This article is cited in 3 papers

Analysis of signals, audio and video information

Assessing creativity using image analysis with neural networks

I. L. Uglanova, Y. S. Gelver, S. V. Tarasov, D. A. Gracheva, E. E. Vyrva

HSE University, Moscow, Russia

Abstract: The present study investigated the possibilities of assessing student creativity based on neural networks approaches for image analysis. The use of psychometric data analysis in the methodology of Latent Class Analysis (LCA) allowed us to obtain data labels to train the neural network without experts’ involvement. The high accuracy in network predictions for identifying image creativity suggested large-scale prospects for machine learning to assess complex educational and psychological characteristics.

Keywords: creativity, image analysis, neural networks, educational assessment, psychometrics, machine learning.

DOI: 10.14357/20718594210108

 English version: , 2022, 49:5, 371–378

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