Solving research tasks by linguistics students based on Artificial Intelligence technologies

Abstract

The didactic and language didactic potential of artificial intelligence (AI)-based technologies enables students to solve a wide range of research problems at all three stages of university study: undergraduate, graduate, and postgraduate. However, AI’s hallucinatory propensity, bias, and unipolarity of provided feedback can inevitably lead to data falsification and destructive consequences. In this article, the authors (a) present a list of universal research objectives, some of which can be fully delegated to AI, some of which should be solved jointly by the teacher, students, and AI, and some of which students should solve independently; (b) present a list of specialized research objectives solved by specialists in foreign language teaching methods; and (c) present the conditions for students at three levels of education to effectively prepare research papers using AI tools. Universal research skills are aimed at solving a fairly wide range of tasks — from developing a work plan and statistical data processing to editing and visualizing data. Narrow-profile research tasks reflect the specifics of foreign language teaching methods and include the development of training exercises and communicative tasks, control materials and questionnaires, processing large arrays of texts, etc. These tasks are often completed by students when preparing the practical sections of qualification papers and in empirical studies. According to the authors, the effectiveness of AI integration into research work is ensured by considering the following conditions: a) when performing research work AI does not replace a human researcher, rather it assumes responsibility for the performance of routine or technical tasks, freeing up the user’s time to solve other, higher-level cognitive tasks. At the same time, students must adhere to the principles of academic ethics; b) all material from generative AI must be subject to critical analysis and verification; c) users must master the ability to correctly formulate prompts to AI in order to receive high-quality and expected feedback; d) the selection of generative AI tools used in research work must be determined by the regulatory framework; d) the student bears full responsibility for the process and results of the research using AI.

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