A Linguistic Taxonomy of Human-AI Interaction: Discursive Strategies in Prompt Engineering for Large Language Models

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Key Points

The research aims to establish a linguistic taxonomy of discursive strategies used in prompt engineering for large language models.
Analyzed the role of prompts as communicative acts involving user intent and context.
Developed a taxonomy of strategies like contextualization and dialogue clarification relevant to prompt engineering.
Investigated the implications of prompt literacy for digital competence in higher education and professional communication.
Identified key strategies that help mitigate ambiguity and direct AI-generated responses effectively.
Demonstrated the significance of prompt literacy for critical language users brightening digital competence in various fields.
Concluded that understanding linguistic taxonomy of AI interaction enhances responsible use of large language models in academic contexts.

Explores discursive strategies in prompt engineering for large language models, highlighting user intent and context.

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Степанова et al. (2026) studied this question.

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