Educating With Edge: Aligning Bloom's Revised Taxonomy With the Substitution, Augmentation, Modification, and...

Background: Artificial intelligence (AI) has rapidly emerged as both an opportunity and a challenge for nursing education. As AI tools become increasingly prevalent in clinical practice, Doctor of Nursing Practice (DNP) programs must reconsider traditional pedagogical strategies. Embedding competencies in informatics and technology into curricula is essential to align with the American Association of Colleges of Nursing Essentials and evolving health care practice. Objective: This article aims to present a practical instructional design framework that guides the integration of AI competencies into DNP curricula, preparing graduates to lead innovation while maintaining the unique identity and impact of the DNP-prepared nurse. Methods: A combined instructional design approach synthesizing Bloom's Revised Taxonomy (BRT) and the Substitution, Augmentation, Modification, and Redefinition (SAMR) model was developed. Bloom's taxonomy provides a structured method for creating learning outcomes across cognitive complexity levels and knowledge domains. The SAMR model complements this taxonomy by scaffolding technology integration from basic enhancement to transformative applications. Results: Synthesizing BRT and SAMR highlighted a flexible instructional design blueprint that aligns cognitive progression with levels of AI engagement. This pairing supports educators to intentionally embed AI-related competencies into coursework, ensuring students advance in both critical thinking and technological fluency. Recent literature reinforces the need for structured AI competencies in DNP education, highlighting the value of frameworks that integrate cognitive and technological dimensions. Conclusions: Deliberate use of BRT and SAMR together offers a practical strategy for embedding AI into nursing curricula. This approach equips faculty with a tool aimed at intentional design that balances cognitive learning outcomes with meaningful AI integration. Implications for Nursing: Adopting this framework allows nursing educators to enhance students' critical thinking, promote technological fluency, and prepare DNP-prepared nurses to effectively leverage AI in health care settings. Through structured instructional design, programs can ensure graduates are ready to navigate and lead innovation in a technology-driven health care climate.