Analyzing the Potential of AI-Powered Writing Evaluation Tools for Developing Students' Analytical Skills

In the contemporary context of learning, the utilisation of artificial intelligence (AI) has emerged as a pivotal concern, particularly concerning the diligent employment of neural networks by students as a medium to augment learning, as opposed to their utilisation as a mere executor of tasks derived from textbooks. This paper delves into the realm of students' engagement with AI-powered tools, offering feedback on their written compositions, summaries, articles, etc. during their university education. The scientific significance of this study lies in its analysis of the potential of modern automated writing evaluation services using large language models, such as ProWritingAid, Quillbot, MagicSchool and DeepSeek, to encourage students to develop their analytical skills while actively participating in corrective assessment of their writing based on feedback received from the AI tools. The necessity of employing automatic feedback mechanisms is further examined within the context of foreign language acquisition for technical students pursuing higher education, with a focus on electronics and electrical engineering as case studies. The analysis yielded recommendations for enhancing the efficacy of feedback provision to students.