Using Bloom's Taxonomy to Develop Effective Assessments in Radiologic Technology Education.

The article focuses on the application of Bloom’s taxonomy—a hierarchical model of cognitive skills including remembering, understanding, applying, analyzing, evaluating, and creating—in developing effective assessments for radiologic technology education. It highlights how this framework supports alignment of learning objectives with assessment methods to promote critical thinking, clinical competence, and lifelong learning in radiologic technology students. The report discusses practical strategies such as backward design, diversified assessment types, and scaffolding to facilitate progression through cognitive levels, ensuring assessments reflect both foundational knowledge and complex clinical reasoning. Additionally, it acknowledges alternative educational frameworks like Fink’s Taxonomy of Significant Learning, Miller’s Pyramid of Clinical Competence, and the Structure of Observed Learning Outcomes taxonomy, which can complement Bloom’s taxonomy in fostering holistic professional development. The article underscores the ongoing relevance of Bloom’s taxonomy in adapting radiologic technology curricula to evolving healthcare demands, technological advances, and inclusive educational practices.