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News
May 14, 2026
Resource Race and Green Transition: Three Unexpected Conclusions from Foresight Centres Research on Climate and Poverty
Beneath the surface of green energy—which most people associate with solar panels, electric vehicles, and reduced CO2 emissions—lies a complex web of geopolitical interests, international inequality, and resource constraints. Researchers from the Laboratory for Science and Technology Studies (LST) at the HSE ISSEK Foresight Centre have published a series of articles in leading international journals on hidden and overt conflicts surrounding critically important metals and minerals, as well as related processes in the energy sector.
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Immersion in Second Language Environment Influences Bilinguals Perception of Emotions
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ASSESSING CREATIVITY IN PRIMARY SCHOOL USING IMAGE ANALYSIS WITH NEURAL NETWORKS: A TWO-STEP APPROACH

P. 8096–8103.
Uglanova I., Gelver E., Tarasov S., Gracheva D., Vyrva E.

Most creativity assessment tools involve graphical solutions (images) evaluated by experts. Scoring with the engagement of human raters requires time and effort, and the automated scoring methods are insensitive to the content. As an alternative to both expert judgments and fully automatic scoring, machine learning (ML) demonstrated a great contribution to the field of  educational assessment. The present study investigates the possibilities of assessing student creativity based on ML for image recognition. The study postulates large-scale prospects for ML to assess complex educational and psychological characteristics.

Language: English
DOI
Keywords: creativityneural networkspsychometrics image analysis

In book

EDULEARN21 Proceedings 13th International Conference on Education and New Learning Technologies July 5th-6th, 2021
EDULEARN21 Proceedings 13th International Conference on Education and New Learning Technologies July 5th-6th, 2021
IATED, 2021.
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