Table Of ContentExplorations in the Learning Sciences, Instructional
Systems and Performance Technologies
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Susanne P. Lajoie, McGill University, Montreal, Quebec, Canada
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John Sweller Paul Ayres Slava Kalyuga
• •
Cognitive Load Theory
John Sweller Slava Kalyuga
School of Education School of Education
University of New South Wales University of New South Wales
Sydney, NSW, Australia, 2052 Sydney, NSW, Australia, 2052
[email protected] [email protected]
Paul Ayres
School of Education
University of New South Wales
Sydney, NSW, Australia, 2052
[email protected]
ISBN 978-1-4419-8125-7 e-ISBN 978-1-4419-8126-4
DOI 10.1007/978-1-4419-8126-4
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Preface
Without knowledge of human cognitive processes, instructional design is blind.
In the absence of an appropriate framework to suggest instructional techniques, we
are likely to have difficulty explaining why instructional procedures do or do not
work. Lacking knowledge of human cognition, we would be left with no overarching
structure linking disparate instructional processes and guiding procedures. Unless
we can appeal to the manner in which human cognitive structures are organised,
known as human cognitive architecture, a rational justification for recommending
one instructional procedure over another is unlikely to be available. At best, we
would be restricted to using narrow, empirical grounds indicating that particular
procedures seem to work. We could say instructional procedure A seems better than
procedure B but why it works, the conditions under which it works or how we can
make it work even better would be rendered unanswerable and mysterious.
In contrast, knowledge of how we learn, think and solve problems – human
cognitive architecture – can provide us with a coherent, unifying base that can be
used to generate instructional hypotheses and data. That base can explain why some
instructional procedures work while others fail. Seemingly disparate, even contra-
dictory data can be explained and reconciled. Most importantly, human cognitive
architecture can be used to generate instructional procedures that we otherwise
would have considerable difficulty conceiving. The structures that constitute the
framework of human cognitive architecture provide an essential prerequisite to
instructional design for both researchers and professional educators. Those struc-
tures allow us to make sense of instructional design issues. Further, we can use our
knowledge of human cognitive architecture to devise instructional theories.
One such theory is cognitive load theory that was explicitly developed as a the-
ory of instructional design based on our knowledge of human cognitive architec-
ture. Cognitive load theory consists of aspects of human cognitive architecture that
are relevant to instruction along with the instructional consequences that flow from
the architecture. This book begins by considering categories of knowledge in Part
I, human cognitive architecture in Part II, categories of cognitive load in Part III,
followed by the instructional effects that flow from these theoretical considerations
in Part IV and the conclusions in Part V.
v
vi Preface
In recent years, the cognitive architecture used by cognitive load theory has
been expanded and anchored within a biological evolutionary framework.
Evolution by natural selection has a dual role in cognitive load theory. First, as
indicated in Chapter 1 of Part I, we can classify information into two categories.
The first category, known as biologically primary knowledge, consists of informa-
tion that we have specifically evolved to acquire while the second category, known
as biologically secondary knowledge, is information that we need for cultural
reasons but have not specifically evolved to acquire. Educational institutions were
devised to facilitate the acquisition of biologically secondary information and
cognitive load theory deals almost exclusively with that category of information.
Chapter 1, by analysing these distinct categories of knowledge, provides an intro-
duction to the evolutionary base used by cognitive load theory.
Evolution by natural selection has a second, equally important role in cognitive
load theory. Evolutionary theory is usually considered as a biological theory
explaining how biological structures, including entire species, arose. That function
is, of course, the primary purpose of evolutionary theory. Nevertheless, evolution-
ary theory can be considered from an entirely different perspective, as a natural
information processing system. By thinking of evolutionary theory in terms of the
manner in which information is processed, we can extend evolutionary concepts to
other information processing systems such as human cognition.
Biological evolution is not normally considered in information processing terms
but there are advantages to thinking of it in this way. When considered as an infor-
mation processing system, biological evolution is able to tell us about a particular
class of theories, natural information processing theories. These theories tell us how
information is processed in nature and evolution by natural selection provides us
with the best known and most detailed natural information processing theory. By
treating biological evolution as a natural information processing theory, we can
throw substantial light on the characteristics of this class of information processing
systems because of the large amount of knowledge that we have available to us
about biological evolution.
Knowing how natural information processing systems such as biological evolu-
tion function is particularly important because human cognition provides another
example of a natural information processing system. If we know how biological
evolution functions as a natural information processing system, that knowledge can
be used to tell us how human cognition functions because human cognition also is
a natural information processing system, analogous to evolution by natural selec-
tion. Knowing the characteristics of natural information processing systems in
general can tell us about some of the central characteristics of human cognition.
Thus, if we know how biological evolution works, it may tell us much about
how human cognition works, assuming both are natural information processing
systems. If we assume the way we learn, think and solve problems is part of nature
because we are part of nature, we need to know how nature learns and solves
problems. That aim can be achieved by treating both evolution by natural selection
and human cognition as a natural information processing system. Chapters 2–4 of
Part II establish and discuss the suggested analogy between evolution by natural
Preface vii
selection and human cognition. In the process, those chapters provide the cognitive
architecture that lies at the heart of cognitive load theory.
Cognitive load theory’s emphasis on human cognitive architecture and its evolu-
tion is not an end in itself. The ultimate aim of the theory is to use our knowledge
of human cognition to provide instructional design principles. The cognitive archi-
tecture discussed in Part II tells us that when processing biologically secondary
information, human cognition includes a working memory that is limited in capac-
ity and duration if dealing with novel information but unlimited in capacity and
duration if dealing with familiar information previously stored in a very large long-
term memory. Instruction needs to consider the limitations of working memory so
that information can be stored effectively in long-term memory. Once appropriate
information is stored in long-term memory, the capacity and duration limits of
working memory are transformed and indeed, humans are transformed. Tasks that
previously were impossible or even inconceivable can become trivially simple.
Accordingly, the aim of instructional design is to facilitate the acquisition of knowl-
edge in long-term memory via a working memory that is limited in capacity and
duration until it is transformed by knowledge held in long-term memory. The char-
acteristics of that memory can provide guidelines relevant to designing instruction.
The initial process of specifying instructional design principles begins in Part III of
this book.
The cognitive load imposed on working memory by various instructional proce-
dures originates from either the intrinsic nature of the instructional material, result-
ing in an intrinsic cognitive load, or from the manner in which the material is
presented and the activities required of learners, resulting in an extraneous cogni-
tive load. Chapter 5 in Part III introduces the instructional applications of cognitive
load theory by outlining the categories of cognitive load, their interactions and their
instructional consequences. Chapter 6 discusses techniques that have been used to
measure cognitive load.
The chapters of Part IV discuss the range of instructional effects generated by the
theory. Over 25 years, researchers from around the globe have used cognitive load
theory to generate a variety of instructional procedures. Those procedures character-
istically are tested for effectiveness by comparing them to more traditional methods
using randomised, controlled experiments. When the results of such comparisons
indicate the superiority of a new procedure over a commonly used procedure, a
cognitive load effect is demonstrated. Cognitive load effects provide us with novel
instructional guidelines that constitute the ultimate aim of cognitive load theory.
These guidelines constitute the major justification for devising cognitive load theory
and are discussed in Chapters 7–17. Each chapter describes one or more of the
cognitive load effects generated by the theory with each effect indicating an instruc-
tional procedure, tested for effectiveness, and recommended for use. The conclusions
of Chapter 18 tie together the various strands of the preceding sections.
Over the two to three decades that cognitive load theory has been used as an
instructional theory, it has undergone considerable development and change. In an
example of a feedback loop, the changes to cognitive load theory have been driven
largely by the instructional effects generated by the theory. Most commonly,
viii Preface
the theory has generated a new instructional procedure at a point in time and that
procedure has been demonstrated in a particular curriculum area using a specific set
of materials. On occasions, the effect has failed to generalise to a different area and
different conditions. Such failures require an explanation and that explanation usu-
ally results in both theory development and new instructional effects and proce-
dures. In this manner, the edifice that constitutes cognitive load theory has been
constructed.
Ultimately, the theory stands or falls according to its ability to generate novel,
useful, instructional procedures, a justification common to all instructional theories.
We hope cognitive load theory passes this test. The most recent version of the
theory, along with the instructional procedures generated by the theory over many
years is presented in this book. We begin, in the next chapter, by using evolutionary
theory to categorise knowledge.
John Sweller
Paul Ayres
Slava Kalyuga
Acknowledgements
There are far too many people who have contributed to cognitive load theory over the
years to be able to thank in anything other than general terms. The first group to thank
is the army of research students who ultimately did most of the work associated with
the theory. Many of those students from around the world have since become highly
respected international scholars in their own right. Without them, this book would not
have been written. We owe them a debt of gratitude that can never be repaid. One of
those ex-students, Elizabeth Owen, carefully read the manuscript and eliminated
many of our more clumsy efforts. We thank her for her work, emphasising that any
remaining confusions are entirely our responsibility. Another research student, Chee
Lee, funded by the Faculty of Arts and Social Sciences at UNSW, did a magnificent
job of organising our reference list and assisting with the figures. Her patience knows
no bounds!
The empirical work described in this book and largely carried out by research
students required the testing of countless students (using those randomised, con-
trolled experiments!) in many of the population centres around the world. They
deserve a special thank you. We hope that as small compensation, our procedures
have assisted them in their studies.
Our many collaborators from around the world have contributed far more to
cognitive load theory than we could ever achieve. The theory is theirs, not ours.
Lastly, and most importantly, we would like to thank Susan, Robyn and Marika.
They have put up with us and for them, cognitive load theory has been a near lifetime
sentence!
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