Prompt engineering as a pedagogical design tool in AI-assisted education in technical disciplines

Abstract

The article focuses on the potential of prompt engineering — the discipline of designing effective queries for large language models (LLMs) — as an innovative pedagogical design tool for AI-assisted education in technical disciplines. The authors analyze the alignment of the principles of prompt engineering with the classical tasks of didactics, emphasizing its role as a meta-tool that enables teachers to design the educational environment to achieve specific learning objectives. The article examines in detail key patterns of prompt engineering, such as ‘Role-Play’, ‘Reliability Analysis’, and ‘Output Automation’, and demonstrates their practical application for automating the creation of personalized learning materials, practical tasks, and assessment tools. Using examples from courses in physics, geometry, probability, and statistics, the article shows how these patterns enable the modelling of professional activity, the development of critical and engineering thinking, and the linking of abstract theoretical knowledge with the solution of real-world practical problems. In addition to didactic tasks, the article considers the use of prompts to automate routine teacher tasks (such as preparing reports and lesson plans), organize extracurricular activities, resolve conflict situations, and support individual work with students. The integration of prompt engineering skills into teachers’ professional competence is essential in the context of the digital transformation of education. However, it is emphasized that this tool should not replace but rather complement the teachers’ fundamental pedagogical skills, creativity, and emotional intelligence, while addressing risks related to information accuracy and the ethical use of AI.