At RUDN University, an intellectual assistant will help professors at classes
“The intelligent teaching assistant analyses recorded lecture materials thoroughly. Based on the analysed data, it can create an outline of the lecture and key words of the class, assess the emotional state of students, analyse the dynamics of the lecture and identify the most difficult topics for the audience,” Anton Poddubsky, Dean of the Faculty of Artificial Intelligence at RUDN University
The algorithm of the programme operation is described below:
The first stage involves using a neural network model to process the audio recording: dividing the sound into time segments (silence, teacher's speech, students' speech). This makes it possible to construct a chronology of the lesson and analyse the dynamics of the pronounced syllables per unit of time.
The second stage involves a deep textual model to create an outline, test questions and a knowledge tree structure.
Additionally, a linguistic analysis of the text is performed to identify the frequency of keywords and stop words.
The analysis of students' emotional state is performed as an addition to the first stage of the algorithm. After identifying the time intervals in which students speak, classification models are applied to this data to determine the emotional colouring of the statements.
“The programme has already shown high efficiency. The text model successfully creates lecture notes for humanities and exact sciences, highlights subtopics of classes and main theses. The processing time for an hour and a half lecture is only 3 minutes, which is significantly higher than existing analogues. Also, during the testing of the assistant, we found that during distance classes the share of silence time is significantly higher than in face-to-face classes. This indicates a decrease in the effectiveness of the distance learning format,” Anton Poddubsky, Dean of the Faculty of Artificial Intelligence at RUDN University.
In the forthcoming future, the programme plans to add a function to generate a 5-10 minute podcast in which two people discuss lecture material.
“Students are also using AI in their studies. Is it possible that one day two AIs will communicate with each other? Generative models have been developing rapidly in recent years. Almost every week we hear about the launch of new tools integrated into the educational process. Artificial intelligence technologies are tools that humans have created to help themselves. The danger arises when AI replaces the thinking process rather than helping to develop it. The use of AI does not cancel the fact that the student must have some knowledge, because the verification of the results of generative model activity is left to a human being. In addition, today all generative models have ‘illusions’ in the AI world, this is called the generative model hallucination problem. Without the intervention of human intelligence, we will not be able to evaluate and differentiate the results obtained by artificial intelligence,” Rezaian Naeem, head of the Artificial Intelligence Laboratory, Faculty of Artificial Intelligence at RUDN University.
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Forests are not only the lungs of the planet, but also home to millions of species. However, it has remained unclear how underground interactions between trees and fungi affect forest species richness in different climatic conditions. Previous studies have yielded conflicting results: in some regions, the dominance of certain fungi reduced tree diversity, while in others it increased it.
The project to develop a cellular model of the placenta became the winner in the Scientific Materials category of the Young Scientists 3.0 competition, organized with the support of the Presidential Grants Foundation and T-Bank.
Ten scientific journals published by RUDN University have been included in the highest level of the state list of scientific publications, the White List.
Forests are not only the lungs of the planet, but also home to millions of species. However, it has remained unclear how underground interactions between trees and fungi affect forest species richness in different climatic conditions. Previous studies have yielded conflicting results: in some regions, the dominance of certain fungi reduced tree diversity, while in others it increased it.