Everyone to the Blackboard: How Artificial Intelligence Is Making Education Multimodal
Is it possible to account for the diverse needs of learners – different learning styles, pace of progress, motivation and attention span? An attentive assistant is stepping in to help: artificial intelligence.
Multimodal Magic
“There is a popular phrase – ‘the future is now.’ In my view, multimodality is something that has already happened to all of us. A new norm is emerging, where concepts like engagement, attention retention and multimodality itself become criteria for success,” says Evgeny Lichkin, an English teacher and author of the Telegram channel The Curious Teacher.
Yes, the traditional model of “one teacher, twenty-five students” often lacks flexibility. AI systems, however, can assess how a student answers questions, how much time they spend on a topic and where they make mistakes – and immediately adapt the material: simpler if it is difficult, deeper if the learner wants more. This is not just a change of format; it is a shift from “one size fits all” to “learning that senses the student.”
Multimodal pedagogy also values multiple formats: text, video, interactivity, simulations and visualization – anything that helps explain complex ideas in different ways. AI makes it possible to combine these formats and choose what works best for a specific learner.
From Routine to Inspiration
AI is increasingly used in lesson preparation. According to research by the educational platform Uchi.ru and the Laboratory for Innovations in Education at the Higher School of Economics, the main area where AI is applied is lesson planning. Technology helps teachers find ideas and topics (29%), methodological solutions (26.8%), create personalized assignments (25%) and design lesson plans (19%). This approach reduces administrative workload and leaves teachers more time for live interaction with students, mentoring and creativity.
AI tools can also provide instant feedback to students, which is especially important in large classes or blended learning formats where it is difficult for one teacher to track everyone. The teacher’s role shifts from simply delivering knowledge to acting as a mentor and guide.
From “Smart Sparrow” to Uchi.ru
Digital education began with interactive presentations and virtual labs – early steps when lessons stopped being just text and became visual experiences. Online simulators and blended learning formats followed, allowing part of the learning journey to take place outside the classroom. The combination of offline and digital learning delivered noticeable gains, especially in science and math.
Over time, technologies became more sensitive. They began to account for pace, learning style and comprehension level. The idea of the “average student” faded, and personalization entered the classroom.
Today, there is a global wave of projects that turn learning into a living, multimodal process. Khan Academy demonstrates how an “intelligent tutor” can work: AI engages in dialogue, identifies weak spots, adjusts pace and pushes learners toward understanding rather than giving ready-made answers. Duolingo applies a similar idea in a gamified format, with algorithms selecting tasks based on learner level and adjusting difficulty as progress is made. Smart Sparrow develops adaptive online courses where content responds to student actions: explaining concepts more deeply after mistakes and offering more complex steps when confidence is high.
Russia already has its own strong examples. Platforms such as Uchi.ru, the Russian Electronic School and the online trainer YaKlass offer courses across core school subjects. Online education has also moved beyond the school curriculum. Platforms like Skillbox provide hundreds of courses in design, programming, marketing and IT, while GeekBrains focuses on IT, analytics, testing and design. Multimodality and AI have become a natural continuation of digital evolution – not just electronic textbooks, but systems that respond to the learner.
Education That Fits
The journey from early computer-based lessons to individualized multimodal environments has been long, but its results are now visible in every modern digital classroom. As learning environments become more diverse, the traditional “one size fits all” approach increasingly looks outdated. Integrating AI into multimodal pedagogy makes it possible to build learning around the learner’s personality, pace and style.
Today, AI continues to refine adaptive learning paths, intelligent “mentors” and flexible courses. Technologies are learning to recognize human mood – a field known as emotional AI or affective computing. Algorithms analyze facial expressions, gestures, tone of voice, text formulations and sometimes even physiological indicators such as pulse and breathing to determine a person’s emotional state. This opens the door to digital education where technology helps not only to know, but to understand oneself and be understood.
