Integrating AI into the cooperative learning method Think-Pair-Share

UDC 378-042.4:004.8+81`24
DOI 10.20339/AM.04-26.081

Wang Lan, Ph.D. in Philology, Lecturer in Russian Language at the School of Foreign Languages, Chang’an University, Xi’an, China, e-mail: wlan2016@163.com, https://orcid.org/0009-0002-7739-8558

Liu Yang, Ph.D. in Philosophy, Senior Lecturer in Russian Language, Xi’an Polytechnic University, Xi’an, China, e-mail: liuyangspring@mail.ru

Cao Panpan, Cand. Sci. (Pedagogy), Associate Professor, Teacher of Russian Language, Ural Federal University named after the first President of Russia B.N. Yeltsin, Yekaterinburg, Russia, e-mail: tsaopanpan@yandex.ru

The relevance of this study is conditioned by the need to address the widespread problem of high situational anxiety in speaking and difficulties in oral expression among non-linguistic students studying a foreign language (using Russian as a case study). The primary objective of the work was to develop the “AI-enhanced Think-Pair-Share” (AI-TPS) learning model and empirically verify its effectiveness. The methodological basis was a quasi-experimental study, during which a comparative analysis of this methodology with the traditional TPS model was conducted (sample size n = 40). The analysis of the obtained results demonstrated that the pedagogically grounded integration of AI provides students with instant corrective feedback and creates a psychologically safe environment for speech practice. This, in turn, contributed to a statistically significant reduction in the level of foreign language anxiety in the experimental group. Furthermore, students using AI demonstrated clear superiority over the control group, showing significant qualitative and quantitative progress in key indicators such as speech fluency, lexical diversity, and syntactic complexity of utterances. In conclusion, the study confirms the high empirical value of human-machine interaction in teaching oral speech and offers a new methodological approach to resolving the contradiction between the lack of classroom practice and delayed feedback.

Keywords: AI-enhanced TPS model, speaking anxiety, oral production, Russian for non-philologists; syntactic complexity, human-machine interaction

This study was supported by the 2025 Undergraduate and Continuing Education Reform Project at Chang’an University (Grant No. ZZ202511).

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