Prompt engineering, the practice of designing and refining inputs for AI systems, has become a pivotal skill in modern learning environments, allowing learners to interact with AI tools more effectively and extract meaningful, relevant outputs. By structuring queries logically, students develop critical thinking and enhance problem-solving skills, as they must anticipate potential responses and refine their questions accordingly. It also enables personalized learning, as learners can tailor prompts to their individual needs and pace, while step-by-step guidance from AI supports deeper understanding of concepts. Experimenting with different prompts fosters creativity and innovation, encouraging learners to explore alternative solutions to academic and practical problems. Engaging with AI tools further develops technical literacy and familiarity with emerging digital technologies, while also raising awareness of AI limitations, biases, and ethical considerations. Iterative prompt refinement promotes feedback-driven learning and reflective thinking, helping learners build resilience and adaptability through trial-and-error interactions. Additionally, prompt engineering supports collaborative learning, enhances communication skills, and provides practical experience in computational thinking and data interpretation. While over-reliance on AI without thoughtful engagement can limit independent reasoning, careful practice ensures that prompt engineering serves as a bridge between technology and cognitive development. Overall, it empowers learners to become active participants in knowledge creation rather than passive consumers, significantly contributing to learning, skill development, and lifelong adaptability in an AI-driven world.
Shaikh et al. (2026) studied this question.