• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Smartphones Not Used for Digital Learning among Russian School Students

Smartphones Not Used for Digital Learning among Russian School Students

© iStock

Despite the widespread use of smartphones, teachers have not fully integrated them into the teaching and learning process, including for developing students' digital skills. Irina Dvoretskaya, Research Fellow at the HSE Institute of Education, has examined the patterns of mobile device use for learning among students in grades 9 to 11.

On September 1, 2024, a new law came into effect banning the use of mobile devices by school students during school hours, including for educational purposes. According to media reports, in 2023, over 80% of parents supported the proposed ban on smartphone use during school classes. Irina Dvoretskaya, Research Fellow at the HSE Institute of Education, analysed how Russian high school students had used smartphones up to that point and whether teachers had provided guidance on the use of digital tools.

For the study, an online survey was conducted in urban and rural schools in Russia among students in grades 9–11 (over 20,000 boys and girls) who owned smartphones. The study revealed that most high school students did not use smartphones for learning. Nearly 60% of respondents either did not use digital devices for educational purposes at all or only used them for basic tasks, such as accessing an electronic diary. Similarly, teachers did not employ educational practices that foster the development of digital competencies in the classroom. Most frequently, smartphones were used as calculators or tools for searching information. According to the study, only 7.34% of high school students can be considered advanced users of digital devices.

Dvoretskaya notes that in the current frontal instruction model used in schools, smartphones indeed tend to distract students from the learning process during class. However, it would be unreasonable to completely exclude gadgets from the educational process, considering their ubiquity and the growing digitalisation of all aspects of life. Otherwise, there is a risk that personal mobile devices will only be used by children as tools for entertainment and communication, rather than education.

Irina Dvoretskaya

Irina Dvoretskaya

'Each year, new user technologies emerge, such as AI chatbots, and banning smartphones in teaching and learning will not help children learn to use them responsibly and productively,' according to Dvoretskaya.

Productive use of a mobile device for active academic work in project-based or research-based learning enables students not only to master subject content effectively but also to develop 21st century skills, including the ability to satisfy their educational interests and needs and to solve various real-life challenges.

The research conducted can assist the administrations of Russian schools in evaluating the potential for integrating personal digital infrastructure into educational institutions. The data collected can also be used to monitor the progress and academic performance of different student groups, develop flexible learning pathways, and create individualised learning materials in the context of advancing artificial intelligence.

See also:

Scientists Test Asymmetry Between Matter and Antimatter

An international team, including scientists from HSE University, has collected and analysed data from dozens of experiments on charm mixing—the process in which an unstable charm meson oscillates between its particle and antiparticle states. These oscillations were observed only four times per thousand decays, fully consistent with the predictions of the Standard Model. This indicates that no signs of new physics have yet been detected in these processes, and if unknown particles do exist, they are likely too heavy to be observed with current equipment. The paper has been published in Physical Review D.

HSE Scientists Reveal What Drives Public Trust in Science

Researchers at HSE ISSEK have analysed the level of trust in scientific knowledge in Russian society and the factors shaping attitudes and perceptions. It was found that trust in science depends more on everyday experience, social expectations, and the perceived promises of science than on objective knowledge. The article has been published in Universe of Russia.

Scientists Uncover Why Consumers Are Reluctant to Pay for Sugar-Free Products

Researchers at the HSE Institute for Cognitive Neuroscience have investigated how 'sugar-free' labelling affects consumers’ willingness to pay for such products. It was found that the label has little impact on the products’ appeal due to a trade-off between sweetness and healthiness: on the one hand, the label can deter consumers by implying an inferior taste, while on the other, it signals potential health benefits. The study findings have been published in Frontiers in Nutrition.

HSE Psycholinguists Launch Digital Tool to Spot Dyslexia in Children

Specialists from HSE University's Centre for Language and Brain have introduced LexiMetr, a new digital tool for diagnosing dyslexia in primary school students. This is the first standardised application in Russia that enables fast and reliable assessment of children’s reading skills to identify dyslexia or the risk of developing it. The application is available on the RuStore platform and runs on Android tablets.

Physicists Propose New Mechanism to Enhance Superconductivity with 'Quantum Glue'

A team of researchers, including scientists from HSE MIEM, has demonstrated that defects in a material can enhance, rather than hinder, superconductivity. This occurs through interaction between defective and cleaner regions, which creates a 'quantum glue'—a uniform component that binds distinct superconducting regions into a single network. Calculations confirm that this mechanism could aid in developing superconductors that operate at higher temperatures. The study has been published in Communications Physics.

Neural Network Trained to Predict Crises in Russian Stock Market

Economists from HSE University have developed a neural network model that can predict the onset of a short-term stock market crisis with over 83% accuracy, one day in advance. The model performs well even on complex, imbalanced data and incorporates not only economic indicators but also investor sentiment. The paper by Tamara Teplova, Maksim Fayzulin, and Aleksei Kurkin from the Centre for Financial Research and Data Analytics at the HSE Faculty of Economic Sciences has been published in Socio-Economic Planning Sciences.

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.

New Models for Studying Diseases: From Petri Dishes to Organs-on-a-Chip

Biologists from HSE University, in collaboration with researchers from the Kulakov National Medical Research Centre for Obstetrics, Gynecology, and Perinatology, have used advanced microfluidic technologies to study preeclampsia—one of the most dangerous pregnancy complications, posing serious risks to the life and health of both mother and child. In a paper published in BioChip Journal, the researchers review modern cellular models—including advanced placenta-on-a-chip technologies—that offer deeper insights into the mechanisms of the disorder and support the development of effective treatments.

Using Two Cryptocurrencies Enhances Volatility Forecasting

Researchers from the HSE Faculty of Economic Sciences have found that Bitcoin price volatility can be effectively predicted using Ethereum, the second-most popular cryptocurrency. Incorporating Ethereum into a predictive model reduces the forecast error to 23%, outperforming neural networks and other complex algorithms. The article has been published in Applied Econometrics.

Administrative Staff Are Crucial to University Efficiency—But Only in Teaching-Oriented Institutions

An international team of researchers, including scholars from HSE University, has analysed how the number of non-academic staff affects a university’s performance. The study found that the outcome depends on the institution’s profile: in research universities, the share of administrative and support staff has no effect on efficiency, whereas in teaching-oriented universities, there is a positive correlation. The findings have been published in Applied Economics.