APPLICATIONS OF GENERATIVE ARTIFICIAL INTELLIGENCE ACROSS BLOOM'S TAXONOMY A SYSTEMATIC REVIEW OF EDUCATIONAL EVIDENCE (2020-2026)

João Paulo Neves Mendonça

doi:10.29121/shodhai.v3.i1.2026.92

Authors

Joao Paulo Santos Neves Mendonça SEDUC-MT, Primavera Do Leste, Mato Grosso, Brazil

DOI:

https://doi.org/10.29121/shodhai.v3.i1.2026.92

Keywords:

Generative Artificial Intelligence, Bloom's Taxonomy, Higher-Order Thinking Skills, Educational Technology, Personalized Learning, Artificial Intelligence In Education

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) has transformed educational practices by providing innovative tools capable of supporting teaching, learning, assessment, and knowledge construction. Among the various educational frameworks, Bloom's Taxonomy remains one of the most widely adopted models for classifying cognitive processes, ranging from lower-order thinking skills, such as remembering and understanding, to higher-order skills, including analyzing, evaluating, and creating. This study investigates the potential contributions of Generative Artificial Intelligence to the development of cognitive skills across Bloom's Taxonomy levels in educational environments. A systematic literature review was conducted to identify, analyze, and synthesize recent research on the application of Generative AI technologies, particularly large language models, in educational contexts. Studies published between 2020 and 2026 were examined using predefined inclusion and exclusion criteria. The findings indicate that Generative AI can effectively support learning activities across all cognitive levels, with particularly strong evidence reported for Understanding, Analyzing, Evaluating, and Creating activities., with particularly strong contributions to higher-order thinking skills. AI-driven systems facilitate personalized feedback, adaptive learning pathways, content generation, problem-solving assistance, and creative task development. However, concerns remain regarding overreliance on AI tools, academic integrity, critical thinking reduction, and ethical implications. The results suggest that Generative Artificial Intelligence has significant potential to enhance educational outcomes when integrated through pedagogically sound approaches aligned with Bloom's Taxonomy. The study contributes to the growing body of knowledge on AI-enhanced learning and provides recommendations for educators, researchers, and policymakers seeking to maximize the educational benefits of emerging AI technologies.

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