Foreign language written creative assignments in a language university in the era of ChatGPT: Problems and classification of solutions

Creative activity is traditionally considered an important element of foreign language learning, which is significant for both its oral and written aspects. Written creative tasks, such as compositions, essays, critical reviews and book or film reviews, completed in the target language, contribute to the development of writing skills and the formation of students’ independent thinking. At the same time, the intensifying digitalization of the educational sphere and the most modern neural network technologies have a transformative impact on the features of working with such written creative tasks. The awareness of this problem is increasing as evidenced by the growing number of publications devoted to the problems of the influence of neural network technologies on foreign language learning in general and on its specific aspects. Scholars consider both the positive aspects of using large language models (LLMs), such as ChatGPT, in foreign language learning. They pay attention to promising areas of development of neural network technologies that are significant for the educational sphere, but also point out a number of problematic aspects of employing such technologies. One of such problematic aspects of the widespread use of neural network technologies is the undesirable and unregulated use of LLMs by students when writing essays, compositions, critical reviews, and book or film reviews. Thus, the relevance of the study is due to the need to find and systematize effective and time-sensitive ways to solve the problem of undesirable use of LLMs by students when completing written creative work in the target language at a language university. The purpose of the study is to systematize and classify a wide range of solutions to the problem of undesirable and unregulated use of LLMs when completing written creative work, proposed in the extensive corpus of analyzed scientific publications. The material for the study includes relevant scientific publications of the last five years devoted to the problematic aspects of the influence of neural network technologies on the educational sphere in general and on university foreign language education in particular. The most promising ways to solve the problem of undesirable use of LLMs by students when completing written creative assignments in the target language are identified. Based on the analysis of modern research and the expert approach, the author of the article has developed a classification of promising ways to solve the problem under consideration. The proposed classification groups possible solutions to the problem into five classes organized according to the following principles: 1. changing the format of the creative task; 2. changing the features of the task while generally maintaining its format; 3. changing the assessment criteria. In addition, highlighted are 4. technological and 5. other ways to solve the problem of undesirable use of LLMs when completing written creative tasks in the context of a language university. The article provides detailed descriptions of each of the possible ways to solve the problem under consideration, presents some potential scenarios for their use, and highlights their strengths and weaknesses. Taking into account the current situation of digital transformation of the educational environment and in the absence of universal and sufficiently reliable methods for detecting texts generated by LLMs, the need for a combination of several ways to solve the problem of undesirable use of LLMs when completing written creative tasks is substantiated. Although this study specifically examines the context of teaching a foreign language in a language university, its results in the form of the proposed classification may be relevant in other educational contexts. The author declares no conflict of interests.

Keywords

Authors

References