Implementing the Revised Bloom’s Taxonomy (2001) in AI-Digital and Online Learning Environments: A Strategic Approach

Abstract

Integrating digital technology in 21st-century education requires a strategic, transformative pedagogical approach to enhance learning outcomes and skill development. As educators, researchers, and policymakers, our role shapes this future. The Revised Bloom’s Taxonomy (2001) offers an essential framework for structuring educational objectives in AI-driven and online learning environments, where cultivating higher-order thinking is paramount. This study explores the strategic application for designing and assessing learning objectives within digital pedagogy, categorizing activities that bolster analytical, creative, and evaluative skills. This taxonomy is a foundational tool for structuring digital learning experiences that meet contemporary educational needs.

The research provides a theoretical analysis of how the taxonomy’s hierarchical approach aids in crafting objectives aligned with advanced digital tools and interactive platforms, enhancing engagement and competency. It also examines alternative revisions to the taxonomy, focusing on the 2001 model, which emphasizes active, dynamic learning. This alignment enables clear and adaptable learning goals that promote effective digital learning and assessment practices, guiding students toward key educational objectives in a technology-enhanced environment despite challenges related to technology access and varied educational contexts.