Larger Groups of Students Use AI More Effectively in Learning
Researchers at the Institute of Education and the Faculty of Economic Sciences at HSE University have studied what factors determine the success of student group projects when they are completed with the help of artificial intelligence (AI). Their findings suggest that, in addition to the knowledge level of the team members, the size of the group also plays a significant role—the larger it is, the more efficient the process becomes. The study was published in Innovations in Education and Teaching International.
Group projects are an essential and common part of higher education, but there is still uncertainty about what makes teamwork effective.
The situation has become more interesting since the emergence of AI, which students have started to actively use in their studies. Experts from HSE University, including Galina Shulgina, Aleksandra Getman, Ilya Gulenkov, and Jamie Costley, explored how the characteristics of groups—the size and level of participants’ knowledge—affect the outcomes of work when AI is involved.
The study included 196 second-year undergraduate students, 55% of whom were male and 45% female. They had to solve problems as part of a team in a 16-week macroeconomics course. The students were divided into groups of five to eight people with varying levels of knowledge and experience. At first, the students worked independently on tasks. Then, they attended four seminars where they used ChatGPT 3.5 as a group tool. The goal was not simply to receive an answer from the AI, but to critically analyse it, apply economic models from the course, and present a comprehensive solution.
Researchers evaluated the quality of solutions based on the accuracy and detail of students' responses. Teams that not only used AI correctly but also revealed its limitations earned the highest scores, demonstrating a deeper understanding of the material.
The scientists identified several patterns in the use of AI by groups. Firstly, the best results were achieved by teams with members of similar levels of expertise. However, teams with a wider range of knowledge often performed less effectively. This is despite the fact that, in pedagogy, it is often believed that diversity of knowledge can help rather than hinder a team's performance.
Galina Shulgina
‘We were surprised to discover that the wider the range of student grades, the lower the quality of the final decision. This may be because the more prepared students spent time discussing and reaching an agreement on a solution, rather than focusing on the task itself, while less prepared students were unable to fully utilise the AI capabilities available to them. More skilled students are better at interacting with AI, as they can formulate more complex queries, critically evaluate the responses, and use this information to reason through problems,’ explains Galina Shulgina, junior researcher at the International Laboratory of Research and Design in eLearning at HSE University.
Secondly, the data showed a clear positive correlation between a larger team size and better performance when working with AI. Larger teams, with seven to eight members, performed better on average compared to teams with five to six members. Each additional member contributed to the final score, contrary to the common belief in pedagogy that smaller teams are more effective. Scientists argue that larger teams have more intellectual resources and a variety of perspectives, which help them interact more productively with neural networks.
Aleksandra Getman
‘However, this does not mean that efficiency gains will continue infinitely. After a certain point, negative effects may start to appear, such as difficulty in coordination and increased time to coordinate and maintain shared understanding of the task,’ explains Aleksandra Getman, junior researcher at the International Laboratory of Research and Design in eLearning at HSE University.
Despite the need for further research, the authors believe that in order to optimise the use of AI in education, students with similar educational levels should be grouped together in large classes. The researchers suggest that AI could be applied to the study of any subject.
Ilya Gulenkov
‘There is a potential for incorporating AI into group work in any course, regardless of the field of study or level of training. The key task of the teacher in organising such work is to set students’ expectations in advance about how and why AI can be used in their coursework. If students see examples of successful application of AI, then it can become an additional team member in any subject. We observe how students are using more advanced versions of the models (ChatGPT 5, ChatGPT 5 Thinking, etc), and we see great potential for student–AI collaboration. This applies not only to simple, standardised tasks, but also to complex ones that require in-depth understanding, working with multiple sources, and advanced reasoning. The role of students' own expertise in interacting with these models is becoming increasingly important. All models now provide plausible answers, but it is essential to critically evaluate their content,’ says Ilya Gulenkov, lecturer at HSE University’s Faculty of Economic Sciences.
See also:
Biologists Discover Unique Properties of MiR-93-5p MicroRNA in Prostate Cancer
Researchers at the International Laboratory of Microphysiological Systems of the HSE Faculty of Biology and Biotechnology investigated how different isoforms of the same microRNA influence gene function in prostate adenocarcinoma. The study found that in some cases, microRNAs can reinforce each other’s effects by targeting and suppressing the same genes. This finding offers a fresh perspective on the molecular mechanisms underlying tumour development and on the search for disease biomarkers. The results have been published in PeerJ.
HSE Economists Use Search Queries to Forecast Birth Rates
Researchers from the HSE Faculty of Economic Sciences have shown that the accuracy of birth rate forecasts for Russia can be improved by almost 50% by incorporating the dynamics of online search queries related to pregnancy and childbirth into forecasting models. In the best-performing models, the forecasting error fell from 4.6% to 3.2%. The findings have been published in Populations and Economics.
When Looking at Their Own Faces, Men Forget Everything
In an experiment involving 15 healthy men, scientists at HSE University investigated how different phases of the cardiac cycle influence the excitability of the motor cortex when participants viewed either their own photograph or the faces of strangers. The researchers found that when participants looked at their own image, the brain’s response to signals from the heart was weaker, meaning that the influence of cardiac activity on the motor cortex decreased. This finding came contrary to expectations, as self-focused attention was thought to enhance the brain's sensitivity to internal bodily signals. The study has been published in Frontiers in Signal Processing.
HSE Researchers Discover Who Eats Out in Russia—And Why
Around one-third of Russians (31.3%) rarely eat out or buy ready-made meals. The core group of active consumers—those who eat out or purchase prepared food almost every day or several times a week—accounts for only about 9% of the population. These are the findings of a study conducted by the HSE Institute for Social Policy. According to the researchers eating out is no longer a marker of high social status in Russia.
Scientists Model How Interactions Between Societies Can Trigger Chaotic Behaviour
Scientists at HSE MIEM have proposed a mathematical model explaining how interactions between societies can influence their stability. Based on the classical theory of evolutionary games, the study reveals an unexpected effect: even a weak informational influence of one society on another can cause one society to remain stable while the other exhibits chaotic behaviour among its individual members. The study has been published in the International Journal of Bifurcation and Chaos.
Ancient Craniiform Brachiopod: A Newly Discovered Species with a Unique Shell Shape and Lifestyle
Scientists from HSE University, MSU, and Tallinn University of Technology have studied a fossil species of ancient brachiopods that lived in a warm sea in what is now northern Estonia more than 445 million years ago. These ancient brachiopods developed a cup-shaped shell with a protective 'cap' that shielded them from overgrowth by other marine organisms. The study has been published in Palaeogeography, Palaeoclimatology, Palaeoecology.
Scientists Develop Bacterium-Sized Microlaser
An international team of researchers, including scientists from HSE University–St Petersburg, has developed microlasers that emit deep-ultraviolet light at a wavelength of 255 nanometres. The devices operate at room temperature, and the smallest of them measures just two micrometres in diameter—roughly the size of a bacterium. These microlasers could be used in sensors, spectroscopic systems, photonic chips, and communication devices. The paper has been published in Optics & Laser Technology.
HSE Develops App for Assessing Phonological Processing in Children
Researchers at the HSE Centre for Language and Brain have developed a new digital tool for assessing children's phonological processing skills—the ZARYA (Sound Analysis of the Russian Language) test battery. It is the first standardised application in Russia designed to provide a fast and reliable assessment of children's ability to distinguish speech sounds, retain them in working memory, and perform phonemic analysis. The app runs on Android tablets and smartphones and is available for download from RuStore. Details of the test validation have been published in the Journal of Speech, Language, and Hearing Research.
Researchers Discover How Spelling Errors Slow Down Reading in Russian
Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.
Scientists Discover Why Europium 'Misbehaves'
Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.