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News
September 21, 2026
Researchers Develop Methodology to Assess the Quality of Legal Representation in Criminal Proceedings
Having a good defence attorney in criminal proceedings can largely determine whether a defendant retains their freedom, health and good name. Researchers at HSE University propose a method for predicting an attorney’s performance based on the outcomes of their previous cases. The methodology takes into account the severity of the charges, the complexity of the cases, and the most likely outcome, drawing on judicial statistics.
September 21, 2026
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.

 

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Exploring the Relationship between Performance and Response Process Data in Digital Literacy Assessment

Journal of Modern Foreign Psychology. 2024. Vol. 13. No. 1. P. 58–68.
Tkachenko Irina, Tarasova K., Gracheva D.

Measuring complex latent constructs is challenging because of their multi-dimensionality. In this context, computer-based assessments have gained popularity due to its ability to handle large diverse data. The aim of the study is to investigate the interrelationship between performance, time, and actions in computer-based digital literacy assessment. The study involved more than 400 8th-grade schoolchildren (approximately 14—15 years old) from secondary schools in Russia. A subset was obtained from indicators capturing the demonstration of analysis of data, information, and digital content, which is a component of the information literacy in the digital literacy framework. The data was used to create latent models in the structural equation modeling framework. Confirmatory one-factor model for the Performance factor showed a good fit to the data (CFI=1; TLI=1; RMSEA=0). The model with dependencies among indicators demonstrated improved model fit (χ2(18)=510,65; p=0,05) compared to the model without such dependencies. The results suggest that performance, time, and actions are interdependent. The findings underscore the need for a comprehensive approach to assessing digital literacy that accounts for these interdependencies, as well as investigating behavioral patterns of interaction with a large amount of information in the digital environment.
 

Research target: Education
Language: English
DOI
Keywords: confirmatory factor analysisstructural equation modelingresponse timeevidence-centered designdigital literacycomputer-based assessmentProcess dataclicks
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