Prompt engineering in education: A systematic review of theory, applications, and future directions
DOI:
https://doi.org/10.63697/jessp.2026.10093Keywords:
Prompt engineering, Generative AI, ChatGPT, Teacher readiness, Educational technologyAbstract
The integration of Generative Artificial Intelligence (GenAI), particularly large language models (LLMs) such as ChatGPT, has significantly influenced current educational practices. Among the competencies necessary for effective interaction with LLMs, prompt engineering has emerged as a focal point. Prompt engineering encompasses the design, organization, and optimization of inputs to GenAI systems to produce accurate, relevant, and pedagogically meaningful outputs. Although empirical, conceptual, and policy-oriented studies on this topic are increasing, research on prompt engineering in education remains fragmented across disciplines and educational contexts. This paper systematically reviews the application of prompt engineering in education, synthesizing theoretical foundations, developmental trajectories, models, frameworks, and application domains. Drawing on recent peer-reviewed literature, with an emphasis on studies published in the past three years, the review consolidates findings on motivation, attitudes, knowledge, and skills related to prompt engineering among both learners and educators. The expanding role of AI in education prompts a critical inquiry: how can AI be integrated into teaching in ways that preserve and enhance the human dimensions of knowledge sharing? This paper introduces a framework for the responsible use of AI that reinforces, rather than replaces, the essential human elements at the heart of education.
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Copyright (c) 2026 Saeed Anowar, Reshma Khatun
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