– What functions does the NTI Competence Center “Technologies for storage and analysis of big data” perform?
– Generally, one of the primary goals of the center is to advance the development agenda for technologies related to storing and processing large datasets. To describe the center’s activities in more detail, its functions can be divided into two broad groups.
The first encompasses all work connected with fundamental research in artificial intelligence and big data. The second relates to the creation and promotion of educational products across diverse fields, including expert and analytical research, technology consulting, IT governance, marketing, and education, among others.
The team responsible for “Guidelines for Applied Education Projects,” led by the speaker, develops educational products with input from specialists and instructors from Moscow State University. These products include training courses, master classes, and other educational events. The group also conducts specialist and analytical research in the area of human capital development.
– What are the prospects for big data technology in education? How will the technology you work with and develop change learning in the next 10 years?
– In the next decade, education should become more human-centered. In this transformation, artificial intelligence and big data will play a very significant role. Human-centered education means the system focuses on individual learners, acknowledging their personalities, preferences, and the ways they perceive content.
– Does that mean personalized education programs will emerge for students in the next ten years?
– The trend is toward customization of learning trajectories and programs. There are startups and projects equipped with powerful AI that can handle large data sets. Yet achieving this will not be simple. Several major challenges must be overcome.
– For example, which ones?
– Deep personalization requires accounting for a student’s reactions and the outcomes of mastering the curriculum. Today, algorithms address this to a limited extent. A second key issue is to avoid large, monolithic modules. Training components should be modular and scalable so that a lesson or part of a lesson can adapt. Third is integration. Personalization must be implemented in a holistic way, not confined to a single platform or school. For the system to work, information systems across schools, universities, additional educational institutions, and online course platforms must be unified and data processed centrally.
Although these barriers are serious, strong progress is visible in IT products, educational organizations, and R&D focused on personalizing educational programs. The outlook for the next 5–7 years remains highly positive.
– Will big data enable the automatic verification of homework and exam papers in the future?
– Certainly yes. A relatively straightforward algorithm can handle evaluation tasks that involve comparing a student’s work with correct answers. Checking assignments often does not require deep contextual understanding, and AI can analyze complex text, identify relationships, and process information efficiently. However, feedback is essential to knowledge development, so the process also includes delivering actionable guidance to learners. That part remains more challenging.
– Will artificial intelligence replace teachers in schools within the next 10–20 years?
– It is unlikely to replace teachers, but it can enhance their effectiveness. AI can help with tasks such as analyzing responses, tailoring material for the class, and selecting resources to address common questions. When a learner struggles with a specific skill, AI can propose targeted materials and examples to support understanding, potentially saving time for the human teacher and enabling deeper, more individualized attention. This approach helps students grasp concepts while preserving the essential human element of teaching.
– Is there any lobby in Russia whose members oppose the introduction of innovations in schools?
– While it is not appropriate to name a lobby, it is clear that not everyone welcomes AI and big data in education. Parents of schoolchildren often express concern about screen time and the potential for reduced direct interaction with teachers. The concern is that an over-reliance on digital tools could erode the classroom atmosphere that supports learning.
– What does that mean in practice?
– It means that the human touch in school education remains essential. Technology should augment teaching, not replace it. Digital solutions and algorithms are best used to complement the teacher’s work, helping to personalize learning while preserving personal guidance and interaction.
– Processing big data involves collecting it. Can anxious parents influence this process in any way?
– The current framework, defined by official regulations, sets the minimum information that parents provide to schools. If personal data is obtained unlawfully, parents can request its destruction and withdraw consent where applicable. It is advisable to communicate with teachers and understand the purpose of each questionnaire, and to contact parents directly if needed.
– Which projects from the Center are expected to premiere soon?
– The center is actively preparing projects aimed at older students, focusing on career awareness in the digital economy: outlining available professions, understanding suitability, and strategies for entering the labor market. On July 30, Inga Nikolaeva will present a lecture on “Children’s career guidance and university choice: what parents need to know today” at a popular science festival. Readers can explore more about events like Geek Picnic in the festival guide.