its aspects involves improving the quality of education through its digital transformation. This approach aligns with modern global trends that facilitate the active development and operation of software, hardware, and robotic systems for organizing, maintaining, monitoring, and managing the educational process. Consequently, the objective of this study is to develop a concept for an intelligent robotic assistant to aid in conducting school lessons. The object of the study is physics lessons conducted in the primary and secondary schools of Kazakhstan until the completion of training.
Methods
For the digital transformation of the research object, methods of system analysis, graphical methods, simulation modeling, and object-oriented design were employed. Formal models of the application features of these methods were created, describing the input and output data, as well as their role within the digital assistant concept.
Results
The digital assistant concept comprises a hardware model and an autonomous robot, detailing its core functionality and its interaction with all participants in the educational process. The robot’s social functions have been defined: demonstrating educational material, answering student questions, and monitoring student behavior and classroom conditions. The structure of the educational content, utilized in the form of technological maps, has been established. Based on this, a digital twin system has been developed, implementing a scenario for the functioning of the intelligent assistant during a lesson in a virtual environment.
Conclusion
The developed concept provides a unified approach to teaching school children, creating conditions for the formation of individual educational trajectories and a favorable, comfortable learning environment. The obtained results constitute a comprehensive educational model that establishes a unified digital ecosystem for the educational organization.
artificial intelligencedigital systemdigitalizationEdTecheducationquality educationThe author(s) declared that financial support was not received for this work and/or its publication.section-at-acceptanceSTEM EducationIntroduction
According to UNESCO, the contemporary stage of social advancement displays a crisis in the quality and lack of quality education (UNESCO, 2025). It is noteworthy that, under the given circumstances, transformation in education is possible, yet it requires the implementation of a scope of measures. These measures should be of an integral and long-term nature as regards the learning process, align with the political, economic, and sociocultural contexts of the country which passes the reforms in education, should have sustainable funding, help promote inclusion, equity, and gender equality in all educational curricula, employ digital technologies, improve teaching skills, and invite stakeholders into the sector.
Education should rely on an integrated, continuous, and comprehensive approach that would develop and ensure the wellbeing of not just some individual students but also the society as a whole (Biancardi et al., 2023; Jones et al., 2021; Narvaez Rojas et al., 2021). Any changes (either local or large-scale and systemic) shall necessarily address the requirements of the social contract defined in each particular state (Kowalczuk-Walędziak et al., 2022; Shahjahan et al., 2022). By way of example, the decision of the People’s Republic of Bangladesh to strengthen the social status of teachers by celebrating World Teachers’ Day at the national level (Kabir and Ahmed, 2024). This became part of the strategy aimed at improving professionalism in teaching and empowering teaching staff. The Education Development Strategy of the Republic of Lebanon focuses on financial support for the students’ families to help reduce the economic burden and eliminate exploitation of child labor, or prevent early marriage (El Hayek, 2023). The given examples demonstrate how transformation in education can vary depending on the region.
Education in Kazakhstan represents no exception and undergoes modernization (Želvys et al., 2021; McLaughlin et al., 2023). The leading vector of its development is the development and implementation of digital tools to improve quality and ensure international competitiveness (Nurbekova and Nurbekov, 2023; Zarubina et al., 2024; Sabzalieva, 2022). Kazakhstan is the first country in Central Asia to be granted international accreditation for quality assessment systems (Madeniet Portaly, 2025). Nowadays, the entire scope of educational materials is provided and accessible for use in a digital format (for instance, the database of the digital educational platform Online Mektep comprises some 24 thousand lessons in different school subjects available in the Kazakh and Russian languages) (Madeniet Portaly, 2025). For the purposes of ensuring access to such resources, approximately 1,700 schools are provided with satellite internet access (Official Information Resource of the Prime Minister of the Republic of Kazakhstan, 2025). For the purposes of keeping high availability of education, approximately 800 new schools were built and commissioned, and approximately 5,000 already functioning schools were modernized over the period from 2022 through 2025 (Central Communications Service under the President of the Republic of Kazakhstan, 2025). To integrate Kazakhstan’s education system with the education systems that meet contemporary international standards, the reforms are being passed in relation to transition to the 12-year education and implementation of a multilingual approach (50% of the subjects on curriculum should be taught in the Kazakh and Russian languages, 20% in a second language, and 30% in English) (Madeniet Portaly, 2025).
Consequently, all conditions for the digital transformation of education are created at the state level, namely, the introduction of robotics-based software and hardware solutions, artificial intelligence, machine learning, and the Internet of Things into the educational process. Given the above, the purpose of the research study is to investigate effective teacher workload distribution at the lesson, involving a digital intelligent assistant.
The scientific novelty of the study lies in the development of a comprehensive educational model based on the principles of adaptive learning and control, the formation of functional literacy, and the design of personalized educational trajectories. The model integrates heterogeneous components—human capital, artificial intelligence, and robotic systems—into a unified educational ecosystem. This synthesis constitutes a significant contribution to pedagogical theory and didactics.
The theoretical significance of this study lies in advancing the theory of pedagogical interaction in the framework of the digital transformation of education. All main subjects taking part in the educational process, their roles, and functions within a looped digital educational ecosystem are defined. The obtained results can be used to refine scientific understanding of the organizational and functional forms of the digital educational settings. The developed digital assistant expands the use of simulators in education, as well as digital learning resources (including the interactive ones) and assistants (teachers, mentors, or tutors). The digital assistant is a tool for the formation of meta-subject knowledge, skills, and abilities and for developing cognitive strategies in students. Such results can be applied in further research studying the transformation of didactic pedagogy.
The practical significance of this study lies in the creation of a tool that overcomes terminological and linguistic barriers in following educational curricula. This contributes to promoting education and creates the environment for exporting Kazakhstan’s educational services. Furthermore, it creates an integrated educational climate in which students obtain a dynamic, personalized educational trajectory; teachers have an objective diagnostic and analytical tool for developing and making justified pedagogical decisions and can rely on the methodological support; and the heads of educational institution witness involvement and interest of a greater number of citizens in receiving education, improvement of effectiveness of the educational process, and systematical monitoring of it. As regards the state authorities, this implies the opportunity to obtain objective data on the state of education in the country to develop relevant educational strategies to meet the needs of the society.
Literature review
The global educational space is characterized as a complex, uneven, and multi-level process involving quantitative and qualitative transformations. These transformations are rooted in the pursuit of unity in approaches, goal-setting, content, terminology, categories, standards, and the assessment of outcomes on a geopolitical scale (Burbules et al., 2020; Moshinski et al., 2021). Its structure comprises numerous components that encompass national educational systems or groups of states and regions. Owing to the substantial number of qualitatively diverse national educational systems, the global educational space contains inherent contradictions. Consequently, various approaches emerge regarding the development of both local and global educational systems. The pace of their evolution is largely contingent upon adopted educational policies, which often reflect a country’s level of development (Hanushek and Woessmann, 2023; Shavkidinova et al., 2023). Developed and developing states are increasing funding for education, thereby stimulating research in the pedagogical sciences and fostering innovations that align with societal needs and technological progress (Edelmann et al., 2023; Ermakova, 2020; Gorin, 2020). Thus, the principal directions associated with contemporary educational transformation can be delineated as follows:
Modernization of the infrastructure. Relevant research highlights key challenges faced by educational institutions, particularly those pertaining to the organization of data processing centers, the establishment of communication channels, and the effective utilization of devices for accessing digital educational resources and specialized platforms (Revko, 2021; Yakubov and Daminova, 2022; Berezi, 2024). Contemporary studies on school infrastructure transformation confirm the hypothesis that student development is influenced not only by curriculum content but also by spatial organization, which plays a critical role (Burbules et al., 2020; Cardellino and Woolner, 2020; Hamzenejad et al., 2025). Equipped classrooms alone are insufficient; equally important are multifunctional and communal spaces that provide flexibility for student development and socialization. Modern technologies, materials, engineering solutions, and architectural trends enable the implementation of projects that integrate equipped laboratories with flexible spaces designed to promote visual and psychological relief for students. This is especially important when conducting classes using information and communication technologies. A central emphasis in this research and related projects is the interdependence of spatial and methodological transformations within an educational institution’s ecosystem (Parveen and Ramzan, 2024; Pettersson, 2021; Rofi’i et al., 2023).
Development, testing, and implementation highlights of various digital systems within the educational process. One category of systems represents the educational methodological and educational organizational complexes that use adaptive algorithms and artificial intelligence technologies to improve efficiency of the processes related to scheduling classes, assessing the activities of all subjects of the educational process, mapping out the communication channels, etc. (Želvys et al., 2021; Ihichr et al., 2024; Jing et al., 2023; Tedeeva et al., 2024). Another class of such systems is designed to create individual educational trajectories, a practice-oriented approach to learning, and the creation of interdisciplinary and convergent connections. For instance, the use of simulation models mirroring the real processes for the educational purposes enables recreation of the conditions and specifics of different processes (mechanical, transport, environmental, biological, etc.) to conduct a virtual experiment to develop professional competencies and assess the degree of their formation when training the specialists in the field of vocational education and training (Karakozov and Samokhvalova, 2024; Dmitriev et al., 2020; Liu et al., 2023). Additionally, the researchers highlight that such simulation models can be applied to predict changes in the processes on the grounds of the observation outcome and that could be obtained during training sessions and theme-related practical classes (Logachev and Beresneva, 2024; Korotun and Goncharov, 2024).
Development of the platforms that aggregate various digital learning resources. The researchers note that over the past decade, the role of passive learning (classical lectures, interrogations, seminars, etc.) has been declining owing to the application of the alternative interactive forms (game technologies, brainstorming, case studies, etc.) (El Hayek, 2023; Nguyen et al., 2021; Yalçin-Incik and Incik, 2022; Afzal et al., 2023). By way of involving such technologies, for students, it is easier to quickly obtain whatever information they require in a compact form. This is consistent with the contemporary paradigm of clip thinking (Kolobaev and Sinitsyna, 2022). Besides, the application of the educational platforms within the educational process helps foster the role of academic autonomy, creating the dynamic personalized educational trajectory (Jing et al., 2023; Gorin, 2020). The studies discuss that such software means do not simply provide the content, yet they monitor the activities of each student (assessing duration and sequence of subject-matter mastery, measuring the level of residual knowledge, etc.), thus providing the statistics to the teacher for further adjustment of the educational trajectory. It is noteworthy that the contemporary level of development of artificial intelligence technologies allows, based on the metrics of student behavior in the digital setting, tailoring the person-centered recommendations in line with achieving certain goals (Dyukina and Kazarinov, 2024; Hamadneh et al., 2022).
Elaboration of the methods for improving computer literacy among the teachers in view of the creation of contemporary educational courses and application of the digital systems and technologies in line with implementation of the educational programs (Dmitriev et al., 2020; Rofi’i et al., 2023). It is noted that the specialized training of the teachers is particularly important when implementing a horizontal convergent approach (Deev and Finogeev, 2023). In this regard, development of the specialized organizational and methodological support is required, which would allow for the formation of the educational environment in which the world around us is one whole, and does not represent a set of separate subjects to be studied (Dmitriev et al., 2020; Alam and Mohanty, 2023). In contrast, when implementing the practice-oriented, or interdisciplinary, approach, the teacher is expected to provide relevant support for the educational process: the timely use of various technological, pedagogical, social and emotional techniques, the pedagogical technologies, software and hardware, as well as the available educational resources (Tedeeva et al., 2024; Gorin, 2020; Safarova, 2023; Tkachenko et al., 2023).
Creation of robotic educational devices. According to the definition provided by the international standard ISO 8373:2021—Robotics, a robot is defined as an actuated mechanism programmable in two or more axes, with a degree of autonomy, moving within its environment to perform intended tasks (ISO 8373:2021, 2026). This definition is pertinent, as a societal stereotype exists wherein computer programs utilizing artificial intelligence are also referred to as robots; examples include intelligent chatbots for messaging or automated calling systems (Root, 2025; Blut et al., 2021).
Contemporary educational systems in various countries employ robots capable of fulfilling multiple roles:
Educational object: A device upon which students practice to develop specific competencies (Tselegkaridis and Sapounidis, 2021).
Teaching assistant: Partially assuming teacher duties, such as delivering lectures, monitoring attendance, and assigning tasks (Alhashmi et al., 2021).
Tutor: Performing functions akin to a mentor, including engaging learners in activities, providing encouragement, and tracking progress (Alam, 2022; Konijn and Hoorn, 2020).
Companion: Representing a less formal variant of a tutor, sometimes designed to allow errors to stimulate student reflection (Rocha and Muchaluat-Saade, 2023; Alam, 2022).
Research underscores the social dimensions of these devices. They are engineered to exhibit specific social behaviors requisite for interaction within a physical environment. Moreover, studies indicate that physically embodied robots exert a significantly more positive influence on learning outcomes compared to virtual assistants (Smakman et al., 2021a; Woo et al., 2021).
Empirical evidence suggests that the presence of a robot in the classroom can enhance children’s motivation, attributable to its novelty and engaging nature (Lampropoulos, 2025; Konijn et al., 2020). Such robots can be programmed to respond with apparent empathy to mistakes or slow comprehension, maintaining consistent friendliness irrespective of the learner’s mood, personality, or external events. However, scholarly discourse also highlights concerns regarding the extensive integration of robots in education. Researchers identify several associated risks:
Incorrect communication strategies arising from system malfunctions or unauthorized third-party access to the software (You et al., 2025).
Cultural value discrepancies: As a robot’s behavior inherently reflects the values of its developers, its cultural dependence on specific mentalities, beliefs, and norms precludes complete depersonalization (Aroyo et al., 2021; van Wynsberghe, 2022; Smakman et al., 2021b).
Transformation of pupil behavior and communication patterns. Observations indicate that children interacting with robots may begin to mimic their mannerisms or perceive them as confidants, sharing personal secrets (Chen et al., 2020; Yang, 2024).
Despite these risks, research and development in educational digitalization have received substantial impetus.
The global COVID-19 pandemic, with its onset in 2020, became the catalyst for accelerating research and the emergence of new developments in the field of education. The timespan of the coronavirus pandemic revealed deep-rooted systemic problems for many national education systems, mainly comprising the dominant use of the traditional teaching model and the unsystematic use of software accompanying the educational process (Kim, 2021; Rof et al., 2022). The researchers discuss that the outcome of the transformation of the entire education system in the aftermath of the pandemic implies the active use of the hybrid teaching method (Wang et al., 2024). Such an approach involves a combination of face-to-face and online classes, the main tools of which are digital technologies underpinned by artificial intelligence, big data, and augmented and virtual reality (Hermita et al., 2024). In addition to the said above, transformation of the traditional roles of the subjects involved into the educational process took place: the teacher-translator turned into a teacher-facilitator (organizer, motivator, and mentor helping the student in the digital or information space); the passive student become active (learning required to independently master the subject-matter and prioritize time, as well as demonstrating the critical thinking skills and responsibility) (Nie, 2023).
Summarizing the review of reference sources pertaining to the field of transformation in education, it is possible to conclude that transformation follows the path of active development and implementation of digital tools which do not just transmit the content in some specific form, yet carry out specific functions of management, monitoring and control of the educational process, and shaping the system of recommendations to ensure support thereof.
Materials and methods
The subject area of the research study is lessons in physics. The lessons in this subject begin in the 7th grade (the lower secondary school, the students aged 12–13 years) and continue until school graduation. The school curriculum covers topics in kinematics, dynamics, molecular physics, thermodynamics, electrostatics, and electrodynamics (Sagatbek and Gabdullina, 2024). The classes comprise mastering theoretical knowledge at the lesson with a teacher, completing oral and written assignments (answering questions, doing tests, solving problems, and doing control works), or independently at home, and conducting experiments as part of the laboratory practice in the classroom, with the mandatory presence of a teacher. Upon completion of the course, the student takes final tests for each academic year. Upon completion of the course, the student may take the Unified National Testing in Physics for admission to the specialized higher education institutions.
Given the purpose of the study, the problem area is the application of the processes by digital assistants aimed at the organization and delivery of lessons in physics. The digital assistant should act as a supportive assistant to the teacher, and not a complete replacement.
A digital assistant is essentially a hardware and software model, which requires, for its creation, adherence to the principles of the software lifecycle model. The software lifecycle comprises numerous primary and secondary processes, the implementation of which, in any particular sequence, transforms the idea into a fully functioning software product. The work was carried out in pursuance of the SCRUM framework.
The choice of this methodology was justified by the insignificant number of project participants, by the fact that there was no clear vision of the final outcome, and by the constantly changing nature of the educational process. Application of this methodology made it possible to define the list of project requirements, which were priority-graded. Each requirement was split into tasks that were completed in short timeframes. The methodologies employed and the results obtained are illustrated in Figure 1.
Methodologies and corresponding results.
Flowchart illustrating the transformation of problem area aspects through system analysis steps like structuring and decomposition, leading to graphical, simulation modeling, and object-oriented design methods, resulting in demonstration materials or a digital twin.
The following general scientific methods were used to implement these tasks:
A system analysis method was applied to the objects and processes in the problem area to determine their possible conditions, patterns of change, and established connections (including in relation to the external environment). This was accomplished through a combination of structuring, abstraction, decomposition, step-by-step refinement, synthesis, systematization, grouping, observation, and questionnaire techniques. The characteristics of applying these methods to the problem domain are presented in Table 1.
A graphical method was applied to the results obtained by using the systems analysis method. It was applied to formalize the data: the subject and problem domain consisted of numerous objects, characteristics, and relationships that were presented in an abstract form, were informational objects, or were of a complex structure. The graphical method allowed these objects to be given a visual form, which was necessary for creating a unified standard for project documentation. Obtaining such documentation enabled the visual representation of the complex objects and systems in a comprehensible way, owing to compliance with the unified graphical language, and facilitated communication between the project participants.
The method of simulation modeling was applied to the results obtained through system analysis. The problem area is dynamic, which means that the majority of the objects can change over time (change the values of their characteristics, or states, under the impact of other objects within the area, or from the external systems). To determine the behavior of such objects or systems over time, a set of rules was established to reproduce predefined scenarios for the subsequent evaluation of their effectiveness or for monitoring changes in the objects’ characteristics (Korotun and Goncharov, 2024; Logachev and Goncharov, 2024). As a virtual environment, a 3D model of a classroom was created, with an equipment layout typical for most schools in Kazakhstan. Using specialized software (AnyLogic), the created 3D classroom model was integrated with a rule-based system governing interactions between objects, their dependencies, and occurring events to implement the digital assistant’s behavioral scenarios.
An object-oriented design method was used to transform the key objects and their characteristics into entities, represented as a set of attributes and methods defining their behavior in the software environment. The application of this methodology was essential to ensure the flexibility of the simulation model within the software environment used.
Characteristics of applying the system analysis method to the problem domain.
No.
Name of the subject
Characterization of evaluation aspect
Output data
Project application characteristics
Qualitative description
Quantitative description
1
Educational program
Physics courseBasic and advanced levels.Full duration of the program.
For each year of study:
Basic level: 68 documents (total 340)
Advanced level: 17 documents (total 85)
Regulatory data includes:
Lesson structure
A list of required resources
Educational content
The structure of educational content
Forms of interaction with students
To define communication scenarios for the designed digital assistant with all stakeholders in the educational processTo collect knowledge base data for the digital assistantTo establish attributes of the simulation model
2
Assessment tools
An appendix to each educational program describes the methods, means, and content for conducting all types of certification within the courseA balanced rating system or other methods for awarding grades during classes
For each year of study:
Basic level: 68 documents (total 340)
Advanced level: 17 documents (total 85)
Documents detailing the balanced rating system: 14Documents detailing grading rules per type of assignment: 411
The form and frequency of certificationsBenchmark points for subjectsThe type, characteristics, and weight of each evaluated aspectThe level of human factor impacting evaluations
To identify interaction scenarios between the designed digital assistant and participants in the educational process during the monitoring and control of all types of certificationTo determine models for evaluating student knowledgeTo gather knowledge base data for the digital assistantTo establish attributes of the simulation model
3
List of equipment, hardware-software solutions, and electronic educational resources
Monitoring of learning activity (distance learning systems, electronic journal, diary)
Number of rooms: 57 classrooms and 12 laboratories
Actual inventory of operating equipmentThe level of utilization of available resources
To verify the possibility of integrating the utilized means into a single digital ecosystem of the educational institutionTo determine the type and format of processed data to enable export and import capabilities within the digital assistant’s ecosystem
4
Current research and development in the field of digital transformation of the educational process
Scientific-theoretical and practical publications indexed in Scopus or Web of ScienceThe regional aspect of the research focuses on Kazakhstan and countries classified as developed or developingPublicly accessible repositories on GitHub are consideredRegional and worldwide rankings of licensed and open-source hardware-software solutions are analyzed
The coverage period is 2020–2025The experience in Kazakhstan encompasses 106 research studies and 43 information and distance-learning systemsWorldwide experience includes 229 research studies, 128 algorithms, software modules, and informational, digital, and distance-learning systems
List of deployed hardware-software and robotic systems in educationList of available algorithms, models, and datasets for digital systems in the learning process
To determine communication scenarios for the designed digital assistant with all participants in the educational processTo collect data for the knowledge base and dataset of the digital assistantTo establish user categories of the digital systemTo define the architecture of the digital assistantTo specify attributes and initial values in the simulation model
5
Practical experience of using digital technologies in the educational process
The responses to the questionnaire and interviews concerning the current or recently completed (within 1 year) professional activities of teachers in KazakhstanNo questions regarding the processing of personal data were includedAn expert survey was conducted, which included not only physics teachers but also instructors from other disciplines within the natural sciences and mathematics cycles, as the nature of the implemented educational process demonstrates similarities in the use of software and hardware
The total number of teachers surveyed is as follows:
Physics: 32 individuals
Other natural sciences cycle disciplines: 9 individuals
Mathematical discipline teachers: 13 individuals
Formal models:
Interaction between teachers and available digital resources within the problem domain
Interaction with students during all types of instructional sessions
Adaptation of educational program components and assessment tools to specific lessons
6
Practical implementation of the educational process
Formal models:
The interaction of teachers with the available digital resources of the problem domain
The interaction with students during all types of instructional sessions
The adaptation of educational program components and assessment tools to specific lessons
Employing this approach enabled the creation of a digital twin of the developed system. The digital twin serves as an accurate virtual replica of both the robotic device itself and the processes involved in its interaction with real-world physical entities. Through its use, key state characteristics of the system were derived, along with modeled behaviors and process alterations. This allows for informed decision-making regarding the robot’s structural design and for analyzing the algorithms governing its behavior without involving pupils or expending resources on upgrading school infrastructure.
ResultsFormalization of the problem area
Lessons in physics in Kazakhstan begin in the 7th grade. The classroom learning load comprises three 45-min lessons. Depending on the material and technical resources at hand, the class may be divided into subgroups. According to the regulations, the class size should not exceed 25 students. In reality, this requirement may not always be met, and the number of students may be greater.
The scope of any lesson (including physics) is pre-determined by the curriculum that abides by the educational standards. The curriculum defines the didactic units to be mastered, as well as the resources that can be used for such purpose. Each teaching unit implies the mastery of the theoretical knowledge, problem-solving, and conducting some particular experiments. Normally, the teacher explains the theoretical scope employing the demonstration aids: a screen and a projector, an interactive whiteboard, devices and equipment, laboratory supplies, or visual aids. For students, such a lesson is linear (the teacher is the source of knowledge): they perceive information by ear and visually, can take notes or be dictated, and, if possible, ask clarifying questions. Depending on the teaching skill and the format of the lesson, the non-linear forms of lessons may take place as well: leading a discussion, presenting the reports followed by a discussion, demonstrating the problem-solving case, or conducting an experiment.
To ensure thorough knowledge, the students, under the teacher’s supervision, can carry out the laboratory assignments using the measuring tools (scales, thermometers, ampere-meters, voltmeters, etc.), equipment (mechanical pendulums, optical instruments, electrical circuits, etc.), or other laboratory supplies (magnets, test tubes, flasks, etc.). If the school’s material and technical infrastructure allows, each sitting place can be equipped with the required equipment for each particular laboratory assignment. In situations when some equipment or tool is unavailable for use in multiple quantities, the teacher conducts the experiment. If desired, the experiment can be repeated by one student in front of the entire class. Based on the results of the conducted experiment, all students perform the appropriate calculations, evaluate the results, and draw conclusions. Such laboratory assignments require preparation, which is provided by the teacher and, if required, by the school’s staffing schedule, by a lab assistant. Preparation involves setting up the workstations (moving the equipment from the lab, turning it on, and checking for proper operation and safety), monitoring its use during the lesson, adjusting the equipment while the student is working on a task, and cleaning up at the end of the laboratory work or the lesson. Table 2 shows the lesson plan for “Floatation of Objects” tailored for the 7th grade.
Technological map of the lesson in physics covering the topic of “Floatation of Objects.”
No.
Lesson stage
Teacher’s activities
Students’ activities
Skills and competencies to be developed
1
Organizational
Greeting and motivating the students to learn
Greeting the teacher. Arrangement of the workspaces
Communicative skills: Ability to listen, receive and process the information, organization and planning of the work
2
Setting the goals and defining the objectives
Demonstration of the video clips on the screen showing the objects floating in various liquids. Discussion with the students about what they have seen (what can be said about the objects shown, how they behave, and what conditions influence their behavior). Based on this discussion, the students are sked to define the topic of the lesson
Watching the video clips. Answering questions (the expected answers: Floating bodies; conditions associated with the bodies floating change depending on the liquid and the volume of the body). Alternatives to the topic of the lesson (the expected options: floating, floating bodies, and similar concepts)
Communicative: Participation in group discussions, ability to find a common solutionRegulatory: Independent formulation of a statement based on facts, examples and other statementsPersonal: Development of motivation, formation of the meaning, and goal setting
3
Bringing the knowledge up to date
Revision of the previous lesson’s topic (Archimedes’ force). Discussion of the answers to the questions:
What forces act on a body immersed in a liquid?
What is the direction of Archimedes’ force?
What is the direction of gravity?
What will happen to the body on which these forces are applied, if the body was initially stationary?
To define an assumption: Floating of bodies depends on two forces, and things behave this way depending on which force is greater.
Participation in the survey. Brainstorming of the answer types (the answers with precise definitions from the textbook are possible). The expected answers: Gravity (vertically downwards) and Archimedes’ force (vertically upwards)
Communicative skills: Ability to listen and engage in the dialogue, to present the arguments, and participate in the group discussionsCognitive: The ability to define the cause-and-effect relationships, to draw conclusions based on reasoning and build the logical chains of reasoningRegulatory: To build the dialogue, to determine the sequence of actions, make the plan of the answers
4
Experiment
Distribution of the assignments and provision of the safety demos, instructions as regards the work schedule, and safety precautions when handling the laboratory equipment. Monitoring of the work, corrective actions, and guiding the team toward finding the right solution
Completion of the assigned task
Communicative skills: The ability to find a common solution, asking questions, taking initiative, the ability to express one’s thoughts with sufficient fullness and accuracy, listening attentively and repeating the actionsRegulatory: Be able to compare the obtained result with the standard one, or the one demonstrated by other participantsPersonal: Shaping one’s life experience
5
Generalization and consolidation of the knowledge
A summary of the work. A discussion about the importance of the topic and its practical application
Answers to the questions
Communicative: Participation in group discussions, ability to summarizeCognitive: Obtaining information and the ability to apply it in real-life situationsRegulatory: The ability to adjust the answer depending on external conditions (answers given by other students, the teacher’ comments), determining the importance of knowledge and its applicability
6
Jotting down the hometask
Demonstration of hometask on the screen
Taking notes on hometask
Regulatory: Determining the level of mastering the material
7
Reflection
Suggestion to continue (orally or in writing): “I evaluate my work during the lesson…,” “today in the lesson I managed to…,” and “I found it difficult…”
Call-out brief answers
Communicative: Cognitive reflectionRegulatory: Self-esteemPersonal: Development of the I-concept
On the grounds of the technological map of the lesson as provided in Table 2, it is envisioned to schedule the practical implementation of the assignments. The excerpts from these assignments are given in Table 3.
The excerpts from practical assignments in line with the lesson covering the topic of “Floatation of Objects.”
No.
Formulation of the assignment
1
Hang two identical weights on a balance scale, one in water and the other one in oilWill the balance scale’s equilibrium be disturbed?
2
A lever balances blocks of different volumesPlace the blocks in waterWill the lever’s equilibrium be disturbed?
3
Using a dynamometer and a body on a string, determine the density of the liquid
4
Hang balls of equal mass but of different volumes from identical springsBring a container of water to each ball and raise it until the balls are completely submergedWhich spring will contract more?
5
Fill a test tube with sand so that it floats vertically in the graduated cylinder, sealed with a stopperMake sure that part of the test tube is above the surface of the waterDetermine the buoyant force acting on the test tube and its gravityAdd more sand to the test tube and determine the gravity and buoyant forceRepeat this until the test tube sinksEnter all the results into the table and draw conclusions about the condition for an object to float in liquid
Given the fact that students complete the assignment at different paces, have varying levels of background experience, and taking into consideration variable device performance, the time it takes to complete the same assignment can vary significantly. This makes it difficult for the teachers to fully monitor the assignment and supervise the students’ performance. A similar problem arises when the students complete computational and graphic tasks that imply solving problems on certain topics. This requires the development of specialized software and hardware to support the teachers during these lessons in physics.
Software and hardware model of a digital assistant
To solve this problem, it is proposed to equip the physics classroom with the software and hardware that would assist the teacher in organizing and conducting the lesson. To perform these functions, the digital assistant implements the following constituents:
1 A robot that can physically navigate around the classroom from one seat to another, along a predetermined route, or act on an event. To make sure the educational process during the physics lessons is efficient, the robot possesses the following functional capabilities:
Classroom monitoring: The ability to detect problems related to infrastructure malfunctions, as well as the occurrence of events that imply a threat to the safety, life, and health of those around them. To achieve this, the robot should be equipped with a camera that records the events in real-time, applying machine vision technology.
Monitoring of the students’ activity: Detecting the non-educational activity, as well as the emergence of the questions (a raised hand indicating that a student has a question to ask). Detecting such events requires the application of machine vision technologies to the video stream received from the robot’s camera.
Individual guidance during the experiment or the assignment: Demonstration of a step-by-step video supplemented with the algorithm for its execution. This should be done during the lesson if the student encounters any problems. To achieve this, the students can plug in their headphones and watch the video broadcast by the robot on their screen.
Transportation of the smaller laboratory equipment and the consumables: Assisting the teacher and a lab technician before and after conducting certain classes. The robot can carry small objects and deliver them to any seat in the classroom.
2 A digital system comprising the software modules that would ensure acquisition, analysis, and generation of the most appropriate action, robot logistics, and integration of the digital learning resources. Logistics is particularly important when multiple robots are simultaneously involved. On the one hand, it allows for a fair distribution of the equal workload among them (dividing the classroom space into sectors serviced by a specific robot) to reach the maximum number of students per unit of time, without disrupting the learning process. On the other hand, it ensures that the resource conflicts between different robots are avoided: overlapping or simultaneous crossing of the routes, duplicating solutions for the same situation or student request.
3 A data storage facility for supporting the robot’s functionality, monitoring, and control of the activities during training sessions.
4 Digital learning resources for use as training or demonstration content by the robot during a lesson. These can comprise both the specially created resources and the resources taken from the school’s digital ecosystem (e.g., Learning Management System, Coursera).
5 Electronic management resources are liable for the organization of the educational activities (e.g., an electronic journal, an educational program, or an individual teacher plan). Within the digital assistant system, these can be allocated as a separate software module that would synchronize the external resources with the digital system. Based on the received external data, the digital system’s algorithms generate the decisions for the robot to execute.
Figure 2 shows a model of the digital assistant levels, and Table 4 briefly outlines them.
Structural model of a digital assistant.
Diagram illustrating the digital ecosystem of an educational organization, showing six horizontal layers: teacher and laboratory assistant, student, robot, settings and interaction modules, request processing and logistics modules, and educational module, with arrows connecting to electronic diary, journal, digital educational resources, interactive laboratory map, and educational resources.
Features of the levels of the digital assistant model.
No.
Level
Type
Feature
Resources used
Internal
External
1
Physical
Controling
The teacher defines the topic, content, and the resources to be used at the lesson. The laboratory assistant (optional) checks, configures, distributes, uses, and collects the equipment (the consumables, demonstration materials) needed for the lesson
Material and technical infrastructure of the physics classroom
Digital learning resources: Demonstration materials (educational videos, presentations, topic-related online simulators, digital models of the physical processes, accessible training courses and online educational platforms)
2
Student
A student who has the opportunity to ask questions, request the review of the completed tasks, the review of the educational content individually, and to receive information about individual steps in the implementation algorithm (practical assignment)
3
Controlled
A robot, or a family of robots, operating in two modes: free and scripted. The free mode involves analyzing the states of the subjects during a lesson (behavior, requests, emergency situations, etc.) and their responding based on the system rules, or the local settings. The scripted mode involves execution of the pre-loaded actions by the teacher for a specific lesson and monitoring the background for any emergency situations to promptly transmit an alarm
Connecting to a WI-FI network via a router installed in the classroom provides access to a local server (the software installed on a personal computer in the classroom, or in another room in the school building) to receive settings from the control-level users and their downloaded educational content for the current lesson (if available), as well as the access to the software components for the offline operation (if there is no internet access). It also receives and transmits the data from the camera for processing, and receives the commands based on the results of the video data processing
Connecting to a WI-FI network via a router installed in the classroom provides access to an external server, which ensures the overall functionality of the digital assistant and access to the external educational content available on the educational platforms
4
Program
Processing
The software modules that provide the receipt and primary processing of the data from the sensors and the devices located on the robot, and the data obtained from the generating-level modules, followed by their transformation for further transmission to the controlled elements of the robot (direction and speed of movement for the wheels, video images on the monitor screen, etc.)
The equipment and sensors installed on the robot allow it to move around the room and communicate directly with the studentThe map of the area, with the saved typical routes, depending on the purpose of travelThe user settings.The set of functions to ensure operation in the autonomous mode (without the Internet connection)
No
5
Generating
Software modules that enable decision making based on the primary data and the rules established in the digital system (implemented using the artificial intelligence technologies)Generation of a request to retrieve educational content
The basic set of functions installed on a local server to ensure autonomous operationThe classes schedule, or the electronic journal, that contains the information about the class, date and topic of the classesThe images from the interactive whiteboard screen
The external server with the business logic of the digital assistantKnowledge database for activation of the functions using the artificial intelligence technologies
6
Providing
The educational resources (video instructions, algorithms to ensure completion of the assignments and solving the problems, video lessons, video lectures, and other materials)
The data server located at school that stores the materials designed by the competent teaching staff
The data server for the third-party companies qualified to distribute the educational content (the electronic libraries, distance learning courses, etc.)
According to the developed model, for the digital assistant to function fully, it is required to have a training room furnished with the following equipment:
A personal computer connected to the school’s local network and having access to the Internet.
WI-FI router providing access to the Internet.
A wheeled robot (if the material and technical infrastructure is limited, each student can use a tablet or a smartphone).
Cases of interacting with a digital assistant
When involving a wheeled robot in the concept of a digital assistant to navigate inside the classroom, the routes there become an important aspect. Positioning of the potential objects on the classroom floor is essential for defining the route network. The usual layout of any random school classroom comprises three rows of desks, each with two seats for two students. Depending on the size of the classroom, one row may abut a blank wall, or a wall with the windows. This means that the two rows have aisles on both sides, while the other row has access to the seats at one side only. Figure 3 shows a schematic diagram of a physics classroom, which is not a specialized laboratory, yet the shown layout is the most typical in schools in Kazakhstan.
Robot route map in the digital assistant system.
Diagram of a physics laboratory and classroom floor plan showing desks, chairs, labeled zones one through six, a large pink whiteboard area, color-coded robot-accessible, technical, and reception areas, and detailed routes for communication, demonstration, supervisory, and educational interactions. A legend explains the symbols for infrastructure, routes, nodes, and areas.
The diagram below shows the route map of a robot (or the robots) acting as a digital assistant at the lesson in physics. The areas not marked in green are those the robot is prohibited from accessing (e.g., due to the physical limitations, such as the presence of a wall cabinet, educational display, or other objects). Given the room restrictions, the robot is inaccessible to the student seating line 6. Consequently, this sector requires full monitoring and needs to be accompanied by a teacher or a lab assistant during the lab work. All other lines (1 to 5) are accessible to the robot, so the students can approach both the robot and the teacher (lab assistant) for assistance.
The goal determines the robot’s route:
If a video needs to be shown to a student, the robot stops in front of them. The student can plug in headphones and view the relevant sections.
If it is required to control the actions in process, or the result obtained, the robot stops at the side of the desk near its center to see all its contents.
If the robot needs to answer a student’s questions, it stops in close proximity to them. In this case, it is also possible to connect the headphones to reduce noise during the lesson.
When the robot is close to the students (regardless of the task being performed), it monitors the surroundings, transmitting the video data for processing using machine vision. Based on this data, it determines the next point to which it will move and monitors the overall condition of the classroom. If the robot’s assistance is not required, it takes up a position in a corner of the main route for a better view and to have ample alternatives for the subsequent movement to the chosen point.
The teacher defines the objective for the lesson before it begins. The teacher uses a personal computer with the digital assistant software installed. The relevant educational resources are then automatically selected, and the number of students (based on the electronic journal) and their location in the classroom are defined. The approximate basic routes are mapped out to ensure general monitoring of the classroom till the moment the first request is spotted (for instance, a raised hand). To avoid conflicts over the student assignments, the following rules are in place:
In the event of several free robots available, the task is handled by the one that is closest to the point of request.
A teacher can cancel an automatically generated task for a robot using a personal computer or their smartphone.
Whenever it is impossible to equip a room with a robot, it can be replaced by the students using the tablets. In such a case, each seat should be equipped with a tablet so that the following actions can be performed, if needed:
To watch the videos demonstrating the sequential performance of the experiments, or the rules for handling the laboratory equipment, on an individual basis.
Transform the experience into a digital one by launching a special digital assistant mode.
Analyze the completed work, or its stages, by collecting the video or photo evidence of the workspace using a tablet. In such a case, a digital assistant will use machine vision technology to assess the accuracy of the equipment settings, or the results, in real-time.
When using the tablets in class, the teachers can act as moderators within the digital assistant setting, assessing the students’ work in real-time.
DiscussionIntelligent assistant in the global context of digital transformation
The analysis of the obtained results was conducted in the framework of the global trends under the digital transformation of education, of variable application of the software solutions depending on the regional and content factors, as well as of the effectiveness of the transformation of the pedagogical technologies and scalability of the software solutions.
From the point of view of the digital transformation of the educational process globally, the proposed concept is in line with general world trends. If we discuss the pedagogical approaches in teaching, it is aimed, primarily, at individualization, namely creation of the individual educational trajectories for the students, and taking into consideration their psychological and physical condition, ability to master educational content, and other individual factors (Alam and Mohanty, 2023; Ivanova, 2024; Gorshenina, 2022; Yudina and Mkrtchyan, 2021). Here, the active tools are software solutions relying on artificial intelligence technologies, big data analytics, simulation, and robotics (Tedeeva et al., 2024; Karakozov and Samokhvalova, 2024; Parveen and Ramzan, 2024). It is noted in the research papers that such technologies should be used comprehensively (Gök et al., 2024; Ahn and Chen, 2022). The analysis of the world rankings of quality education proved that the introduction of the complex principles of digital transformation in the educational process yields high performance indicators of such activities (for instance, the countries of the European Union, Singapore, South Korea). Thus, the political initiative of the European Union defined the timeline from 2020 to 2030 as the digital decade, within the framework of which the digital education plan ought to be implemented (Digital Education Action Plan) (Shmatko and Volkova, 2025). It is based on the common principles for ensuring high-quality, inclusive, and accessible digital education in Europe and supporting harmonization of the education and training systems of the Member States with the requirements of the digital era (Shehaj, 2022). The developed concept of a digital assistant is in line with this practice. It is a technological initiative that consolidates pedagogical practices, methods, and resources within a single digital platform to create a unified digital educational system that provides students and teachers with the detailed information needed for learning purposes, taking into account the individual specifics of each subject within this system.
The outcome of the studies confirms that not all students are capable of exercising self-control and self-study due to their age, so digital transformation requires defining the teacher’s role in the educational process (Tarieva and Khinchagashvili, 2023; Alekseeva and Bogolyubova, 2023). The teacher should become a mentor and a guide not only in the context of the subject but also in relation to the specifics of using the software tools in line with completion of the assigned tasks (Yakhontov and Samoylukov, 2024). Such studies emphasize concerns associated with the students’ use of artificial intelligence technologies in terms of violating the principles of academic integrity during learning (Surahman and Wang, 2022). The developed concept allows for distribution of the roles between the teacher and digital assistant within the educational process, so that it would be possible to effectively provide consultations on topics of interest to the students, and monitor their activities. The use of a robot in the digital assistant system allows for student engagement in the learning process, and ensures continuous monitoring of the educational process without increasing the negative impact of total control.
The researchers note that the primary focus in education has shifted to the application of the practice-oriented techniques that would enable visual demonstration of the complex processes and interdisciplinary connections that come along (Edelmann et al., 2023). For such purposes, the software solutions are being actively developed to provide interactivity and visualization in learning. The virtual and augmented reality technologies are fully involved for that. It needs to be pointed separately that the virtual trainers, or simulators, relying on the simulation models of the natural processes are being introduced into the educational process to implement a practice-oriented approach to learning (Sharlay, 2021; Logachev, 2024; Gdansky and Karpov, 2020; Gdanskii et al., 2019). The identified problem area includes complex real-world processes and systems, the demonstration of which within a classroom setting (a training laboratory) is only possible when using such technologies. Integration of a robotic digital assistant into the concept, which allows for demonstrations using the specialized equipment and controls the experiments in physics, results in the effect of the “total immersion” in the nature of the physical processes being studied, and the consequences that may arise from certain actions.
Limitations of the intelligent assistant and risks associated with its use
When developing any software product, it is required to consider the risks associated with subsequent changes to the software and hardware. The studies related to the development of the market for such software discuss frequent change of its players, the global growth of the new solutions, and the development of technology and techniques, which entail rapid obsolescence of the current digital achievements (Hanelt et al., 2021). Maintaining functionality of the software product over a long period of time requires not only its ongoing support (release of the updates), but also creation, at the design stage, of the architecture that allows for integration of the new solutions and decommissioning of the existing modules without failures (Cervantes and Kazman, 2024; Kumar et al., 2023). The developed structure of the digital assistant supports this approach and allows for scalability of the system, which is consistent with the principles of modern software development.
Even if the developed concept complies with the principles of the digital transformation strategy for education and designing the software and hardware solutions, this development has its limitations.
First, at this stage, the work is conceptual in its nature, so it is impossible to confirm or refute hypotheses about the digital assistant’s effectiveness without any empirical testing. The conclusions are based on the outcome of the analysis of the existing alternatives, theoretical models, and research conducted in the fields of pedagogical science and digital process transformation.
Second, there are territorial limitations associated with the focus on a specific country. The education system of Kazakhstan is characterized by certain socio-cultural, technological, and labor-related aspects that influence educational processes. Accordingly, the results obtained cannot be fully extrapolated to all education systems.
Third, there are social and psychological constraints and staff shortage. Success and effectiveness of implementing a digital assistant requires further research, because it is required to consider the realia associated with the teachers’ digital literacy and their resistance to digital tools (the fear of being replaced by artificial intelligence), as well as the transformation of the students’ motivation (the impact of digital technologies on independence in the educational process).
Furthermore, the use of social robots entails several inherent risks:
Technical risks: Vulnerabilities to cyberattacks and erroneous algorithmic operations (Ayele et al., 2023; Giansanti and Gulino, 2021; Fosch-Villaronga and Mahler, 2021).
Social risks: Misunderstandings between humans and robots, which may undermine the teacher’s authority (Aroyo et al., 2021; Ceha et al., 2022; van Ewijk et al., 2020).
Psychological risks: Emotional dependency that could lead to social isolation or the substitution of authentic interpersonal relationships with artificial interactions (Chen et al., 2020; Yang, 2024).
Ethical risks: The dissemination of false or harmful information, compounded by uncertainties regarding accountability for failures in autonomous systems (You et al., 2025; Fisher et al., 2021; Webster et al., 2020).
These risks are characteristic of contemporary social robots in general, and the proposed solution is no exception. Nevertheless, the developed architecture incorporates measures to mitigate such risks through advanced technical safeguards, including antivirus software, firewalls, multi-factor authentication, data encryption, and backup procedures. The use of simulation models facilitates the creation of documentation for acceptance testing phases, thereby supporting the development of regulations and operational guidelines that protect digital assets.
The digital assistant functions as a customizable tool, tailored to the curricula of specific schools. All educational materials, assessment systems, speech patterns, and vocal characteristics are defined directly by educators. Content undergoes a moderation process before being integrated into the teaching process, ensuring compliance with standards set by the teacher and restricting dissemination to approved material. The collaborative operation of the digital assistant and robot during instructional sessions allows for the timely detection of behavioral discrepancies in the robot, enabling prompt adjustments or system deactivation when necessary.
Conclusion
Digital transformation of any process is a complex task, and it requires not only technological solutions but also the implementation of the infrastructural, staff, methodological, and regulatory requirements. Creation of a digital assistant for arranging and delivering the lessons in physics at school is the initial stage of this global project. It will enable the assessment of the project’s prospects and the attitude of the teachers, school management teams, students, and parents toward the implementation of a pilot solution supported by the developed concept. The success of the contemporary educational process depends on many factors, with communication between all its participants when assessing the teaching techniques and quality of the educational services being one of them.
Kazakhstan’s entry into the global educational space implies a new perspective on the professional challenges and solutions, stimulating innovation, design, development, and implementation of the software solutions to shape a new educational paradigm. Today’s students are growing up in a new information environment, in which the early developed computer literacy skills and information perception skills are needed, and presuppose a rethinking of the traditional teaching methods and aids.
Implementation of the specialized software tools contributes to the continuous modernization of knowledge, skills, and abilities for free orientation in the new realities, as well as expanding or opening new outlooks for the methodologies that would promote practice-oriented and interdisciplinary approaches.
The developed concept of a digital assistant serves as a strategic guideline for further practical developments in EdTech in Kazakhstan. The use of interactive and immersive learning formats will help maintain the students’ interest in any subject concerned, while integration of artificial intelligence, big data analytics, and machine vision technologies shall ensure continuous support for individual educational trajectories and adaptation of the educational materials to each student’s degree of comprehension.
Further research in this field shall focus on creating a prototype and assessing its impact on the students’ digital literacy, critical thinking, and self-education skills, which are all in line with the ultimate goal of modernizing the educational methods and the educational scope in Kazakhstan.
Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.
Author contributions
VG: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft. IKr: Data curation, Project administration, Resources, Supervision, Writing – original draft. YS: Conceptualization, Formal analysis, Methodology, Writing – review & editing. IKu: Formal analysis, Visualization, Writing – original draft. VB: Resources, Software, Validation, Writing – original draft.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Edited by: Raquel Fernández-Cézar, University of Castilla-La Mancha, Spain
Reviewed by: Nurul Sulaeman, Mulawarman University, Indonesia
Nurkasym Kylychbekovich Arkabaev, Osh State University, Kyrgyzstan