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eLIBRARY ID: 8377
ISSN: 2074-1588

eLIBRARY ID: 8377
ISSN: 2074-1588

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Evolution of testing and assessment systems in foreign language teaching: from computers to GPT

Evolution of testing and assessment systems in foreign language teaching: from computers to GPT

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Recieved: 06/28/2025

Accepted: 10/01/2025

Keywords: AI in language education, control and assessment, adaptive testing, personalization of learning, automatic writing evaluation systems

DOI Number: 10.55959/MSU-2074-1588-19-28-4-3

To cite this article

Titova S.V. Evolution of testing and assessment systems in foreign language teaching: from computers to GPT. // Moscow University Bulletin. Series 19. Linguistics and Intercultural Communication 2025. Vol. 28. Issue 4. 36-58 https://doi.org/10.55959/MSU-2074-1588-19-28-4-3.

Сreative Commons Atribiution - NonCommercial 4.0 International (CC BY-NC 4.0)
This work is licensed under a Сreative Commons Atribiution - NonCommercial 4.0 International (CC BY-NC 4.0)
Issue 4, 2025
Titova S.V. (Lomonosov Moscow State University)

Abstract

The article presents a comprehensive analysis of changes in approaches to monitoring and assessing language proficiency from the advent of the first computers to the introduction of modern generative artificial intelligence models. The study aimed to trace the historical evolution of intelligent assessment systems, conduct a comparative analysis of existing solutions, identify ways to integrate AI into language education, and assess prospects for further development in this field. Particular attention is paid to automatic written text assessment systems, the stages of their integration into learning, and intelligent adaptive testing platforms capable of personalizing assignments to the level and needs of students. The study’ s results demonstrate that modern intelligent systems significantly expand the capabilities of teachers and students, providing more accurate and rapid assessment of written assignments and facilitating the development of individual educational trajectories. The integration of generative models into testing systems opens up new prospects for language education but requires a rethinking of the role of the teacher, improved methods and ethical standards, and training of specialists capable of effectively using AI tools in educational practice.

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