PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 4, 20260 citationsOpen Access

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)

View Full Paper
MWMing-Jer Wang

Key Points

  • This work aims to enhance understanding of learning mechanisms to improve STEM education outcomes.
  • Introduced Learning Mechanism Taxonomy as a conceptual framework for learning and thinking.
  • Provided conceptual diagrams and structural visualizations to illustrate key concepts.
  • Shared for scholarly discussion prior to formal journal submission.
  • Demonstrated the potential of LMT to facilitate higher-order thinking in STEM education.
  • Clarified relationships between cognitive mechanisms and knowledge networks.
  • Highlighted the importance of transferable thinking for long-term retention.

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

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ming-Jer Wang (2026) studied this question.

synapsesocial.com/papers/6a2116acd499ed480b16f90ahttps://doi.org/10.5281/zenodo.20500972
Ask AI
Helpful
Bookmark
Share
View Full Paper