Chen, Jeff2026-03-232026-03-232026-05-052025*A2025http://hdl.handle.net/2263/109195Mini Dissertation (MBA)--University of Pretoria, 2025.This qualitative study explored how LLMs affect Knowles's Andragogy and Bloom's Taxonomy within a corporate or institutional knowledge transfer context. The study specifically focused on the adult learner. An exploratory and inductive methodology was employed through the process of semi-structured interviews. Participants were senior professionals who were acknowledged AI leaders in their organization and regularly required to impart knowledge. The literature review and thematic analysis revealed that LLMs act as enablers of andragogical principles, but this effect is conditional upon the learner's intent to learn compared to task completion. It was also found that LLMs transform Bloom's linear hierarchy into an iterative feedback loop. This feedback loop necessitated the development of a new questioning layer. The questioning layer was found to be dependent on the learners’ ability to critically evaluate, validate and self-reflect LLM output. The study’s main contribution lies in providing a conceptual link between Knowles’ Andragogy and Bloom’s Taxonomy. Informed by the proposed intent condition for Knowles’ Andragogy and the questioning layer for Bloom’s Taxonomy in LLM-augmented environments.en© 2025 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.UCTDLarge Language Models (LLMs)Adult LearningKnowle's AndragogyBloom's taxonomyLearner intentMini Dissertationu24072533N/A