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  • Neural Network for Assessing English Language Proficiency Developed at HSE University

Neural Network for Assessing English Language Proficiency Developed at HSE University

Neural Network for Assessing English Language Proficiency Developed at HSE University

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The AI Lingua Neural Network has been collaboratively developed by the HSE University’s AI Research Centre, School of Foreign Languages, and online campus. The model has been trained on thousands of expert assessments of both oral and written texts. The system evaluates an individual's ability to communicate in English verbally and in writing.

Individuals interested in assessing their speaking and writing proficiency are invited to complete a series of tasks, including writing an essay, answering interview questions, and composing a monologue. Completing the tasks takes no more than 60 minutes, and the test is accessible on any digital device. Results, along with brief comments, are available within 30 minutes.

This format enables a representative assessment of the range of skills most commonly used in oral and written communication. When evaluating responses, the neural network considers over 45 parameters developed by experts at the HSE School of Foreign Languages. The result is determined through a comprehensive assessment of lexical, grammatical, and phonetic/stylistic aspects of speech, as well as characteristics such as coherence, logical presentation of thoughts, and skills in description, reasoning, and narration.

Based on the results of the tasks, a final score is calculated, and a language proficiency level is assigned, ranging from elementary to upper-intermediate. The proficiency level scale developed at the HSE School of Foreign Languages and integrated into the neural network aligns with all international language testing systems.

'An AI model capable of evaluating oral and written tasks with open-ended responses remains a rarity in language education. It can be described as a cutting-edge category of AI-based assessment systems, as the neural network has been trained to identify a variety of complex indicators of speech behaviour to determine candidates' levels of communicative competence,' according to Ekaterina Kolesnikova, Head of the HSE School of Foreign Languages.

The model has been trained on thousands of expert assessments of oral and written texts produced by actual participants in academic communication. The process of ongoing training and refinement of the model continues. Currently, the neural network is in its beta stage, undergoing testing and calibration for further integration into the process of assessing student work as part of independent English proficiency examination. It is planned for the neural network to function as one of the experts.

'The project to develop AI Lingua is an example of adapting large foundational models for a specific applied field—education. We have come all the way from testing various scientific hypotheses to implementing models in the final product, which is available as an online service for self-assessing English proficiency. Our solution is distinguished by its ability to simultaneously evaluate not only text responses but also audio speech, producing a language proficiency level based on a comprehensive set of criteria. To achieve this, we studied a substantial number of open-source solutions and subsequently conducted additional training on works analysed by professional linguists,' explains Alexey Masyutin, Director of the AI Centre.

The HSE University's team also notes that there are plans to develop models for other foreign languages. This will assist foreign language learners in conducting self-assessments of their knowledge, receiving timely feedback with the necessary level of detail, and tracking their progress in language proficiency development.

'The integration of AI solutions into the language skills assessment process fundamentally transforms the approach to language learning, making it more convenient and user-friendly. We are developing a tool that not only records the current level of knowledge but also dynamically tracks progress, offering everyone the opportunity for regular and objective self-assessment,' emphasises Sergey Roshchin, Vice Rector of HSE University.

The beta version of the English proficiency self-assessment tool is available for free with a promo code sent via email upon registration.

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