RU
Pedagogy. Theory & Practice
  • Original research article
  • April 17, 2026
  • Open access

A didactic model for developing sociolinguistic appropriateness in foreign language academic writing for linguistics undergraduates through the integration of prompts based on artificial intelligence and peer assessment

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Abstract

The research aims to theoretically substantiate and describe a didactic model for developing sociolinguistic appropriateness in foreign language (L2) academic writing among linguistics undergraduates by integrating prompts based on artificial intelligence (AI-based prompts) and peer assessment. The article presents the model’s structure and details its implementation within a face-to-face English academic writing course as part of the “Practical Course of the First Foreign Language” discipline. The described model involves a sequential workflow: drafting, obtaining AI-based prompts via standardized requests (considering genre and addressee), self-correction, peer review by two classmates using an analytical rubric, and final editing. The analytical rubric provides a unified criterion-based foundation for the formative assessment of the text’s sociolinguistic appropriateness and is utilized both during peer review and when evaluating AI-generated recommendations. The scientific novelty of the study lies in the development of a reproducible formative assessment procedure for L2 academic writing, in which AI-based prompts and peer assessment are unified by a common criteria framework. As a result of testing the model through a formative experiment, it was established that the score increase in the experimental group significantly outperformed the control group: 3.6 points on the total scale and 1.2 points for the sociolinguistic appropriateness component, compared to 1.4 and 0.4 points, respectively. Approximately 40% of the edits in the experimental group were related to register, speech etiquette, audience awareness, and the degree of hedging (categoricalness). The findings suggest that the proposed model is a promising didactic solution for organizing step-by-step L2 academic writing within face-to-face educational settings.

Research materials

  1. Council of Europe.Common European Framework of Reference for Languages: Learning, Teaching, Assessment.Companion Volume. Strasbourg: Council of Europe Publishing, 2020.
  2. UNESCO. Guidance for generative AI in education and research. P.: UNESCO, 2023.

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Author information

Ivan Evgenievich Rodikov

Peoples’ Friendship University of Russia named after Patrice Lumumba, Moscow

About this article

Publication history

  • Received: February 8, 2026.
  • Published: April 17, 2026.

Keywords

  • социолингвистическая уместность
  • академическое письмо на иностранном языке
  • подсказки на основе искусственного интеллекта
  • взаимооценивание
  • формирующее оценивание
  • sociolinguistic appropriateness
  • foreign language academic writing
  • prompts based on artificial intelligence
  • peer assessment
  • formative assessment

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© 2026 The Author(s)
© 2026 Gramota Publishing, LLC

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Creative Commons Attribution 4.0 International (CC BY 4.0)