How Learning Happens

Seminal Works in Educational Psychology and What They Mean in Practice

Paul A. Kirschner, Carl Hendrick

• Editorial: Routledge
• Año: 2020
• ISBN:
  9780429589959
• Edición: 1
• Categoría: Education
• Categoría: Education General

How Learning Happens introduces 28 giants of educational research and their findings on how we learn and what we need to learn effectively, efficiently, and enjoyably. Many of these works have inspired researchers and teachers all around the world and have left a mark on how we teach today.

Exploring 28 key works on learning and teaching, chosen from the fields of educational psychology and cognitive psychology, the book offers a roadmap of the most important discoveries in how learning happens. Each chapter examines a different work and explains its significance before describing the research, its implications for practice, how it can be used in the classroom and the key takeaways for teachers. Clearly divided into six sections, the book covers:

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• How the brain works and what this means for learning and teaching

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• Prerequisites for learning

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• How learning can be supported

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• Teacher activities

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• Learning in context

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• Cautionary tales and the ten deadly sins of education.

Written by two leading experts and illustrated by Oliver Caviglioli, this is essential reading for teachers wanting to fully engage with and understand educational research as well as undergraduate students in the fields of education, educational psychology and the learning sciences.

PART 1

How does our brain work?

Riddle

What is a small part of a whole, weighs less than 2% of that whole, uses between 20% and 25% of the available energy, consists of around 190 billion parts, and is mechanical, electrical, chemical, and biological?¹

What a miracle, our brains! We humans have wonderful bodies. Because of this lump of soft tissue in our heads, weighing – on average – a little more than a kilo, we are able to receive, process and respond to countless signals from our environment through our eyes, ears, skin, noses, and mouths. Almost effortlessly, we ignore a multitude of unimportant signals and respond specifically to the relevant ones. To top it all off, we can also store an infinite amount of information from those signals for later use.

But how do we make proper use of this miracle when it comes to learning and instruction? John Sweller (2017) stated: “[W]ithout an understanding of human cognitive architecture, instruction is blind”. ² In this respect, it could be the case that many of us in the teaching profession are flying blind.

In this part we discuss how our brains work and what that means for learning and teaching. We explain why students learn some things almost effortlessly without instruction, while other things are learnt with great difficulty through instruction, how our memory works and how we can make it work better, how we (learn to) solve problems, how and why images and words together can help us learn better, and why children should not be taught as if they were small adults.

1 Answer: The brain!

2 Sweller, J. (2017). Without an Understanding of Human Cognitive Architecture, Instruction is blind. The ACE conference. Retrieved from https://youtu.be/gOLPfi9Ls-w.

1 A novice is not a little expert

Novices and Experts

Paper

“Categorization and representation of physics problems by experts and novices”³

3 Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1979). Categorization and representation of physics problems by experts and novices. Cognitive Science 5, 121–152 Available from: https://onlinelibrary.wiley.com/doi/epdf/10.1207/s15516709cog0502_2.

QUOTE

“Not only do experts have more knowledge and can work faster than beginners, they also look at or tackle problems differently (i.e. what you know determines what you see)”.

Why you should read this article

Homunculus

A miniature human

In 1537, a Swiss physician, alchemist, and astrologer named Paracelsus outlined a method for creating homunculi (Latin for little people). Short but sweet, a mini-human is created by nourishing a male sperm on human blood in a horse’s womb where a small version of a living human child grows. This evolved into what became known as preformationism, the theory that animals develop from miniature versions of themselves. Sperm were thought to be complete preformed individuals called animalcules, which developed in the woman’s womb into fully formed beings. In 1694, Nicolaas Hartsoecker, in his Essai de Dioptrique about what could be seen with the aid of Antoni van Leeuwenhoek’s microscope, wrote of and produced an image of a tiny human form curled up inside the sperm (see Figure 1.1), which he called le petit animal (animalcule) with the human version being le petit l’infant (homunculus). The sperm was a homunculus, identical in all but size to an adult. It is just a matter of growth!

Figure 1.1 Preformation, drawn by Nicolas Hartsoecker

As odd as this may sound today, many people actually think that this same thing is true about the cognitive/intellectual development of a child (and by extension, a novice) into an adult (and by extension, an expert). A good example of this is discovery learning. The thinking behind this form of education is that since the epistemology of the scientist (i.e. an expert) is to discover and create new knowledge through experimentation, many mistaken educators and researchers have chosen to apply this approach to the school as a pedagogy for teaching students (i.e. novices) (Kirschner, 2009). Michelene Chi, Robert Glaser, and Paul Feltovich broke with this myth showing how experts not only know more than novices, but that they also think differently.

Abstract of the article

This study investigates the differences between how physics problems are represented in novices and experts in relation to the organisation of physics knowledge. Different experiments included; problem categories as a means of representation, category differences used by experts and novices, differences in category knowledge, and aspects of the problems that form problem categorisation and how they’re represented. The results from these experiments suggest that experts and novices represent problems differently with particular categorisation of the problems and also that the success in completing the problems depends on domain-specific knowledge. Experts use deep physics principles to categorise and solve problems whereas novices use superficial features.

The article

In their search for differences between experts and beginners in solving problems, Chi and her colleagues focused on the very first step when solving a problem, namely reading and interpreting the problem. When dealing with a new problem, the first question is always: what kind of problem is this? To answer this question, you often try to remember similar problems that you have encountered before. You search for landmarks. Classifying the problem in a specific category of similar problems is the first step in solving it. The idea is that experts already interpret or categorise problems when reading in a way that’s different from beginners, and therefore they’re able to solve them more easily, more quickly, and better.

Landmarks help classify a problem

How people categorise a problem depends on previous experiences with similar problems, which shapes how they determine what the problem is and the quality of their solutions. We know this since 1946 when A. D. de Groot published his PhD thesis (which was later translated into English in 1965) on how chess masters interpret chess problems. He found that the chess masters’ knowledge and the way of thinking is essentially different from that of beginners. Not only do experts have more knowledge and can work faster than beginners, they also look at or tackle problems differently (i.e. what you know determines what you see). Masters quickly recognise a particular chess position and then determine subsequent moves based on their prior experiences. In the same way, doctors interpret the history (anamnesis) and charts of a new patient by using their knowledge of similar clinical histories and charts that they have dealt with and then make their diagnoses based on this. Thus, our prior knowledge determines the quality of our problem-solving. As experts have both more knowledge as well as qualitatively better knowledge (this is called deep, conceptual knowledge), the categorisation of problems will give them a head start on beginners.

Conceptual knowledge

Deep understanding of concepts and principles

Prior knowledge about problems and their solutions are built through experience with many different types of problems. In this way, experts have acquired rich knowledge about different types of problems and their solutions which they store in their long-term memory; that is they have rich knowledge schemata.

THE TERM SCHEMA was first used in psychology by Jean Piaget (1896–1980), a Swiss psychologist who studied cognitive psychological development in children. In his words (1952), a cognitive schema is “a cohesive, repeatable action sequence possessing component actions that are tightly interconnected and governed by a core meaning”. See it as a way of org...