Missing components in e-learning designs: a learning-to-change thesis and a proposal for design-based research
Tsang-Hsiung Lee, Yun-Hsia Liang
Abstract
Tsang-Hsiung Lee, Yun-Hsia Liang
Abstract
Abstract:- Contemporary learning theories inform online teachers to (re)design the course to be more authentic, flexible, and most importantly, learner-centered. However, to have a real impact on the reality, still not much literature address how, and more importantly, why? A phenomenon we observed that unexpected emergence of systemic changes, or even transformation, seemed quite common at the level of a course and in the context of professional learning. Among these changes, learning to change in BOTH teaching and learning to achieve high quality learning (we called it a learning-to-change thesis) is possibly one of the most critical, which lack of research in the present literature. This study explored some possibilities of conducting design-based research for this thesis in the future studies. Key-Words:- Learning to Change, Design-Based Research, E-learning Designs, Blended Learning 1
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Abstract:- Contemporary learning theories inform online teachers to (re)design the course to be more authentic, flexible, and most importantly, learner-centered. However, to have a real impact on the reality, still not much literature address how, and more importantly, why? A phenomenon we observed that unexpected emergence of systemic changes, or even transformation, seemed quite common at the level of a course and in the context of professional learning. Among these changes, learning to change in BOTH teaching and learning to achieve high quality learning (we called it a learning-to-change thesis) is possibly one of the most critical, which lack of research in the present literature. This study explored some possibilities of conducting design-based research for this thesis in the future studies. Key-Words:- Learning to Change, Design-Based Research, E-learning Designs, Blended Learning 1
Key concepts: Learning sciences, Experiential learning, Phenomenon, Context (archaeology), Active learning (machine learning), Synchronous learning, Learning design, Quality (philosophy)