Strategies of using artificial intelligence for written corrective feedback in language education

Abstract

The article discusses the strategies for using artificial intelligence (AI) in the context of providing written corrective feedback in language education. It provides an overview of the latest research in this area, starting from the most significant publications in the field of Russian neurodidactics and international conferences dedicated to the use of AI in education, to practical examples of using chatbots for feedback in language teaching. The article emphasizes the transformation of the role of language educators through the application of artificial intelligence, highlighting the importance of focusing the teacher on the essential aspects of students’ communicative development while delegating the technical aspects of proofreading written assignments to artificial intelligence. The application of such technologies changes the ways feedback is provided, allowing for a more in-depth linguistic analysis and the creation of more extensive comments on written works. Examples of specific requests made to artificial intelligence when marking assignments and examples of their implementation are provided. In addition, the article summarizes the strengths and weaknesses of using AI technologies for assessment and draws conclusions about its role in providing written corrective feedback. The article also highlights the need for a thoughtful integration of AI into the educational process and calls for further research on the impact of artificial intelligence technologies on the development of students’ written productive language skills.

References

1. Ershova T.A. 2020. Razvitie professionalno-kommunikativnyh umenij pismennoj obratnoj svyazi studentov lingvodidakticheskih specialnostej (anglijskij yazyk) [Development of professional and communicative skills of written feedback of students of linguodidactic specialties (English language)]. PhD dis. Tambov. (In Russ.)

2. Korenev A.A. 2018. Obratnaya svyaz’ v obuchenii i pedagogicheskom obshchenii [Feedback in education and educational communication]. Rhema, no, 2, pp. 112–127. (In Russ.)

3. Коrenev A.A. 2023. Professional’no-kommunikativnye strategii kak komponent soderzhaniya yazykovogo obrazovaniya pri podgotovke budushchikh uchitelei i prepodavatelei inostrannogo yazyka [Professional communicative strategies as an element of language training in language teacher education.]. Rhema, no. 3, pp. 97– 121. (In Russ.)

4. Safonova V.V. 2021. Lingvodidakticheskie razmyshleniya o mediativnom obrazovanii prepodavatelya-issledovatelya v sisteme yazykovoi podgotovki k mezhdunarodnomu partnerstvu i sotrudnichestvu [Linguodidactic reflections on mediative education of a teacher-researcher in the system of language training for international partnership and cooperation]. Moscow State Linguistic University Bulletin. Education and Educational Sciences., no. 1, pp. 151–164. (In Russ.)

5. Sysoev P.V. 2023. Tekhnologii iskusstvennogo intellekta v obuchenii inostrannomu yazyku [Artificial intelligence technologies in teaching a foreign language]. Inostrannye yazyki v shkole, no. 3, pp. 6–16. (In Russ.)

6. Titova S.V. 2022. Proektirovanie tsifrovogo uchebnika kak innovatsionnogo sredstva obucheniya [Designing a digital textbook as an innovative learning tool]. Moscow State University Bulletin. Series 19. Linguistics and Intercultural Communication, no. 3, pp. 41–60. (In Russ.)

7. Titova S.V., Basova I.A., Korenev A.A., Marinina E.V., Safonova V.V., Sysoev P.V., Tareva E.G., Kharlamenko I.V. 2023 Karta kompetentsii pedagoga inostrannykh yazykov v usloviyakh tsifrovizatsii obrazovaniya [Competency map of a teacher of foreign languages in the conditions of education digitalization]. Moscow, Editus. (In Russ.)

8. Ellis R. 2008. A typology of written corrective feedback types. ELT journal, vol. 63, no. 2, pp. 97–107.

9. Sabitzer B. 2011. Neurodidactics — a new stimulus in ICT and computer science education // INTED2011 Proceedings, pp. 5881–5889.