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- Herausgeber: John Wiley & Sons
- Kategorie: Bildung
- Sprache: Englisch
Go beyond personal experience and discover scientific principles that will elevate your teaching
The international bestseller How Do We Learn? decodes years of cognitive science research into actionable strategies for K-12 teachers, curricula designers, and administrators. You'll discover how classic and emerging findings can transform pedagogy by pointing at practices that take advantage of the innate structures of the human brain. Written in an easy-to-understand style, this book delves into the cognitive mechanisms that govern learning and memory. You'll also discover the socioemotional factors that influence students' motivation and performance.
Researchers have investigated key teaching methods such as feedback and evaluation to identify how school environments influence self-motivation to learn. In this book, Héctor Ruiz Martín unites scientific principles with personal engagement, helping teachers ensure that students can thrive in the classroom and beyond.
- Learn how students learn so you can help them achieve academic success
- Get practical tips and strategies for aligning your teaching with scientific evidence
- Gain fascinating insights into the human mind and discover how to promote student achievement through socioemotional engagement
- Help students feel motivated and achieve at their best
How Do We Learn? offers rigorous scientific insights—explained in accessible terms and translated into actionable steps that K-12 teachers in all disciplines can put into practice right away.
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Veröffentlichungsjahr: 2024
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Table of Contents
COVER
TABLE OF CONTENTS
TITLE PAGE
COPYRIGHT
DEDICATION
FOREWORD
Note
INTRODUCTION
SECTION 1: THE SCIENCE OF HOW WE LEARN
1.1 The Scientific Study of Learning and Teaching
Personal Experience and Cognitive Biases
Confirmation Bias and Cognitive Dissonance
The Scientific Method as a Remedy for Cognitive Biases
Levels of Research on Learning and Teaching
Experiments in the Classroom
A Phenomenon Dependent on Many Variables
Correlation Does Not Imply Causation
Evidence-Informed Teaching
Pseudoscientific Myths
SECTION 2: THE COGNITIVE PROCESSES OF LEARNING
2.1 Components of Memory
Multiple Memories
Short-Term Memory and Long-Term Memory
Long-Term Memory Systems
Explicit Memory
Implicit Memory
Procedural Memory
Classical Conditioning and Emotional Conditioning
2.2 Organization of Memory
Analogies of Human Memory
A Memory Model
Prior Knowledge
Making Connections
Levels of Processing Theory
Active Learning
Activating Prior Knowledge
Assessment of Prior Knowledge
Learning with Understanding
Design of Activities
2.3 Memory Processes
A Virtually Infinite Warehouse
Retrieving What Has Been Learned
Retrieval Practice
Desirable Difficulties
What Happens When We Retrieve a Memory or Knowledge?
Retrieval Does Not Only Improve Factual Learning
Methods for Practicing Retrieval
Spaced Retrieval
Interleaved Retrieval Practice
Repetition
Forgetting: Loss of Information or Inability to Retrieve it?
Memory Is Not Like a Muscle
2.4 Reorganizationof Memory
The Persistence of Ideas
Learning Facts and Learning Concepts
Learning New Concepts
Types of Conceptual Change
Conceptual Change and Lectures
Promoting Conceptual Change in the Classroom
Guiding Students Toward Conceptual Change
Self-Explanations
2.5 Transfer of Learning
Learning and Transferring
The Doctrine of Formal Discipline
Factors Facilitating Transfer
Learning with Understanding
Learning Is Transferring
2.6 Working Memory
Beyond Short-Term Memory
Limitations of Working Memory
The Components of Working Memory
Cognitive Load Theory
Working Memory Capacity as a Learner Attribute
Working Memory and Learning in School
Measuring Working Memory
Working Memory and Learning Difficulties
Managing Cognitive Load in the Classroom
2.7 Deep Learning
Talent or Practice?
What Sets Experts Apart from Novices?
Perception
Reasoning
Problem-Solving
Critical Thinking
Creativity
How Is Expertise Achieved?
Practice Makes Perfect
Decomposing and Integrating
Practice in the School Context
SECTION 3: SOCIAL AND EMOTIONAL FACTORS IN LEARNING
3.1 The Role of Emotions in Learning
Learning and Emotions
What Do We Mean When We Talk About Emotions in Education?
What Are Emotions?
How Does Emotion Modulate Learning and Memory?
The Effect of Surprise and Curiosity on Memory
Emotions for Learning
Emotions and Performance
3.2 Motivation
An Overlooked Factor
What Is Motivation?
Goals
Factors Determining Motivation
Motivation and Academic Performance
How Can Students’ Motivation Be Increased?
The Foundations of Values and Expectations
3.3 Beliefs
Subjective Knowledge
Beliefs and Expectations
Attributions
Attributional Training
Feedback and Attributions
Beliefs About Ability
Mindsets
Mindsets and Academic Results
Can We Promote a Growth Mindset?
How to Promote a Growth Mindset
Labels
Mindsets and Stereotypes
There Are No Positive Labels in School
Criticisms of the Impact of Beliefs on Learning
Note
3.4 The Social Dimension of Learning
Made to Learn from Each Other
Emotions in Social Learning
The Pygmalion Effect
Learning Through Social Interaction
Cooperative Learning
Learning to Cooperate
Diverse Classrooms?
SECTION 4: SELF-REGULATION OF LEARNING
4.1 Metacognition
Learning to Learn
Metacognitive Skills for Self-Regulated Learning
Autonomous Learners
4.2 Self-Control
Self-Control for Learning
Self-Control and Academic Achievement
Factors Modulating Self-Control Capacity
Promoting Self-Control in School
The Limits of Inhibitory Control
Development of Inhibitory Control
4.3 Emotional Self-Regulation
Untimely Emotions
Self-Regulating Emotions for Learning (and Performance)
Performance-Related Emotions
Promoting Emotional Regulation
Strategies for Emotional Self-Regulation
Learning Environments That Support Emotional Regulation
Executive Functions and Emotional Regulation
4.4 Resilience and Grit
The Ability to Persevere
Successful Cases
Grit, Motivation, and Metacognition
Grit and Beliefs
Cultivating Grit
Criticism of Grit
SECTION 5: KEY TEACHING PROCESSES
5.1 Instruction
Effective Lessons
Rosenshine's Principles
Direct Instruction
Sequencing and Dosing
Modeling
Review
Asking Questions
Structuring and Guiding Practice
5.2 Feedback
A Relevant Factor with Mixed Effects
The Nature of Feedback
Types of Feedback
Effectiveness of Various Forms of Feedback
Feedback and Motivation
Positive and Negative Feedback
Grades and Feedback
5.3 Assessment
A Key Process in Teaching and Learning
Assessment Parameters
What Do Assessment Tests Really Measure?
Assessing Transfer
Assessment as a Learning Tool
Formative Assessment Variables
Evidence on the Effectiveness of Formative Assessment
The Contribution of Assessment to the Consolidation of Learning
APPENDIX: PSEUDOSCIENTIFIC MYTHS ABOUT LEARNING
Educational Neuromyths
Learning Styles
Critical Periods and Enriched Environments
Brain Potential
Cerebral Laterality and Dominant Hemispheres
REFERENCES
END USER LICENSE AGREEMENT
List of Tables
Chapter 1
Table 1 Probability that a coin will always come up heads when tossing it se...
Chapter 6
Table 1 Cognitive processes that can be performed with acquired knowledge, b...
Chapter 12
Table 1 Behaviors that students tend to adopt based on subjective value, exp...
Chapter 18
Table 1 Examples of feedback that appeal to the qualities of the student, ac...
Appendix
Table 1 Prevalence of some neuromyths in a sample of 137 teachers from the U...
List of Illustrations
Chapter 1
FIGURE 1
FIGURE 2
FIGURE 3
FIGURE 4 Examples of images obtained using functional magnetic resonance ima...
FIGURE 5 Graph showing the curious correlation between the divorce rate in M...
Chapter 2
FIGURE 1 Extent of Henry Molaison's surgery compared to a complete, healthy ...
FIGURE 2 Mirror tracing task.
FIGURE 3 Types of long-term memory.
Chapter 4
FIGURE 1 The three key processes of memory.
FIGURE 2 Results of a test consisting of inferential questions conducted one...
FIGURE 3 Results of an experiment in which three groups of students studied ...
FIGURE 4 Proportion of questions answered correctly in the tests before each...
FIGURE 5 Points obtained in a comprehension test at the end of a statistics ...
FIGURE 6 Number of elements recalled after a massed or spaced study session,...
FIGURE 7 Results from the exercises completed during the learning sessions a...
Chapter 5
FIGURE 1 Frame from the documentary
A Private Universe
(Schneps & Sadler, 19...
FIGURE 2 Some Earth models that the students drew for the Vosniadou and Brew...
FIGURE 3 Functional magnetic resonance images showing brain regions activate...
Chapter 6
FIGURE 1
FIGURE 2
FIGURE 3
FIGURE 4
Chapter 7
FIGURE 1 Changes in the working memory capacity of an average child are show...
Chapter 8
FIGURE 1
FIGURE 2 Rubik's Cube showing one of its more than 43 trillion possible conf...
FIGURE 3 Number of masterworks created by composers based on the number of y...
Chapter 9
FIGURE 1 Types of emotions according to the two-dimensional gradational mode...
FIGURE 2 On the left, the number of details consistent and inconsistent with...
FIGURE 3 Number of details correctly remembered in each phase of the story (...
FIGURE 4 Percentage of words recalled after the preliminary test, based on w...
FIGURE 5 Yerkes-Dodson Law for cognitively demanding tasks.
Chapter 10
FIGURE 1 Types of goals.
FIGURE 2 Types of subjective value in relation to learning goals.
FIGURE 3 Self-efficacy measures and results in a mathematics test for three ...
Chapter 11
FIGURE 1 Relationship between beliefs, values, expectations, and motivation....
FIGURE 2 Results in reading comprehension tests before and after receiving a...
FIGURE 3 Student enjoyment and performance in a highly difficult task after ...
FIGURE 4 Mathematics grades of 373 high school students distributed accordin...
FIGURE 5 Results of an intervention to promote a growth mindset on math grad...
FIGURE 6 Percentage of courses completed satisfactorily before and after an ...
Appendix
FIGURE 1 Rats’ rearing environments in Rosenzweig's experiments (1972).
Guide
Cover
Title Page
Copyright
Dedication
Foreword
Introduction
Table of Contents
Begin Reading
Appendix: Pseudoscientific Myths About Learning
References
End User License Agreement
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HOW DO WE LEARN?
A SCIENTIFIC APPROACH TO LEARNING AND TEACHING
(EVIDENCE-BASED EDUCATION)
Héctor Ruiz Martín
Copyright © 2024 Héctor Ruiz Martín. All rights reserved.
Original Spanish edition Copyright © 2021 Editorial Graó de IRIF, S.L, Barcelona
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
ISBNs: 9781394230518 (Paperback), 9781394230525 (ePDF), 9781394230532 (ePub)
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permission.
Trademarks: Wiley and the Wiley logo are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates in the United States and other countries and may not be used without written permission. All other trademarks are the property of their respective owners. John Wiley & Sons, Inc. is not associated with any product or vendor mentioned in this book.
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Library of Congress Control Number is Available
Cover Design: WileyCover Image: © malerapaso/Getty Images
English translation: Oriol Solé MulaIllustrators: Sandra Villa Valenzuela and Isabel Soler ChorroPhotographs: 123rf.com and Wikimedia Commons
To those who dedicate their lives to education
FOREWORD
I first read (or perhaps, more precisely, started reading) How Do We Learn? after hearing Héctor Ruiz Martín speak at a researchED conference in Santiago, Chile, in November 2022.
Having now read the book fully, twice, I am convinced that it will prove to be one of the most important books in education for the foreseeable future, destined to enter the pantheon of must-read books on the science of learning. If you work in education, you simply cannot afford not to read this book. It is indispensable, full stop.
But let me return to my introduction to Héctor and his work. It might not seem especially remarkable to point out that hearing him speak in Santiago caused me to instantaneously buy and read his book, save for the fact that, at the time, it was available only in Spanish (under the title ¿Como Aprendemos?) and my Spanish was rudimentary at best.
Reading ¿Como Aprendemos? the first time entailed six months of hard cognitive labor for me. I struggled phrase by phrase and sometimes word by word. But I persisted. Even through the haze of my partial understanding, the book offered up one insight after another.
Still, I ask myself now, what about Héctor's presentation might have driven me to go to such lengths to read his book in Spanish? After all, I had listened to informed presentations on cognitive psychology before; in fact, I knew a lot of the science Héctor was discussing to some degree or another. I had read dozens of other books on the topic and there were ones in my native language that I could have read in a fraction of the time.
Ironically, some of the things that were so effective about his presentation, and that might also be said about this book, might at first sound insufficiently dramatic to warrant a six-month personal translation odyssey.1 It was carefully explicated. It was thorough and logically and progressively organized. And its style was calm and patient.
Let me begin with this last point, which was remarkable because Héctor, there on the stage, as he often is in this book, was engaged at least in part in quietly dismantling a series of common misconceptions and distortions about how people learn—edu-myths, as you might call them—and this sort of work is often done elsewhere in a style that tends toward judgment and rancor, as if it was a deliberate choice of people who held incorrect ideas about learning to do so.
But Héctor proceeded in Santiago, as he does here, with patience and without judgment, steadily helping his audience to reconceptualize first one key idea and then another. Gradualism, I am reminded, has been a more productive force in the history of ideas than revolution, and that's how Héctor's work plays out. You don't realize at first that he is preparing to shift your worldview. You merely follow as he goes steadily from point to point until the ideas start to coalesce and suddenly you realize that you understand something very well and quite differently than you did previously.
The ideas are not just clear, they are connected, and through those connections a model emerges. It is powerful because it is cohesive. Suddenly you understand not just bits and pieces but something bigger.
Interestingly, this exact topic, conceptual change, or how to change the minds of learners who already believe something else—possibly something erroneous—is a topic Héctor writes about explicitly in this book, and he notes that it requires time and patience.
But also more than patience. Something like trust must also be built up. As Jonathan Haidt points out in The Righteous Mind: Why Good People Are Divided by Politics and Religion, we are most likely to change our opinions not when confronted by someone who disparages us but in discussion with someone who understands us, whom we have come to trust and feel connected to. The motive in a book like this has to be truth and not ideology, and you feel that right from the outset. “I am a scientist first,” Héctor told me in Santiago, and his is a book for people who are motivated to seek the best, clearest, and comprehensive summary of our aggregated knowledge about human cognition. It's a book for people who want to know what the evidence tells us, whether it's what they expected or not.
The phrase “well-organized” might also seem at first unprepossessing as a term of praise, but like patience, it too is profoundly important. We can only aspire to guide people to understand differently by “building the concepts” one by one, Héctor writes. We have to make sure people understand all the research, but then also connect the pieces together.
In seeking to understand how people learn we are not seeking to understand a handful of useful ideas, but to grasp a body of knowledge, and that means understanding how it fits together. To facilitate that, sequence is highly relevant. The order, the thoroughness, the organization of the knowledge is really, really important. Durable and useful learning, as I learned from reading this book, is built on the connections between the ideas we understand. An organized methodical presentation of connected ideas from an interlocutor whose motives you trust leads to a systematic understanding of the big picture. That perhaps is what this book gives its readers more than any other—the comprehensiveness of it, the thoroughness, the linkages among ideas.
But the gradual, progressive, impeccably organized flow of ideas in the book is important in another way too. “Properly sequencing learning goals and adjusting task difficulty not only has positive consequences for the effectiveness of our memory … but also indirectly affects our motivation. Cognition and motivation are interconnected,” Héctor explains in this book. When you feel things coming together, you grasp that you are building a substantive and useful understanding. Success at learning is one of the greatest sources of motivation to a learner. That you feel yourself understanding deeply and connecting the dots causes you to persist. This is yet another powerful lesson for our classrooms that Héctor will explain in this book. Take it from a guy who read his book in a language he didn't speak.
Earlier I used another potentially unprepossessing term not generally heard in the arts of marketing and persuasion to praise Héctor's work: carefully explicated.
You can count on Héctor to know the science from just about every angle, but one of the best parts of his presentation in Santiago—and which is also true of this book—was the way he not just explained the principles of cognitive psychology but brought them to life. He didn't just tell us why the brain worked the way it did and leave it at useful abstraction; he demonstrated it there in the hall with 400 participants or so, causing us, for example, to remember more from a list of words whose meaning we thought deliberately about and connected to our prior knowledge than from a list we thought deliberately about but didn't try to link to prior knowledge. He ran a live experiment on us to prove the point, in other words. And it worked!
Active learning, he showed us, entailed the brain actively making connections between knowledge that was already encoded in long-term memory and the object of present inquiry.
As he explains it in this book, in one of the most profoundly insightful passages:
The simple yet powerful idea that emphasizes the importance of students actively seeking meaning in what they are learning, trying to relate it to their prior knowledge, reflecting on its implications for what they already know, and ultimately, thinking about it forms the basis of what is known as active learning.
Active learning is often confused with educational practices in which the student “does things”—or what is known as learning by doing. But active learning could be better defined as learning by thinking. It encompasses any learning experience in which the student actively thinks about the learning object, seeking meaning and comparing it with their prior knowledge.
His ability to help his listeners conceptualize ideas through images is another theme you will notice. A photo of Héctor on stage in Santiago shows him making this idea profoundly accessible by presenting it visually.
Memory and learning, he is telling us here, come from the connections created between new information and existing knowledge (or between ideas already present in our memory that had never been connected before). It's the connections—the lines between and among the dots—that represent the building of durable meaningful knowledge.
As his ability to demonstrate—with an ad hoc experiment, with an image to crystallize an abstract idea—shows, he is able to combine vast knowledge with a pragmatic bent, and this is a rare thing. The “curse of knowledge” or the “expert's blind spot” is yet another idea that you will encounter in this book. It is the idea that the more you know about something, the harder it is to explain what you know to a novice or even understand why and how it became clear to you.
So while he is a research scientist of encyclopedic knowledge, he also “speaks teacher” and can translate his knowledge into practical suggestions of what it might look like on Monday morning with 30 14-year-olds.
All of which I suppose explains why I persisted with my ad hoc translation project and why, though I was expecting big things when I at last read the English translation, I was stunned again by its breadth, depth, and cohesion.
We live in a time of promise—when we know far more about how learning works than ever before—and by a wide margin—and when a broad awakening to the importance of that knowledge has begun to sweep the education sector, and this trend has the capacity to radically change the depth and scope of learning that happens in a thousand settings across society. This is both an incredible opportunity for teachers of all stripes but also an immense responsibility.
The knowledge is there—and so is the need. “Returns to education,” the benefits people get from learning more in school, are higher than they have ever been. By necessity then, the converse of this is also true. The costs borne by students of not learning are ever greater. There is a lot of discussion these days about educational equity. In many ways the greatest form of equity lies in whether students get access to teaching that applies the science of learning as well as it can be by teachers who understand it well enough to make decisions to adapt and adjust their lessons for maximum benefit.
And in How Do We Learn?, that body of knowledge is present, all in one place, carefully and patiently explained, organized in a logical and sequential manner with real-world examples to help bring it to life. This book is a gift—an immensely powerful one—that Héctor Ruiz Martín has provided, now, too, to readers in English. I am convinced as I have said that it will prove to be one of the most important books in this new era: a, if not the, standard work on learning science.
And so now, the rest of the task is ours: to read it and study it and to think deliberately about its implications so that we can bring them to life for the students we serve.
DOUG LEMOV
AUTHOR, TEACH LIKE A CHAMPION, ANDMANAGING DIRECTOR OF UNCOMMON SCHOOLS
Note
1
I should note here, in case you had any questions, that this book is professionally translated by first-rate experts, and my only role has been to read their work and say, “Wow, that's really good.”
INTRODUCTION
“Learning results from what the student does and thinks and only from what the student does and thinks. The teacher can advance learning only by influencing what the student does to learn.”
Herbert A. Simon (1916–2001)
Researcher in politics and cognitive science
Once, a journalist asked me if learning was an instinct. I responded, “Would you say that seeing is an instinct?” Indeed, learning, like seeing, is something our brain does continuously, whether we want it or not. Evolution has endowed us with an organ that not only allows us to interact with our surroundings but also to adapt and optimize our responses by learning from each and every experience.
Learning occurs in the learner's brain. Therefore, in the educational context, the primary protagonist of learning is the student. In fact, learning happens without the need for formal teaching. Nevertheless, regarding the type of knowledge and skills offered in school (literature, mathematics, history, science, reading, writing, etc.), teaching is the most effective way to promote learning (Geary, 2007). Teaching occurs when the teacher creates conditions and provides or facilitates experiences that trigger learning in students, always in relation to specific goals. But the teacher does not “generate” learning; their role is to provide optimal circumstances for it to unfold and encourage students to engage in actions that lead to achievement. Therefore, teaching is a facilitation of learning.
Although the brain learns from all experiences, not everything we experience is remembered in the same way. The way the brain has evolved shapes which experiences or actions are more effective in producing lasting learning. Interestingly, we are not born knowing how the brain learns; we do it spontaneously, and at most, some instincts may promote it. For example, curiosity prompts us to pay attention and explore the new, but we do not inherently know which actions optimize learning—even those inferred from personal experience may not necessarily be the most optimal (Karpicke et al., 2009). It could be compared to many other things we can do but do not know how to do optimally. For example, while we all know how to jump, it took decades of professional athletics to discover that jumping as high as possible requires a specific technique (backward flip, known as the Fosbury flop) which is neither intuitive nor obvious. Similarly, knowing how the brain learns can enable us to develop techniques or methods that optimize our capacity to learn. It can also make us much more effective as teachers.
This book starts with the premise that the processes of learning and teaching can be analyzed through the lens of the scientific method, and we can use the evidence derived from this research to guide decisions aimed at improving educational practices. Without a doubt, there is a significant artistic element in teaching, much like in medicine; and like in medicine, teaching has a scientific aspect—one that we have barely developed and transferred to classrooms. Of course, there are organizational and economic factors in educational systems that influence the success of their mission (as with healthcare). Still, this book primarily focuses on the processes of teaching and learning—that which happens inside classrooms and is, to a greater or lesser extent, in the hands of both students and teachers.
In recent decades, science has significantly advanced its understanding of learning processes, at both the neurological and the psychological levels. Additionally, educational research has gathered multiple pieces of evidence regarding the potential of the transfer of scientific knowledge about how the brain learns to teaching and learning processes in education. This line of research, in turn, has analyzed educational practices that yield better results, aiming to identify reproducible patterns.
In this sense, my goal with this book is to contribute to disseminating, especially among teachers, what research has revealed about how learning occurs and the factors that have a greater impact, in order to promote it in the academic context. My commitment has been to do so in an engaging and accessible manner, while also maintaining the necessary rigor for this task. Bearing in mind the evidence provided by research to date and its alignment with the scientific consensuses, I have stressed the need to exercise caution due to the demands of a science as inexact as this. Therefore, I would like readers to be aware that this is not a book intended to proclaim unequivocal, positivist, and exaggerated messages that distort reality—messages that gain popularity and contribute to book sales simply because they are messages we want to hear.
Because of the recent “fad” of neuroeducation, the rigorous science of learning proper is seeing a horde of opportunists disseminating messages that have nothing to do with its conclusions. Pseudoscience always spreads faster than science, likely because scientific explanations tend to be inherently more complex and nuanced. Science always demands doubt and requires multiple pieces of evidence to assert anything with a degree of certainty, while pseudoscience always asserts its claims with certainty from the outset. Nevertheless, this book aims to contribute to the realm of scientific dissemination with the double rigor demanded by such a crucial topic as education. Naturally, no one is entirely free from bias. So it may well be that, throughout this book, my objectivity may not have been as absolute as intended. Therefore, I apologize if, in any case, I have inadvertently been too extreme with any assertion. In any case, I have tried to adhere to the evidence and faithfully reflect the ideas of other researchers. I have also included references to scientific articles supporting each assertion; a text aiming to provide an evidence-based approach to teaching and learning would not be consistent if it did not provide such evidence. Readers will notice that many of these references are not recent; I have chosen to primarily cite foundational articles in each area, reflecting that educational research is nothing new. The novelty lies not so much in what we scientifically know about learning but in bringing that knowledge into the classrooms.
While this book may shy away from sensationalism, it still, I hope, contains inspiring ideas. There is nothing more fascinating than synthesizing the key elements that, according to science, can genuinely impact education. In this sense, although in some cases I have ventured to translate certain research conclusions into specific actions that students and teachers can take to optimize learning—actions supported by empirical evidence—this is not a recipe book. In fact, it cannot be. If anything, educational research has taught us that there is no foolproof recipe. No educational method is universally effective for all students, purposes, or contexts. For example, is project-based learning effective? Is it beneficial to conduct exams? The answer, obviously, is that it depends. Didactic methods depend on too many variables for it to be reasonable to lump them all together just because they share some of them. Take online teaching, for example. In online teaching, students learn remotely using computer programs. However, this is not what determines whether or not this method is effective. Some online programs are remarkably effective, while others leave much to be desired. If we equate two online courses merely because they are online, we may be comparing apples and oranges from an educational perspective.
Therefore, this book focuses on the fundamentals, exploring the specific variables that make methods effective based on our understanding of how people learn. What factors contribute to team activity promoting meaningful learning? In what circumstances can exams be beneficial? What makes an online course effective? My main objective is to bring scientific models that explain the phenomenon of learning closer to teachers, empowering them to base their decisions on these models. This should always be in alignment with their own criteria, which must consider their students and their context. The transfer between theory and practice in a field like ours is typically neither straightforward nor direct. Fortunately, there are scientific disciplines that study learning phenomena relatively close to the real context, even within the classroom itself.
That said, it is important to clarify that this is not a book about neuroscience (or neurobiology). Although undoubtedly fascinating, neuroscience, in recent years, has made great strides in understanding the biological processes that constitute the physical substrate of learning. However, neurobiology can tell us little about what to do in the classroom (Anderson & Della Sala, 2012). The gap between the knowledge generated by this science and educational practice is too large. The intricacies of the brain captivate us, and knowing how it works is no doubt a major interest of ours. But let's not fool ourselves—understanding how neurons behave or which brain regions are involved in specific tasks will not help us in deciding how to organize an educational experience to achieve learning goals.
One of the scientific disciplines that is in a better position to contribute to the analysis and improvement of learning and teaching processes is cognitive psychology. As a deeply empirical branch of psychology, it studies how the brain obtains, manipulates, stores, and uses information initially received through the senses. Unlike neuroscience, which analyses the biological aspects of the brain, cognitive psychology draws conclusions by examining behavior and performance data. Cognitive psychology relies mainly on laboratory research, but it also draws insights from studies in everyday settings, such as the classroom. Recent advances in neurobiology have informed cognitive psychology and have helped validate models of how the mind processes information, including the mechanisms involved in learning. The truly beneficial scientific insights for educators, however, originate from psychology itself.
Within these pages, I present a cognitive perspective on the phenomenon of learning, precisely because this approach is considered by most scientists to better support the methodological decisions that teachers and students make daily. I also rely extensively on educational psychology, a multidisciplinary branch that draws on cognitive psychology, developmental psychology, and other related sciences to explore learning in its real context. Perhaps the most interesting thing about this discipline is that it conducts much of its research in the classroom, allowing hypotheses about which methods or measures will impact student performance to be tested in the most direct way possible, even if it comes at the expense of generalizability. Let's say it is the most direct bridge between basic research and its real-world application context.
Finally, it is crucial to emphasize that this book does not aim to define the goals of education. Science will never answer such a question because it is not a query that can be resolved through the scientific method. Instead, each educational community must establish its objectives based on the criteria it deems appropriate. However, once the goals are established, science can assist in revealing the methods more likely to help achieve them.
For historical reasons, this book revolves around how students can achieve meaningful, lasting, and transferable learning across any field of knowledge. It also addresses how they can improve their academic performance, an aspect not necessarily synonymous with meaningful learning. After all, these are the two major themes that science has investigated in greater depth. As we will see throughout this book, its conclusions validate the efficacy of certain practices that we have been conducting for decades. Still, they also reveal others that can significantly contribute to improving teaching and learning processes.
To conclude, my humble desire is that this book proves to be of use to teachers and students, as well as to all people interested in learning how learning works. After all, the journey of becoming a learner is an ongoing process.
HÉCTOR RUÍZ MARTÍN
ORIGINAL TEXT: DECEMBER 2019
SECTION 1THE SCIENCE OF HOW WE LEARN
Before delving into the topic of what we know about how people learn and what we can do to promote learning based on these ideas, the opening chapter explores how science has gained this knowledge and what precautions should be taken when applying it.
Thus, in the first section of the book, I explain how research is conducted in the field of teaching and learning processes and why this research provides unique insights to support the decisions we make daily, both as educators and as students. Furthermore, I advise on the nature and limitations of scientific knowledge, particularly in a field as complex as the one discussed here, and emphasize the importance of interpreting research results appropriately, with cautiousness and critical thinking.
1.1The Scientific Study of Learning and Teaching
“It's unbelievable how much you don't know about the game you've been playing all your life.”
Mickey Mantle (1931–1995)
Baseball player
Personal Experience and Cognitive Biases
As educators, we make countless decisions every day so that our actions and those of our students have a positive impact on their learning in all its dimensions. In addition to small day-to-day decisions, we also make important, high-impact choices when planning our teaching for the upcoming school year, selecting the educational materials we will use, or participating in decisions that define the educational project of our school.
Typically, we base all these decisions on our intuition, which is fueled by the knowledge and beliefs about education that we have built upon a vast body of personal experiences. The origin of these experiences that shape our conceptions of teaching and learning dates back to our time as students in the educational system, and for many educators, this extends uninterrupted into their professional careers. During this life journey through the educational system, first as students and then as educators, it is only natural that we accept the validity of many of its assumptions and, conversely, question others based on our personal experience.
However, how reliable are the intuitions we have developed about education based on our personal experience? If personal experience is the best way to determine what is best for our students, why do not all (equally experienced) teachers agree on which methods yield the best results? To begin with, each of us goes through different personal experiences, which can make comparisons challenging. Nonetheless, what truly compromises the reliability of our personal experiences is how we interpret them, which is influenced by the way our brain operates. And here lies the problem: the human brain exhibits multiple “biases” that distort its understanding of reality when it relies solely on personal experience. This is what we call cognitive biases.
To understand the problem of cognitive biases, take a look at the following images. Would you believe me if I told you that the horizontal lines in Figure 1 are straight and parallel? They are. Go ahead, take a sheet of paper and place it along each line and see for yourself.
FIGURE 1
FIGURE 2
Now look at Figure 2. Would you say that the tower at the right is more tilted? The truth is that both are identical, even in their inclination.
And what about Figure 3? Would you believe me if I told you that the squares marked with the letters A and B are exactly the same color? Well, they are.
These situations, like many more, prove that our brain normally operates by manipulating and altering sensory information. That is, we do not perceive things as they are; the brain processes sensory information and “adjusts” it before placing it into our consciousness. Mechanisms that alter sensory information have obviously evolved over millions of years to make us more effective in interacting with the environment in which our species has developed—an environment that, by the way, was quite different from the one most of us inhabit today.
FIGURE 3
The fact is that the brain does not only “trick” us when it comes to what we perceive. Just as the brain modifies our perception, it also has mechanisms to “fine-tune” how we think and remember (Kahneman & Tversky, 1972). In other words, our reasoning and memories are subject to brain mechanisms that operate outside our consciousness and shape our thinking when we try to make sense of reality. We may not be aware of their existence, but these mechanisms play a role in the processes that help us interpret the world around us and make decisions. The problem is that they did not evolve so we could fully grasp the world as it is, but rather in a way that was practical for our survival and allowed our species to endure. We use these mechanisms to make immediate judgments and responses in situations that call for quick decisions, when it is not possible to process all available information, or when we lack information. These mechanisms divert us from logical thinking and steer us toward decisions fueled by our emotions—even when we think we are being rational. They also hinder our ability to appreciate the practical significance of statistical probability (why are we more afraid of flying than driving when many more people die in car accidents than in plane crashes?) and make us particularly vulnerable to fallacies, deceptive types of reasoning that may seem correct but are, in fact, flawed.
In summary, because of certain spontaneous cognitive “adjustment” mechanisms that our brain activates spontaneously, all humans exhibit various biases that influence how we understand the world, reason, and make decisions. These biases have nothing to do with our preferences, our likes, or our ethical or moral ideas. Cognitive biases are involuntary psychological phenomena that distort the way we process information—how we perceive it, how we interpret it, and how we remember it. For example, a common cognitive bias occurs when we think that the price of an item at $4.99 is much more appealing than one at $5.00, or when we perceive that a black object weighs more than the same object in white. These biases also come into play when we quickly establish cause-and-effect relationships based on a single experience.
Note: Fallacies
Biases make us inclined to consider some types of reasoning as valid that, when carefully examined through the lens of logic, are not really so. These types of reasoning are called fallacies. Fallacies are powerful rhetorical tools for persuading others, which is why many politicians are quick to use them in their speeches. They are also effective for convincing oneself or reaffirming one's own ideas. The following are three of the most common fallacies:
Ad hominem
fallacy
. This occurs when an argument does not refute the interlocutor's position or claims, but instead seeks to discredit the interlocutor personally to undermine their position. For example, an
ad hominem
fallacy occurs when we say, “You say that this method is better, but you don't use it in your own classes,” since it attempts to refute the proposition—the proposed method—by attacking the proponent. The fact that a person's actions are not consistent with their words does not mean that what they propose is not valid (“Do as I say, not as I do”). We also commit these fallacies when we disqualify the interlocutor's claims by referring to their education or profession: “You're not a teacher, so what you say is of no use to me.”
Ad verecundiam
fallacy
. This is an argument that appeals to the prestige or authority of some individual or institution to support a claim, despite not providing evidence or reasons to justify it. For example, “Piaget, the renowned educational psychologist and father of constructivism, stated the same thing I just mentioned.” Of course, it is interesting that he claimed it (whatever it was), but that does not mean it is true. Several of Piaget's ideas about children's cognitive development have actually been refuted by decades of research in developmental psychology.
Ad populum
fallacy
. This occurs when we attribute our opinion to the majority's opinion and then argue that if most people think something, it must be true. Just because most people in the 17th century believed the Sun revolved around Earth does not mean that this was true. Similarly, even if most teachers believe that memory can be improved in general by exercising it through memorizing academic content, this does not mean it is true.
Confirmation Bias and Cognitive Dissonance
Cognitive psychologists have identified dozens of biases influencing how we reason about reality. One of the most prominent biases that can clearly impact our decisions as teachers is confirmation bias—the tendency to notice, pay attention to, and remember information that confirms our beliefs, while disregarding information that contradicts them (Oswald & Grosjean, 2004). This bias causes us to interpret the same information in a completely different way than others would, seeing it as more aligned with our convictions. It even leads us to ignore evidence when it is right in front of us and preferentially perceive evidence that supports our views (Lord et al., 1979). To see this bias in action, just watch two fans of rival basketball teams watching the same game on TV.
Furthermore, this bias causes us to forget information that does not fit with our ideas in favor of information that does (Stangor & McMillan, 1992). Thus, confirmation bias acts when we remember situations that confirm our hypotheses but ignore or forget situations where they did not hold. For example, a person who believes that using technology in class is counterproductive to learning will preferably remember students’ comments about the disadvantages of these tools and forget the positive comments. They will not consider whether the complaints are well founded or if they have a solution since they align with their ideas. In fact, it is when our beliefs are challenged that confirmation bias drives us to seek information that proves us right. However, we specifically seek the information that proves us right. We rarely decide to investigate further into the opposing view, and, in fact, when we do and come across information that supports the opposing hypothesis, we shamelessly dismiss it to continue searching for the one we want (Nickerson, 1998). As psychologist Ziva Kunda (1990) pointed out, “People are more likely to arrive at conclusions that they want to arrive at.” In fact, Francis Bacon had already been aware of this in 1620 when he observed that “most people prefer to believe what they prefer to be true.”
Therefore, confirmation bias is more evident when our beliefs are challenged. When that is the case, we may start feeling personally attacked. After all, the more deeply rooted our beliefs about how the world around us is and how it works, the more they become a part of our own identity. The inner conflict that arises when our ideas clash with information or experiences that contradict them is a phenomenon known as cognitive dissonance (Festinger, 1957).
Usually accompanied by an uneasy sensation, cognitive dissonance prompts us to react by trying to regain “balance” through confirmation bias, which helps us reaffirm our convictions, even leading us to ignore evidence. In a way, confirmation bias is an unconscious resistance to changing our ideas, an automatic system for protecting our identity.
Confirmation bias is reinforced by other biases, such as the so-called bandwagon effect, the tendency to do or believe something simply because many others do or believe it (Leibenstein, 1950). Indeed, there is an involuntary psychological tendency to follow or imitate the actions and thoughts of others to fit into the group we belong to. Undoubtedly, this bias also influences our understanding of education.
These cognitive biases, along with many others, make us very ineffective at analyzing reality without even realizing it. Therefore, when it comes to teaching and learning processes, we must go beyond personal experience and use strategies that help us free ourselves from our biases and discern between what most likely “works” and what does not, based on empirical evidence untainted by our minds. To this end, there is no better remedy than the scientific method.
The Scientific Method as a Remedy for Cognitive Biases
Think of the scientific method as a pair of glasses crafted by humanity to correct our cognitive biases when we look at the world around us. It invites us to collect data methodically and analyze it logically and systematically. In doing so, it allows us to establish cause-and-effect relationships with greater precision than our personal experiences alone. As Carl Sagan once said, it may not be a perfect method, but it is the best one we have for such purposes.
It is important to emphasize that the scientific method goes beyond just learning from direct experience. In this sense, it differs from personal experience in how it collects and analyzes data and how it uses that data to draw logical conclusions. Only then can direct experience break free from our cognitive biases.
For instance, someone may be convinced that presenting a concept in a particular way in primary education can lead to misconceptions hindering later learning in secondary education. This is their hypothesis, possibly based on intuition, later confirmed by observing cases in their classes (which they will readily remember). But how do we determine how widespread or anecdotal these misconceptions are in the classroom? And, most importantly, how can we tell if the presentation of the concept in primary education is indeed the cause of these misconceptions? Relying solely on spontaneous observation and subjective assessments will subject us to confirmation bias, making us see and remember what we already believe. Conversely, by choosing to analyze the situation scientifically, we can objectively shed more light on the matter.
Of course, this does not mean that every time we face a decision as teachers, we must conduct experiments and scientifically analyze them to find supporting evidence. Fortunately, several researchers (many of them also teachers) have already done this for us and published their results. Still, it is not necessary to consult scientific literature for every step we take. However, when it comes to significant decisions, especially those requiring substantial investments of resources—be it money, time, effort, enthusiasm, or opportunity (the opportunity cost of doing one thing is missing out on another potentially better option)—it is advisable to learn about what research has to offer, and not just to have our hypotheses supported! However, it is important to remember that science will never tell us what we should or should not do; it can only inform us about what is more likely to happen when we do this or that.
Levels of Research on Learning and Teaching
There are several scientific disciplines studying the processes of learning and teaching from different perspectives, focusing on complementary aspects.
First, neurobiology explores how learning occurs at the molecular, cellular, and organ system levels. In essence, it examines how the nervous system serves as the physical foundation for learning-related phenomena. In its studies, neurobiology employs animal models and, when possible, also works with human subjects—either in post-mortem settings, during surgical procedures, or with cell cultures. In recent decades, this field has greatly benefited from the ability to “observe” the brain of a healthy person in action while they engage in mental or motor activities. This milestone has been made possible through the development of neuroimaging technology, such as functional magnetic resonance imaging (fMRI), allowing us to observe which regions of the brain become more active than usual when individuals undertake various tasks. Figure 4 presents two examples of such images (although in black and white).
At a different level of study lies cognitive psychology, a deeply empirical branch of psychology that investigates how the brain acquires, processes, and stores information. However, it does not study the physiology of the brain. Instead, cognitive psychology models its operation by assessing the changes that certain sensory or motor experiences cause in people's behavior and performance. For example, an experiment in this discipline might explore whether individuals remember a story better when they read it or when it is explained to them. Consequently, cognitive psychology is much more equipped to guide us in educational practice than neurobiology. In fact, it draws on the advances of neurobiology to support its models and theories, thus acting as a link between scientific advancements in understanding how the brain works and education.
FIGURE 4 Examples of images obtained using functional magnetic resonance imaging.
Source: M.R.W.HH / Wikimedia Commons / Public domain.
Note: Cognitive Psychology and Neurobiology
Although the brain does not work like a computer, we can use a computer analogy to understand the difference between the approach proposed by cognitive psychology and that offered by neurobiology when it comes to studying the processes of learning.
Imagine we want to figure out how a computer program works when there is no instruction manual or tutorial to show us how to use it. The approach of cognitive psychology would involve pressing buttons and trying different combinations to observe what happens, that is, how the program responds. In contrast, neurobiology would open the computer, study its circuits, and analyze what happens within them when the program is running.
Although this analogy may seem somewhat forced, it effectively illustrates which of the two approaches is closer to guiding us on what to do in the classroom to promote learning—essentially, how to get the most out of the metaphorical computer program.
Cognitive psychology, in fact, provides valuable data and models for the field known as educational psychology—a multidisciplinary specialty that relies on cognitive psychology and related disciplines, such as developmental psychology and evolutionary psychology, to study learning and teaching processes in real contexts. It is the discipline closest to the classroom, and its main strength lies in directly bringing research into classrooms. When educational psychology focuses on teaching and learning specific knowledge areas, it branches into various “didactics,” such as mathematics didactics, language didactics, or science didactics.
Of course, many other disciplines contribute to the study of teaching and learning processes, from sociology to computer science. Still, I have chosen to concentrate on those that predominate in the approach covered in this book.
With that said, I believe it is necessary to clarify where the field known as educational neuroscience fits into this landscape. Strictly speaking, the term neuroscience has always referred to research on the structure and functioning of the nervous system from a physiological perspective, and consequently, it is equivalent to the neurobiological discipline. That is why initially the concept of educational neuroscience pertained only to neurological studies on brain function related to learning and memory. However, in recent years, as scientific evidence on how the brain learns that is most relevant to educational practice has come primarily from cognitive psychology and related disciplines, the term educational neuroscience has been increasingly used in a broader sense than its original meaning, encompassing these disciplines under the same umbrella. In other words, in nonspecialist circles the term has evolved into a synonym for any discipline that employs the scientific method to analyze how we learn (Anderson & Della Sala, 2012).
Experiments in the Classroom
Educational research conducted directly in the classroom usually adopts two types of approaches: descriptive or experimental. In the first case, the aim is to gather data, whether numerical or qualitative, that objectively describe how things are. This type of research allows for the detection of correlations; that is, the coincidence of two or more variables, such as observing that children with higher self-esteem tend to coincide with those who achieve better academic results. On the other hand, experimental research aims to analyze the relationship between different variables and identify cause-and-effect relationships. For example, does higher self-esteem cause students to get better grades? The way to conduct such research would involve acting on the variable we assume to be the cause (self-esteem) and observing if, by modifying it, the variable we presume to be the effect (academic results) also changes. The rest of the variables that could affect academic results should be controlled during the experiment.
Thus, to conduct the experiment that addresses the previous question, we could set up two groups of students who are very similar in their average characteristics, such as the ratio of boys to girls, socioeconomic status, group's average grade, and so forth (this is better achieved by distributing the students in each group randomly). From here, one group could be exposed to a self-esteem enhancement program (assuming we already know it works), while the other group would receive sessions on any other topic (e.g., neuroscience). After the interventions, we could collect new data on their academic grades and measure the improvement in each group compared to their grades before the experiment. Then we would compare the academic improvements of each group to see if that of the group that received the self-esteem intervention is different from that of the group that did not receive it. If it were, we could conclude that our experiment would have provided evidence of the presumed effect of self-esteem on academic results.
