Science of Learning in Theory

Science of learning in theory explores the definition of the ‘science of learning’ and the evidence for it.

This group of resources provides an introduction to the ‘science of learning’ and the evidence for it. For us, the science of learning connects the insights from cognitive science and educational psychology about how students learn with implications for teaching practice. In short, knowledge of human cognition is a precondition of learning and must inform teaching.

If you’re brand new to the science of learning, watch this introductory video here:

To dig deeper, here are some key concepts related to human cognition that help explain the science of learning:

Biologically primary knowledge includes things like basic social relations and problem-solving skills we have evolved to learn, and do not need to be taught. In contrast, biologically secondary knowledge includes foundational skills — like reading, writing, maths as well as coding, Cubism and how to kick a football — we can only learn through instruction. The primary purpose of schools is to equip students with the biologically secondary knowledge they need to make the most of their world. 

It’s often believed that by teaching broad skills like inquiry or critical thinking, they can become ‘multipurpose muscles’ — transferable across domains and contexts. While there are some problem-solving skills that can be applied across context, these are biologically primary and do not need to be taught. In our schools, learners can only develop critical thinking and inquiry skills through strong knowledge of individual domains. 

Working memory our active mental workspace, but it’s severely limited and can only handle small amounts of new information. New knowledge needs to make it through the working memory bottleneck to enter our long-term memory, and a strong long-term memory can also help strengthen working memory.  

Managing students’ cognitive load is necessary in order to make learning happen. Research on cognitive load has yielded many insights about designing instruction, such as the importance of providing worked examples and scaffolding tasks for novice learners and fading guidance as students become more adept with what they are learning. 

 What does this mean for teaching? The set of pedagogical practices best supported by cognitive science is explicit instruction. Explicit instruction is often misunderstood as ‘chalk and talk’ or lecturing. Instead, it is highly interactive and student-focused, as in this description from Anita Archer and Charles A. Hughes: 

Effective and explicit instruction can be viewed as providing a series of instructional supports or scaffolds—first through the logical selection and sequencing of content, and then by breaking down that content into manageable instructional units based on students’ cognitive capabilities (e.g., working memory capacity, attention, and prior knowledge). Instructional delivery is characterized by clear descriptions and demonstrations of a skill, followed by supported practice and timely feedback. Initial practice is carried out with high levels of teacher involvement; however, once student success is evident, the teacher’s support is systematically withdrawn, and the students move toward independent performance. 

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