Cognitive load theory in health professional
education: design principles and strategies
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van Merrienboer, J. J. G., & Sweller, J. (2010). Cognitive load theory in health professional education:
design principles and strategies. Medical Education, 44(1), 85-93. https://doi.org/10.1111/j.1365-
2923.2009.03498.x
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Cognitive load theory in health professional education:
design principles and strategies
Jeroen J G van Merrie
¨
nboer
1,2
& John Sweller
3
CONTEXT Cognitive load theory aims to
develop instructional design guidelines based
on a model of human cognitive architecture.
The architecture assumes a limited working
memory and an unlimited long-term memory
holding cognitive schemas; expertise exclu-
sively comes from knowledge stored as schemas
in long-term memory. Learning is described as
the construction and automation of such sche-
mas. Three types of cognitive load are distin-
guished: intrinsic load is a direct function of
the complexity of the performed task and the
expertise of the learner; extraneous load is a
result of superfluous processes that do not di-
rectly contribute to learning, and germane load
is caused by learning processes that deal with
intrinsic cognitive load.
OBJECTIVES This paper discusses design
guidelines that will decrease extraneous load,
manage intrinsic load and optimise germane
load.
DISCUSSION Fifteen design guidelines are
discussed. Extraneous load can be reduced by
the use of goal-free tasks, worked examples and
completion tasks, by integrating different
sources of information, using multiple
modalities, and by reducing redundancy.
Intrinsic load can be managed by simple-to-
complex ordering of learning tasks and work-
ing from low- to high-fidelity environments.
Germane load can be optimised by increasing
variability over tasks, applying contextual
interference, and evoking self-explanation. The
guidelines are also related to the expertise
reversal effect, indicating that design guidelines
for novice learners are different from guide-
lines for more experienced learners. Thus,
well-designed instruction for novice learners is
different from instruction for more
experienced learners. Applications in health
professional education and current research
lines are discussed.
cognitive load theory
Medical Education 2010: 44: 85–93
doi:10.1111/j.1365-2923.2009.03498.x
1
Department of Educational Development and Research, Maastricht
University, Maastricht,
The Netherlands
2
CELSTEC, Open University of the Netherlands, Heerlen, The
Netherlands
3
School of Education, University of New South Wales, Sydney,
New South Wales, Australia
Correspondence: Jeroen J G van Merrie
¨
nboer, Maastricht University,
FHML, Department of Educational Development and Research,
PO Box 616, 6200 MD Maastricht, The Netherlands. Tel: 00 31 43
3885727; Fax: 00 31 43 3885779;
E-mail: j.vanmerrienboer@educ.unimaas.nl
ª Blackwell Publishing Ltd 2009. MEDICAL EDUCATION 2010; 44: 85–93 85
INTRODUCTION
Cognitive load theory (CLT) was initially developed
in the 1980s.
1
By means of strictly controlled exper-
imental studies, it aimed to develop instructional
design principles and strategies based on a model of
human cognitive architecture. Right from the start,
CLT provided instructional design principles that
were seen as counterintuitive by many practitioners
in the field of education. For example, the recom-
mendation to provide novice learners with many
worked examples rather than problems to solve
contradicted the prevailing opinion of the time that
solving problems was the best way to learn to solve
problems. The theory has developed substantially
since the 1980s (see reviews
2,3
). Having established a
variety of basic instructional designs that prevented
the application of cognitive resources to unnecessary
aspects of a task, an increasing number of cognitive
load theorists from around the world considered how
to deal with highly complex learning tasks, how to
stimulate learners to actually use available cognitive
resources for learning, and how to deal with the
growing expertise of learners in educational
programmes of longer duration.
Applications of CLT in medical education are
beginning to appear.
4,5
Moreover, educational
approaches in the health professions increasingly
stress the use of authentic tasks, which are expected
to help students integrate the knowledge, skills and
attitudes necessary for effective task performance in
professional life.
6
Authentic learning tasks designed
on the basis of real-life tasks have many different
solutions, are ecologically valid and usually cannot be
mastered in a single session. Whereas CLT may not be
relevant to teaching simple tasks, it is critical when
complex learning tasks are used because they impose
a high load on the learner’s cognitive system.
7,8
Therefore, this article argues that design guidelines
based on CLT are highly relevant to teaching in
complex domains like the health professions, espe-
cially when authentic learning tasks are part of the
curriculum. The article briefly presents, in order, the
cognitive architecture assumed by CLT, the main
design principles and strategies based on this archi-
tecture, and a discussion of the presented framework.
COGNITIVE ARCHITECTURE
Cognitive load theory assumes a cognitive architec-
ture that is broadly supported by research in cognitive
psychology and can be explained readily from an
evolutionary perspective.
9
This section briefly
summarises the theory in terms of memory systems,
learning processes supported by those systems, and
associated types of cognitive load.
Memory systems
Cognitive load theory assumes that the human
cognitive system has a limited working memory that
can hold no more than five to nine information
elements (the famous ‘seven plus or minus two’)
10
and actively process no more than two to four
elements simultaneously. It is able to deal with
information for no more than a few seconds and
almost all information is lost after about 20 seconds
unless it is refreshed by rehearsal. The theory
emphasises that these working memory capacity and
duration limitations only apply to novel information
obtained through sensory memory. Working memory
has no known limitations when dealing with infor-
mation retrieved from long-term memory. In effect,
long-term memory alters the characteristics of work-
ing memory. Long-term memory holds cognitive
schemas that vary in their degree of complexity and
automation. Human expertise comes from knowl-
edge organised by these schemas, not from an ability
to engage in reasoning with many elements that have
not been organised in long-term memory. Human
working memory simply is not able to process many
elements.
Expertise develops as learners mindfully combine
simple ideas into more complex ones. A medical
student, for example, gradually combines simple
ideas about consequences, enabling conditions and
faults into so-called ‘illness scripts’, a term that
describes a particular type of schema which allows the
user to distinguish between alike diseases. Illness
scripts can be interpreted during problem solving
and reasoning and so help to reach an accurate
diagnosis. These schemas organise knowledge but
also heavily reduce working memory load because
even a highly complex schema can be dealt with as
one element in working memory.
Fully automated schemas are developed as a function
of extensive practice and can act as a central
executive, organising information or knowledge that
needs to be processed in working memory. Under
these circumstances there are no limits to working
memory. For instance, an experienced medical doc-
tor recognises a ’warm shock’ resulting from redis-
tribution of cardiac output at a single glance. By
contrast, when dealing with novel information for
86 ª Blackwell Publishing Ltd 2009. MEDICAL EDUCATION 2010; 44: 85–93
J J G van Merrie¨nboer & J Sweller
which no schema-based central executive is available,
working memory has limitations. Thus, for a novice
student, a patient with a warm shock may show little
more than an unstructured set of symptoms.
Learning processes
Working memory must inevitably be limited in
capacity when dealing with completely novel, unor-
ganised information because, as the number of
elements that need to be organised increases linearly,
the number of possible combinations of elements
that must be tested for effectiveness during problem
solving increases exponentially. Random testing of
the effectiveness of possible combinations based on
many elements becomes effectively impossible be-
cause of a combinatorial explosion. This problem of
exponential growth can only be accommodated by
severely limiting the number of information units
that are processed simultaneously. This is what
learning processes such as schema construction and
schema automation do by organising information in
long-term memory. Schemas can be constructed
during the problem-solving process by bringing
elements together (i.e. chunking), by incorporating
new elements in schemas already available in long-
term memory or, more commonly, by obtaining
already schematised information from other people.
Schemas can then be treated as a single element in
working memory and thus heavily decrease cognitive
load associated with the performance of later tasks.
Constructed schemas may become automated if they
are repeatedly applied and yield desired results. As is
the case for schema construction, automation can
free working memory capacity for other activities
because an automated schema, acting as a central
executive, directly steers behaviour without needing
to process it in working memory. Because automation
requires a great deal of practice, automated schemas
only develop for those aspects of performance that
are consistent across task situations, such as routines
for operating medical equipment and standard pro-
cedures for using software applications. Thus, from
an instructional design perspective, well-designed
instruction should not only encourage schema
construction, but should also support schema
automation for those aspects that are consistent
across tasks.
6,11
Types of cognitive load
Novel information must be processed in working
memory in order to construct schemas in long-term
memory. The ease with which information may be
processed in working memory is a focus of CLT.
Working memory load may be affected by the
intrinsic nature of the learning tasks (intrinsic load),
by the manner in which the tasks are presented
(extraneous load), and by the learning that actually
occurs (germane load) when dealing with intrinsic
load.
Intrinsic load cannot be altered by instructional
interventions without altering the task to be learned
(e.g. simplification) or by the act of learning itself. It
depends on the number of elements that must be
processed simultaneously in working memory, a
number which, in turn, depends on the extent of
element interactivity of the materials or tasks that must
be learned. Element interactivity is the degree to
which the elements of something to be learned can,
or cannot, be understood in isolation. For example,
vocabulary is an example of low element-interactive
material in the field of language learning. Although
there are thousands of words to be learned, most
people can quickly learn some simple words because
words may be learned in isolation from all other
words. Grammar, by contrast, is an example of high
element-interactive material. Most people have diffi-
culty in generating grammatically correct sentences,
even when all the words to be used in the sentence
are known. This is because many elements must be
considered simultaneously; that is, to build sentences
that are grammatically correct, one must attend to all
the words within the sentence at once while also
considering syntax, tense and verb endings.
Tasks with high element interactivity are difficult to
understand and yield a high cognitive load because
learners must deal with several elements simulta-
neously. The only way to foster understanding and to
reduce intrinsic cognitive load is to develop schemas
that incorporate the interacting elements. It follows
that a large number of interacting elements for one
person might be included within a single element for
another more experienced person who already has a
schema that incorporates the elements. Thus, ele-
ment interactivity can be estimated only by counting
the number of interacting elements dealt with by
people at a particular level of expertise.
By contrast with intrinsic load, extraneous load is
imposed by instructional procedures. Extraneous
load may be imposed, for example, when learners
must use trial and error or other weak problem-
solving methods that require them to arbitrarily try
out things without being given proper guidance,
12
when they must integrate information sources that
are distributed in place or time, or when they must
ª Blackwell Publishing Ltd 2009. MEDICAL EDUCATION 2010; 44: 85–93 87
Cognitive load theory
search for information that is needed to complete a
learning task. Overloading one of the processors that
constitute working memory may also increase it.
Visual and auditory working memory are partially
independent. If multiple sources of information that
are required for understanding are all presented in
visual form (e.g. a written text and a diagram), they
are more likely to overload the visual processor than
if the written material is presented in spoken form,
thus enabling some of the cognitive load to be shifted
to the auditory processor.
13
Germane load, finally, refers to the working memory
resources used to deal with intrinsic cognitive load,
which lead to learning. For instance, learners con-
struct schemas that deal with the interacting elements
associated with intrinsic cognitive load by working on
a series of tasks and abstracting away from them by
identifying structural features and surface features in
a process of induction or ‘mindful abstraction’. They
also construct schemas when they connect new
information elements to the things they already
know, that is, to existing schemas in long-term
memory, in a process of elaboration. These processes
of dealing with intrinsic cognitive load include
elements related to previous tasks or to knowledge
already available in long-term memory and thus
require working memory resources that correspond
to a germane cognitive load that is directly relevant
for learning.
Cognitive load theory assumes that intrinsic and
extraneous cognitive loads are additive. Whether
extraneous load presents students with a problem
depends, in part, on the intrinsic load. If intrinsic
load is low, a high extraneous load resulting from an
inadequate instructional design may not be harmful
because the total cognitive load is within working
memory limits. Indeed, research has shown that
instruction designed to decrease extraneous load has
negligible effects on learning simple tasks (i.e.
involving low element-interactive materials
14
). There
simply is no need to decrease extraneous load
because there are sufficient cognitive resources
available to deal with the low intrinsic cognitive load.
However, for teaching complex tasks (i.e. involving
high element-interactive materials), the sum of the
intrinsic and extraneous loads may easily surpass
working memory capacity and yield overload
(Fig. 1a). Then, extraneous load and, if the reduction
of extraneous load is still insufficient, intrinsic load
must be lowered to free up processing resources
necessary for learning (Fig. 1b). The more extrane-
ous cognitive load is reduced, the more working
memory resources can be devoted to intrinsic cogni-
tive load and so the easier it becomes to induce a
germane cognitive load for learning (Fig. 1c). The
next section discusses design guidelines for managing
cognitive load.
DESIGN GUIDELINES
Design principles and strategies based on CLT aim to
prevent overload and optimise germane load in order
to improve learning. The main principles and
strategies for decreasing extraneous load, managing
intrinsic load and optimising germane load are
summarised and illustrated in Table 1. Moreover,
they are related to the expertise reversal effect, which
indicates that principles that work well for novice
learners may not work well or may even have negative
effects for more experienced learners.
Decreasing extraneous load
Sweller et al.
2
reviewed six research-based principles to
decrease extraneous load for novice learners. Firstly,
the goal-free principle suggests replacing conventional
tasks with goal-free tasks, which provide learners with
a non-specific goal (e.g. replace ‘find the most
probable aetiological explanation for these symp-
toms’ with ‘find as many aetiological explanations for
these symptoms as you can’). If learners are given a
specific goal, they start reasoning from this goal and
try to find operators that reduce the difference
between the goal state and the given state. This
backward search process yields a high extraneous
load that can be avoided by eliminating a specific
goal that renders working backward from the goal
impossible.
Secondly, the worked example principle suggests replac-
ing conventional tasks with worked examples that
must be carefully studied by the learners. Because
(a)
(b)
(c)
Figure 1 The additive nature of intrinsic and extraneous
load: (a) overload; (b) preventing overload by decreasing
extraneous load, and (c) optimising germane load by
increasing intrinsic load
88 ª Blackwell Publishing Ltd 2009. MEDICAL EDUCATION 2010; 44: 85–93
J J G van Merrie¨nboer & J Sweller
