The New Science of Learning

EDU800 Annotation Week 1

Sawyer, R. K. (2006). Chapter 1 introduction: The new science of learning. In R. K. Sawyer (Ed.). The Cambridge Handbook of the Learning Sciences(p. 1-16). New York: Cambridge University Press.

Chapter One from Sawyer’s book provides insight into how the established educational theories are now being questioned and some are considered flawed, and how learning science is emerging to help develop new models for teaching and learning in educational institutions. The newer theories emphasize the students learning to think, and the practice of externalizing and articulating their knowledge leads to more effective learning. The active, creative and deep learning findings from cognitive scientists, demonstrate that reflection (metacognition), scaffolding, problem solving and thinking to be more effective than the instructionist theory.

Sawyer provides a path and guide to implement Learning Science through Educational Technology. In addition, he provides compelling alternatives to instructionist approaches. The new learning science approach opens up a new way for educational scientists to experiment and test new learning theories, and for researchers to view and advance the science of teaching and learning.  This article raises the game for us to learn, scientifically, how to better teach.  With technology increasingly involved in education, the abstract aspects of active learning, reflection, articulation and learning can be implemented in a concrete way with software applications, Educational AI, providing a clearer path to deep learning than without technology.

For those in pursuit of an Doctorate in Educational Technology Doctorate (DET), this article breaks the ice, provides the first step on a journey to exploring the science of teaching and learning.  It establishes the framework to study Educational Technology techniques, approaches, models, and theories.  It also provides the foundation to build upon for research into developing and implementing technological solutions, leveraging emerging software and networked applications, to the problems faced in teaching in higher education, regardless of subject matter.  By breaking from the flawed approaches to teaching and learning of the past, and treating learning as a science, the future of learning in an increasingly technological society, can be advanced.


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