The Impact of Aligning Artificial Intelligence Large Language Models With Bloom's Taxonomy in Healthcare Education

Abstract

The innovation of large language models (LLMs) has widened possibilities for renovating healthcare education through AI-powered learning resources, such as chatbots. This chapter explores the assimilation of LLMs with Bloom's taxonomy, demonstrating how this foundational framework for designing and assessing learning outcomes can support the development of critical thinking, problem-solving, and decision-making skills in healthcare learners. Through case examples and research presentations, this chapter illustrates how LLM chatbots provide interactive, scaffolding, and contextually relevant learning experiences. However, it also highlights the importance of designing these tools with key principles in mind, including learner-centeredness, co-creation with domain experts, and principled responsibility. By embracing a collaborative, interdisciplinary, and future-oriented approach to chatbot design and development, the power of LLMs can be harnessed to revolutionize healthcare education and ultimately improve patient care.

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