Executive Summary

Abstract

Nearly all teachers and other stakeholders in education pursue a common aim: we want the students whom we teach and guide during their formative years to think deeply about what we teach them. We want them to be able to go beyond their current experiences and have a deep understanding of the world.

Full text

SpringerBriefs in Education
TimSurma· ClaudioVanhees· MichielWils·
JasperNijlunsing· NunoCrato· JohnHattie·
DanielMuijs· ElizabethRata· DylanWiliam·
PaulA.Kirschner
Developing Curriculum
forDeep Thinking
TheKnowledge Revival

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Tim Surma ·Claudio Vanhees ·Michiel Wils ·
Jasper Nijlunsing ·Nuno Crato ·John Hattie ·
Daniel Muijs ·Elizabeth Rata ·Dylan Wiliam ·
Paul A. Kirschner
Developing Curriculum
for Deep Thinking
The Knowledge Revival

Authors
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Tim Surma
Thomas More University of Applied
Sciences
Antwerp, Belgium
Michiel Wils
Thomas More University of Applied
Sciences
Antwerp, Belgium
Nuno Crato
University of Lisboa
Lisbon, Portugal
Daniel Muijs
Queen’s University Belfast
Belfast, UK
Dylan Wiliam
UCL Institute of Education
University College London
London, UK
Claudio Vanhees
Thomas More University of Applied
Sciences
Antwerp, Belgium
Jasper Nijlunsing
Thomas More University of Applied
Sciences
Antwerp, Belgium
John Hattie
The University of Melbourne
Parkville, VIC, Australia
Elizabeth Rata
The University of Auckland
Grafton, New Zealand
Paul A. Kirschner
Open University of the Netherlands
Heerlen, The Netherlands
Thomas More University of Applied
Sciences
Antwerp, Belgium

Foreword
This book, written by experts from eight nations, explains why imparting specific
shared knowledge in early grades is important for achieving high levels of citizen
competence and high levels of equality and equity. As the result of a worldwide
collaboration, it is an open-access book. It is free to everyone everywhere. Special
thanks is owed to Prof. Paul Kirschner of the Netherlands for herding into a unity
these far-flung distinguished scholars, scientists, and public servants. Thank you,
Paul!
This international effort may come to be seen in the future as the sign of a new
beginning for teaching young pupils—a farewell to individualistic “child-centered”
doctrines, and a ringing in of a new, more effective early education in modern
democracies. The science presented in the book is up to date, some of it very recent.
Its general principles go back several years. These had their most memo-
rable expression in a 1994 resolution approved unanimously by the Parliament of
Norway—translated into English as follows by Prof. Gudmund Hernes:
It is a tenet of popular enlightenment [i.e., the enlightenment of a whole people] that shared
frames of reference must be the common property of all the people—indeed must be an
integral part of general education—to escape avoidable differences in competence that can
result in social inequality and be abused by undemocratic forces.
Those who do not share the background information taken for granted in public discourse
will often overlook the point or miss the meaning. Newcomers to a country who are not
immersed in its frames of reference often remain outsiders because others cannot take for
granted what they know and can do; they are in constant need of extra explanations.
Common background knowledge is thus at the core of a national network of communication
between members of a democratic community. It makes it possible to fathom complex
messages, and to interpret new ideas, situations, and challenges. Education plays a leading
role in passing on this common background information—the culture everybody must be
familiar with if society is to remain democratic and its citizens sovereign.
I have not found a better summary of what this present collaborative effort has
documented with the latest experimental results.
A foreword is not the place to develop a full-throated attack on the individualistic
“child-centered” approach of recent decades and its incorrect empirical assumptions.
vii

viii Foreword
Such a polemical tone is far from the straightforward expositions of the distinguished
writers from diverse lands who have produced this welcome gift. These scholars and
scientists are neither accusatory nor polemical.
They show from diverse angles and fields of research that the shared knowledge
revival in early grades is wrongly conceived as politically conservative. Rather, the
shared knowledge approach is an essential path to equity in a democracy. These
scholars from multiple nations show in detail with the latest scientific findings why
a carefully sequenced shared-knowledge curriculum in early grades is essential to
fairness and essential also to the complex cognitive skills demanded by modernity.
I’m grateful for the kind mentions of my own work in this book and for the invita-
tion to write this foreword. My years in the vineyard prompt me to add this observation
to the reader of this book: when the term “knowledge” is used in describing the deci-
sive experimental results cited in this book, it will be helpful for readers to think
“shared knowledge,” to grasp that knowledge possession and knowledge use often
involves a language transaction demanding silently shared background knowledge
between writer and reader, teacher and pupil. Language is the means by which we
humans co-ordinate our shared knowledge to create nations and achieve common
goals.
That’s why the word “shared” is important to connect with the word “knowledge.”
Knowledge gets fixed in our minds and communicated to others across generations
through shared language, which itself depends upon shared knowledge—even when
that knowledge is unstated. Human tribes flourished over other creatures in evolu-
tionary time (as evolutionary psychologists have explained) because shared knowl-
edge enables shared language which enables a human tribe to transform itself into a
massive creature that can defeat and eat large creatures. Here’s a memorable passage
from the evolutionary psychologist Joseph Henrich:
The disappearance of many megafaunal species eerily coincides with the arrival of humans
on different continents and large islands. For example, before we showed up in Australia
around 60,000 years ago, the continent was home to a menagerie of large animals, including
two-ton wombats, immense meat-eating lizards, and leopard-sized marsupial lions. These,
along with 55 other megafaunal species, went extinct in the wake of our arrival, resulting in
the loss of 88% of Australia’s big vertebrates.
It seems heartless to recount such a story until we consider that these lizards and
marsupial lions did not achieve their immensity by picking berries. Our tribal festivals
would have saved countless smaller creatures from the fearsome predators. From the
viewpoint of the human tribe, the cooperative principle based upon language and
shared knowledge was achieved by schooling the tribe’s children.
The tribal human school was fostered by shared language built up not only for
wombat-hunting techniques but also for other elements of cumulative tribal knowl-
edge through the agency of language. A distinguished evolutionary psychologist,
Michael Tomasello puts the case this way:
Cumulative cultural evolution takes place when the inventions in a cultural group are passed
on to the young with such fidelity that they remain stable in the group until a new and improved
invention comes along (the so-called ratchet effect). Modern humans had a stronger ratchet

Foreword ix
than early humans and apes because they had—in addition to powerful skills of imitation—
proclivities both to teach things to others and also to conform to others when they themselves
were being taught. And so it is, with this wave of group-mindedness and conformity, that we
get the possibility of cultural groups creating and constantly improving their own cognitive
artifacts—from procedures for whale hunting to procedures for solving differential equations.
(M. Tomasello. A Natural History of Human Thinking, 2014)
That shared knowledge principle holds true in human schooling from the primor-
dial cave to the early American “Common School” to the jazziest use of AI in the
current classroom. Shared knowledge remains the foundation of human education.
So, heartfelt thanks to the distinguished authors of this open educational resource,
and especially to Paul Kirschner for selflessly bringing this book into being.
Charlottesville, USA Prof. Dr. E. D. Hirsch

Acknowledgements
We thank Daniel Willingham, Dirk Van Damme, and Henk Byls for their feedback
on earlier versions of the manuscript.
xi

Contents
1 Introduction .................................................... 1
References ...................................................... 2
2 How Knowledge Matters ......................................... 5
2.1 Knowledge Matters: A Learning Perspective . . . . . . . . . . . . . . . . . . . . 6
2.1.1 A Basic Understanding of Human Cognitive Architecture . . . 6
2.1.2 How Can Prior Knowledge Facilitate Better Learning? . . . . . 9
2.1.3 Why Complex Cognitive Skills Require Knowledge . . . . . . . . 11
2.1.4 Reading Comprehension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2 Knowledge Matters: A Sociological Perspective . . . . . . . . . . . . . . . . . 21
2.2.1 From Objectivist to Constructivist Thinking Perspectives . . . 22
2.2.2 Skills for the Twenty-first Century and Neoliberal
Influences ............................................ 23
2.2.3 Bringing Knowledge Back in . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.3 Knowledge Matters: A Democratic Perspective . . . . . . . . . . . . . . . . . . 27
2.4 How Knowledge Matters Summarised . . . . . . . . . . . . . . . . . . . . . . . . . . 30
References ...................................................... 30
3 Knowledge and the Curriculum .................................. 37
3.1 EverythingStartswiththeCurriculum .......................... 37
3.2 Curriculum as a Pendulum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.3 Towards the Best of Both Worlds: A Knowledge-Rich
Curriculum ................................................. 46
3.4 On Content-Richness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.4.1 TheSelectionofContent ............................... 47
3.4.2 The Basis of the Selection Process . . . . . . . . . . . . . . . . . . . . . . . 48
3.4.3 The Impact of Hierarchy and Structure in Knowledge
and Sequence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.4.4 The Relation Between Knowledge and Skills . . . . . . . . . . . . . . 51
3.5 On Coherence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.5.1 Horizontal Coherence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.5.2 Vertical Coherence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
xiii

xiv Contents
3.5.3 Coherence and Disciplinary Knowledge . . . . . . . . . . . . . . . . . . 55
3.6 OnClarity .................................................. 59
3.6.1 The Importance of Clear Learning Goals . . . . . . . . . . . . . . . . . 59
3.6.2 The InterpretationofLearningGoals ..................... 60
3.6.3 The Importance of Good Alignment . . . . . . . . . . . . . . . . . . . . . 62
3.7 A Knowledge-Rich Curriculum and Student Achievement . . . . . . . . . 68
References ...................................................... 70
4 Concluding Remarks ............................................ 75
References ...................................................... 77
5 Executive Summary ............................................. 79
5.1 How Knowledge Matters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
5.1.1 Knowledge Matters: A Learning Perspective . . . . . . . . . . . . . . 79
5.1.2 Knowledge Matters: A Sociological Perspective . . . . . . . . . . . 80
5.1.3 Knowledge Matters: A Democratic Perspective . . . . . . . . . . . . 81
5.2 Knowledge and the Curriculum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.2.1 EverythingStartswiththeCurriculum ................... 82
5.2.2 Curriculum as a Pendulum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5.2.3 Towards the Best of Both Worlds: A Knowledge-Rich
Curriculum ........................................... 83
5.2.4 A Knowledge-Rich Curriculum and Student
Achievement ......................................... 84
5.3 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
References ...................................................... 85
Appendix: How is Knowledge Remembered? .......................... 89
References ......................................................... 91

Chapter 1
Introduction
Nearly all teachers and other stakeholders in education pursue a common aim: We
want the students whom we teach and guide during their formative years to think
deeply about what we teach them. We want them to be able to go beyond their current
experiences and have a deep understanding of the world. We want to enable them
to thrive and find their path through life, long after their formal education ceases.
We want them to be able to think critically, work together, solve problems, read for
understanding, and perform many other complex tasks. If we want students to be able
to do all this, we should just include it in the curriculum and teach them, right? In this
book, we discuss why this apparently obvious strategy of simply teaching children
how to “think deeply” does not work, and we offer an alternative way forward.
In recent decades, many trends in the curriculum have been observed, some-
times collectively described as a curriculum turn. One of the characteristics of this
turn is the frantic push to encourage skill acquisition with a focus on generic skills
and competencies such as problem-solving, reading comprehension, collaboration,
communication with each other, and so forth (Priestley & Biesta, 2013). Critics
have argued that these trends have downplayed the importance of knowledge in
the new curriculum (Rata, 2012; Wheelahan, 2010; Young, 2007) to the point of
seeing it as either irrelevant or something that can be learned through the act of
practicing these generic skills and competencies. To an extent, these criticisms have
been supported by empirical evidence that shows a reduction in the specificity of
content in curricula (and thus the acquisition of domain-specific knowledge) and a
diminishing emphasis on the importance of knowledge in relation to general skills
and competencies (Priestley & Sinnema, 2014).
The continuing decline in reading comprehension scores, as well as in science
and, more recently, mathematics across several OECD countries (OECD, 2023), has
highlighted the need for a renewed focus on knowledge as a necessary foundation
for teaching and acquiring complex cognitive skills. Additionally, a notable shift has
been observed in the OECD discourse, in which the importance of disciplinary or
subject-specific knowledge is now seen as a crucial fundamental basis for equitable
© The Author(s) 2025
T. Su r ma et a l ., Developing Curriculum for Deep Thinking,
SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-74661-1_1
1

21 Introduction
opportunities (OECD, 2019). This deviates greatly from previous OECD reports that
prioritised generic skills and competencies (Hughson & Wood, 2022). Social realists
(Barrett, 2024), sociological theorists who have emerged as successors of construc-
tivist thinkers (Rata, 2024a), and several cognitive psychologists now agree that a
curriculum rich in domain-specific knowledge is crucial if we hope to achieve equi-
table opportunities for all. In line with the ideas of E. D. Hirsch (2016), they believe
that focusing on rich and broad content knowledge ensures that all students, regard-
less of background, have equal access to a foundational body of knowledge, which
helps mitigating disparities and promotes a more inclusive educational experience.
This book discusses the prominent role of knowledge in how we learn, think,
read, understand, and solve problems. We draw ideas from cognitive psychology,
educational psychology, sociology, and curriculum studies, and combine these ideas
with case studies describing real-life classroom experiences. The publication seam-
lessly aligns with a clearly observable global knowledge revival: various educational
systems are re-evaluating the role of knowledge in their curricula, and in a growing
number of academic and non-academic publications the role of knowledge to promote
equity, unity and progress in a modern society is emphasised. Our goal is therefore
to explain why a knowledge-rich curriculum is the soundest way forward to both
effectively teach knowledge and complex skills in school.
References
Barrett, B. (2024). Rob Moore, social realism, and the sociology of education and knowledge. In
E. Rata (Ed.), Research handbook in curriculum and education, Chap. 5 (pp. 79–87) Edward
Elgar Publishing.
Hirsch, E. D. (2016). Why knowledge matters: Rescuing our children from failed educational
theories. Harvard Education Press.
Hughson, T. A., & Wood, B. E. (2022). The OECD Learning Compass 2030 and the future of
disciplinary learning: A Bernsteinian critique. Journal of Education Policy, 37(4), 634–654.
OECD. (2019). Conceptual learning framework: Knowledge for 2030 concept note. https://www.
oecd.org/education/2030-project/teaching-and-learning/learning/knowledge/in_brief_Knowle
dge.pdf
OECD. (2023). PISA 2022 Results (Volume I): The state of learning and equity in education, PISA,
OECD Publishing.
Priestley, M., & Biesta, G. (Eds.). (2013). Reinventing the curriculum: New trends in curriculum
policy and practice. A&C Black.
Priestley, M., & Sinnema, C. (2014). Downgraded curriculum? An analysis of knowledge in new
curricula in Scotland and New Zealand. In Creating curricula: Aims, knowledge and control
(pp. 61–86). Routledge.
Rata, E. (2012). The politics of knowledge in education. British Educational Research Journal, 38,
103–124.
Rata, E. (2024). Introduction: Social realism, didaktik, and cognitive science in curriculum and
education. In E. Rata (Ed.), Research handbook on curriculum and education (pp. 1–18). Edward
Elgar Publishing.
Wheelahan, L. (2010). Why knowledge matters in curriculum: A social realist argument. Routledge.
Young, M. (2007). Bringing knowledge back in: From social constructivism to social realism in the
sociology of education. Routledge.

References 3
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give appropriate
credit to the original author(s) and the source, provide a link to the Creative Commons license and
indicate if changes were made.
The images or other third party material in this chapter are included in the chapter’s Creative
Commons license, unless indicated otherwise in a credit line to the material. If material is not
included in the chapter’s Creative Commons license and your intended use is not permitted by
statutory regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder.

Chapter 2
How Knowledge Matters
Abstract We, in education, all have a common aim: We want students to be able to
think deeply about what we teach them, go beyond their current experiences, and have
a deep understanding of the world. We want to enable them to think critically, work
together, solve problems, read for understanding, and carry out complex cognitive
tasks. If we want students to be able to do all this, we should just include itt in the
curriculum and teach them, right? In this chapter, we discuss why this apparently
obvious strategy of simply teaching children how to think deeply does not work,
and offer an alternative way forward. This chapter discusses the prominent role of
knowledge in how we learn, think, read, understand, and solve problems. Insights
from cognitive and educational psychology, sociology, and curriculum studies are
used to underpin the current knowledge revival that is widely being observed in
education.
Keywords Knowledge-rich ·Education ·Knowledge acquisition ·Complex
cognitive skills ·Democratic citizenship
“What we know is a drop
what we don’t know is an ocean” (Isaac Newton).
What you know determines what you see (Kirschner, 1991). Another and possibly
more prosaic way of saying this is: Knowledge begets knowing. The more extensive
one’s knowledge-base is in terms of both its breadth and its depth the more easily
new knowledge is acquired and remembered (Alexander et al., 1994; Ausubel, 1968;
Shapiro, 2004). Knowledge is also essential for carrying out the complex cogni-
tive skills such as critical thinking (you think critically about something) problem-
solving (you solve problems in something) and reading comprehension (you compre-
hend something written about something). The more robust one’s knowledge-base
the more seamlessly and efficiently these complex cognitive skills—which require
students to “think deeply” and are precisely those that teachers aim to develop in
their students—are acquired and can be carried out. The subsequent chapter describes
© The Author(s) 2025
T. Su r ma et a l ., Developing Curriculum for Deep Thinking,
SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-74661-1_2
5

6 2 How Knowledge Matters
the significance of knowledge from cognitive sociological and democratic perspec-
tives. These different perspectives draw on various research traditions each with its
own procedures and standards for what constitutes a convincing argument. What is
presented is therefore a mixture of scientific and humanities approaches all serving
the objective of illustrating the critical role of knowledge in promoting deep thinking.
2.1 Knowledge Matters: A Learning Perspective
2.1.1 A Basic Understanding of Human Cognitive
Architecture
We need to examine our cognitive architecture to understand where knowledge fits
within human cognition. Some forms of knowledge appear to be acquired effortlessly
due to our evolutionary development over numerous millennia. Such knowledge,
resulting in skills like communicating with those around us, speaking our mother
tongue, recognising facial expressions and physical signals, recognising others,
understanding the relation between an incline and things rolling down from it …
is recognised by evolutionary psychologists as being biologically (or evolutionarily)
primary knowledge (Geary & Berch, 2016). In contrast, a second category consists
of knowledge that is more recent in nature. It was not until a couple of hundred or
even thousand years ago that most people in a few societies learned to read and write,
solve algebraic problems, and engage in discussions about geographical, scientific,
political, cultural, and historical phenomena. This category of knowledge is known as
biologically (or evolutionarily) secondary knowledge and, unlike our innate ability
to seemingly effortlessly acquire the first category (without many/most of them a
person could not live long enough to procreate), we lack a natural mechanism to
just as effortlessly assimilate the second—more cultural—category through mere
exposure. It must be consciously taught and effortfully learned, building upon, yet
distinct from biologically primary knowledge. Schools were established to impart
this biologically secondary knowledge that is rarely acquired spontaneously, as it
is vital for functioning in contemporary societies. When we speak of knowledge
in educational systems, we mainly refer to biologically secondary knowledge, and
cognitive psychologists have been investigating how human cognitive architecture
processes this information for many decades.
Broadbent (1958) is considered one of the first scientists to use an information
processing metaphor to portray the human attentional processing system. He postu-
lated, around the same time as Miller (1957; The Magical Number Seven, Plus or
Minus Two), that humans have a limited capacity to process information and, due
to this limited capacity, a selective filter—acting like a bottleneck—is needed for
information processing. He compared human information processing capacity to a
limited amount of information that can be conveyed through a given channel at a

2.1 Knowledge Matters: A Learning Perspective 7
given time: “if we send a Morse code with a buzzer, we cannot send a dot and a dash
at the same time, but must send them successively” (Broadbent, 1958,p.5).
Shortly thereafter, Atkinson and Shiffrin (1968) put forward a multi-store model
of memory composed of a sensory memory where information from all of our senses
enters memory; a short-term memory (STM) which receives and retains input from
both the sensory memory and the long-term store; and finally this long-term store,
where information that has been repeatedly rehearsed in the short-term store is
permanently stored.
Subsequently, Baddeley and Hitch (1974) proposed a new memory model that
challenged the prevailing view of short-term memory. They suggested that short-term
memory is composed of multiple, distinct components that work together, allowing
us to hold information in our minds and manipulate it. This is what became known
as working memory (WM). In their original work, they spoke of a verbal and visual
store, but more recent research (e.g., Baddeley & Andrade, 2000) has expanded this
to include other memory stores such as olfactory, gustatory, and tactile. Baddeley
and Hitch also discussed the role of long-term memory in working memory, noting
that it plays a crucial role in the ability to hold and manipulate information over
longer periods of time. They suggested that working memory and long-term memory
are separate but interdependent systems. This led to a widely used and functionally
practical memory model, which is simplified in Fig. 2.1 (based on Willingham, 2021).
Working memory is essentially the cognitive workspace in which information
is temporarily stored and acted upon. That is, it is the system that supports our
capacity to “keep things in mind” when carrying out complex tasks. For instance,
when pondering the question: “What similarities exist between a raincoat and a
notebook?” we would extract pertinent details about raincoats (e.g., water-resistant,
worn outdoors, protective gear) and notebooks (e.g., bound pages, used for writing,
portable) from long-term memory. The next step would involve assessing these
characteristics for any commonalities (Willingham, 2019). We carry this out in our
working memory. Working memory capacity is notably finite, having a capacity for
only four to seven unconnected elements at any given time. We cannot hold a lot in
Fig. 2.1 A simple representation of human memory (based on Willingham, 2021)

8 2 How Knowledge Matters
our working memory, and even the small amount we can hold does not remain there
for a very long time (i.e., 3–20 s) if nothing is done with it. Imagine being asked to
identify a common attribute among a raincoat, a notebook, a teaspoon, a guitar, and
a refrigerator. Our working memory could possibly retain the names of these five
items, but supporting details for each item and the cognitive resources to evaluate
them collectively would exceed our processing limitations.
Let’s look at a second example that illustrates the constraints of working memory.
Imagine you have to learn the chemical interactions below:
2NaCN+H2O+CO2=Na2CO3+2HCN
2H +CNO2CNa2O:NaH3+2CCN2O
You are exposed to these formulas for 30 s each. After one minute, they are hidden,
and you are asked to write them down. How well did you do? Well, it probably
depends. This experiment, a modern-day version of de Groot (1965) studies with
chess masters, was conducted with experts and non-experts in chemistry (Zhilin &
Tkachuk, 2013). After respondents in both groups were exposed to the equations for
30 s, experts immediately recognised that the first equation represented a reaction in
which sodium cyanide (NaCN) reacts with water (H2O) and carbon dioxide (CO2)to
produce sodium carbonate (Na2CO3) and hydrogen cyanide (HCN). The experts also
recalled real chemical equations better than the novice participants, but experts and
novices had no significant difference in recalling the fake equation. Novices tended
to remember both real and fake equations symbol-by-symbol from left to right, with
increasing mistakes in the same order. On the other hand, experts remembered the real
equation as a whole, and could chunk (combine smaller, unitary bits of information
into larger and more meaningful ones) some chains in the fake sequences, resulting
in slightly better memory.
These findings support the idea that experts can chunk information based on the
knowledge in their long-term memory and can see patterns in new situations. They
combine (or “chunk”) smaller bits of knowledge into a single knowledge unit. This
chunking (combining smaller units of information into larger ones) is a function
of our prior knowledge in our long-term memory. Long-term memory, thus, assists
working memory while thinking. It is an expansive repository within our cognitive
structure that possesses a seemingly limitless capacity for storing information. It
facilitates the consolidation of discrete elements into coherent wholes (i.e., chunks),
thereby economising scarce working memory resources. The first chemical equation
probably only contains one chunk of information for the expert. This frees cognitive
space from working memory—a cognitive shortcut—to consider other aspects of the
task. It makes learning look easier as the information needed to carry out the task pops
up seemingly effortless. What you already know does not require much mental effort,
so experts with vast amounts of domain-specific knowledge can tackle new problems
in their domain of expertise more efficiently (i.e., with more speed and accuracy)
than novices do (Willingham, 2021). The key words here are ‘in their domain’. A
good chess player is not a good checkers or go-player, just as the chemists in the

2.1 Knowledge Matters: A Learning Perspective 9
experiment cannot do this when dealing with a geology problem let alone a problem
dealing with a language they do not speak. Their skill is not generic, but rather
specific to particular subject matter—what psychologists call ‘domain-specific’.
Knowledge is stored in long-term memory in cognitive structures or schemas.
They can be seen as structures of organised and interconnected knowledge elements
comprising concepts, words, and ideas. Schemas can also consist of other schemas,
much like how the concept of ‘a tree’ can be explained in terms of its roots, trunk,
branches, leaves, and fruits. Each of these terms can also be broken down further, such
as the veins, chlorophyll, and cells of a leaf. Renn (2020) refers to these complex
interdependencies as the ‘architecture of knowledge’. However, schemas are not
permanently fixed. We can also start from ‘inside the box’ and expand it in a different
direction. For instance, starting from the concept of chlorophyll, one may discover
examples such as green pasta or spirits, in which chlorophyll is used as a colouring
additive (E140). In other words, knowledge can be organised into various hierarchies,
forming complex schemas of interconnected ideas, and serve as conceptual coat
hangers or anchors for the organisation of knowledge and learning new ideas (Hattie,
2023).
2.1.2 How Can Prior Knowledge Facilitate Better Learning?
Possessing knowledge and skills in long-term memory frees up valuable space in
working memory to tackle more complex cognitive thinking tasks such as problem-
solving, critical thinking, and reading comprehension, as discussed below. If you have
ever wondered why we have elementary school students memorise the multiplica-
tion tables, drill verb conjugations, perfect their spelling, expand their vocabulary,
and acquire background knowledge, the following will help you to understand. It’s
all about automaticity. Seemingly counterintuitively, the best ways to become profi-
cient in a skill often do not resemble the skill itself (Wiliam, 2018). For instance, if
someone wants to become proficient at playing a musical instrument like the piano,
they might find that simply playing the piano for hours on end isn’t the most efficient
way to improve. A novice piano player might first want to train and automate certain
hand movements or learn about music theory. Outside education, this subtle under-
standing of the importance of automaticity is well understood and is often seen as
a precondition for true mastery. How many passionate young football (in America:
soccer) players meticulously practice isolated dribbling techniques to succeed on the
pitch? And how many actors or musicians memorise their lines or riffs to be able to
improvise on stage? Beyond improving on the practiced task, this approach has the
added benefit of conserving ‘mental bandwidth’ to do more. And it goes even further
than that. Try to study the following three rows of twelve digits.
Row 1 :610894121158
Row 2 :106614921815

10 2 How Knowledge Matters
Row 3 :198520192023
Which row do you remember best? Let’s take a guess. You found row 1 to be
the hardest to learn. Row 3 was the easiest to learn because you possibly saw it as
referring to recent years. Row 2 could also be easy to remember, yet only if you
have sufficient background knowledge of history: 1066 was the year of the Battle
of Hastings; in 1492 Columbus ‘discovered’ America, and in 1815 Napoleon met
his Waterloo. However, if you do not possess this background knowledge, Row 2
would appear as difficult as Row 1. Knowledge in your long-term memory not only
reduces the complexity and difficulty of acquiring new knowledge (i.e., turning added
information into knowledge), it also seems easier to do so, while simultaneously
enhancing retention. Whereas the numbers from Row 1 might already be fading from
memory, those from Rows 2 and 3 are more likely to remain embedded in memory.
That is because new information that can be connected to prior knowledge tends
to stick around longer. The slower you forget, the longer you retain. Psychologists
have spent decades studying the processes involved in slowing down forgetting and
effectively storing knowledge in long-term memory. They have identified a range of
learning strategies, the detailed exploration of which lies beyond the scope of this
book. For a brief introduction, see Appendix A.
If prior knowledge supports thinking, makes learning easier, and leads to more
durable learning, it is tempting to conclude that our children simply need to learn a
vast amount of knowledge. Right? The more prior knowledge, the better. Yet, this is
the point at which we must proceed with caution. Whether and how prior knowledge
influences learning depends on the nature of that prior knowledge itself (Brod, 2021).
Knowledge alone does not lead to better learning. To be effective, prior knowledge
must meet several important criteria.
First, it must be activated. For example, imagine students learning about the
formation of the Himalayas. Potentially relevant prior knowledge might include
understanding what a mountain range is and how plate tectonics play a role in this,
knowing that the Himalayas are located in Asia at the point where two plates collide,
and that Asia is a continent that includes India and most of Russia, among other
facts. Some children might even have a basic understanding of concepts such as
shifting tectonic plates and continental drift. The issue of prior knowledge not being
activated by learners has been extensively researched, particularly in children, who
often have not yet become resourceful in using cognitive control strategies to use
their prior knowledge strategically. On the other hand, well integrated knowledge
will become active on its own. In essence, it is not enough for prior knowledge to
be available; it must also be (consciously or unconsciously) activated and applied to
guide the learning process. The teacher’s role is critical here, tasked with mapping out
what children should already know to fully comprehend the content of a new lesson
and activating it, for example, with pre-questions (retrieval practice) or advance
organisers.
Second, even if learners activate some prior knowledge, it must also be relevant
to the learning task to be beneficial. Students might know about India’s extensive
colonial history with Britain and that the British set up hill stations in the foothills of

2.1 Knowledge Matters: A Learning Perspective 11
the Himalayas, but this information is not really helpful when trying to understand
geological formations in the Himalayas. Students might even hold misconceptions
(i.e., faulty beliefs) about plate tectonics, such as wrongly assuming that each conti-
nent rests on a separate tectonic plate, with continental boundaries aligning with
plate edges. This could make it harder for them to grasp the role of India in the
northward thrust that continues to elevate the Himalayas today. Irrelevant and faulty
prior knowledge might even hinder subsequent learning (Simonsmeier et al., 2022).
Finally, prior knowledge should ideally be congruent with the new information
even when activated and relevant. For instance, within the geography curriculum,
certain words such as plate, drift, and mantle possess technical definitions that may
prove challenging for students to comprehend because of the presence of alterna-
tive, common-sense or common-language meanings of those words that significantly
deviate from their technical connotations. The greater the necessary reorganisation
of existing knowledge, the more challenging it can be for learners to integrate new
information into existing knowledge schemas. While higher congruency between
prior knowledge and new information usually enhances learning of the new infor-
mation, it has been demonstrated that highly incongruent new information can also
be effectively learned, particularly when it triggers a significant level of surprise in
learners (Brode, 2021). Thus, the complex nature of prior knowledge underscores
that its impact on learning depends on more than simply the quantity of knowledge
available. However, if prior knowledge is activated, relevant, and congruent, then its
impact on learning can be significant.
2.1.3 Why Complex Cognitive Skills Require Knowledge
While knowledge storage and schema building in long term memory are important,
they are not enough. We are greedy. Education should also have the ambition to
engage with this knowledge and foster the acquisition and use of complex cognitive
skills in students such as critical thinking, problem solving, and reading compre-
hension. However, the question arises as to whether critical thinking or any of these
complex cognitive skills can be generically taught across or without reference to
specific knowledge domains. If you ask historians to describe what critical thinking
is, they say very similar things to what mathematicians say. Hence, it is natural to
think that they are the same skill. In contrast, they are in fact a collection of super-
ficially similar skills (e.g., evaluating the relevancy of certain things or determining
the validity of an argument) and/or procedures (i.e., the steps to take in carrying out
research) that rely on different underlying cognitive processes. While it should be
acknowledged that the idea of teaching generalised critical thinking skills is attrac-
tive, we should not consider those processes as a collection of skills that can be
employed at any given time or in any given context. Those who have endeavoured to
teach complex skills such as critical thinking as a separate course in the curriculum
have operated under the assumption that it is a skill akin to driving a car, and once
acquired, can be applied in any given situation. They assumed students who learned

12 2 How Knowledge Matters
to think critically in history lessons about, for instance, the role of the French revolu-
tion in nation-building in Europe, would transfer those critical thinking skills to novel
situations, such as critical thinking about zero-emission policies to combat global
warming. Or they assumed that students who learned to solve open-ended problems
in physics would be able to transfer that skill to solve problems in psychology. The
steps seem similar or identical, but cognitive science research has revealed that crit-
ical thinking or other complex cognitive skills are not of that nature. The processes
of thought are intricately intertwined with the content of the thoughts themselves; in
other words, with domain-specific knowledge.
In a landmark experiment, researchers presented participants with a scenario illus-
trating an ill-defined problem wherein an X-ray, capable of treating a tumour, also
posed the risk of damaging a lot of healthy tissue:
Suppose you are a doctor faced with a patient who has a malignant tumor in his stomach.
It is impossible to operate on the patient, but unless the tumor is destroyed the patient will
die. There is a kind of ray that can be used to destroy the tumor. If the rays reach the tumor
all at once at a sufficiently high intensity, the tumor will be destroyed. Unfortunately, at this
intensity the healthy tissue that the rays pass through on the way to the tumor will also be
destroyed. At lower intensities the rays are harmless to healthy tissue, but they will not affect
the tumor either. What type of procedure might be used to destroy the tumor with the rays,
and at the same time avoid destroying the healthy tissue? (Gick & Holyoak, 1983, pp. 3)
Participants were thus tasked with determining how to use the X-ray to eliminate
the tumour, a problem that only a minority solved within 20 min. Subsequently,
another group was exposed to a military scenario mirroring this dilemma, but it was
solvable in the same way. In this scenario, a general plans to seize a fortress situated at
the heart of a country. The fortress is accessible by several roads, but each is heavily
mined. While small groups can pass the roads safely, a large force would detonate the
mines. To overcome this, the general splits his army into smaller units, sends each
along a different road, and has them converge on the fortress at the same time. The
“convergence” solution to the military problem is analogous to the X-ray problem
(i.e., scattering the forces to avoid collateral damage and having forces converge at
the point of attack). Despite reading this story immediately prior to addressing the
medical problem, they failed to perceive the analogy with the convergence solution, as
depicted in Fig. 2.2. Remarkably, solution rates surged when the story was explicitly
mentioned (Gick & Holyoak, 1983).
This underscores the idea that employing the analogy in a novel situation was
not the main challenge; rather, the difficulty lies in recalling it and seeing its need or
Fig. 2.2 Schemes that
illustrate the principle
underlying the convergence
solution

2.1 Knowledge Matters: A Learning Perspective 13
usefulness. These findings offered crucial insights into teaching critical thinking. The
challenge in transferring critical thinking skills lies in the fact that domain-specific
examples on how to think critically should be offered to students (they will act as
worked examples for future similar tasks), and that they are archived in long-term
memory, and resurface only using specific triggers.
The ability to think critically about open-ended problems such as the radiation
problem described above is facilitated by vast knowledge in the specific area. Knowl-
edge plays a role in solving these problems in at least three ways (Willingham,
2019). First, as described earlier, knowledge from long-term memory assists working
memory because of the experts’ ability to chunk new information into new or already
existing coherent wholes. Recognising a situation similar to a previously encoun-
tered one helps you identify areas of strength and weakness, thereby freeing up
valuable thinking space in working memory. Second, the recognition process of
the open-ended problem (‘ah, this is a radiation problem’) can still be applied to
components of a yet more complex, open-ended problem. Complex critical thinking
may involve the application of multiple simpler solutions from memory, which can
be combined when solving new, more complex problems. The final way in which
knowledge can contribute to critical thinking is by enabling the individual to employ
thinking strategies in combination with domain-specific knowledge, stored in long-
term memory. When discussing the recognition of underlying structures such as in the
radiation problem, the issue arose from having an effective thinking strategy stored
in memory, yet failing to retrieve it due to a lack of recognition of its relevance for
the particular situation. However, some situations that require critical thinking can
be easily identified. For instance, we can teach graduate students in a certain domain
to evaluate the logic behind scientists’ arguments and prompt them to assess whether
students can infer causal claims with the scientific methodology used. Those graduate
students should have no difficulty recognising the type of problem they are facing and
may have already stored the correct thinking strategy in long-term memory, in this
case combined with some statistical knowledge. They know what needs to be done,
yet they might still face the problem of not having the necessary domain-specific
knowledge, which may hinder their ability to utilise the strategy.
Complex cognitive skills such as critical thinking are therefore not a collection of
skills that can be employed at any given time or in any given context. They should be
seen as a form of thought that requires knowledge with which to engage. The same
applies to the other complex cognitive thinking skills to a greater or lesser extent.
It would be amazing if we could teach our students to solve open-ended problems
in geography in a way that would also improve their ability to solve open-ended
problems in mathematics, yet this is not how our brains work. Problem-solving in
geography requires students to learn specific geographical content knowledge. No
matter how much we train students to solve math problems or teach them Latin, it
does not make them better ‘problem-solvers’ or ‘logical thinkers’ in other domains
such as in a natural science (De Bruyckere et al., 2020; Thorndike, 1923). It remains
clear that without relevant prior knowledge, cross-discipline learning is not what
many in education once hoped it would be. Interestingly, the PISA 2022 survey
included Creativity as an additional domain, yet it revealed a high correlation between

14 2 How Knowledge Matters
mathematical knowledge and creativity, indicating a strong relationship between
higher-order skills and domain knowledge (OECD, 2024; Ward & Kolomyts, 2010).
However, this does not imply that problem-solving without prior knowledge is
consistently ineffective. At times, it can be beneficial to start with problem-solving
in a particular topic to identify what students already know and need to learn and
motivate them to dig deeper. This is often the case in goal-free or goal-nonspecific
problems where learners are given information (objects, their mass, angle of incline,
friction) and then are asked to determine what they can do with it (Ayres, 1993;Van
Merriënboer & Kirschner, 2017). Take the following example from Van Merriënboer
and Kirschner (2017, p. 73):
Usually, learners receive goal-specific problems, such as “A car with a mass of 950 kg
accelerating in a straight line from rest for 10 seconds travels 100 meters. What is the final
velocity of the car?” This problem could easily be made goal nonspecific by replacing the
last line with ‘Calculate the value of as many of the variables involved here as you can.’
Here, the learner would calculate the final velocity, acceleration, and force exerted by the
car at top acceleration. And if the word ‘calculate’ was replaced by ‘represent,’ the learner
could also include graphs and the like. Nonspecific goal problems invite learners to move
forward from the givens and to explore the problem space, which may help them construct
cognitive schemas.
This can then be followed by more targeted teaching and knowledge building, and
finally returning to problem-solving to reinforce their understanding (Kapur, 2008).
2.1.4 Reading Comprehension
“Reading is the basis for the acquisition of knowledge, for cultural engagement, for
democracy, and for success in the workplace” (Castles et al., 2018, p. 5). Moreover,
its importance in education cannot be overstated as it is essential for further learning
in all subjects. At the same time, reading is one of the most complex mental acts a
person can do and entails the development of cognitive thinking skills in five areas, the
so called ‘big five’: phonics, phonemic awareness, vocabulary, fluency, and language
comprehension (National Reading Panel, 2000; National Research Council, 2000;
RAND Reading Study Group, 2002; Pearson & Cervetti, 2015). In the following
paragraphs it will become clear to you as a skilled reader just how many complex
processes are being executed in your mind while you read this book, and why this is
important when teaching reading to students.
The schematic model in Fig. 2.3 (Willingham, 2017) summarises the complexity
of the cognitive processes involved in reading at roughly three highly interconnected
levels: (1) letters and phonemes; (2) words; and (3) sentences, paragraphs, and full
texts.
When teaching reading, the most effective programs first address the develop-
ment of alphabet knowledge, phonemic awareness, and oral language (i.e., listening
and oral fluency), the so-called prereading skills. Most children already possess
relatively developed spoken-language skills, including knowledge of the meanings

2.1 Knowledge Matters: A Learning Perspective 15
Fig. 2.3 Model of reading (Willingham, 2017)
of many spoken words, when they start to learn how to read (Castles et al., 2018).
Subsequently, a focus on explicit and implicit vocabulary instruction, comprehension,
and phonics instruction with repeated opportunities to read—silently and aloud—
to develop fluency is considered the most powerful combination for early reading
instruction (Hattie, 2023). The Reading Rope, a visual representation created by
Hollis Scarborough, helps us understand the complex processes involved in how the
brain learns to read (see Fig. 2.4). The two meta-strands, language comprehension
and word recognition, once again contain their own subsets of distinct components.

16 2 How Knowledge Matters
In the case of language comprehension those are background knowledge, vocabu-
lary, language structures, verbal reasoning and literacy knowledge, and with regard to
word recognition respectively phonological awareness, decoding and sight recogni-
tion are involved. Language comprehension and word recognition are interconnected
and interdependent, so when students progress toward fluency with sufficient prac-
tice and instruction, word recognition becomes increasingly automatic, and language
comprehension becomes increasingly strategic (Scarborough et al., 2009).
With sufficient mastery, the initially heavy demand on students’ working memo-
ries while reading is gradually reduced. This means they can commit more cogni-
tive resources to comprehending what they are reading, that is, the complex mental
processes involved in constructing meaning from and in individual sentences, across
paragraphs, and finally in full texts. Principles similar to those in reading also apply
Fig. 2.4 Reading rope (Scarborough et al., 2009)

2.1 Knowledge Matters: A Learning Perspective 17
to arithmetic fluency and math problem solving as among others David Geary (2011),
and Xin Lin and Sarah Powell (2022) have shown in their work.
In what follows, we describe how knowledge elements play a role at each of
the interconnected levels as described in the overall Model of Reading depicted in
Fig. 2.3, to facilitate the gradual development of those complex reading processes
that distinguish successful from struggling readers, and how background knowledge
plays a particularly important role in deep reading comprehension at the level of
sentences, paragraphs, and full-texts.
2.1.4.1 Letters and Phonemes
Letter knowledge and phonemic awareness are the first requirements for learning how
to decode text in alphabetic languages (Ehri et al., 2001; Ruan et al., 2018), namely
to be able to “distinguish one letter from another, hear individual speech sounds,
and know the mapping between letters (and letter groups), and speech sounds”
(Willingham, 2017 p. 47). Consequently, an important component of initial reading
instruction is effectively teaching letters and awareness of individual speech sounds,
so that students’ knowledge of the relationships between speech sounds and (groups
of) letters (the alphabetic principle) can become increasingly automatised (Hattie,
2023). With sufficient practice, students can then apply it through phonics; that is, use
their knowledge of the relationships between speech sounds and (groups of) letters
to decode text, and read familiar and unfamiliar words.
2.1.4.2 Words
Word-specific knowledge. While initially very demanding, with extensive practice
students can gradually automate the letter-sound translation process (sounding a
word out), and reduce the demands on their working memories. As the comprehen-
sion processes in reading in the next phases are so demanding, it is very impor-
tant that readers can free up enough space in working memory by making reading
faster and easier. At the word level, this requires word-specific knowledge (Perfetti,
2007), which implies that readers need to develop very strong relationships between
word sounds, spellings, and meanings (see the middle part of Willingham’s model,
Fig. 2.3), which in turn will provide them with nearly automatic word recognition.
Extensive practice in reading individual words and later sentences and texts, as well
as explicit spelling and morphology instruction (Graham & Santangelo, 2014) and
explicit vocabulary instruction, can boost this process. That way, students’ reading
fluency is built over months and years.
Vocabulary breadth and depth. Vocabulary knowledge in the broad sense is very
important, as both vocabulary breadth (i.e., knowing many words) and depth (i.e.,
having many and strong connections between words) matter to reading comprehen-
sion (Elleman et al., 2009; Nation & Snowling, 1998; Ouellette, 2006). Deep vocab-
ulary knowledge not only includes knowing the meanings of words (i.e., semantics),

18 2 How Knowledge Matters
their structure (i.e., morphology), spelling, and use (i.e., grammar), but also links to
other words (i.e., word/semantic relationships).
In terms of vocabulary breadth, research has shown that readers need to know up
to 95 percent of the words in a text to understand it at a general level, and even 98
percent to really comprehend it (Carver, 1994; Hsueh-Chao & Nation, 2000; Schmitt
et al., 2011). If this so-called coverage drops to 80 percent, readers can at best only
understand the overall gist of a text (Nation, 2001), and most readers would find it so
difficult to extract the gist that they would likely give up. Sometimes, the meaning
of unknown words can be derived from the context, but only to a limited extent.
To do so, readers would already need to have a relatively large vocabulary, and the
coverage in the specific text they read would need to be nearly 98 percent, or only
one unknown word for every 50 known words (Hsueh-Chao & Nation, 2000; Laufer,
1992; Laufer & Yano, 2001). Moreover, too much task-switching between problem-
solving and comprehension during reading occupies working memory resources
required for understanding and can therefore interrupt the flow of reading (Csik-
szentmihalyi, 1990; Kirschner & De Bruyckere, 2017; Willingham, 2017). Regular
interruptions make reading less fluent, more difficult, and less enjoyable. For the
same reason, looking up the meaning of unknown words in, for instance, online
glossaries is only of limited use, and they have the additional disadvantage that word
definitions are offered in just one context, whereas the meaning of words is precisely
very sensitive to the context in which it appears (Willingham, 2017).
The importance of vocabulary depth is somewhat more difficult to understand,
but we will try to illustrate it with an example. Students may know that a scorpion
is an animal with a pair of grasping pincers and a long tail. If that is all they know,
do they then know the word ‘scorpion’? Yes, but only in a shallow way. Deeper
knowledge of the word would also invoke connections to concepts like ‘predatory’,
‘the desert’, ‘stinger’, and ‘venomous’. This is important, as different facets can be
required for understanding in different contexts, and authors often omit information
(i.e. background knowledge) they expect their readership to know. So if students
only know that a scorpion is an animal with a pair of grasping pincers similar to a
crab’s that has a long tail, a precautionary message like ‘Don’t pick up a scorpion,
and definitely watch out for its tail.’ might inform them to a certain extent. However,
someone who also knows that it has a venomous stinger, and uses it not only to hunt,
but also to defend itself, will be much better informed before approaching a scorpion.
This example shows how words are situated in meaning networks, and how they
activate related words. That depth of your vocabulary knowledge helps you fill in
the ‘gaps’ between sentences and paragraphs, as authors implicitly expect you to
possess certain background knowledge to understand the ideas conveyed in the texts
they write, yet they do not explicitly include it all. That would simply render most
texts extremely long and unreadable. Besides the richness of those word relationships,
also the speed you can access them with facilitates reading (Oakhill et al., 2012).
As mentioned above, that speed is determined by the strength of the relationships
between word sounds, spellings, and meanings, also known as readers’ word-specific
knowledge (Perfetti, 2007).

2.1 Knowledge Matters: A Learning Perspective 19
Sentences, paragraphs, and full texts. When it comes to deep reading compre-
hension at the sentence, paragraph, and text level, the construction-integration (CI)
model of text comprehension (Kintsch, 1998; Kintsch & van Dijk, 1978) remains
the most detailed interactive model to describe the mental processes in the minds of
readers (integrated in the lower part of Willingham’s model; Fig. 2.3). It describes
how the words and syntax are situated in a text’s surface structure, from which
readers later create sentence representations (also called propositions). Readers then
construct a text-base model (or idea-web; Willingham, 2017) by connecting these
propositions in the text’s main idea. This text-base model represents quite literally
‘what the text says’ and is subsequently inserted in their working memories. Besides
sufficiently automated basic reading processes described above at the letter, phoneme,
and word level, students also need knowledge of syntactic rules and text structure to
facilitate this mental construction of the main idea of the paragraph or text they read.
However, this main idea of the text alone is not enough for deep understanding.
This is where background knowledge comes into play. Only through the integration
of the text-base with relevant background knowledge and experiences from long-term
memory (readers’ pre-existing schemas) can readers truly come to a deeper under-
standing of a text. The mental model that is subsequently created is called the situa-
tion model (Zwaan & Radvansky, 1998), and is a reader’s dynamically constructed
detailed mental representation of the text. Besides readers’ overall language and
decoding ability as described, now the breadth and depth of their background knowl-
edge, including vocabulary, comes into play, which differs among students, thus
leading to distinct situation models for each reader. Four intersecting dimensions
of background knowledge can thereby be distinguished (McCarthy & McNamara,
2021):
(1) amount (how many relevant concepts readers already know);
(2) accuracy (how correct the knowledge is that readers already possess);
(3) specificity (how related their knowledge is to the information in the text); and
(4) coherence (how interconnected the knowledge is that readers already possess).
The good news is that situation models are also cumulative; so, if the same reader
becomes more knowledgeable about a topic, the schemas and situation model will
evolve (Kintsch, 1998). However, if students lack the necessary background knowl-
edge to integrate the text base, a less effective situation model results, and they
consequently experience more difficulty understanding a text (Kendeou & Van Den
Broek, 2007).
The previous sections have shown that “while word knowledge speeds up word
recognition and thus the process of reading, world knowledge speeds up comprehen-
sion of textual meaning by offering a foundation for making inferences (Hirsch, 2003,
p. 12).” Let us now more closely consider how background knowledgefacilitates deep
reading comprehension.
The Importance of Background Knowledge. A review study on experimental
research with primary-school aged children on the role of background knowledge in
reading comprehension (Smith et al., 2021) has confirmed the critical importance of
both reading ability (the upper part of Willingham’s model, Fig. 2.3) and background

20 2 How Knowledge Matters
knowledge (the lower part) for deep reading comprehension. It was found that higher
levels of background knowledge on a topic, both in terms of quantity and quality,
consistently lead to better text comprehension in both high- and low-ability readers,
and that increased background knowledge impacts reading comprehension differ-
ently in students with distinct reading ability. Highly knowledgeable students with
low reading ability can even compensate for the latter at the level of the text-base
model and improve overall comprehension of a text (Recht & Leslie, 1988), but still
experience some difficulties in making inferences at the level of the situation model.
On the other hand, increased knowledge in students with high reading ability operates
more directly at the level of the situation model, deepening understanding even more
so than in the case of high-knowledge low ability readers. In sum, these results show
that background knowledge is very important to achieve deep text comprehension
besides well-developed reading ability (see also van Bergen et al., 2018,2021).
We can now easily see from the previous sections that students’ deep reading
comprehension won’t improve unless we also pay serious attention to building their
background knowledge, or “word and world knowledge” (Hirsch, 2003). Yet in
reading instruction, despite the fact that deep reading (and listening) comprehen-
sion requires students to make inferences that depend heavily on background knowl-
edge, much teaching time is devoted to generic reading strategy instruction depicted
as ‘inferencing skills’, such as finding the main idea of a text based upon signal
words, to boost reading comprehension (see Sect. 2.2 for a broader discussion on
the origin of these ideas). However, besides the clear initial value in practicing these
comprehension strategies (Hattie, 2023; Willingham & Lovette, 2014), the same
research base has equally shown that after an initial surge, the effects of reading
strategy instruction on students’ reading comprehension quickly reach a plateau,
and have little further impact (Elleman, 2017; Rosenshine & Meister, 1994; Stevens
et al., 2019; for a full overview see Willingham, 2023). That is because the goal of
comprehension strategies is to activate students’ background knowledge. However,
if the relevant background knowledge is lacking, conscious comprehension strate-
gies cannot activate it. Recent research has highlighted that the effects of reading
strategy instruction are therefore significantly strengthened by instruction in back-
ground knowledge (Peng et al., 2023), and that the relation between knowledge and
reading is indeed bidirectional and positive throughout the elementary years: in other
words “knowledge begets reading, which begets knowledge” (Hwang et al., 2023).
A distinct approach to reading instruction therefore argues that, besides a focus
on fluent reading ability, more content-rich instruction time in school should be dedi-
cated to the well-thought out and balanced accumulation of background knowledge
to allow better reading comprehension (Cabell & Hwang, 2020; Cervetti & Hiebert,
2019; Hirsch, 2003, Hirsch, 2016; Hwang & Duke, 2020; Neuman et al., 2014;
Willingham, 2006; Willingham, 2017; Willingham & Lovette, 2014). As described
in the previous section, it is important to underline, however, that building back-
ground knowledge “[…] is not just accumulating facts; rather, children need to
develop knowledge networks, comprised of clusters of concepts that are coherent,
generative, and supportive of future learning in a domain” (Neuman et al., 2014,
p. 147). Reading and listening to different expository and narrative texts on the

2.2 Knowledge Matters: A Sociological Perspective 21
same subject for extended periods of time, and talking about the information and
concepts they contain, can boost reading comprehension and vocabulary in the class-
room (Hirsch, 2003; Wright et al., 2022). This could be particularly helpful for
disadvantaged students, who depend mostly on schools to be exposed to advanced
vocabulary and rich content knowledge (Hart & Risley, 2003; Hirsch, 2006; Will-
ingham, 2017), whereas more advantaged students might improve more rapidly
thanks to the language boost and solid knowledge base they receive outside the
school environment, the so-called Matthew effect (Kaefer et al., 2015; Pfost et al.,
2014; Rigney, 2010; Stanovich, 1986). Moreover, the often challenging transition for
students from ‘learning to read’ to ‘reading to learn’ from the fourth-grade onwards
is often associated with the fact that, besides problems related to coding and fluency
skills (Goodwin, 2011), particularly disadvantaged students might lack sufficient
background knowledge to really grasp the meaning of the expository texts they
increasingly need to read in school to learn about all kinds of important topics in
different subjects (Chall & Jacobs, 2003; Willingham, 2017). These text types are
particularly demanding, as their informative nature builds on readers’ knowledge of
specific topics (Beck & McKeown, 1991). A common knowledge base, built system-
atically and cumulatively in school from an early age onwards, could address many
of these challenges, while at the same time ensuring deep learning experiences for all
students, in line with the findings from cognitive psychology research as described
above.
Up until now we have focused on the importance of knowledge for learning and
the acquisition of complex cognitive skills such as critical thinking and reading
comprehension. In what follows, we will discuss how the current situation came
about with reflections of a sociological nature on the role of knowledge in education
over the years (Sect. 2.2), followed by an account of its importance from a democratic
and emancipatory viewpoint (Sect. 2.3).
2.2 Knowledge Matters: A Sociological Perspective
In section two, we take a sociological perspective into why and how knowledge
has been displaced in education. Starting with different views on knowledge, we
further explain how constructivist and neoliberal sentiments have changed the role
of knowledge. We then introduce a new line of thought that shows how to bring
knowledge back into education.

22 2 How Knowledge Matters
2.2.1 From Objectivist to Constructivist Thinking
Perspectives
Knowledge has often been associated with concepts such as ‘truth’, ‘fact’, ‘social
inequality’, and ‘class differences’. These topics gained significant attention during
the early 1970s when the New Sociology of Education (NSOE) emerged. During
this period, concerns regarding social class and distributional effects in education
became increasingly evident. In this century, we can assume that a so-called “objec-
tivist” (sometimes also referred to as positivist or instructivist) view of knowledge
was more prevalent. Objectivism views knowledge as independent of individual and
social contexts, devoid of value judgments, and purely objective. The statement 3
+2=5 is a fact. That Michelangelo created frescoes on the ceiling of the Sistine
Chapel in Rome is a fact. That the natural behaviour of a body is to stay in the same
place or to move in a straight line at a constant speed and, without outside influences,
a body’s motion preserves its status is a fact (hard science). Objectivists emphasise
the development of comprehensive theories and universally applicable knowledge,
aiming to uncover ‘absolute truths’ about the world. However, this perspective has
been criticised for neglecting the social dimension of knowledge, which can poten-
tially lead to an absolutist stance that asserts universal truths without considering
their situatedness and potential biases. One of the new concerns on the objectivistic
view the New Sociologists brought to the fore in the 1970s was the social differen-
tiation in education and the reproduction of social inequalities that were associated
with the exclusionary structures of educational knowledge. Who had access to the
knowledge of the powerful? Did a child from a working-class family acquire the
same knowledge as one with highly educated parents? From this time onwards, soci-
ologists have posited a connection between the organisation of knowledge in schools
and broader social inequalities and power dynamics.
Authors such as Michael Young criticised these exclusive knowledge systems
(Young, 1971) by uncovering their intimate connections to social class structures.
The knowledge taught in schools was considered a tool to reinforce the dominance of
the ruling social group and its perspectives. For instance, knowledge of the history and
reign of the Tudors was seen as interesting and valuable for a particular ruling class
in charge of society, while knowledge of how to make concrete was seen as inferior
to that of the liberal arts. For this reason, the New Sociology of Education sought
to uncover the hidden interests lying beneath the surface of educational knowledge
and how it was taught (Moore, 2007). Over the years that followed, this perspective
evolved and found expression in various theories about what happens when learning
takes place (e.g. constructivism), and about what can be known (e.g. postmodernism).
Radical constructivists assert that knowledge is constructed from and deeply
embedded within an individual’s social and cultural environment. Isaac Newton’s
first law of motion acquires meaning because learners connect the new information
to their prior (folk?) experiences of motion (‘the ball on the grassy field did not move
until I kicked it!’). They emphasise the role of human agency in shaping knowledge,

2.2 Knowledge Matters: A Sociological Perspective 23
recognising that it is influenced by societal norms, cultural perspectives, and indi-
vidual experiences, and thus knowledge can only be constructed in a particular social
context.
A postmodern perspective takes this further and states that “objective truth” is
nothing more than the dominant viewpoints of the powerful elite among the variety
of human experiences and the multitude of perspectives. However, these views on
knowledge run the risk of relativism, where all knowledge is considered subjective
and context-specific, potentially undermining the possibility of grounding knowledge
in any objective truth. The problem that arises from this line of thinking is that
it reduces knowledge to its context and the knowers that possess it. This shift in
conceptualising knowledge resulted in the abandonment of knowledge as ‘truth’
or ‘fact’ to knowledge as nothing more than the viewpoints of typically dominant
social groups. This also shifts the validation of knowledge from the content itself to
the identity of the knower. Knowledge is no longer considered objective or neutral,
but is seen as a tool the oppressive elite uses for political control. Although the
absolute objectivist notion of knowledge was abandoned long ago, constructivist
and postmodern views on knowledge have found fertile ground in education (Moore,
2013), both in thinking about what we want our children to learn (content) and in
how we want to achieve this (teaching).
It is important to note, however, that these changes in the role of knowledge in
education are much older than the 1970s. As Hirsch (2016) persuasively argues, these
changes have roots in the romantic movement (eighteenth century) with the ideas
of Wordsworth and Hegel that inspired Dewey, whose ideas then became a part of
the so-called progressive movement in the US around 1920. The trends in the 1970s
represent one of the latest continuations of these forms of thought, which have now
garnered considerable influence.
2.2.2 Skills for the Twenty-first Century and Neoliberal
Influences
These tendencies were amplified with the rise of neoliberalism. The focus of educa-
tion shifted from cultural and civic socialisation towards a focus on employability and
economic growth (Meyer & Benavot, 2013). Although almost two centuries earlier
Herbert Spencer (1861) had already argued for a utilitarian and practical business-
oriented education, this recent change can be attributed to the impact of globalisa-
tion and the need for nations to design their educational systems and curriculum as
tools for economic development, and even national competitiveness (Yates & Young,
2010). This led to the abandonment of the idea of education as a goal in itself and
shifted the focus to skills and competencies (a term borrowed from human resource
management terminology) that students could later employ in the labour market.
As argued by Wheelahan et al. (2022), the shift towards prioritising skills in educa-
tion is rooted in human capital theory. Initially descriptive, emphasising the link

24 2 How Knowledge Matters
between education and jobs, it evolved into a normative stance, asserting education
should focus on employability. By the 2000s, it had become prescriptive, demanding
education to align with workforce needs, leading to government policies shaping and
funding education accordingly.
The call for developing skills relevant to the twenty-first century is the latest form
of this trend (Rotherham & Willingham, 2010), and can be traced back to 2003,
when the twentieth anniversary of an influential report (A Nation at Risk, 1983)trig-
gered numerous analyses of the progress of American education. The introduction of
new fundamental skills was recommended, including computer literacy, and various
generic—and by the authors considered transferable—cognitive skills, such as crit-
ical thinking and problem-solving. However, as shown in Sect. 2.1, complex cogni-
tive thinking skills such as critical thinking, communicating, working together (i.e.,
collaborating) and problem-solving are not only grounded in knowledge, but have
also been key components of human progress throughout history. This is evident from
early advancements in astronomy and mathematics in antiquity, such as the devel-
opment of alphabets and writing, the construction of the Egyptian pyramids, and
the development of Greek philosophical thought, to scientific progress in the Middle
Ages, including Avicenna’s early medical practices and Johannes Gutenberg’s inven-
tion of the printing press using movable type to name but a few. The main difference
with the skill movement was that these skills should now become universal, and not be
left to chance for the happy few. Private industry and labour market economists have
played a significant role in advocating for competencies such as complex thinking
and communication skills (Levy & Murnane, 2013). At the start of the millennium,
the top skills demanded by the most prominent and most influential companies in the
United States had shifted from traditional skills such as reading, writing, and mathe-
matics to complex skills like ‘teamwork’, ‘critical thinking’, ‘problem-solving’, and
‘interpersonal abilities’. By 2015, the interest in the so-called twenty-first-century
skills had become a global phenomenon, as evidenced by the contribution of the
World Economic Forum, which outlined 16 essential proficiencies for education in
the twenty-first century (see Table 2.1).
This economic undertone is also strongly reinforced by international educational
policy actors, such as the European Union with its European Qualification Frame-
work, which allows cross-country comparison of skills; the Programme for Inter-
national Student Assessment (PISA) led by the OECD to assess selected student
competencies; and professional training programs led by UNESCO (Mulder et al.,
Table 2.1 World economic forum—education for the twenty-first century (adapted from Scheerens
et al. (2020)
Foundation literacies Literacy and numeracy; scientific literacy, ICT literacy, financial literacy,
cultural literacy, civic literacy
Competencies Critical thinking, problem-solving, communication, collaboration
Character qualities Creativity, initiative, persistence, grit, adaptability, curiosity, leadership,
social and cultural awareness

2.2 Knowledge Matters: A Sociological Perspective 25
2007, as cited in Goudard et al., 2020). While these competencies often require
a foundation in domain-specific knowledge, expectations frequently overlook this
requirement. They are commonly depicted as generic abilities that, when mastered,
can work in a wide range of situations. Some arguments surrounding this trend (‘Give
a man a fish, and you feed him for a day. Teach a man to fish, and you feed him for
a lifetime’) even suggest that the sheer volume of new knowledge being generated
diminishes the importance of actual content; it posits that the means of acquiring
information have become more crucial than the information itself. This leads some
to claim that as knowledge dates so quickly, teaching is no longer valuable (De Bruy-
ckere et al., 2015). These claims also underestimate the extent to which knowledge is
required to make sense of answers provided by new powerful AI-driven technologies
such as ChatGPT. Information in itself, though, does not equate to understanding that
information.
One can, for example, ask ChatGPT to “describe the decisive moment in the 2003
Rugby World Cup Final”. The answer: ‘In the dying moments of the first half of extra
time, England was awarded a penalty in front of the posts. Jonny Wilkinson, England’s
fly-half, stepped up and successfully kicked the drop goal, securing three points for
England. This iconic moment occurred with just 26 s left on the clock, propelling
England into a 20–17 lead’ will, however, not make much sense unless one has some
background knowledge of the sport, including what a drop-goal is, what a fly-half is,
and what extra time means. Moreover, it is incorrect as the decisive moment actually
came in the second period of extra time, when, with 30 s remaining, Wilkinson kicked
a drop goal (not a penalty kick) to break the 17–17 tie. Consequently, knowledge is
also required to know whether an answer is likely to be correct, reflects biases (such
as has been the case in, for example, depictions of people of different ethnicities), or is
even simply the result of a so-called AI hallucination (as in this particular case). This
all leads to concerns that an exaggerated emphasis on generalised 21st-century skills,
and a blind trust in technology conflict with our understanding of human learning
as described above, and may fail to adequately serve students—particularly those
from disadvantaged backgrounds—grappling with social inequity (Rotherham &
Willingham, 2010).
All of the above, however, does not mean that education should not have any links
to employment (as we will discuss below), nor that complex thinking skills are not
important; they very much are. Rather, it underscores the necessity of recognising
that domain-specific knowledge is crucial when imparting skills to students, and that
generalised lessons on, for instance, critical thinking are not that productive. In this
sense, we need to bring knowledge back in.
2.2.3 Bringing Knowledge Back in
At the onset of this century, a group of scholars, self-identifying as social realists,
expressed discontent with these trends, asserting that they had downgraded knowl-
edge in education (Barrett, 2024). This downgrading denies learners access to what

26 2 How Knowledge Matters
they call powerful knowledge, which most often affects students from disadvantaged
backgrounds the most (Wheelahan, 2010). For this reason, they argued for the need
to ‘bring knowledge back in’ (Muller, 2000; Rata, 2012; Wheelahan, 2007; Young,
2007). Taking a realist perspective, they recognise the social nature of knowledge
in its production (which withholds it from absolutism) yet reject the reduction of
knowledge to knowers (which counters relativism). They do this by acknowledging
that some knowledge is more objective than others in ways that transcend the imme-
diate conditions of its production (Moore & Young, 2001). In other words, while
knowledge is socially produced, some types of knowledge are more powerful, and,
yes, ‘better’, than others. With this better knowledge, however, it is not meant that it
is beyond debate, or that it is fixed. “Better knowledge means the best knowledge we
have, and the best means we have for creating new knowledge for the kind of world we
envisage for the next generation” (Young & Lambert, 2014, p. 31). Based on this idea
and the theories of Bernstein and Durkheim, Michael Young (2009,2013) produced
a theory of powerful knowledge. He positions the production of powerful knowl-
edge within specific social and intellectual groups, often represented by academic
disciplines. This disciplinary knowledge holds more power as compared to everyday
knowledge because it is produced in “communities of inquiry” that use specific
methods to create and validate claims of knowledge (Young & Muller, 2015). In this
context, academic disciplines such as mathematics, physics, and history are valuable
because they can generate focused discussions that ensure reliability, revisability,
and the emergence of new insights (Muller & Young, 2019).
The powers of disciplinary knowledge reside in going beyond individual experi-
ences, providing individuals with a robust framework to understand the world. For
example, it can help students understand that the Earth is round, a realisation that goes
beyond the visual appearance of a seemingly flat horizon. Although this concept may
seem profound to new learners, the underlying geometry and arithmetic are surpris-
ingly straightforward. The ancient Greek mathematician Eratosthenes ingeniously
demonstrated this almost two and a half millennia ago. By observing differences in
the shadows cast by vertical objects at the same moment in different locations on
Earth, Eratosthenes not only inferred the curvature of the Earth, but also calculated
its circumference. Rooted in fundamental geometry and arithmetic, his calculations
provided compelling evidence for a spherical Earth. Disciplinary knowledge thus
provides learners with more dependable interpretations and insights into the world,
allowing them to explore topics and subjects their experiences alone would never let
them have access to. It also serves as a language that allows individuals to question
its own foundations and the authorities from which it derives. The acquisition of
disciplinary knowledge enables individuals to envision alternative possibilities and
think beyond the confines of their immediate surroundings.
For these reasons, Young advocates inclusive access to powerful knowledge in
education, asserting equal educational rights for all children. He argues that if ‘better
knowledge’ exists, everyone should have the right to access it (Young & Lambert,
2014). This does not mean that powerful knowledge is the silver bullet for all our
problems, and that we should just start teaching the ‘best’ knowledge in our disci-
plines and everything will be alright. Muller (2023) points out that this is expecting

2.3 Knowledge Matters: A Democratic Perspective 27
too much from the concept. What constitutes powerful knowledge changes as disci-
plinary knowledge itself evolves; in some areas, such as environmental science, quite
rapidly (Yan, 2015). Furthermore, what counts as powerful knowledge in particular
disciplines, such as history, is itself subject to debate, and contextually differentiated
(Sheehan, 2021). For these reasons it is important to clarify that this perspective does
not assert the presence of an unchanging or universally accepted canonical knowl-
edge across disciplines. It is also important to point out that disciplinary knowledge
in the academic disciplines themselves on the one hand, and disciplinary knowl-
edge in schools on the other, are two different things. Disciplinary knowledge in the
disciplines needs to be translated by expert teachers and subject specialists. While
powerful knowledge cannot serve as a silver bullet, it can help us as a future-oriented
principle where we strive towardsa more desirable future and reappreciate knowledge
and the emancipatory and democratic qualities it brings.
2.3 Knowledge Matters: A Democratic Perspective
In a democratic society devoted to equal opportunities and governance for and by the
people, one of our democratic responsibilities, namely deciding what our children
should know, is complex. What we know plays a significant role in shaping our
identities and who we are, or are perceived to be (Moore, 2000). Deciding what our
children should learn does not only play a role in what we want the future of our
society to be like, but also in who we want our children to become. This leads us to
a very difficult question: What kind of knowledge is so important that we will not
leave its transmission up to chance? A question that becomes ever more difficult to
answer as the production of knowledge in our society grows. One could argue that the
response to this question depends heavily on the answer to a different question: what
is the purpose of education? While there are many possible answers, most can be
divided into four broad categories: personal empowerment,cultural transmission,
preparation for work, and preparation for citizenship (Wiliam, 2013). These
broad philosophies do not exclude one another but are sometimes in conflict. A
balance is needed, as one without the other can have unwanted consequences.
For example, an education system focused only on preparation for work could
lead to an instrumentalist view where only knowledge that is considered “useful”
for economic growth is taught. Such an instrumentalist view might overlook the
intrinsic value of knowledge for personal empowerment and cultural transmission
and diminish the broader benefits that a well-rounded education can bring. It also
lends itself to the inference that employers should have a significant voice in deciding
what children learn, and it’s not obvious that they would wield this power in a way
that benefits society as a whole.
The knowledge and skills we think everyone will need for further economic devel-
opment could also be misguided, since we don’t have a crystal ball to tell us what the
future holds. On the other hand, an educational system solely focused on personal
empowerment might lead to a disconnect between the knowledge and skills taught

28 2 How Knowledge Matters
in schools and what students need to function in the labour market upon which our
societal prosperity relies. Discovering and maintaining this balance and determining
what should be taught is a project that never ends, given that an effective system
today may prove inadequate in the future as society changes. However, choices need
to be made. In the next paragraphs, we will take a closer look at the aim of preparing
our children for citizenship in a democratic society and how knowledge plays an
important role in this process.
When examining knowledge from a democratic perspective, one cannot overlook
the ideas of E.D. Hirsch and his notions of cultural literacy. Hirsch (1988, p. xiii)
defined being culturally literate as “possessing the basic information needed to thrive
in the modern world”. With this concept, he pointed out the significance of back-
ground knowledge in language comprehension, and how disadvantaged students
rely primarily on schools to provide this knowledge. As explained in the first section,
student’s already acquired knowledge (we refer to this as ‘background’ knowledge)
acts as a cognitive scaffold, enabling students to connect added information and their
pre-existing understanding of the world. When communicating, we assume a vast
amount of shared background knowledge. For disadvantaged students, who may face
limitations in exposure to a rich array of experiences and information outside schools,
this can limit them, not due to a lack of ability, but because of a lack of access to
knowledge (remember the scorpion in the section on reading comprehension?).
This is why, when knowledge is no longer explicitly addressed in schools, or
assumed to be primarily constructed from children’s own experiences, the most disad-
vantaged students suffer the most. This is problematic not only for these individuals
but also for society as a whole. As Hirsch (2009) states, shared knowledge fosters a
sense of commonality among diverse citizens in a democratic society. In a society
characterised by cultural diversity, a common body of knowledge ensures that citi-
zens can engage in informed discussions, debates, and decision-making processes.
It promotes a sense of belonging and inclusivity, as individuals draw upon shared
references that go beyond individual differences. One can imagine that when access
to this shared knowledge is hindered or not evenly distributed, issues of inequality
in education may widen. This is why the erosion of the role of knowledge within the
educational landscape can have dire consequences (Hirsch, 2016).
Hirsch’s ideas have significantly influenced the resurgence of and emphasis on
knowledge as a vital component of society and education. Nevertheless, his ideas
have been criticised due to their perceived traditional and conservative nature. Social
realists such as Michael Young share Hirsch’s views on the importance of knowl-
edge in our society and its vital role in education. Yet, these social realists relo-
cate (powerful) knowledge within academic disciplines, making what is taught and
learned in classrooms more reflective of the characteristics of disciplinary knowl-
edge developed by specialist communities. They also share Hirsch’s view on knowl-
edge as a prerequisite for fostering equitable opportunities for all and for social
justice. Leesa Wheelahan (2010) further strengthens this viewpoint from a demo-
cratic perspective, emphasising the crucial role of disciplinary knowledge in granting
individuals access to society’s ongoing conversation about itself. Providing access
to disciplinary knowledge is crucial for an effective democracy, as it allows societies

2.3 Knowledge Matters: A Democratic Perspective 29
to contemplate the ‘not-yet-thought and unthinkable’ and fosters the imagination of
alternative futures (Bernstein, 2000). Disciplinary knowledge is the result of a global
learning process. Young echoes this sentiment and argues that disciplinary, powerful
knowledge empowers learners to go beyond their own experiences. It also arms them
with the language to participate in discussions on politics, morality, environmen-
talism, migration, and many other topics prevalent in civil society. Furthermore, it
also gives them the capacity to scrutinise the foundations of knowledge, the authority
upon which it stands, and thus, the tools to be critical of it (Young, 2007). Let us
illustrate this with the following excerpt from a fictitious news article:
The struggle over this aid forms a growing obstacle to progress in negotiations during climate
summits. As long as wealthy countries do not provide the assistance they have pledged, many
poor countries are unwilling to do more to reduce their greenhouse gas emissions. According
to most experts, emissions will rise rapidly in poor countries and emerging economies.
Not only do the authors of this article expect much broad background knowledge
from their readership, but also a good understanding of domain-specific knowledge.
Why are greenhouse gases such a problem? Is this a valid claim and why? If this
is true, why do poorer countries not want to reduce them if rich countries do not
assist? As previously discussed in the section on reading comprehension, even if
the reader can successfully decode and read this article, much more is needed to
deeply comprehend it and contribute meaningfully to the discussion. This is why, as
Wheelahan (2010) argues, disciplinary knowledge is socially powerful knowledge.
Students need knowledge to be able to participate in societal debates. This does
not mean that every child needs to become a mathematician or historian, but they
do need access to a foundation of disciplinary knowledge to be able to reason and
develop an understanding of how that knowledge is used and validated in debates.
However, this extends beyond merely theoretical debates. It applies equally, for
example, to workers who require access to disciplinary knowledge that supports
their professional practice. Today, a car mechanic needs to understand theoretical
automotive engineering concepts, such as combustion engines, electronic systems,
and diagnostic techniques. If mechanics only rely on practical experience without
digging into the underlying theory, they might find it challenging to troubleshoot and
adapt to advancements in vehicle technology. While practical experience remains
extremely important, theoretical knowledge equips them with the insights needed
to understand new technologies, discuss industry developments, and meaningfully
contribute to conversations on automotive innovation.
While deciding what knowledge ought to be provided to our children will (and
should!) always be the result of societal debate, ensuring that knowledge itself is not
forgotten is crucial for equitable opportunities for all and our democratic society.
Hirsch has shown us the importance of a common knowledge base and helped bring
knowledge back into the conversation, whereas social realism has brought knowledge
back into social theory, while at the same time emphasising the importance of the
disciplinary aspect of knowledge.

30 2 How Knowledge Matters
2.4 How Knowledge Matters Summarised
Our perspective on knowledge is shaped by the lens through which we view it. From a
cognitive psychology standpoint, the value of a well-established knowledge base for
learning, and complex cognitive skills such as critical thinking and reading compre-
hension is unequivocally recognised. We now know that humans have the capacity to
construct a robust knowledge base within long-term memory, that provides us with the
resources to enhance the efficacy of working memory during cognitive tasks. When
examining knowledge from various perspectives, it is evident that its significance has
been subject to fluctuating societal trends, and that those societal viewpoints have
at times overshadowed the importance of knowledge. Revitalised by contemporary
democratic and social perspectives, and bolstered by consistent findings from cogni-
tive psychology, we are now witnessing a revival of the importance of knowledge
in education. It has now re-emerged as a prerequisite for improved learning, critical
thinking, and deep reading comprehension, as a facilitator for collective discourse,
and as a catalyst for equitable opportunities for all. All these aspects have implications
for the curriculum, which is at the heart of the third part of this publication.
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Chapter 3
Knowledge and the Curriculum
Abstract The curriculum is a complex concept central to educational debates. Over
the years, the role of knowledge in the curriculum has, like a pendulum, shifted
between two extremes, from highly visible to virtually invisible knowledge elements.
In this chapter, we consider the lessons learned from both extremes, proposing a
knowledge-rich curriculum as the soundest way forward to both effectively acquire
knowledge and complex cognitive skills in school, but also as a crucial lever to
achieve equitable opportunities for all students. In understanding how a knowledge-
rich curriculum can enhance learning, three overarching principles are discussed:
(1) content-richness, (2) coherence, and (3) clarity. These principles are illustrated
through practical examples from schools and educators who have effectively imple-
mented knowledge-rich curricula, and combined with insights from relevant research
on curriculum studies.
Keywords Knowledge-rich ·Curriculum ·Knowledge acquisition ·Complex
cognitive skills ·Curricular coherence ·Curricular clarity ·Content-richness ·
Equitable opportunities
3.1 Everything Starts with the Curriculum
In the previous sections, we discussed the importance of knowledge and how it
constitutes an essential component of deep thinking. This has important implications
for the curriculum in educational settings. Nuno Crato (2021) neatly highlights its
utmost importance in that regard as follows:
First, everything starts with the curriculum. This is the education founding document. It can
be national, federal, regional, or established at local levels. It can be more detailed or less
specific, it can be later translated in standards or contain them, but without clear learning
goals no education system can progress. Second, the curriculum, or curricular structure if it is
made from different pieces, ought to be ambitious, demanding, and set clear objectives. These
objectives must be sequenced, setting solid foundations for students’ progress. Knowledge
is a necessary foundation to develop skills and values. Third, everything needs to be coherent
around curricular goals. It does not make sense that assessment instruments evaluate some
© The Author(s) 2025
T. Su r ma et a l ., Developing Curriculum for Deep Thinking,
SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-74661-1_3
37

38 3 Knowledge and the Curriculum
learning goals, textbooks stress others, and schools are rewarded for attaining still different
student goals (p. 20).
However, to state that the concept ‘curriculum’ is complex is at the same time
quite an understatement. Formulating a definition that covers its complexity is there-
fore a very challenging task, akin to ‘waiting for Godot’. Those readers with back-
ground knowledge on Samuel Beckett’s play will have no problem understanding
this comparison. This complexity is also reflected in the literature, with Ian C. Rule
identifying 119 distinct definitions of curriculum in 1973 (Portelli, 1987). Some even
go as far as to state that “there are as many definitions as authors” (Thijs & van den
Akker, 2009, p. 9). For the sake of clarity and for the purpose of this book, however,
we will define the curriculum as a ‘plan for learning over time’ (Taba, 1962; Thijs &
van den Akker, 2009). Acknowledging that this definition still has its limitations,
we believe it is important to start this section by highlighting some factors regarding
the complexity of curriculum as a concept. Understanding these factors may help
clarify why curriculum is at the centre of so many debates in education, and why
these debates are so important.
A first factor to consider is the broad or narrow perspective you adopt when
considering the concept ‘curriculum’. Learning is not limited to what happens at
school; students’ social environment also plays a significant role. Think about what
children could learn by joining the Scouts, taking music lessons, or playing basketball
with friends at the local court, but also what their parents might teach them by taking
them to museums, and the topics that are or are not discussed at the dinner table.
These aspects are also referred to as the societal curriculum (Deng, 2017). In this book
we focus on the content and learning activities organised at school and the system
behind it (Popham & Baker, 1970; Tyler, 1949), yet we take into consideration these
important factors that can influence the learning potential of students. Kerr (1968)
resumes this viewpoint as follows: “All the learning which is planned or guided by
the school, whether it is carried on in groups or individually inside or outside the
school” (p. 16).
A second and perhaps even more important factor is the fact that curriculum
depends on a conception of education and learning. What do we as a society, as
schools, as teachers value, and what is the goal of schooling? In other words, why do
students learn in school? The answer to this question also determines the emphasis
placed by an educational system, individual schools, and even individual teachers.
It also implies that shaping the curriculum is about making choices.

3.1 Everything Starts with the Curriculum 39
The work of Tyler (1949) provides us with valuable guidelines in this regard. He
poses four fundamental questions that can provide direction in the decisions that
need to be made:
•What educational purposes should the school seek to attain? (standards,
curriculum philosophy, epistemology)
•What educational experiences can be provided that are likely to attain these
purposes? (curriculum, instruction)
•How can these educational experiences be effectively organised? (curriculum,
teaching)
•How can we determine whether these purposes are being attained? (assessment,
evaluation)
Van den Akker (2003) equally emphasises this purposefulness, and stresses that
every curriculum starts with a rationale with a view to student learning, upon which
other factors within the educational context can be aligned. He illustrates this with
the metaphor of a curricular spider web, as depicted in Fig. 3.1. In this representation,
any alteration to this rationale can consequently prompt changes to various elements
of the curriculum, including the provided content, the articulation of learning objec-
tives, assessment methods, and more. This underlines the inherent complexity of
curriculum, in which, similar to a spider web, “every chain is as strong as its weakest
link”(p. 5).
A third factor to consider is that when it has been determined in the curriculum
what we want students to learn, this does not automatically equal what students actu-
ally learn. That is due to discrepancies between what Bauersfeld (1979) calls the
intended curriculum (what we want students to learn), the implemented curriculum
(how these intended learning goals are then enacted), and the attained curriculum
(what students actually learn). Below, we will discuss these discrepancies in more
detail. On top of the discrepancy between the intended and the attained curriculum,
another issue emerges regarding curriculum intentions and what students eventu-
ally learn. As Kelly (2009) points out “some educationalists speak of the hidden
curriculum, referring to those things which students learn at school because of the
way in which the school’s work is planned and organised, and through the mate-
rials provided, but which are not overtly included in the planning or sometimes even
in the consciousness of those responsible for the school arrangements”(p. 10). In
other words, curriculum building and implementation are never neutral. Reynolds
and Hattan (2024) address the latter issue from a gender viewpoint with a recent
example of a unit on American presidents that clearly lacks female or other repre-
sentation. What kind of implicit message is communicated with regard to certain
students’ possibilities to become president? And what might change if, for instance,
influential Congressional representatives such as Kamala Harris, Michelle Obama,
or Hillary Clinton were included in the unit? Moreover, as curriculum building is
about making choices and teaching time is scarce, this implies a risk that some voices
will be more present than others in the curriculum. Eisner (1985) calls this the null
curriculum: “the options students are not afforded, the perspectives they may never
know about, much less be able to use, the concepts and skills that are not part of their
intellectual repertoire” (p. 107).

40 3 Knowledge and the Curriculum
Fig. 3.1 The curricular spider web (retrieved from Van den Akker, 2003)
All of the above then leads to a fourth factor that comes into play, namely that the
curriculum can be organised at different levels, which Priestley and colleagues
(2021) categorise as:
•the supra level (transnational discourse about curriculum, formulated by organi-
sations like the European Union and the Organisation for Economic Co-operation
and Development (OECD);
•the macro level (national level on which curriculum frameworks and standards
are developed such as the national curriculum in England;
•the meso level (local curriculum agencies, textbook publishers, and educational
designers that bring the curriculum to the classroom);
•the micro level (schools and teachers who design educational programs and their
lesson plans);
•the nano level (classroom level where teachers translate standards and their content
into teaching activities that result in student learning).
The degree of autonomy teachers have in shaping the curriculum depends on the
local context, ranging from strict governmental control with a prescriptive curriculum
and textbooks, including high-stake centralised testing, towards the other end of the
spectrum where individual teachers have complete freedom in what they want to

3.2 Curriculum as a Pendulum 41
teach, without any form of output control. Considering the context and the ratio-
nale at the different levels, and taking into account the insights about the intended,
implemented, attained, null and hidden curriculum, it can easily be concluded that
implementing a curriculum is indeed complex and its content should be subjected to
thorough societal debate.
Stein and colleagues (2007) schematically illustrate the complexities in measuring
the actual ‘impact’ of a curriculum on learning outcomes, identifying several medi-
ating factors that can influence its implementation in a dynamic model “in a series of
temporal phases from the printed page (the written curriculum), to the teachers’ plans
for instruction (the intended curriculum), to the actual implementation of curricular-
based tasks in the classroom (the enacted curriculum) (p. 321)” (see Fig. 3.2). For
instance, teachers’ translation of the written curriculum (e.g. textbooks) into curric-
ular intentions acts as an important mediating factor in what is eventually taught
to and finally learned by students. Teachers’ experience with the enactment of the
curriculum in the classroom will also shape and transform their future interactions
with the translation from the written to the intended curriculum.1
While its implementation is clearly complex, different trends with regard to the
role of knowledge in the curriculum can still be identified, as will be further examined
in the following section.
3.2 Curriculum as a Pendulum
The role of knowledge in the curriculum can be metaphorically described as a
pendulum oscillating between two extremes, from highly visible to virtually invis-
ible knowledge elements. This pendulum swing is especially noticeable at the macro
level. As discussed above, curriculum implementation is complex, which means that
what happens at the macro level does not necessarily immediately occur in the class-
room. Therefore, in what follows we will first discuss trends regarding the role of
knowledge in the written curriculum rather than its full implementation in the class-
room. Let us consider two examples of the written curriculum at the macro level to
illustrate this point. In Fig. 3.3 you find an excerpt from the Belgian national history
curriculum for primary education in 1954.
Imagine us asking a random Belgian student in 1960: “When and where was
Napoleon defeated?” It is reasonable to assume that most students could answer
this question. Knowledge items are prominent in this curriculum, ensuring that the
awareness of these historical figures and events is not left to chance. Every Belgian
1This use of the term ‘intended’ differs from its use in the international assessment TIMSS, where
‘intended’ refers to what Stein et al. name ‘written curriculum’.

42 3 Knowledge and the Curriculum
Fig. 3.2 Curriculum implementation (retrieved from Stein et al., 2007)
Fig. 3.3 Snippet from 1954 Belgian national history curriculum for primary education (translated
from Dutch)

3.2 Curriculum as a Pendulum 43
child attending primary education at that time would likely have had some notions
of Napoleon and Charlemagne. However, if we were to ask those same students
how Napoleon’s defeat was an indirect cause of the founding of the Belgian nation,
the responses might vary. The question remains whether this is an issue. One could
argue that the knowledge elements included here can act as future background knowl-
edge to understand more complex curricular content in secondary education. When
discussing 20th-century European history, history teachers know that all students
should be familiar with Napoleon and Waterloo, making it easier to study historical
texts and organise class discussions as there is some common ground on the topic.
On the other hand, this curricular approach can be tempting to focus solely on the
prescribed content knowledge, and thus limit oneself to rote learning. If the curricular
goal was simply for students to memorise isolated facts, they could learn them in any
order. After all, one isolated fact is as easy to learn as any other. Hence, we could
compile a canonesque list (i.e. an authoritative and sanctioned collection of every-
thing we want students to know), teach them in any random order, and tick off the
list when it has been taught in the classroom. However, without connections between
knowledge areas, it is guaranteed the understanding will be shallow, and retention
will be poor. Let us now consider a second example of knowledge representation in
the written curriculum at the macro level: an excerpt from the Welsh national science
curriculum (Fig. 3.4).
This type of curriculum can be associated with ‘the new curriculum’ (Priestley &
Sinnema, 2014), and can be closely tied to the societal influences and changes
described in the previous part of this book. This contrast appears as a kind of
pendulum movement whenever educational systemsreact against a more prescriptive
curriculum at the macro level. Although its implementation varies from one country
to another some commonalities can be identified.
Fig. 3.4 Welsh national science curriculum (retrieved from https://hwb.gov.wales/curriculum-for-
wales)

44 3 Knowledge and the Curriculum
First, the so-called new curriculum is mostly associated with skill-oriented stan-
dards that focus on generic competencies and 21st-century skills, often defined irre-
spective of specific content topics, and formulated as student outcomes (Meyer &
Benavot, 2013). Generic competencies such as critical thinking, problem-solving,
creative thinking, communicating, and entrepreneurship are often included. As previ-
ously mentioned, a substantial body of research has shown that these competencies
cannot be taught independently of content.
Second, there can be a lack of specificity in terms of which knowledge should
be acquired, posing challenges for school leaders, teachers, textbook makers, and
test developers in interpreting the curriculum (Priestley & Sinnema, 2014). For
instance, in ‘being curious and searching for answers is essential to understanding
and predicting phenomena’, teachers might not know which ‘phenomena’ students
have previously studied. A lack of clarity risks a lack of coherence, not only in
terms of previously acquired knowledge and learning progressions within and across
subjects, but also within other aspects of the educational system, such as (national)
assessment, accountability, inspection, professional development, etc. (Oates, 2011).
We will discuss this in more detail below. Also, broadly formulated standards at the
macro level are often intended to grant more autonomy to teachers and schools.
Nieveen and Kuiper (2021) highlight, however, that variation in the interpretation
of standards in Dutch schools is so diverse that monitoring educational quality has
become nearly impossible. Kuiper and Berkvens (2013) conclude that these standards
do not automatically lead to autonomous decisions taken by teachers regarding the
curriculum. This occurs for several reasons. For instance, school leadership teams
and teachers may not always have sufficient expertise to handle this freedom, often
relying heavily on textbooks. Or, experienced curricular freedom is constrained by
strict output regulations, such as high-stakes national testing or rigorous inspection.
A third feature concerns the learner-oriented pedagogies implied by curricular
goals such as ‘explore and observe’. From this viewpoint, the curriculum focuses on
the students’ interests and experiences and differentiates to an individual level based
on the students’ needs. It also prescribes how teachers should enact the curriculum. It
is not enough to learn about a topic; students should also ‘experience’ it, and ‘reflect’
on it. This is often accompanied by the concept of learning to learn and letting
students become responsible for their own learning (Sinnema & Aitken, 2013).
A fourth feature we can distinguish is the tendency to strive for over-ambitious
thinking targets too early in education, and independent of the required background
knowledge, such as teaching generic ‘problem-solving’ in early childhood educa-
tion (Britz, 1993), or ‘thinking scientifically’ with three-to five-year-olds in Wales.
Of course there is nothing wrong with conceptual thinking at a young age. Chil-
dren should learn abstract ideas like, for instance, the meaning of the equal sign.
At the same time we also know from the first part of this book that children are
not (yet) ‘mini-historians’ or ‘mini-scientists’, precisely because they still need to
build sufficient knowledge schemas to handle those complex cognitive thinking skills

3.2 Curriculum as a Pendulum 45
(Kirschner & Hendrick, 2020). It is important to build those necessary foundations
before you can move on to complex thinking skills within a domain.
The two curriculum examples discussed above highlight distinct approaches to
incorporating knowledge into the written curriculum at the macro level. In the first
instance, knowledge takes a prominent role at the core of the curriculum, yet in a static
fashion with a list of things every child should know, without encouraging any further
interaction with the material. We know, however, that in order to facilitate background
knowledge that truly supports future learning and reading, it is important to build
true knowledge networks with coherent clusters of concepts in a domain (Neuman
et al., 2014). Conversely, the second example portrays a contrasting extreme where
knowledge seems rather absent, focusing on interactive engagement to gain generic
competencies. As previously mentioned, there is of course a difference between the
written and enacted curriculum. Having this type of written curriculum does not
automatically mean that, for instance, tick box behavior will take place, but it might
have a subtle influence.
Both examples can be positioned in Young and Muller’s (2010) perspectives
of thinking about curriculum, which they labelled as ‘futures’. The first example
touches upon a so-called Future 1 curriculum, what can be described as a collection
of learning content, treating knowledge as fixed, unchanging and based on tradition.
These curriculum types typically organise content into traditional subjects and can be
traced back to the schooling system that established a formal curriculum of essential
knowledge in the 19th and early twentieth centuries. In their extremest forms they
could be described as absolute scripts for ingestion. The second example, on the
other hand, touches upon a so-called Future 2 curriculum and can be associated
with the societal changes described in the previous part of this book. It holds a
radical constructivist view of knowledge, a learner-oriented focus, and prioritises an
outcome-based curriculum that reduces knowledge’s central role in further learning,
and in developing complex skills in school. It is important to point out, however,
that re-embracing the importance of knowledge does not imply advocating a Future
1-curriculum, as both futures have their challenges. Yet, as noted by Muller (2023),
the historical shift from Future 1 to Future 2-curriculum involved the elimination of
both the negative ánd the positive elements of Future 1, which is why a return to
knowledge must consider the lessons learned from this pendulum movement.

46 3 Knowledge and the Curriculum
3.3 Towards the Best of Both Worlds: A Knowledge-Rich
Curriculum
In training a child to activity of thought, above all things we must beware of what I will
call ’inert ideas’—that is to say, ideas that are merely received into the mind without being
utilised, or tested, or thrown into fresh combinations. (Whitehead, 1929,p.1)
In this third section, we focus on a curriculum designed to address the challenges
posed by the pendulum movement as described above, which we henceforth refer
to as a knowledge-rich curriculum. Our rationale is clear: given the importance
of knowledge for further learning, as a prerequisite for teaching complex skills in
school, and from a democratic and emancipatory perspective, it should have a central
and visible place in the curriculum. At the same time, this does not imply that the
curriculum should just provide a list of concepts and facts students should know,
and teachers should be reduced to mere transmitters of knowledge. Neither does
it imply that a knowledge-rich curriculum is built by cherry picking some knowl-
edge elements from one curriculum and adding a few important skills from another
in an eclectic way, aiming for the middle ground between both extremes, such as
the pendulum metaphor may wrongfully suggest. It cannot be overstated that we
aim for deep and meaningful learning, both deep understanding and application of
concepts, and therefore do not overlook the importance of complex thinking skills
(such as problem-solving, critical thinking and reading comprehension), as they are
crucial aspects to real understanding. These skills are, however, developed as students
develop knowledge in a deep way. On the one hand, skills are a byproduct of domain-
specific knowledge. On the other, they are better developed when teaching is also
skill-concerned and focused on the correct interpretation and application of knowl-
edge. In other words, in designing and implementing the curriculum, it is important
to have a knowledge-led approach (Crato, 2025). Yes, we are greedy. We want it all.
Returning to the provisional definition of curriculum in the first section, we can
hereby specify that a knowledge-rich curriculum is defined as follows:
a plan for learning over time that is concept-led and knowledge-led (Oates, 2011), which
encompasses a wide range of specified knowledge, and provides ample depth and opportu-
nities to engage with that knowledge (Rata, 2021a). It sets high expectations for all students
and systematically builds their knowledge of words and the world (Hirsch, 2016). It aims
at a broad and steady foundation for complex thinking skills, such as critical thinking and
reading comprehension, but also knowledge building that is further amplified and deepened
by those complex skills. A comprehensive knowledge-rich curriculum covers subjects and
concepts that go beyond children’s day-to-day experiences and is based on the ‘best’ disci-
plinary knowledge available at that time (Young & Lambert, 2014). It ensures that every child
has access to a broad and solid knowledge base in school, even if it has not been (partially)
acquired from an early age onwards outside school.

3.4 On Content-Richness 47
However, building a knowledge-rich curriculum is not an easy task. Different
authors will have their own perspectives on the key principles of a knowledge-rich
curriculum. Although a comprehensive list of principles may be more inclusive, it
can also become unwieldy. A brief list may miss out on crucial aspects, yet it can still
serve as a useful outline. Therefore, we present three overarching principles that we
found to be most beneficial and influential in understanding how a knowledge-rich
curriculum can enhance learning, namely (1) content-richness, (2) coherence, and
(3) clarity.
3.4 On Content-Richness
A curriculum led by concepts and knowledge might initially seem clear and straight-
forward. It is not. A number of crucial questions come to the fore quickly, demanding
thorough and deep analysis. Which content and concepts should be selected? What
knowledge cannot be left to chance? And who decides? The answers to those ques-
tions will strongly depend on the purpose and context of the educational system and
the specific level at which curriculum is being built. Therefore, a societal debate
represented by the stakeholders in education is of utmost importance and must be
thoroughly held. It also implies that socio-political factors will influence the answers
(Thijs & van den Akker, 2009). In what follows, we aim to provide some guidelines
as to (a) which content to select; (b) on what basis choices can be made; (c) how
hierarchy and structure in knowledge have an impact on sequence; and (d) how to
balance knowledge and skills.
3.4.1 The Selection of Content
First, which content do we want students to learn in school? Recent ‘back-to-
basics’ movements have advocated allocating more time to mathematics and first
language instruction in primary education. However, additional disciplines from the
humanities, arts, and sciences can provide a broader perspective on the world and
equip students with the comprehensive knowledge base necessary for acquiring and
executing complex cognitive skills such as reading comprehension. But not only that.
A healthy and balanced curriculum is needed for students to find their “element”,
that is, what they are passionate about and good at. Hence, a diverse range of subjects
and experiences is necessary, thus including traditional academic disciplines as well
as creative arts, technology, and other areas of study (Wiliam, 2013).
An important issue, however, is time. Every curriculum committee is tasked with
reducing the coverage and yet everyone increases it. There indeed is a tendency to
incorporate every societal issue in education, while the educational system cannot
tackle, let alone solve, every societal concern (Cuban, 1992, as cited by van den
Akker et al., 2003). As Whitehead noted in 1929: “We enunciate two educational

48 3 Knowledge and the Curriculum
commandments, ‘Do not teach too many subjects,’ and again, ‘What you teach, teach
thoroughly. (p. 2)” The risk of overload is legitimate and forces us to make choices
between what we consider important and even more important (Wiliam, 2013), and
this inevitably means that some content will not be part of the curriculum (the null
curriculum; Eisner, 1985). Educational programs in high-performing countries also
seem to focus on fewer topics but emphasise teaching them in a deeper and more
profound manner (Schmidt et al., 2002). We should therefore avoid a curriculum that
is “a mile wide and an inch deep” (Schmidt, McKnight & Raizen, 1997, p. 62). A
guiding question on this matter could be: What should not be left to chance? This is not
to say that we should restrict the curriculum entirely to just a few important disciplines
or subjects. Knowledge and concepts are not limited to disciplinary boundaries.
Tackling a topic or concept from different disciplines and viewpoints allows digging
deeper into it, broadening knowledge schemas in long-term memory, and, if the
topics are well-chosen, provide a broad yet sufficiently profound knowledge base for
all students.
These insights regarding the selection and specificity of content also prompt the
question of at what level these choices should be made, and to what degree. From a
democratic perspective, with a view to creating a common knowledge base one could
argue to determine and specify most of the content at the macro level. However, it
is also important to consider the highly diverse contexts of different schools within
an education system and to be mindful of their local context. This can naturally only
be achieved by also providing certain degrees of freedom and autonomy, allowing
schools and teachers to shape the curriculum. A fully prescriptive curriculum at the
macro level that aims to select and specify a hundred percent of the lesson time would
of course jeopardize the crucial role schools and teachers play in the context-specific
enactment of the curriculum. However, as Oates (2011) points out, a certain degree of
curricular control is equally necessary, as it also contributes to the coherence within
an education system. We will further elaborate on this point below. On what basis
can choices be made?
3.4.2 The Basis of the Selection Process
For this second aspect regarding content selection, it is useful to look at the knowl-
edge theories of social realists, who advocate a revaluation of the role of disci-
plinary knowledge in education, which they differentiate from everyday knowledge.
Whereas the latter arises from daily experiences and the social environment, much
akin to what Geary (2012) calls ‘folk-knowledge’, disciplinary knowledge is built
upon centuries of systematic study by specialist communities in areas such as mathe-
matics, biology, physics, and more. For some disciplines, however, this is easier and
more straightforward than for others. However, regarding the curriculum, let us keep
it simple: disciplinary knowledge enables us to consider things that are unlikely to be
known solely through experiences or observations. For instance, merely observing
a polluted river will never allow us to comprehend the chemical element ‘nitrogen’

3.4 On Content-Richness 49
(Rata, 2021a,2021b). This is when disciplinary knowledge from chemistry is needed.
By learning about this concept in a chemistry class, students can understand the
effects of nitrates on land and waterways. In terms of reliability and objectivity,
there is, therefore, more solid knowledge that can guide the curriculum and create
a language to provide insight into a world beyond one’s own current experiences
or observations.A critical point, however, must be held in mind. While acknowl-
edging that some knowledge is more solid and better grounded than others, it does
not imply that knowledge is fixed. Consider our knowledge of dinosaurs. When the
first Iguanodon was discovered, it was depicted with a horn on its nose (see Fig. 3.5).
Meanwhile, we now know that this ‘horn’ was actually a claw, which was probably
used in defence of predators (see Fig. 3.6). When contemplating curriculum, this is a
principle that we must always keep in mind, emphasising the importance of structural
curriculum revisions based on state-of-the-art disciplinary knowledge.
Fig. 3.5 First drawing of an Iguanadon by Mantell (1834)
Fig. 3.6 Later drawing of an Iguanodon. Retrieved from Slate Weasel–Own work, CC BY-SA 4.0,
https://commons.wikimedia.org/w/index.php?curid=97909961)

50 3 Knowledge and the Curriculum
3.4.3 The Impact of Hierarchy and Structure in Knowledge
and Sequence
A third aspect that is important to consider is the hierarchy and structure within the
knowledge itself, and how this influences the careful sequencing of topics in the
curriculum. For instance, when teaching about the impact of microplastics in water
on the human body, numerous concepts must be grasped, including microplastics,
water as a biotope and as a human resource, and the human body, including digestion.
Each of these concepts can also be approached from various disciplines with their
own disciplinary hierarchy. Content selection thus automatically puts curriculum
makers in a position wherein a learning plan must be determined within and across
disciplines. From a biological point of view, for example, it would be useful to deter-
mine what you need to know about the human body before you can come to a solid or
necessary understanding of the human digestive system to tackle the microplastics
problem. One must also take into consideration what was learned across disciplines
to determine whether all necessary knowledge building blocks are in place to tackle
the new problem. Below, we will discuss this further in the section on curriculum
coherence. We want to emphasise here that if we consider ‘the impact of microplas-
tics on the body’ to be part of the curriculum, prerequisite knowledge leading to
understanding this concept must be included in the curriculum, starting in the earlier
years. This aligns perfectly with the ideas posited by Ausubel (1968) on meaningful
learning. When our goal is for students to engage with knowledge, hence providing
them with meaningful learning activities, led by concepts and knowledge, we must
take into consideration that the most important single factor influencing learning is
what the learner already knows. It is important to note that content is not restricted by
age, and knowledge building can start from a very young age. A thoughtful, content-
rich early years curriculum can complement a nurturing, play-learning environment.
Contrary to earlier beliefs about Piaget’s developmental stages, the developmental
processes in children are continuous and variable, with more variability than consis-
tency in children’s abilities (Willingham, 2008). Dispelling myths about preschool
education, preschoolers are more knowledge-ready than commonly thought, and indi-
vidual differences in exposure to knowledge strongly influence their development. As
Bruner already hypothesised in 1960 (p. 33): “Each subject can be taught effectively
in some intellectually honest form to any child at any stage of development”.

3.4 On Content-Richness 51
3.4.4 The Relation Between Knowledge and Skills
“Content in the absence of thinking is inert and meaningless; but thinking in the absence of
content is vacuous.” (Robert. J. Sternberg, cited in Tobias and Duffy (2009, p. 10))
A fourth and very important aspect to discuss regarding content-selection in a
knowledge-rich curriculum is the relation between knowledge and skills. This rela-
tion is often presented as a false dichotomy, suggesting that a focus on one would
exclude a focus on the other, and vice versa. It seems useful to pause for a brief
moment to consider what is meant by the term ‘skills’. On the one hand, there are
complex cognitive skills as discussed in the first section of this book, which mainly
rely on domain-specific knowledge, and are hardly teachable in a generic way, outside
a specific context. To be able to think critically about something and deeply under-
stand a text on a particular topic, you need a solid base of background knowledge
on that topic. Making sense of things and being able to apply it in novel situations
is, in fact, memory in disguise. We also noted that there has been a shift in curricula
over the past decades with a more explicit focus on skills, yet without sufficiently
including the necessary knowledge base. However, we also emphasised that we do
not advocate curricula that solely promote memorisation of disconnected facts. From
our rationale and our understanding of the importance of knowledge, these complex
skills do deserve a significant place in the curriculum, yet within specific domains,
and with a view to deep understanding of specific concepts.
On the other hand, there are also more ‘mechanical’ skills that can be taught
within a specific subject domain itself. Consider, for example, a program where
students must learn welding. The basic act of welding is something to be practiced
and automated before moving on to more complex situations. The same can be said
for multiplication tables or solving addition problems. As pointed out earlier in this
book, just like a professional footballer that may have endlessly practiced in isolation
taking the perfect free kick to place the ball perfectly in the upper corner, certain
skills can also be practiced and automated in the school context with a view to their
application in more complex scenarios. Time to practice these skills is something
that needs to be considered when selecting content in the curriculum, as well as
how these skills evolve in complexity and context. A future stone mason who has
only practiced using the same materials and the same tools in the same situation,
will possibly encounter difficulties when those materials or tools are absent in new
situations. Therefore, it can be helpful in a knowledge-rich curriculum, for students
to understand the underlying rationale of certain techniques and even materials,
enabling them to better assess new situations, selecting reasons for executing specific
actions in a particular way, and approaching them creatively. While making mortar,
based on knowledge, the future mason should be able to decide how much sand,
cement, water and soap ought to be added to the mixture, whatever the weather
conditions may be (i.e., when it rains the sand is wet, therefore less water is needed),
instead of blindly following a fixed recipe (e.g., three parts sand, one part cement,
one part water, a cup of soap).

52 3 Knowledge and the Curriculum
The placement of these skills, however, will largely depend on the sequence
in which concepts and knowledge are introduced. As mentioned above, the hier-
archy and structure of knowledge concepts serve as an important guide in creating
a coherent curriculum, with new knowledge building upon what was previously
learned and increasing in complexity. For example, within a subject like physics,
it would be logical to learn states of matter, gases, compressibility of gases, pres-
sure, elasticity, and so on. A curriculum that is concept- and knowledge-led aims
to incorporate important skills in this sequence, thus organising them in a logical
manner based on the knowledge hierarchy at hand. This is in contrast to a curriculum
where (generic) skills are central, risking a fragmented and episodic presentation
of knowledge elements without considering their hierarchical structure and logical
progression in complexity. For instance, let us consider the skill of fixing a flat tire.
We can start from this skill to teach many of the earlier mentioned concepts in
physics such as pressure, gases compressibility, elasticity … But to predominantly
follow a skills-led approach runs the risk of not leading to a structured knowledge of
physics, but to disconnected concepts. Looking back at the example from the written
curriculum at the macro level in Wales, we can see this reflected as well. Although
the importance of knowledge is not denied, no systematic structure respects its hier-
archical nature. Attempts are made to describe an increase in complexity regarding
the skills themselves, but it quickly becomes difficult to differentiate between simple
methods of inquiry (progression step 2) and suitable methods of inquiry (progression
step 3). In the section on clarity, we will further elaborate on this topic. Again, we
want to emphasise that we by no means deny the importance of skills, and that they
constitute an important part of the curriculum. Therefore, it is necessary to consider
how the included knowledge will be applied when it comes to content selection.
3.5 On Coherence
Curriculum coherence is a precise technical term that not only entails arranging
content in such an order that it supports age-related progression, but also aligns all
components of the educational system in such a way that they are working together
effectively to achieve educational objectives (Oates, 2011; Schmidt & Prawat, 2006).
On the one hand, a coherent curriculum thus considers the organisation of the
concepts and content within it and will be vital if one is to create a seamless and logical
conceptual progression in what children learn over time, referred to by Thijs and van
den Akker (2009) as vertical coherence. However, as stated above, knowledge and
concepts are not limited to the boundaries of disciplines. It is therefore important to
take into account how these concepts align with each other across subjects, which is
referred to as horizontal coherence (Thijs & van den Akker, 2009). On the other hand,
a coherent curriculum also implies alignment in terms of learning goals, pedagogy,
teaching materials, etc. In the current section we will address vertical and horizontal
coherence, namely the organisational structure within the curriculum and its content

3.5 On Coherence 53
and concepts, followed by coherence and disciplinary knowledge. In the following
section on clarity, we will discuss coherent system alignment in more detail.
3.5.1 Horizontal Coherence
Horizontal coherence refers to the organisation of content across topics, subjects,
and domains, based on the idea that subjects are not isolated bodies of knowl-
edge. When connections regarding concepts between different fields of study are not
explicitly made, most students have difficulty making the connections themselves
(Wiliam, 2013). Consider, for example, the concept of ‘woman’. Would students gain
a comprehensive understanding if they approach this concept solely from the field of
biology? To grasp its full complexity, it would probably be necessary to explore how
the role of women has evolved throughout history, how different religions perceive
femininity and the place of the woman therein, and how social role patterns unfold
in various societies and cultures around the world. Particularly in primary education,
theme-based education can be a well-thought approach to facilitate deep learning
about the same concept from various subject areas in the course of several weeks.
However, it should be held in mind that disciplinary knowledge offers powerful
ways of thinking about the world that does not develop naturally. Effective interdis-
ciplinary work thus relies on solid disciplinary foundations and engagement (Rata,
2019; Wiliam, 2013). Moreover, when themes are developed without thinking about
carefully sequencing the different topics and concepts in time knowledge building
runs the risk of becoming fragmented. In contrast to a theme-based approach, the
disciplinary approach treats concepts within the boundaries of the different disci-
plines. The disciplinary approach is often adopted in secondary schools, but can also
be adopted earlier on, as shown below in the example of the Primary Knowledge
Curriculum.
3.5.2 Vertical Coherence
“It is in all cases more powerful to be concerned about connecting the lesson with prior
learning and understanding than attend to the oft-made claims of relating the lessons to the
real or some future world.” (Hattie, 2023, p. 303)
Vertical coherence is about ensuring logical progression over time (weeks, months,
years, and grades), where prior learning forms a foundation for future content. For
instance, in preschool, teachers can already engage in knowledge-building activities,
such as situating different countries on a globe (see Curriculum Case 1). When
geographical concepts are systematically and sequentially expanded over the years,
students develop the necessary schemas to address more complex and contemporary
topics. Discussing, for instance, slavery in colonial history, or religious conflicts in

54 3 Knowledge and the Curriculum
the Middle East becomes less cognitively taxing when students already have a firm
grasp of world regions, countries and capitals, of natural resources and their role
in wealth creation, etc. A clearly sequenced curriculum provides teachers with a
roadmap that guides them from what is known to what has to be learned.Itis
crucial to emphasise that we are discussing substantive sequence here, where we let
the content guide the progression rather than achievement levels.
However, content sequencing is complex, demands careful consideration, and is
seldom linear. Consider, for example, the sequence of teaching geometric shapes.
In various European countries, it is common to teach triangles first, followed by
parallelograms. In Japan, it is the other way around, as parallelograms consist of two
triangles. Although there is no perfect universal sequence that applies to everyone,
thinking about sequence helps determine what students need to know before moving
on. Otherwise learning can become fragmented and episodic. For instance, one could
teach about dinosaurs and the prehistoric ages in pre-school one week, and about
Ancient Egypt during another. Although these lessons could be interesting and fun,
valuable opportunities are missed to provide sufficient depth and a solid foundation
for future learning, endangering the act of meaningful learning (Ausubel, 1968). In
the same way as subjects require logical sequence based on prior knowledge, the
timing of introducing and revisiting specific content is equally important. This prin-
ciple is embodied in Jerome Bruner’s Spiral Curriculum (1960), in which concepts
are introduced early in the curriculum and revisited with increasing complexity.
Curriculum Case 1
Core Knowledge Foundation kindergarten curriculum
In the Core Knowledge Curriculum for kindergarten (Core Knowledge Founda-
tion, 2010), knowledge is built and acquired cumulatively. Building upon founda-
tions laid in earlier grades, learning about continents and oceans (‘what students
should already know’), kindergarteners are introduced to the voyages of Christopher
Columbus, how he sailed to the American continent with the Niña, the Pinta, and
the Santa María, and so on (‘what students need to learn’). The following excerpt
of the core curriculum illustrates how vertical coherence is implemented in prac-
tice by describing the prior knowledge kindergarteners should have acquired (‘What
Students Should Already Know’) before systematically linking it to the new learning
objectives (‘What Students Need to Learn’).
What Students Should Already Know
•What maps and globes represent and how they are used
•Rivers, lakes, and mountains: what they are and how they are represented on maps
and globes
•The locations of the Atlantic Ocean and Pacific Ocean
•The locations of the North Pole and South Pole
•The meaning of some basic terms of spatial orientation necessary for working
with maps
•The names and relative locations of the seven continents

3.5 On Coherence 55
•Some familiar associations with each continent, such as wildlife, landmarks, etc.
•The cultures of the Eastern Woodlands, American Southwest, and Pacific North-
west Native Americans, including how they lived, what they wore and ate, what
their homes were like, what their beliefs and stories were/are, and what their status
is today
What Students Need to Learn
The Voyage of Columbus in 1492
•How Queen Isabella and King Ferdinand funded Columbus’s voyage
•The Niña, Pinta, and Santa María
•Why Columbus used the terms Indies and Indians
•Why Europeans thought Columbus had found a new world
The Pilgrims
•Why the Pilgrims founded a colony
•The Mayflower and Plymouth
•How the Thanksgiving Day celebration came about
July 4, Independence Day
•The birthday of the United States of America
•Democracy (rule of the people): Americans wanted to rule themselves rather than
be governed by a faraway king
•Why freedom did not exist for all people in the new nation: some people were
enslaved
3.5.3 Coherence and Disciplinary Knowledge
Moreover, coherence is also important at the level of disciplinary knowledge. In
creating a curriculum, we must consider the structure of the knowledge itself.
Coherent content standards in curriculum are organised as a logical sequence of
topics, aligning with the hierarchical nature of disciplinary knowledge, ensuring that
what and how students are taught reflects fundamental concepts within the academic
discipline (Rata, 2021a; Schmidt et al., 2002). This reasoning is connected to the
concept of ‘big ideas’, statements that attempt to describe some major understanding
in a particular discipline, analogous to a giant mental schema with interconnected
concepts. Big ideas can be used as a starting point to structure the curriculum, and
the ideas themselves can be broken down into several important components, such
as what needs to be assessed, what evidence is needed to determine whether students
really understand certain concepts, and what students need to be able to know and do
(Hattie, 2023; McTighe, 2000; Wiggins & McTighe, 2005; Wiliam, 2013). This helps
us to see how the different topics are connected and allows us to see the coherence
of the whole curriculum.

56 3 Knowledge and the Curriculum
Curriculum Case 2
Big ideas of science–Retrieved from Wiliam (2013)
An international team of science education experts compiled a list of ten big ideas of
science and an additional four fundamental ideas about science (Harlen et al., 2010).
•All material in the universe is made of very small particles.
•Objects can affect other objects at a distance.
•Changing the movement of an object requires a net force acting on it.
•The total amount of energy in the universe is always the same but energy can be
transformed when things change or are made to happen.
•The composition of the Earth and its atmosphere and the processes occurring
within them shape the earth’s climate.
•The solar system is a very small part of one of millions of galaxies in the universe.
•Organisms are organised on a cellular basis.
•Organisms require a supply of energy and materials for which they are often
dependent on or in competition with other organisms.
•Genetic information is passed from one generation of organisms to another.
•The diversity of organisms, living and extinct, is the result of evolution.
Big ideas about science
•Science assumes that for every effect there is one or more causes.
•Scientific explanations, theories and models are those that best fit the facts known
at a particular time.
•The knowledge produced by science is used in some technologies to create
products to serve human ends.
•Applications of science often have ethical, social, economic and political
implications.
The concept of ‘big ideas’ is also illustrated in the Curriculum Design Coherence
Model (CDC Model; Rata, 2019), where researchers, in collaboration with teachers,
took disciplinary knowledge as a starting point in curriculum design (Rata, 2021a).
The Knowledge in Education Research Unit, based at the University of Auckland
in New Zealand, developed the CDC model. Since its creation in 2018, the CDC
Model has undergone continuous development and is based on extensive research
(Rata, 2021a). The model consists of four interconnected elements (see Fig. 3.7), with
the first two elements relying on an understanding of different types of knowledge
(‘knowledge-that’, a broad term used for the coherent connection of concepts and
content. The third element is ‘know-how-to’, a term referring to skills in using the
’knowledge-that’). The CDC Model’s purpose is to connect concepts, content, and
the application thereof so they can be utilised to promote curriculum clarity and
coherence. “The findings from the Knowledge Project indicate that […] using the
CDC Model’s concept-cohering approach to curriculum design provided a way to
avoid the limitations of both content-list and skills-based approaches” (Rata, 2021a,
p. 448).

3.5 On Coherence 57
Fig. 3.7 The curriculum design coherence model (Rata, 2021a,2021b)
Curriculum Case 3
The CDC Model into practice (Rata, 2021a,2021b)
The CDC Model illustrates how the various principles of Content, Clarity, and Coher-
ence are intricately connected. Below, the different steps are briefly outlined and
illustrated.
Element 1: Selecting and sequencing subject concepts from a subject proposition
Teachers are required to outline a subject proposition and select the subject concepts.
An example proposition on ‘Exercise’ in physical education: is ‘Exercise utilises the
body’s energy to build stamina and strength’ (concepts are italicised). This propo-
sition links the subject to key concepts, providing coherence to the design process.
Subject concepts are crucial for design coherence and remain consistent, but their
meaning deepens in complexity over the years.
Element 2: Connecting subject concepts to content knowledge
The subject concepts identified in Element 1 are linked to actual course content,
creating knowledge-that. This involves a back-and-forth process between subject
concepts and content to achieve the best alignment. In the example of physical educa-
tion, content expressing the ‘strength’ concept could include specific muscles’ names,

58 3 Knowledge and the Curriculum
roles, and position. Subject content is not just an information list; it is a thought-
fully curated selection of material expressing the meaning of subject concepts. Three
criteria were proposed for selection:
•Material should be selected based on quality and aims to express the proposition
in a truthful manner.
•The fallible nature of knowledge should be acknowledged. New insights can
emerge in various ways. Therefore, it can be useful to spend some time to include
the intellectual history of the big idea or proposition from a particular discipline.
•Content selection is intentionally social and/or political. It is guided by the ques-
tion: Is this the subject content that we, as a society, want the next generation of
citizens to know?
Element 3: Connecting ‘knowledge-that’ to ‘know-how-to’
This is the connection between ‘knowledge-that’ and ‘know-how-to’. It encompasses
two types of know-how-to: First, performance focuses on applying procedural rules in
practice and achieving mastery. Second, judgment focuses on understanding subject
concepts to solve problems and evaluate solutions through conceptual reasoning.
Both need to be specifically taught and increase in complexity.
Element 4: Evaluating ‘knowledge-that’ and ‘know-how-to’
The evaluation system is intended to assess how well students master know-how-to
in relation to their understanding of ‘knowledge-that’—the concept and substantive
knowledge. Assessment and feedback are viewed in terms of:
•Recall: how well do learners remember the content?
•Skill and technique: how well can learners perform a certain skill or technique?
•Judgement know-how-to: how effectively can substantive knowledge be used to
explain and justify the purpose of a specific action?
For more examples and further explanations about how to use the CDC model in
practice, see Rata (2023).

3.6 On Clarity 59
3.6 On Clarity
Besides content-richness and coherence, a third important aspect of a knowledge-
rich curriculum is clarity. We will illustrate the importance of curricular clarity with
an example. In a Flemish technology curriculum at the macro level, it is stated that
students should be able to ‘illustrate how technical systems are based on knowl-
edge about material characteristics or natural phenomena.’ This example highlights
that while knowledge is seen as a prerequisite, it is not explicitly articulated but
viewed in function of skills. While this standard might be perceived as providing
‘autonomy in implementation’ to teachers, we previously noted that this freedom is
often exercised by entities other than teachers themselves. Additionally, as shown
earlier in the example from Wales, such objectives risk an incoherent curriculum,
making it difficult to establish clear and systematic plans for learning. Furthermore,
we also argued in the section on content selection that it is important to make choices
regarding curriculum content and that a thorough debate is necessary. Although this
debate is always social and political in nature, it is advisable to make clear deci-
sions. However, in such a debate there is a risk in problematic consensus-seeking
among different stakeholders, each aiming for their own content to be integrated.
The result of this could be an amalgam of vague objectives where it becomes unclear
what should and should not be included in the curriculum (Oates, 2011). Therefore,
setting clear expectations is a third important characteristic of a knowledge-rich
curriculum. We start this section by (a) emphasising the importance of clear goals
for teachers and student learning. We then move on to the issue of (b) interpreting
learning objectives and their impact on the discrepancy between the intended and the
achieved curriculum. Finally, we address (c) the importance of good alignment in
the educational system, including the curriculum, teaching, the teaching materials,
assessment and quality monitoring, and other aspects of the system.
3.6.1 The Importance of Clear Learning Goals
The first aspect of curriculum clarity, the importance of clear learning goals, is rather
straightforward: teachers should know what has previously been learned. If theyknow
what students ought to know and be able to do at a specific age or grade level, teachers
can effectively access and revisit existing prior knowledge before expanding on it.
Remember the experiment with the sequence 106614921815 in the first part of this
book? If knowledge and concepts are specified in the curriculum, the impact of prior
knowledge on further learning becomes not just individual, but collective. Teachers
can then draw upon a shared classroom foundation of prior knowledge rather than
relying on the fragmented understanding of individual students, and frantically trying
to provide that knowledge quickly to those who lack it.

60 3 Knowledge and the Curriculum
It seems crucial to further explore at what curricular level clarity in learning goals
should be organised to what extent. At the meso- and micro-levels, it is possible,
and perhaps even logical, for teachers to build on what has previously been learned
through clear objectives. However, the caveat that needs to be made here is that the
societal impact also remains limited to the meso- and micro-level of the curriculum,
namely the teachers, schools, or school groups that engage with it. If we revisit our
rationale, where from a social-democratic perspective we aim to provide a common
knowledge base, and give every child access to a robust knowledge foundation,
the biggest impact can be achieved by setting clear expectations at the curricular
macro level through clearly formulated goals. However, the level of specificity of
these learning goals might differ between subjects, and distinct curricular levels in
different educational systems. A shared understanding between educators is the goal,
clarity is a means to this end.
3.6.2 The Interpretation of Learning Goals
A second aspect of curriculum clarity pertains to the interpretation of learning goals.
As mentioned above, there is an ever-present discrepancy between what is intended
at the curricular macro-level, and the enacted curriculum in classrooms (Bauersfeld,
1979; Thijs & van den Akker, 2009). The teacher is the key mediating factor in this
translation process, deciding how the written curriculum turns into learning experi-
ences and, ultimately, the knowledge and skills learned by students. Returning to our
earlier example from the technology curriculum, ‘to illustrate how technical systems
are based on knowledge about material characteristics or natural phenomena’, it is
apparent that the possibilities to achieve this standard are boundless. For instance,
while one teacher might be engaging 6-year olds in crafting festive Christmas hats
from paper and cardboard, another might be introducing the principles of levers. The
broader the standards, the more diverse the interpretations, transforming education
into a lottery for students and parents regarding the depth and breadth of knowledge
and skills provided at distinct schools. From a democratic and social perspective, it
can even be argued that too broadly formulated learning goals jeopardise a shared and
coherent knowledge base, which introduces the possibility of increasing knowledge
inequality, and is most detrimental for disadvantaged students.

3.6 On Clarity 61
At the other end of the spectrum, an interesting example of integrating specific
knowledge elements in the curriculum, while maintaining some degrees of freedom
can be found in the following excerpt from the new English national curriculum, as
shown in Fig. 3.8.
While some content in this example is very specific, such as naming and locating
the world’s seven continents and five oceans, others are more open to interpreta-
tion, like ‘understanding geographical similarities and differences through studying
the human and physical geography of a small area of the United Kingdom and a
contrasting non-European country’. This provision enables geography teachers to
weave in local, contextual nuances when translating the intended curriculum into
practice. Concurrently, it establishes ‘non-negotiables’, namely a shared and specific
understanding of fundamental geographical facts and figures as important building
blocks for complex thinking skills within the geography domain.
Fig. 3.8 English national curriculum (retrieved from https://assets.publishing.service.gov.uk/
media/5a7c1ecae5274a1f5cc75e97/PRIMARY_national_curriculum_-_Geography.pdf)

62 3 Knowledge and the Curriculum
Fig. 3.8 (continued)
3.6.3 The Importance of Good Alignment
A third aspect regarding clarity, constitutes its impact on the alignment within the
system. First, the discrepancy between the intended and the achieved curriculum
will eventually depend on the teachers’ quality and the materials used. In some
countries, such as the UK, teachers seem to create many learning materials them-
selves (Oates, 2014). While this may appear positive at a first glance, there are
risks. Apart from the impact on workload, it may also lead to a lack of coherence
and clear learning progressions (Steiner et al., 2018). On the other hand, in many
countries teachers mainly rely upon textbooks, which seem to play a crucial role
in improving educational systems and in supporting effective teaching and learning
(Oates, 2014). However, the quality of these materials can vary significantly, directly
affecting learning outcomes and student achievement (Dockx et al., 2020), especially
where commercial, rather than educational, interests dominate textbook design. If
we combine these insights with the previous aspect, namely the interpretation of
learning objectives, we also see that in many systems where teachers tend to rely
heavily on textbooks, the interpretation of learning goals is mostly left to textbook

3.6 On Clarity 63
makers. Although some systems have quality control in place, others do not, and thus
the interpretation of learning objectives depends more on commercial players. There-
fore, clear learning goals at the macro and meso level have the potential to minimise
a variety of interpretations, hence minimising the discrepancy and assuring better
alignment between the intended, the enacted and the achieved curriculum.
Second, clarity in goals can not only lead to better alignment between the learning
goals and activities. Clarity also means that we can more reliably assess to what extent
these learning goals have actually been achieved. Consider, for instance, the contrast
between the following three intentions made at the beginning of the new year:
•I aspire to engage in more athletic activities in 2024.
•I have set my sights on increasing my running routine in 2024.
•I am determined to complete a marathon in November 2024 in less than three
hours.
While each of these intentions allows for a spectrum of interpretations and imple-
mentations, it is evident that the alignment and assessment of the last intention far
surpasses its predecessors. If learning goals are not stated clearly, they result in
a kaleidoscope of implementations while complicating the task of monitoring its
quality (Steiner et al., 2018). At the macro level, especially in countries where some
form of output regulation is organised through, for example, centralised testing or
inspection, clear expectations can lead to better alignment between the intended
and achieved curriculum and thus to better quality monitoring of the system itself.
Interestingly, Oates (2011) and Wiliam (2014) elaborate on this interaction between
curriculum and assessment at the macro level, and list several implications when this
interaction is poor. Regarding clarity, Oates (2011) suggests that when statements
are over-generic it will become difficult to develop fair tests due to the diversity
in learning programmes. Thus, validity will be compromised. This leads, perhaps
unexpectedly, to a form of teaching to the test in which “teachers have little choice
under such circumstances to do anything other than relate learning to past test papers
rather than the objectives of the curriculum, since the curriculum offers inadequate
guidance as to what will appear in the tests (Oates, 2011, p. 131)”.
While all of the above clearly points to the importance of clear learning objectives,
at the same time some caution is warranted. Specificity implies several risks, one
of which is the risk of curricular overload. Too many clear objectives could poten-
tially lead to a perverse effect where those clear goals are reduced to a checklist and
curriculum coverage instead of aiming for deeper understanding and true engagement
with knowledge. It could also lead to overassessment, resulting in either excessively
long tests, or tests that inadequately sample the domain, making it difficult to accu-
rately measure students’ achievements (Oates, 2011; Wiggins & McTighe, 2005).
An additional caveat is that increasing specificity is not easy to do. McTighe (2000,
p. 2) termed this the “Goldilocks problem”: some learning goals are too big, some
are too small and only a few are just right. In response to this problem, Wiggins and
McTighe (2005) suggest identifying the “Big Ideas” and curriculum priorities based
on the content, as illustrated in Fig. 3.9.

64 3 Knowledge and the Curriculum
Fig. 3.9 Big ideas. Retrieved from Wiggins and McTighe (2005, p.71)
A third factor regarding system alignment is the potential impact of curriculum
clarity on other aspects of education. If we expect kindergarten students to be
introduced to concepts such as plate tectonics and volcanoes, it is evident that teachers
delivering these contents should also have sufficiently mastered them (i.e., you cannot
teach what you do not know; Kirschner et al., 2022). In an environment where clear
concepts and knowledge lead the curriculum design, it is essential for teachers to
learn about it in initial teacher education or even earlier and refine their expertise
to align with evolving curriculum expectations. The curriculum therefore influences
what should be learned in teacher education and professional development. This line
of thinking might stir some debate in countries where teacher autonomy is cherished.
However, Priestley and colleagues (2021, p. 2) argue that “teachers will always find
ways to work around even the most prescriptive policies,” and that experienced
teachers were even more effective in doing so. Even with a specified and clear
curriculum, teachers still shape the enacted curriculum (Watkins, 1997). A curriculum
is transformed when it enters the classroom (Sizer, 1999; Stein et al., 2007); therefore,

3.6 On Clarity 65
teacher quality remains of the highest importance, even when implementing the
clearest curriculum.
Curriculum Case 4
Content, coherence and clarity into practice: The Primary Knowledge Curriculum
The Primary Knowledge Curriculum (PKC) has grown out of the Knowledge Schools
Trust, a group of seven schools in London and Berkshire. Since 2013, driven by the
idea of academic excellence and the desire to succeed for all children regardless of
their background, this school group has been developing and enacting a knowledge-
rich curriculum for its primary schools. To date, the Knowledge Schools Trusts has
already worked with hundreds of schools and trusts nationwide in various contexts
and supported them in embedding this curriculum in combination with high-quality
professional development. The PKC is characterised by ambitious content that is
well-specified and well-sequenced, horizontally as well as vertically. In what follows
we will show how the three c’s (content, coherence and clarity), as described above,
can be put into practice.
Content-richness. The Primary Knowledge Curriculum is based on the idea of
powerful knowledge. Its aim is for children to acquire knowledge that takes them
beyond their everyday experiences through the knowledge and traditions of various
disciplines. Looking at concepts through the lens of different disciplines, each having
their own traditions and unique way of looking at the world, provides the opportu-
nity to develop a deep understanding. For instance, while learning about Chinese
painting in year 5 arts lessons children also learn about the Ming dynasty. In the
example below, this is illustrated with the concept of ‘trade’, a concept that is tackled
through history, geography and even arts.
Coherence. As previously stated, concepts are taught and learned in depth using
knowledge from various disciplines. In contrast to thematic approaches, where the
boundaries between disciplines sometimes blur, the PKC places importance on the
distinct disciplines themselves, given the specific traditions that make each of these
approaches unique. Crucial importance is also attached to vertical coherence, not only
within but also across disciplines: In order being able to learn about globalisation in
year 6 the foundations for the concept of “trade” are already put in place in the early
years. In year 2, for instance, children learn in history lessons about ancient Romans
in Britain and that forums functioned as marketplaces (as shown in Fig. 3.10). In year
3, from a geographical perspective, children learned that rivers are used by people
to trade and that major cities developed alongside them. Furthermore, they learn
that trade is the buying and selling of goods and services, and that many goods and
services are being traded in Western Europe. From a historical perspective, children
learn that unique skills and their products become valuable trade items in lessons
about the Neolithic Age and about the link between migration and the exchange
of goods, ideas, and technologies when encountering the Anglo-Saxons, Scots, and
Vikings. As Fig. 3.10 shows, clear learning paths are designed, leaving very little to
chance.

66 3 Knowledge and the Curriculum
Fig. 3.10 Theme based curriculum building through disciplinary knowledge sequencing.
source Primary Knowledge Curriculum
Clarity. The PKC is furthermore characterised by specifying the content to be
learned. As illustrated by Fig. 3.11, learning objectives are formulated as big ideas that
year 3 students need to capture as well as key vocabulary they need to master. Through
specification of content, it becomes possible for teachers to purposely identify prior
learning and then to build upon it.
Complex skills. By systematically building a solid foundation of knowledge and
vocabulary within and across disciplinary domains, children become capable of
undertaking complex activities, such as writing nuanced essays in which they address
complex research questions like “how has globalisation changed the world.” This is
illustrated in the following example by a year 6 student (Fig. 3.12). These tasks not
only allow students to demonstrate their learning but also reinforce and deepen their
understanding.

3.6 On Clarity 67
Fig. 3.11 Detailed lesson plan of a knowledge-rich curriculum. source Primary Knowledge
Curriculum (PKC)
In summary, the curriculum as a concept is complex in its conceptualisation and
how it is built and enacted in our educational institutions. Over the years the role
of knowledge in the curriculum has, like a pendulum, shifted between extremes.
Taking into account what we know from both the first and second part of this book,
we want the best of both worlds, what has been identified as a knowledge-rich
curriculum. This involves three overarching principles that we found to be most
beneficial in understanding how a knowledge-rich curriculum can enhance learning,
namely (1) content-richness, (2) coherence, and (3) clarity. Now that we know what
a knowledge-rich curriculum looks like and why it is important, we will take a closer
look at what is currently known about a knowledge-rich curriculum and student
achievement.

68 3 Knowledge and the Curriculum
Fig. 3.12 Essay writing in a knowledge-rich curriculum. source own photograph
3.7 A Knowledge-Rich Curriculum and Student
Achievement
At the supra level, international assessments such as the Programme for International
Student Assessment (PISA), organised by the OECD, and Trends in International
Mathematics and Science Study (TIMSS), administered by the IEA, are large-scale
surveys designed to assess pupil achievement across a number of countries. Some
results at these levels seem to indicate that structured knowledge-led approaches lead
to better results than skills or competence-based approaches, including for developing
applied skills (Crato, 2021, p. 19). Some countries’ experiences also point into the
same direction. In Portugal, for instance, a structured and knowledge-led curriculum
at the macro level led to impressive improvements, followed by a significant drop

3.7 A Knowledge-Rich Curriculum and Student Achievement 69
when this trend was subsequently reversed (Crato, 2022, p. 54–55), both in terms
of average student scores and in terms of equal educational opportunities. Although
these macro-level statistics are correlational in nature, and can therefore only suggest
relations and not determine causal effects, and while we know that the implementation
from a written curriculum at the macro level until its enactment in the classroom is
quite complex and challenging (Stein et al., 2007), promising experimental evidence
at the meso and microlevel seems to corroborate these positive findings with regard
to student achievement.
Until recently, the effects of building background knowledge through a
knowledge-rich curriculum on primary students’ achievement had only been inves-
tigated in a limited number of experimentally designed interventions. Those inter-
ventions typically focused on building domain and topic knowledge in first, second,
and/or third grade with a view to improving reading comprehension, ranged between
1 and 3 years, and showed significant but small, or no effects on standard measures
of reading comprehension (Connor et al, 2013; Kim et al., 2021,2023; See et al.,
2015).
However, a recent large-scale experimental study (Grissmer et al., 2023) suggests
that the former interventions might not have been implemented early and long
enough for larger effects to accumulate. This study measured the long-term effects
on Reading/English Language Arts, Science, and Mathematics achievement after 4–
7 years of intervention in 14 Charter schools using the Core Knowledge Sequence,
which specifies topics and their sequence and suggests materials (Core Knowledge
Foundation, 2010). Interestingly, the K-8 curriculum that was used was implemented
from kindergarten onwards, and the Reading/ English Language Arts and Mathe-
matics measurements (state achievement data) were collected in 3rd to 6th grade,
and those for science in 5th grade. Across all schools, students’ Reading/English
Language Arts results significantly improved with 16 percentile points, the equiva-
lent of raising US performance from 15th out of 50 countries to the top 5 in the 2016
PIRLS test.
Moreover, as reading and verbal comprehension are essential for further learning
in all subjects, these results suggest that students’ future achievement is likely to
also increase in many other areas. More promising even with a view to educational
equality, is the fact that at a low-income school in the sample, achievement gaps at
third to sixth grade in Reading/English Language Arts, Science, and Mathematics
were completely eliminated, suggesting that systematically building general knowl-
edge in primary school could also help address educational inequality and diminish
the Matthew effect (Kaefer et al., 2015; Pfost et al., 2014; Rigney, 2010; Stanovich,
1986). Replicating and extending this study by profoundly analysing knowledge-rich
curriculum implementation and enactment, and mapping the intermediating factors
and their effects on student achievement may be one of the most crucial endeavours
in current educational research.

70 3 Knowledge and the Curriculum
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References 73
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give appropriate
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the copyright holder.

Chapter 4
Concluding Remarks
Over the course of several decades, the position of knowledge within education has
been marked by turbulence and notable fluctuations. However, recent advancements
in cognitive psychology, and a shift in sociological and democratic perspectives have
created a more favourable environment for a revaluation of the concept of knowledge.
Now, it has the opportunity to play a central role within education and curriculum: that
of the essential condition for future learning. In cognitive psychology, we observed
that existing knowledge schemas in long-term memory support human thought so
that we can successfully complete complex thinking tasks, such as problem solving,
critical thinking, and deep reading comprehension. From a sociological perspective,
we noted how distinct epistemological ideas and societal trends changed the percep-
tion of knowledge, and how a new school of thought has emphasised its return and
vital role for social justice and equitable opportunities for all. In addition, from a
democratic standpoint, knowledge has been found crucial in ensuring that individ-
uals are empowered to contribute meaningfully to both societal and professional
debates.
All of the above has implications for the curriculum. While earlier, the curriculum
either metaphorically tended to promote knowledge tick box behaviour, or, at the
other extreme, tended to rely on almost knowledge-free competency-based concepts,
we are now evolving towards a knowledge-guided curriculum that values knowledge
in itself, yet also attaches specific skills to particular knowledge domains. Although
we know that teaching generic skills has little to no transfer, teaching complex skills,
such as problem-solving and critical thinking, should not be abandoned. When care-
fully built with knowledge as a foundation within a domain, we can achieve both
knowledge building and complex thinking by engaging deeply with that knowledge.
Van Merriënboer and Kirschner (2017) refer to the teaching of this and the support of
its achievement as first- and second-order scaffolding. The first positive effects from
longitudinal studies of implementing a knowledge-rich curriculum are promising,
and we look forward to further research on creating and implementing a curriculum
that is characterised by content-richness, coherence, and clarity.
© The Author(s) 2025
T. Su r ma et a l ., Developing Curriculum for Deep Thinking,
SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-74661-1_4
75

76 4 Concluding Remarks
This rebirth of knowledge in the curriculum has various implications for the field
of education. In some cases, the curriculum has been underplayed in educational
policymaking, often focusing on issues such as the structure and governance of
education systems or qualification frameworks. While these are important matters,
what children and young people learn is of central importance and should therefore
lie at the heart of educational policy. An effective system is marked by coherence,
in which all aspects of the educational system are well aligned with each other, not
only within and across subjects in the form of clear learning progressions, but also in
the form of assessment, inspectorate, teacher autonomy, accountability, professional
development, etc. Based on the rationale and educational purposes, the curriculum
is at the heart of this process. A knowledge-rich curriculum should therefore be
designed for coherence and progression using effective design methods. Coherence
and progression are created by connecting big ideas, specific content, knowledge and
complex skills aiming at full knowledge engagement, a concept-cohering process that
connects the curriculum material to students’ cognition. Dangers, however, lie in the
fact that the curriculum can become a political football field in which government offi-
cials and other educational stakeholders constantly add their own favourite elements,
including all of the societal problems that education is expected to solve but is not
capable of solving, as happened with the secondary English Language curriculum
in England. Another risk is problematic consensus-seeking, resulting in vague and
unclearly formulated learning goals, affecting both curricular coherence and clarity.
Decisions will have to be made. Therefore, an arm-length curriculum body is best
tasked with formulating and revising the curriculum. For example, a planned cycle
of regular reviews should be incorporated into the curriculum development process
and be a statutory task of the curriculum body.
Finally, a knowledge-led curriculum also has implications for teachers’ education
and professional development. The introduction of a knowledge-rich curriculum
needs to be accompanied by an extensive program of continuous professional devel-
opment (CPD) for teachers and school leaders, and will involve significant changes
in the curriculum for initial teacher education. Teacher education and ongoing
CPD initiatives should include the principles and methods of effective knowledge
design. Teachers should understand how coherence occurs, how subject concepts
connect to materialised content, why engagement with knowledge should follow the
subject concept-content selection, and the relationship between this concept-cohering
curriculum and the intellectual processes which build students’ cognitive architec-
ture. Teacher quality remains paramount to successfully implement a knowledge-rich
curriculum.
Designing a coherent curriculum is not an easy task and requires thorough
thinking. “As a result, curriculum is, and should be, a most contested topic, the
essence of democratic debate, and the core debate about what is taught and valued
in schools” (Hattie, 2023, p. 304).

References 77
References
Hattie, J. (2023). Visible learning: The sequel: A synthesis of over 2100 meta-analyses relating to
achievement. Taylor & Francis.
Van Merriënboer, J. J., & Kirschner, P. A. (2017). Ten steps to complex learning: A systematic
approach to four-component instructional design. Routledge.
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give appropriate
credit to the original author(s) and the source, provide a link to the Creative Commons license and
indicate if changes were made.
The images or other third party material in this chapter are included in the chapter’s Creative
Commons license, unless indicated otherwise in a credit line to the material. If material is not
included in the chapter’s Creative Commons license and your intended use is not permitted by
statutory regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder.

Chapter 5
Executive Summary
Nearly all teachers and other stakeholders in education pursue a common aim: we
want the students whom we teach and guide during their formative years to think
deeply about what we teach them. We want them to be able to go beyond their
current experiences and have a deep understanding of the world. We want them to
be able to think critically, work together, solve problems, read for understanding,
and perform many other complex tasks. This book discusses why the apparently
obvious strategy of simply teaching children how to think deeply does not work and
offers an alternative way forward. It reviews the evidence for the prominent role of
knowledge in how we learn, think, read, understand, and solve problems, drawing
ideas from cognitive psychology, educational psychology, sociology, and curriculum
studies, combined with real-life classroom experiences. Its goal is to elucidate why a
knowledge-rich curriculum is not only the soundest way forward to both effectively
teach knowledge and complex skills in school, but is also crucial if we hope to achieve
equitable opportunities for all students.
5.1 How Knowledge Matters
5.1.1 Knowledge Matters: A Learning Perspective
When we speak of knowledge in educational systems, we refer to biologically
secondary knowledge (Geary & Berch, 2016) which, as opposed to biologically
primary knowledge, cannot be acquired spontaneously, and must be consciously
taught and effortfully learned. Examples include reading and writing, solving alge-
braic problems, and engaging in discussions about geographical, scientific, political,
cultural, and historical phenomena. From a cognitive psychology standpoint, the
© The Author(s) 2025
T. Su r ma et a l ., Developing Curriculum for Deep Thinking,
SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-74661-1_5
79

80 5 Executive Summary
value of a well-established knowledge base for learning is unequivocally recog-
nised. Humans have the capacity to construct a robust knowledge base within long-
term memory, which provides us with resources to enhance the efficacy of working
memory during cognitive tasks (Baddeley & Andrade, 2000; Baddeley & Hitch,
1974). What you know determines what you see (Kirschner, 1991). The more exten-
sive one’s knowledge base is in terms of both its breadth and depth, the more easily
new knowledge is acquired and remembered (Alexander et al., 1994; Ausubel, 1968;
Shapiro, 2004). Complex schemas of interconnected ideas can then serve as concep-
tual coat hangers or anchors for the organisation of knowledge and learning new
ideas (Hattie, 2023). However, knowledge alone does not lead to improved learning.
To be effective, prior knowledge must be activated, relevant, and congruent. Then
its impact on learning can be significant (Brod, 2021). Knowledge is also crucial for
carrying out complex cognitive skills, such as critical thinking (you think critically
about something; Willingham, 2019), problem solving (you solve problems in some-
thing; De Bruyckere et al., 2020; Thorndike, 1923; Willingham, 2021), and reading
comprehension (you can decode and subsequently comprehend something written
about something; Kendeou & Van Den Broek, 2007; Kintsch, 1998; Kintsch & van
Dijk, 1978; McCarthy & McNamara, 2021; Willingham, 2017). Indeed, seemingly
counterintuitively, the best ways to become proficient in a skill often do not resemble
the skill itself (Wiliam, 2018). The more robust one’s knowledge base, the more
seamlessly and efficiently these complex cognitive skills—precisely, those teachers
aim to develop in their students—are acquired and can be carried out.
5.1.2 Knowledge Matters: A Sociological Perspective
Our perspective on knowledge is shaped by the lens through which we view it. When
examining knowledge from a sociological perspective, it is evident that its signif-
icance has been subject to fluctuating societal trends. Societal viewpoints have, at
times, overshadowed the importance of knowledge, yet social realists (Barrett, 2024),
sociological theorists who have emerged as successors of constructivist thinkers
(Rata, 2024a), agree that focusing on rich and broad content knowledge ensures that
all students, regardless of background, have equal access to a foundational body of
knowledge, reducing disparities, and promoting a more inclusive educational expe-
rience. For this reason, they argue for the need to ‘bring knowledge back in’ (2024a;
Muller, 2000; Rata, 2012; Wheelahan, 2007; Young, 2007). In that regard, Young
(2009,2013) produced a theory of powerful knowledge, acknowledging that while
knowledge is socially produced, some types of knowledge are more powerful, and,
yes, ‘better’, than others. He positions the production of powerful knowledge within
specific social and intellectual groups, often represented by academic disciplines.
This disciplinary knowledge then needs to be translated by expert teachers and
subject specialists, thus providing students with more dependable interpretations
and insights into the world, and allowing them to think about topics and subjects
their experiences alone would have never let them have access to.

5.1 How Knowledge Matters 81
5.1.3 Knowledge Matters: A Democratic Perspective
Deciding what our children should learn does not only play a role in what we want
the future for our society to be like, but also in who we want our children to become.
This leads us to a very difficult question: What kind of knowledge is that important
that we will not leave its transmission up to chance? A question that becomes even
more difficult to answer as the production of knowledge in our society grows. One
could argue that the response to this question depends heavily on the answer to an
other question: What is the purpose of education? Although there are many possible
answers, most can be divided into four broad categories: personal empowerment,
cultural transmission, preparation for work, and preparation for citizenship (Wiliam,
2013). These broad philosophies do not exclude one another, but are sometimes in
conflict. A balance is needed, as one without the other can have unwanted conse-
quences. When examining knowledge from a democratic perspective, one cannot
overlook the ideas of E.D. Hirsch and his notions of cultural literacy, which he
defined as “possessing the basic information needed to thrive in the modern world”
(Hirsch, 1988, p. XIII). When communicating, we assume a vast amount of shared
background knowledge. For disadvantaged students, who may face limitations in
exposure to a rich array of experiences and information outside schools, this can
limit them, not due to a lack of ability, but because of a lack of access to knowledge.
This is why, when knowledge is no longer explicitly addressed in schools, or assumed
to be primarily constructed from children’s own experiences, the most disadvantaged
students suffer the most. This is problematic not only for these individuals but also
for society as a whole. As Hirsch (2009) states, shared knowledge fosters a sense
of commonality among diverse citizens in a democratic society. In a society charac-
terised by cultural diversity, a common body of knowledge ensures that citizens can
engage in informed discussions, debates, and decision-making processes. It promotes
a sense of belonging and inclusivity as individuals draw upon shared references that
go beyond individual differences. When access to this shared knowledge is hindered
or not evenly distributed, issues of inequality in education may widen. This is why
the erosion of the role of knowledge within the educational landscape can have dire
consequences (Hirsch, 2016).
Social realists (Barrett, 2024) share Hirsch’s views on the importance of knowl-
edge in our society and its vital role in education. Yet, they relocate (powerful)
knowledge within academic disciplines, making what is taught and learned in class-
rooms more reflective of the characteristics of disciplinary knowledge developed by
specialist communities. They also share Hirsch’s view on knowledge as a prereq-
uisite for fostering equitable opportunities for all and social justice. Wheelahan
(2010) further strengthens this viewpoint from a democratic perspective, emphasising
the crucial role of disciplinary knowledge as socially powerful knowledge. It arms
students with the language to participate in discussions on politics, morality, envi-
ronmentalism, migration, and many other topics prevalent in civil society. Further-
more, it also gives them the capacity to scrutinise the foundations of knowledge,
the authority upon which it stands, and thus, the tools to be critical of it (Young,

82 5 Executive Summary
2007). In sum, while deciding what knowledge ought to be provided to our children
will (and should!) always be the result of societal debate, ensuring that knowledge
itself is not forgotten is crucial for equitable opportunities for all and our democratic
society. Hirsch has shown the importance of a common knowledge base and helped
bring knowledge back into conversation, whereas social realism has brought knowl-
edge back into social theory, while at the same time emphasising the importance
of the disciplinary aspect of knowledge. All these factors have implications for the
curriculum.
5.2 Knowledge and the Curriculum
5.2.1 Everything Starts with the Curriculum
The curriculum is complex in its conceptualisation and how it is made and takes form
in our educational institutions. For the sake of clarity and for the purpose of this book,
we define the curriculum as a ‘plan for learning over time’ (Taba, 1962; Thijs & van
den Akker, 2009). Highlighting some factors regarding the complexity of curriculum
as a concept may help clarify why curriculum is at the centre of so many educational
debates, and why these debates are so important. A first factor to consider is the broad
or narrow perspective that you adopt when considering the concept of ‘curriculum’.
Learning is not limited to what happens at school; students’ social environment also
plays a significant role. These aspects are also referred to as the societal curriculum
(Deng, 2017). In this book we focus on the content and learning activities organised
at school and the system behind it (Tyler, 1949; Popham & Baker, 1970), yet we take
into consideration these important factors that can influence the learning potential of
students.
A second, and perhaps even more important, factor is the fact that the curriculum
depends on a conception of education and learning. What do we value as society, as
schools, as teachers, and what is the goal of schooling? The work of Tyler (1949)
and van den Akker (2003) provides us with valuable guidelines in this regard. A
third factor to consider is that determining what we want students to learn does not
automatically equal what students actually learn, due to discrepancies between the
intended curriculum (what we want students to learn), the implemented curriculum
(how these intended learning goals are then enacted), and the attained curriculum
(what students actually learned) (van den Akker, 2009). Besides the curricular inten-
tions, teachers and textbooks also act as mediating factors in what is actually taught
to students. Due to the way in which the school’s work is planned and organised,
and through the materials provided students can also learn things that are not overtly
included in the curriculum, the so-called hidden curriculum (Kelly, 2009). All of
the above then leads to a fourth factor, namely that the curriculum can be organ-
ised at different levels, which Priestley and colleagues (2021) categorise as (1) the
supra level; (2) the macro level; (3) the meso level; (4) the micro level; and (5)

5.2 Knowledge and the Curriculum 83
the nano level. In sum, considering the context and rationale at the different levels,
and taking into account the insights about the intended, implemented, attained, and
hidden curriculum, it can easily be concluded that implementing a curriculum is
indeed complex and should be subject to thorough debate.
5.2.2 Curriculum as a Pendulum
Over the years the role of knowledge in the curriculum has, like a pendulum,
shifted between two extremes, from highly visible to virtually invisible knowledge
elements. These extremes can be positioned in Young and Muller’s (2010) perspec-
tives of thinking about curriculum, which they labelled ‘futures’. The former, with
highly visible knowledge elements, corresponds with the so called Future 1, where
a curriculum can be described as a collection of learning content, treating knowl-
edge as fixed, unchanging, and based on tradition. The latter, with virtually invisible
knowledge elements, corresponds with Future 2 and prioritises an outcome-based
curriculum that reduces knowledge’s central role in further learning and in devel-
oping complex skills. It is important to underline that the historical shift from Future 1
to Future 2-curriculum involved the elimination of both the negative ánd the positive
elements of Future 1, which is why a curricular return to knowledge must consider
the lessons learned from both futures (Muller, 2023). Social realists have termed this
solution Future 3, from here on referred to as a ‘knowledge-rich curriculum’.
5.2.3 Towards the Best of Both Worlds: A Knowledge-Rich
Curriculum
A knowledge-rich curriculum constitutes a plan for learning over time that is concept-
led and knowledge-led (Oates, 2011), which encompasses a wide range of specified
knowledge, and provides ample depth and opportunities to engage with that knowl-
edge (Rata, 2021). It sets high expectations for all students and systematically builds
their knowledge of words and the world (Hirsch, 2016). It aims at a broad and steady
foundation for complex thinking skills, such as critical thinking and reading compre-
hension, as well as knowledge building, which are further amplified and deepened by
these complex skills. A comprehensive knowledge-rich curriculum covers subjects
and concepts that go beyond children’s day-to-day experiences and is based on the
’best’ disciplinary knowledge available at that time (Young & Lambert, 2014). It
ensures that every child has access to a broad and solid knowledge base in school,
even if it has not been (partially) acquired from an early age onwards outside school.
Three overarching principles were found to be most beneficial for understanding
how a knowledge-rich curriculum can enhance learning: (1) content richness, (2)
coherence, and (3) clarity.

84 5 Executive Summary
In terms of content richness, four important elements are thoroughly discussed: (a)
which content to select; (b) on what basis choices can be made; (c) how hierarchy and
structure in knowledge have an impact on sequence; and (d) how to balance knowl-
edge and skills in a knowledge-rich curriculum. Curriculum coherence entails (a)
vertical coherence, that is, considering the organisation of the concepts and content
within it, which is vital if one is to create a seamless and logical conceptual progres-
sion in what students learn over time; and (b) horizontal coherence, that is, how
these concepts align with each other across subjects (Thijs & van den Akker, 2009).
Moreover, it should also consider (c) the structure of the knowledge itself (Schmidt
et al., 2002; Rata, 2021). Big ideas can be used as a starting point, which can subse-
quently be broken down into several important components, such as what needs to be
assessed, what evidence is needed to determine whether students really understand
certain concepts, and what students need to be able to know and do (Hattie, 2023;
McTighe, 2000; Wiggins & McTighe, 2005; William, 2013). Clarity is the third
important feature of a knowledge-rich curriculum. In view of setting clear expecta-
tions, the following elements are discussed: (a) emphasising the importance of clear
goals for teachers and student learning; (b) interpreting learning objectives and their
impact on the discrepancy between the intended and the achieved curriculum; and
(c) the importance of good alignment in the educational system.
5.2.4 A Knowledge-Rich Curriculum and Student
Achievement
Until recently, the effects of building background knowledge through a knowledge-
rich curriculum on primary students’ achievement had only been investigated in a
limited number of experimentally designed interventions, and showed small, or no
effects on student achievement (Conor et al., 2013,Kim,etal.,2021; Kim et al., 2023;
See et al., 2015). However, a recent large-scale experimental study (Grissmer et al.,
2023) suggests that the former interventions might not have been implemented early
or long enough for larger effects to accumulate. The K-8 Core Knowledge Sequence
was implemented In 14 U.S. Charter schools from kindergarten onwards, and after
four to seven years of intervention across all schools, students’ Reading/English
Language Arts results significantly improved with 16 percentile points, the equiva-
lent of raising US performance from 15th out of 50 countries to the top five in the
2016 PIRLS test. A low-income school in the sample showed even more promising
results, completely eliminating achievement gaps at third to sixth grade in Reading/
English Language Arts, Science, and Mathematics. This suggests that systematically
building background knowledge in primary school could also help address educa-
tional inequality and diminish the Matthew effect (Rigney, 2010; Stanovich, 1986).
Replicating and extending this study may be one of the most crucial endeavours in
current educational research.

References 85
5.3 Concluding Remarks
Revitalised by contemporary democratic and social perspectives, and bolstered by
consistent findings from cognitive psychology, we are now witnessing a revival of the
importance of knowledge in education. It has now re-emerged as a prerequisite for
improved learning, critical thinking, problem-solving and reading comprehension,
as a facilitator for collective discourse, and as a catalyst for equitable opportunities
for all. All of the above has implications for the curriculum. Earlier, the curriculum
either tended to promote knowledge tick box behaviour, or, on the other extreme,
tended to rely on almost knowledge-free competency-based concepts. We are now
evolving towards a knowledge-guided curriculum that values knowledge in itself,
yet also attaches specific skills to particular knowledge domains. Although we know
that teaching generic skills has little to no transfer, teaching complex skills, such
as problem-solving and critical thinking, should not be abandoned. When carefully
built with knowledge as a foundation within a domain, we can achieve both knowl-
edge building and complex thinking by engaging deeply with that knowledge. The
first positive effects from longitudinal studies of implementing a knowledge-rich
curriculum are promising, and we look forward to further research on creating and
implementing a curriculum that is characterised by content richness, coherence, and
clarity.
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Appendix
How is Knowledge Remembered?
Let’s explore what it takes to store knowledge effectively in our long-term memory.
As stated earlier, a key element in learning is what we already know. It’s much
easier to add new information to an organised set of existing knowledge than to start
learning something completely new. However, when we don’t have much relevant
prior knowledge, we face the challenge of our working memory’s limited capacity
and need to find ways to efficiently process all the new information coming in.
There are two main challenges with long-term memory: first, developing effective
ways to encode information so that it’s fully processed and second, using retrieval
strategies that make it easier to access memories. There’s a wealth of books and
articles on learning principles that address both challenges, which are valuable
resources for further reading. To give you a starting point, we will outline some key
learning strategies that relate to learning and teaching the curriculum (Table A.1).
Based on Winne & Nesbit, 2010; Dunlosky et al., 2013; Hattie & Yates, 2013;
Koedinger et al., 2013
© The Editor(s) (if applicable) and The Author(s) 2025
T. Su r ma et a l ., Developing Curriculum for Deep Thinking,
SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-74661-1
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90 Appendix: How is Knowledge Remembered?
Table A.1 principles that promote durable learning
Learning principle Learners benefit when …
Worked examples They see how success looks like instead of being left to discovery
methods. Worked examples provide a form of modelling through
demonstrations of successful procedures or products.
Dual code and
multimedia
Words are accompanied by relevant pictures. Our working memory can
combine words and images efficiently.
Coherence Materials and multimedia explicitly link related concepts to each other
and minimise distracting irrelevant material.
Segmentation Complex new information is broken down into manageable and
structured subparts.
Prior knowledge Relevant prior knowledge is activated.
Multiple examples Multiple examples (such as concrete and varied representations, stories)
are provided, compared.
Practice New knowledge is practiced.
Interest Content is grounded in real-world issues that hold significance for the
learner.
Spaced practice Learning sessions are spaced over time compared to massing learning
sessions.
Retrieval practice They retrieve information from memory compared to recognise or
reread information.
Generative practice They think about and produce explanations, outlines, summaries,
drawings, answers, mindmaps from memory compared to having them
recognise or reread information.
Scaffolding Support is adjusted to learners needs, and removed when they get more
knowledgeable.
Interleaved practice Practice sessions intermix different comparable knowledge and skills
compared to practicing them in a block fashion.
Test expectation They expect a final test or exam.
Feedback Feedback on their performance in a learning task is provided.
Questioning and
explaining
They pose and answer deep-level questions that elicit explanations.
Self-regulated
learning
They receive explicit instruction in how to self-regulate their learning as
learners often lack an an accurate understanding of their own cognitive
processes.

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© The Editor(s) (if applicable) and The Author(s) 2025
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SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-74661-1
91