Generative AI tools are transforming educational landscapes, offering educators the potential for meaningful integration beyond basic applications. Presenters will share various prompt engineering strategies, as well as results from a research study conducted with undergraduate students studying English as a Foreign Language. This study introduced prompt engineering as a systematic didactic framework that shifts AI from a replacement threat to a collaborative learning partner, offering practical pathways for educator upskilling and student autonomy across disciplines.

Theoretical Framework and Research Context: Rather than viewing AI as an external tool, prompt engineering positions AI interaction as a co-constructive process requiring critical thinking, linguistic precision, and iterative refinement. Building on Nazari and Saadi's (2024) structured framework, this approach transforms AI engagement from passive consumption to active collaboration, where both educators and students develop metacognitive strategies for effective human-AI partnerships.

The Study: A quasi-experimental study with 84 students examined systematic prompt engineering training versus traditional AI usage. Participants learned structured strategies for AI interaction, focusing on iterative prompt refinement, critical evaluation of outputs, and reflective practice. Data were collected pre- and post-intervention and analysis showed significant improvements in output quality (Cohen's d = 0.73). Participants developed enhanced metacognitive awareness and critical thinking skills, and reported increased confidence in learning autonomy while maintaining a critical stance toward AI-generated content.

Educational Implications for All Disciplines: For educators, prompt engineering offers a structured entry point into AI integration that builds on existing pedagogical skills rather than requiring technical expertise. The Nazari and Saadi (2024) framework enables teachers to model critical thinking, scaffold student learning, and maintain pedagogical authority while embracing technological advancement. Students develop valuable 21st-century competencies: precise communication, iterative problem-solving, and critical evaluation skills essential across all subjects.

Challenges and Opportunities: This collaborative approach transforms classroom dynamics, requiring educators to balance digitally competent guidance with student autonomy (Engel et al., 2023). Key challenges include developing assessment strategies that value process over product, addressing digital equity concerns, and maintaining academic integrity. However, the potential for personalized learning, enhanced student engagement, and teacher professional growth outweighs risks when systematically implemented.

Conclusions: Prompt engineering represents a paradigm shift from AI as threat to AI as educational partner. By focusing on collaborative competencies rather than technical skills, educators across disciplines can confidently integrate AI while maintaining pedagogical integrity and fostering deeper student learning.