Learning Mechanism Taxonomy (LMT): A Complement to Bloom's Taxonomy for Elevating STEM Learning from Memorization to Higher Cognitive Processes in the AI Era (Full Discussion Preprint Manuscript with Diagrams)

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Authors: Wang, Ming-Jer
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Abstract

This version provides the full discussion preprint manuscript with conceptual diagrams and structural visualizations corresponding to the previously released abstract and full manuscript versions. It presents the complete conceptual framework of the Learning Mechanism Taxonomy (LMT), a mechanism-oriented framework for understanding learning, conceptual organization, and transferable thinking. The added diagrams are intended to improve accessibility, clarify structural relationships, and support interdisciplinary scholarly discussion. This manuscript is shared for scholarly discussion and feedback prior to formal journal submission and in preparation for broader discussion concerning STEM learning and higher cognitive processes in the AI era. Version 3 (v3) extends earlier public versions through the addition of conceptual diagrams and structural visualizations. Keywords:Learning Mechanism Taxonomy, LMT, Bloom’s Taxonomy, knowledge networks, STEM education, cognitive mechanisms, conceptual understanding, long-term retention, higher-order thinking, AI in education, transferable thinking, learning transfer

Fields of Study & Subjects

Educational Assessment and Pedagogy Science Education and Pedagogy Neuroscience Education and Cognitive Function

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 June 2026
Language
EN
Document type
Preprint