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Making learning visible: The role of concept mapping in higher education

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  • University of Surrey and University of Wisconsin- Madison

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This article develops the concept-mapping method as a tool for enhancing teaching quality in higher education. In particular, it describes how concept mapping can be used to transform abstract knowledge and understanding into concrete visual representations that are amenable to comparison and measurement. The article describes four important uses of the method: the identification of prior knowledge (and prior-knowledge structure) among students; the presentation of new material in ways that facilitate meaningful learning; the sharing of 'expert' knowledge and understanding among teachers and learners; and the documentation of knowledge change to show integration of student prior knowledge and teaching. The authors discuss the implications of their approach in the broader context of university level teaching. It is not suggested that university teachers should abandon any of their tried and tested methods of teaching, but it is shown how the quality of what they do can be significantly enhanced by the use of concept mapping.
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Studies in Higher Education
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Making learning visible: the role of concept mapping in higher education
David Haya; Ian Kinchina; Simon Lygo-Bakera
a Kings College London, UK
To cite this Article Hay, David , Kinchin, Ian and Lygo-Baker, Simon(2008) 'Making learning visible: the role of concept
mapping in higher education', Studies in Higher Education, 33: 3, 295 — 311
To link to this Article: DOI: 10.1080/03075070802049251
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Studies in Higher Education
Vol. 33, No. 3, June 2008, 295–311
ISSN 0307-5079 print/ISSN 1470-174X online
© 2008 Society for Research into Higher Education
DOI: 10.1080/03075070802049251
http://www.informaworld.com
Making learning visible: the role of concept mapping in higher education
David Hay*, Ian Kinchin and Simon Lygo-Baker
Kings College London, UK
Taylor and FrancisCSHE_A_305093.sgm10.1080/03075070802049251Studies in Higher Education0307-5079 (print)/1470-174X (online)Original Article2008Society for Research into Higher Education333000000June 2008DavidHaydavid.2.hay@kcl.ac.uk
This article develops the concept-mapping method as a tool for enhancing teaching quality in
higher education. In particular, it describes how concept mapping can be used to transform
abstract knowledge and understanding into concrete visual representations that are amenable
to comparison and measurement. The article describes four important uses of the method: the
identification of prior knowledge (and prior-knowledge structure) among students; the
presentation of new material in ways that facilitate meaningful learning; the sharing of
‘expert’ knowledge and understanding among teachers and learners; and the documentation
of knowledge change to show integration of student prior knowledge and teaching. The
authors discuss the implications of their approach in the broader context of university level
teaching. It is not suggested that university teachers should abandon any of their tried and
tested methods of teaching, but it is shown how the quality of what they do can be
significantly enhanced by the use of concept mapping.
Introduction
In the UK (as in many countries), higher education has changed dramatically in the last 20 years.
The numbers of students taking part in university education has risen from 500,000 in the 1960s
to 2 million today (see the Higher Education Research Opportunities website; HERO 2007). As
participation has increased, so too has the variety of entry-level qualifications and experiences,
cultures, expectations and motivations of our university students. Some aspects of the qualifica-
tion process have also changed. Modular course provision has become common, and assignment
tasks tend to be richer and more varied than they previously were. Nevertheless, the basic meth-
ods of university teaching remain largely unchanged. This is despite significant increase in aver-
age class size and a considerable decline in staff to student teaching ratios. In large-class
situations, in particular, many lecturers are troubled by an apparent lack of opportunities for
student questions, the difficulty of achieving genuine student-centred teaching and a real need
for tools with which to measure student learning quality. These issues are the concern of this
article. To address them we focus on just one method – concept mapping – and show how it can
be used to enhance the quality of university teaching without recourse to large-scale change in
teaching methodology.
The article is presented in three parts. First, we explore what it means to learn at university
level. We develop a simple definition of learning with utility among all of the cognate disciplines
of higher education. We use this as a framework for better understanding university teaching
practice, and identifying some of the issues that must be addressed if university teaching is to be
improved. Second, we explain the concept mapping method and show how it can be deployed in
the course of teaching. We focus on the ways that lecturers can identify and respond to the needs
of their students (even among large classes), and we show how students can be helped to learn
*Corresponding author: Email: david.2.hay@kcl.ac.uk
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296 D. Hay et al.
meaningfully for themselves. We end the article with a brief discussion of the wider role of the
university academic. Many university staff appointments require commitment to both teaching
and research. We show how research into student learning within specific subjects and disci-
plines can help to integrate teaching and research activities. We argue that concept mapping can
facilitate teacher–student interactions in the creation and extension of knowledge, as well as its
transmission. We suggest that the emergence of new and individually acquired meaning is a
genuinely authentic definition of higher education.
Towards a common definition of university learning
It is an aim of this article that we explore and develop a common definition of university-level
learning. There are several important texts on university teaching (e.g. Prosser and Trigwell
1999; Nicholls 2002; Ramsden 2002), and all of them offer significant insights into what it
means to teach at university level. They also all agree that university teaching should be under-
pinned by a theory of learning, but none attempts to define a general model of university learn-
ing. Instead they draw heavily on the research into student learning approaches (e.g. Säljö 1975;
Marton and Säljö 1976, 1984; Entwistle, Meyer and Tait 1991). As a consequence, many of these
texts emphasise issues of ‘difference’ among learners as a basis for teaching. This is not easily
reconciled with the demands that are faced by the teachers of higher education (Nicholls 2002).
The ‘learning style’ literature is also circumspect, because it lacks any underpinning theory (see
Coffield et al. 2004a, b), and often fails to distinguish between the different processes of learning
and of teaching (Jarvis 2006).
Learning as change
In order to provide an alternative to the ‘learning style’ approach we start with one of the most
widely used general models of adult learning: Kolb’s learning cycle (Kolb and Fry 1975). This
is shown in Figure 1.
Figure 1. Kolb’s learning cycle (after Kolb and Fry 1975).
Kolb and Fry (1975) describe learning as a cycle. First the person has an experience [1], then they observe and reflect upon it [2]. This is done in order to form new ways of thinking about the subject [3], so that finally what has been newly understood can be tested [4] before the phases of the cycle are repeated.
Although Kolb’s learning cycle has its origins in the literature of continuing education, there
can be little doubt that it can contribute to an understanding of learning at university level. This
is because it takes ‘experience’ as the starting point for learning, and suggests that learning
occurs by similar and sequential processes. Thus, individuals must experience, reflect, theorise
and test new knowledge in order to learn. Kolb and Fry (1975) suggest that this is true of learners
in all situations, including the classroom experience of formal teaching. The approach subsumes
the notions of difference, since it suggests that, while different people may have different affin-
ities for one part or other of the cycle, ultimately learning occurs only when the cycle as a whole
is complete.
A similar approach has been developed by Jarvis (e.g. Jarvis 1992, 1993). Jarvis interviewed
200 students (Jarvis 1993) and used their descriptions of learning to build general and abstract
descriptions of learning (Jarvis 1992). These were then combined to construct a single model
(Figure 2).
Figure 2. Jarvis’s model of learning (after Jarvis 1992).Jarvis (1992) states that the person [1] is the most important element in any description of learning. This is because he defines learning as personal change (compare the difference from [1] to [9] and from [1] to [4]). According to Jarvis, there are nine possible outcomes of learning (or non-learning) and these can be defined by the various routes through the processes of reflection, evaluation, experimentation and memorisation.
The model has some broad similarities with Kolb’s learning cycle but it is also different.
Perhaps most significantly, Jarvis starts with ‘the person’ as the central agent in the process of
learning (Jarvis 2006). With hindsight it might be obvious that learning exists only as a personal
and subjective experience, but prior to Jarvis’s work this was not so succinctly stated. Second
(and related to this), Jarvis argues that learning is actually defined as personal change: if
someone is changed by an experience then they have learnt from it and the absence of change is
indicative of non-learning. Thus Jarvis (1992) provides a powerful synthesis with the following
definitions and implications for pedagogy:
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Studies in Higher Education 297
Learning is personal change.
The absence of change is non-learning.
Change must be measured to differentiate between learning and non-learning outcomes.
Furthermore, Jarvis’s model has some important things to say about the causes of non-learn-
ing and the quality of change where learning occurs. First, presumption (‘I know that
already’), non-consideration (‘I don’t need to know that’) or rejection (‘I have thought about
it but it is not something I need to know’) all lead to non-learning. Second, learning (where it
does occur) can be reflective (using practice, evaluation, reasoning and memory to achieve
change) or it can be non-reflective (relying on memory alone). Thus, Jarvis’s model states
that the learner chooses (deliberately or otherwise) to adopt strategies that will affect the qual-
ity of their learning. This issue of ‘learning quality’ is the focus for much of the following
discussion.
The quality of change in learning
Some very similar conclusions to those of Jarvis were reached, independently, by Novak (e.g.
Novak 1998). Novak describes cognitive change within a single continuum that extends between
rote and meaningful learning. He defines meaningful learning in the following ways:
(1) Relevant prior knowledge. That is, the learner must know some information that relates to the
new information to be learned in some nontrivial way.
(2) Meaningful material. That is, the knowledge to be learned must be relevant to other knowledge
and must contain significant concepts and propositions.
concrete
experience [1]
observation and
reflection [2]
forming abstract
concepts [3]
testing in new
situations [4]
concrete
experience [1]
observation and
reflection [2]
forming abstract
concepts [3]
testing in new
situations [4]
concrete
experience [1]
observation and
reflection [2]
forming abstract
concepts [3]
testing in new
situations [4]
Figure 1. Kolb’s learning cycle (after Kolb and Fry 1975).
Kolb and Fry (1975) describe learning as a cycle. First the person has an experience [1], then they observe
and reflect upon it [2]. This is done in order to form new ways of thinking about the subject [3], so that
finally what has been newly understood can be tested [4] before the phases of the cycle are repeated.
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298 D. Hay et al.
(3) The learner must choose to learn meaningfully. That is, the learner must consciously and delib-
erately choose to relate new knowledge to knowledge the learner already knows in some
nontrivial way. (Novak 1998, 19)
As a ground for pedagogy, this is even more specific than the work of Jarvis. It suggests that rote
learning can be distinguished from meaningful learning by measures of integration among newly
acquired and prior knowledge (Hay 2007). Novak’s definition of meaningful learning is
summarised in Figure 3.
Figure 3. Novak’s concept map of meaningful learning (after Novak 1998).This concept map explains Novak’s definition of meaningful learning and provides a framework for understanding how Novak understands teachers’ roles in the support of learning.
Like Jarvis, this approach suggests that knowledge and understanding should be measured
before and after teaching, but, more than this, Novak provides an empirical framework for
assessing the quality of any change that may have occurred. Novak also developed the concept-
mapping method for just this purpose. This has been extended by Hay (2007) and Hay, Wells,
and Kinchin (forthcoming), and is explained in Figure 4.
Figure 4. Measures of learning quality.Hay (2007) used the concept mapping method to compare students’ knowledge structures before and after teaching. In this summary of the data, concepts are shown as circles and the links between them are drawn as lines.
Briefly, Figure 4 is a graphic summary of data reported by Hay (2007) and Hay, Wells, and
Kinchin (forthcoming), where concept mapping was used to track knowledge change among
university students. Where there was no change in knowledge (before and after learning), this
the person [1]
the person:
reinforced but
relatively
unchanged [4]
the person:
changed and
more
experienced [9]
practice
experimentation [5]
memorisation [6]
reasoning and
reflection [7]
the experience [2]
of the situation [3]
evaluation [8]
Figure 2. Jarvis’s model of learning (after Jarvis 1992).
Jarvis (1992) states that the person [1] is the most important element in any description of learning. This
is because he defines learning as personal change (compare the difference from [1] to [9] and from [1] to
[4]). According to Jarvis, there are nine possible outcomes of learning (or non-learning) and these can be
defined by the various routes through the processes of reflection, evaluation, experimentation and memo-
risation.
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Studies in Higher Education 299
Figure 3. Novak’s concept map of meaningful learning (after Novak 1998).
This concept map explains Novak’s definition of meaningful learning and provides a framework for un-
derstanding how Novak understands teachers’ roles in the support of learning.
added concepts
NON-
LEARNING
ROTE
LEARNING
MEANINGFUL
LEARNING
top (organising) concepts rejected concepts retained concepts
BEFORE INTERVENTION AFTER INTERVENTION
knowledge structure
remains unchanged
some prior-concepts
are rejected and new
ones are added, but no
new links are made
and the newly added
concepts are not linked
to the prior knowledge
structure
new concepts
are linked to the retained
knowledge structure and new
links are made between those
parts of the prior knowledge
structure that are retained
Figure 4. Measures of learning quality.
Hay (2007) used the concept mapping method to compare students’ knowledge structures before and after
teaching. In this summary of the data, concepts are shown as circles and the links between them are drawn
as lines.
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300 D. Hay et al.
was deemed non-learning (after Jarvis), and where change occurred, the degree of integration
between new material and extant parts of the prior-knowledge structure was used to classify the
learning quality. Rote (or surface) learning was observed where the new material was added
superficially without integration, and meaningful (or deep) learning occurred where new and old
material were recombined to make new meanings.
The importance of prior knowledge
Together, the approaches of Jarvis and Novak define learning as change. Where knowledge
change is a consequence of the integration of new material and the prior-knowledge structure,
this satisfies the criteria of meaningful learning. Rote learning entails superficial changes in
knowledge without integration. This definition can be applied in any discipline, and is just as
applicable to skills learning or to changing behaviours, but for simplicity we will focus here on
cognitive change alone. This is because change in knowledge and understanding is a feature of
all university-level learning, whereas the learning of skills and behaviours is less widely
distributed among the disciplines of higher education.
That learning is change and that change is measurable is a simple definition with wide
utility. But it also necessitates that prior knowledge must be measured as the first step in docu-
menting learning. Prior knowledge is the baseline from which learning can be calculated and
its quality assessed. The definition also suggests that the quality of students’ learning will be
determined in large part by their starting positions. Students who have a good grasp of a topic
beforehand will be better equipped to make sense of the teaching they receive. This is common
sense, and it is therefore surprising that it is not more widely acknowledged in teaching and
curriculum design at university level. It is not enough to argue that selection for university
entrance ensures common standards of knowledge and understanding. Our own data show that
there can be considerable difference in the understandings of students who have achieved
similar examination results (Hay 2007; Hay et al. forthcoming; Hay, Wells, and Kinchin forth-
coming). Most universities use attainment at schools level to determine access to higher educa-
tion, but most teachers continue to report a wide range of pre-existing understandings among
their students.
Two articles provide empirical evidence for the role of prior knowledge in student learning
(Hay et al. forthcoming; Hay, Wells, and Kinchin forthcoming). Their data suggest that, without
the active participation of teachers in the measurement of student prior knowledge, teaching is
‘locked up’ in structures and in terminology that is inaccessible to students. As a consequence,
‘experts’ can give ‘lessons’ that other ‘experts’ will deem to be excellent, while failing to
engender understanding among their student audience. In such cases, students learn by rote (if
they learn at all) or resort to other resources from among their wider human social interactions.
Hay et al. (forthcoming; Hay, Wells, and Kinchin forthcoming) also show that there are three
different dimensions to prior knowledge, all of which can affect student learning. These are
conceptual richness, knowledge structure and misconceptions. The three dimensions are
explained as follows:
(1) Students are obviously advantaged by a rich prior knowledge, and helped too if there is
a good overlap between what they know already and at least some of the teaching that
they experience. It is out of prior knowledge that students interpret what they are taught,
and the richer their knowledge to begin with, the greater the likelihood of subsequent
understanding.
(2) The structure of prior knowledge (the ways in which it is organised) can have an impor-
tant impact on a student’s capacity for learning. Kinchin, Hay, and Adams (2000) show
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Studies in Higher Education 301
that different people go about structuring their understanding in different ways: Hay and
Kinchin (2006) suggest that some of these cognitive structures are more amenable to
change (learning) than others. Figure 5 is a summary of this strand of research.
(3) Prior knowledge inevitably forms a scaffold for new learning, but where it comprises
significant misconceptions then new knowledge acquisition is impeded. Understanding
student misconception to begin with is an important part of the work of a teacher, and
has long been understood in schools-level education (see Driver et al. 1994), and more
generally, in adult education too (see Jarvis [2006], for example).
Figure 5. Prior-knowledge structure and learning.Hay and Kinchin (2006) show that some ways of organising and storing knowledge are more amenable to learning than others. Different knowledge structures in particular (chains, spokes and networks: Kinchin, Hay, and Adams 2000) have different utilities but they also have different propensities for change.
Figure 5. Prior-knowledge structure and learning.
Hay and Kinchin (2006) show that some ways of organising and storing knowledge are more amenable to
learning than others. Different knowledge structures in particular (chains, spokes and networks: Kinchin,
Hay, and Adams 2000) have different utilities but they also have different propensities for change.
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302 D. Hay et al.
All these issues make it important that students are helped to understand their own starting
positions. As Ausubel suggests, understanding students’ prior knowledge is a key step in teach-
ing (Ausubel 1963, 1968; Ausubel, Novak, and Hanessan 1978): ‘The most important single
factor influencing learning is what the learner already knows; ascertain this and teach him/her
accordingly’ (Ausubel 1968, 36).
In small-group teaching and one-to-one tutorials, measures of, and responses to, student prior
knowledge are an integral part of teaching. It is in large classes and in the delivery of lectures,
in particular, that most university teachers fail to use student prior knowledge as a basis of
teaching. This is not a purposeful neglect of the issue, but arises from a lack of awareness of the
tools with which prior knowledge can be measured in large groups. It is important, then, that
Novak’s concept-mapping method can be used to measure prior knowledge in a class of 400
students just as quickly and as easily as with a single person. This is explained below.
The concept-mapping method
Concept mapping is one of a broad family of graphic organising tools, that includes mind
mapping (Buzan and Buzan 2000) and spider diagramming (Trowbridge and Wandersee 1998).
Yet Novak’s method (Novak 1998) has some very specific rules that set it apart from other tech-
niques. These are a consequence of the careful definition of learning (already described), and
facilitate the use of the method for the measurement of learning quality.
A concept map comprises the ‘bare bones of language’. Concept maps consist of concept
labels that identify specific ideas (concepts) and the links between them, which explain how
concepts are related to make meaning. A pair of concepts and their respective link makes a single
proposition, and a concept map is made from any number of propositions to give a personal defi-
nition of any particular idea or phenomenon (Novak 1998). Each proposition is a statement of
understanding and the validity of each assertion is open to scrutiny. Thus, the method is much
more stringent than mind mapping, for example, and actively differentiates between knowledge
(of appropriate concept labels) and understanding (that is the product of concept linkage). It is a
powerful teaching tool since it facilitates the declaration of understanding among teachers and
students.
The method can be taught in 10–20 minutes, and most students will find another 20–30
minutes sufficient to construct a reasonable map. This means that concept maps can be made
within the time allocated for most university teaching sessions. Analysis of large numbers of
maps can be time consuming (although quicker by far than the analysis of, say, individuals’
interview transcripts), but Kinchin, Hay, and Adams (2000) show that a considerable amount of
information can be gleaned very quickly indeed using structure alone as an indicator of prior
knowledge. More stringent methods of analysis are described by Hay (2007) and Hay, Wells,
and Kinchin (forthcoming), and can be combined with a simple sampling strategy. Alternatively,
students themselves can be made responsible for the analysis of their prior knowledge, either in
groups or individually. This can be a particularly powerful approach when it is combined with
repeated measurement in the course of learning, so that students can see their knowledge and
understanding change.
Concept mapping is already used in many different ways in school and university educa-
tion. These are summarised in Table 1 and include lesson planning, measurement of change,
organisation of group work and the sharing of knowledge and understanding. The use of
concept mapping in the measurement of prior knowledge has already been discussed, and two
more applications of the method are described below. Above all else, however, concept
mapping can be used to make abstract knowledge and understanding visible to underpin its
utility.
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Studies in Higher Education 303
Tab le 1. Uses of the concept mapping method.
Use Explanation References
Assessing change
In the course of learning
Concept maps are made by students to describe the same topic over
and over again in the course of learning.
The concepts and links are compared to assess the changes that have
occurred.
Novak and Musonda 1991;
Novak and Symington 1982;
Eskilsson and Helldén 2003;
Iuli and Helldén 2004;
Hay 2007; Hay, Wells and Kinchin Forthcoming.
Identifying student
misconceptions
Persistent misconceptions can be shown by analysis of the
propositions used to describe individuals’ understandings
Kinchin 2000; 2002; Hay et al 2008.
Teaching practice The quality of the dialogue between teachers and students can be
enhanced through the use of concept mapping since the method
facilitates an exchange of individual knowledge and understanding.
Kinchin 2003; Kinchin 2004;
Kinchin, deLeij and Hay 2005;
Kinchin and Hay, 2007.
Lesson planning Teachers can use concept maps to plan their lessons: where they map
their own understanding first and use their maps to organise the
knowledge and information that they will present, second.
Martin 1994; Kinchin and Alias 2005; Kinchin 2006a,b;
Kinchin and Hay 2007
Assessment Concept maps can be used to test knowledge and understanding for the
purposes of both formative and summative assessment. Edmondson 2000.
Cognitive typology Concept maps have been used to show the cognitive structures that
different people use to structure and organise their thinking.
Kinchin, Hay and Adams 2000;
Hay and Kinchin 2006.
Identification of expertise Concept maps can be used to show measurable differences between
experts and novices.
Novak and Gowin 1984;
Kinchin 2001.
Team working Different knowledge, understanding and team roes can be managed
and integrated through the use of concept mapping.
Hughes and Hay 2001;
Kinchin and Hay 2005.
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304 D. Hay et al.
Measuring change and learning quality
We have already seen how concept mapping can be used to reveal prior knowledge. This is a
necessary baseline if the method is to be used to track change. When a student maps the same
topic in the course of their study, then a comparison of two or more such ‘snapshots’ enables
measurement of learning quality (Hay 2007). Those parts of the knowledge structure that are
new can be readily differentiated from those that are old, and the degree of integration (between
new and previously existing ideas) can be measured. Figure 6 shows some of the results that can
be obtained using this approach in the course of teaching. Figure 6a is a model of rote learning
and Figure 6b is an example of meaningful change. Both are based on real data, and illustrate
one of the key issues that we have argued already; that student prior knowledge is a good
predictor of the meaning that can be constructed out of subsequent teaching.
Figure 6. Measuring the quality of learning.Concept mapping can be used to reduce abstract knowledge to concrete diagrammatic representation. When the same topic is mapped through time then the maps can be compared to measure change. This affords the documentation of learning quality and reduces specific ‘learning events’ to observable phenomena.
Figure 6c shows some of the complex changes that may occur in the course of learning;
changes that may cause teachers and learners considerable problems if they are not made visible.
The student in this case study began a course of learning with a simple prior-knowledge structure
and learnt, at first, by rote addition. Later, however, they found that what was new was irrecon-
cilable with what they had understood to begin with. The result was a period of ‘disjuncture’,
during which the student was less able to explain the topic than they had been before. Eventually
they achieved a new grasp of meaning, but this came after a difficult period in which they might
easily have given up. By making the learning process visible, the concept-mapping method can
show who is in most need of support and when this support should be given.
Among others, Laurillard (2002) states that there is remarkably little published work docu-
menting cognitive change among learners at university. This is perhaps attributable to learning
having been deemed too complex and too intractable an issue to be amenable to empirical
measurement. The approach that we have described here suggests that this is not so. Indeed publi-
cations by Hay (2007) and Hay et al. (forthcoming) show that concept mapping can be done to
achieve longitudinal measures of student learning quality in higher education. We suggest that
this should become a central strategy in the practice of higher education teaching. It is relatively
simple to achieve and can provide a research-led foundation for university teaching. The tracking
of student knowledge change should also be linked to measures of convergence on ‘expert’ under-
standing.
Sharing knowledge in the course of learning and teaching
Figure 7 shows how students go about the integration of new material within existing prior
knowledge. If what is new is not integrated it must be acquired by rote and is likely to be quickly
forgotten. But there is a broad consensus among university lecturers that rote learning is common
in higher education (see Ramsden [2002] and Kinchin, Lygo-Baker, and Hay [2008] for a more
detailed discussion of these issues). This probably explains why most university teachers claim
to teach even some of the most basic issues again and again at higher levels of study. Ultimately,
learning can only be the responsibility of the learner. As both Jarvis and Novak point out, the
learner must choose to learn meaningfully. But such a stance does not negate the responsibilities
of the teacher. Teachers can (and should) teach in ways that encourage student meaning making.
As we have already seen, this should begin with measurement of student prior knowledge,
almost by necessity. Concept mapping can be used to do this, but afterwards the method can also
be repeated to make the students’ new and emerging understanding visible to the teacher. Doing
so provides a framework for understanding what is being understood and what is not. Our own
data show that the neglect of meaningful learning among students is often a consequence of
the ways in which new material is presented (Hay, Wells, and Kinchin forthcoming). Rote
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Studies in Higher Education 305
Figure 6. Measuring the quality of learning.
Concept mapping can be used to reduce abstract knowledge to concrete diagrammatic representation.
When the same topic is mapped through time then the maps can be compared to measure change. This
affords the documentation of learning quality and reduces specific ‘learning events’ to observable
phenomena.
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306 D. Hay et al.
learning is often attributable to the teaching that students receive, and to the ways in which
students come to perceive the assessment of their learning at university (Kinchin, Lygo-Baker,
and Hay 2008).
Figure 7. A general model of learning quality.Students must choose to learn meaningfully by the purposeful integration of new knowledge with existing understanding. Some students can grasp the meaning of new teaching quickly because their prior knowledge supports new understanding (1a); others will find new learning more difficult as a consequence of their prior knowledge (1b). Some students will remain unchanged despite the teaching they receive and this comprises non-learning (2). Students who first learn byrote will learn meaningfully later if they can integrate their new learning with their prior knowledge. Otherwise they will tend to forget what they have been taught and revert to non-learning.
Kinchin and Hay (2007) show how conventional teaching, and large-class lectures in partic-
ular, can act to promote rote learning (Figure 8). This is because lecturing requires that teachers
convert complex scholarly networks of knowledge to simple and linear narrative chains. These
chains are disclosed in lecturing, but the underlying understanding from which they were first
constructed is rarely made clear to students. This is compounded by so much lecture-style deliv-
ery being accompanied by a linear sequence of bullet points in PowerPoint (Kinchin 2006a, b).
The overall effect is not conducive to meaningful learning. It emphasises linearity (rather than
the connectivity out of which genuine understanding arises) and suggests to students that there
is a single right answer to be memorised (Kinchin and Hay 2007). That which is learned by
memory alone is easily forgotten, and non-learning in higher education is a common
consequence (Kinchin, Lygo-Baker, and Hay 2008).
the student ís prior
knowledge structure
is robust enough
to include the new
material in non -trivial
ways witho ut
recourse to
deep structural Change
LEARNING
the teacher presents
new material
examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the existing
prior -knowledge
structure prove
irreconcilable (at
least in the mind
of the student
the student learns to
repeat the new
material
the student repeats
only what they
knew before
NON -
LEARNING
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
Their knowledge
And understanding
LEARNING
the student chooses the student chooses
either or either or
either or
leading
to
the student ís prior
knowledge structure
is robust enough
to include the new
material in non -trivial
ways witho ut
recourse to
deep structural Change
LEARNING
the teacher presents
new material
examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the existing
prior -knowledge
structure prove
irreconcilable (at
least in the mind
of the student
the student learns to
repeat the new
material
the student repeats
only what they
knew before
NON -
LEARNING
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
Their knowledge
And understanding
LEARNING
the student chooses the student chooses
either or either or
either or
leading
to
which requires
that they switch
to an alternative
strategy
the student reverts
to alternative
strategies
the student ís prior
knowledge structure
is robust enough
to include the new
material in non -trivial
ways witho ut
recourse to
deep structural Change
LEARNING
the teacher presents
new material
examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the existing
prior -knowledge
structure prove
irreconcilable (at
least in the mind
of the student
the student learns to
repeat the new
material
the student repeats
only what they
knew before
NON -
LEARNING
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
Their knowledge
And understanding
LEARNING
the student chooses the student chooses
either or either or
either or
leading
to
the student ís prior
knowledge structure
is robust enough
to include the new
material in nontrivial
ways witho ut
recourse to
deep structural change
(LEARNING)
the teacher presents
new material
to examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the
prior -knowledge
are irreconcilable
(at least in the mind
of the student)
the student learns to
repeat the new
material by rote
the student repeats
only what they
knew before
(NON -
LEARNING)
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
their knowledge
and understanding
(LEARNING)
the student chooses the student chooses
either or either or
either or
leading
to
which requires
that they switch
to an alternative
strategy
the student reverts
to an alternative
strategy
1a
1b
2
causing
DISJUNCTURE before
the student ís prior
knowledge structure
is robust enough
to include the new
material in non -trivial
ways witho ut
recourse to
deep structural Change
LEARNING
the teacher presents
new material
examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the existing
prior -knowledge
structure prove
irreconcilable (at
least in the mind
of the student
the student learns to
repeat the new
material
the student repeats
only what they
knew before
NON -
LEARNING
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
Their knowledge
And understanding
LEARNING
the student chooses the student chooses
either or either or
either or
leading
to
the student ís prior
knowledge structure
is robust enough
to include the new
material in non -trivial
ways witho ut
recourse to
deep structural Change
LEARNING
the teacher presents
new material
examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the existing
prior -knowledge
structure prove
irreconcilable (at
least in the mind
of the student
the student learns to
repeat the new
material
the student repeats
only what they
knew before
NON -
LEARNING
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
Their knowledge
And understanding
LEARNING
the student chooses the student chooses
either or either or
either or
leading
to
which requires
that they switch
to an alternative
strategy
the student reverts
to alternative
strategies
the student ís prior
knowledge structure
is robust enough
to include the new
material in non -trivial
ways witho ut
recourse to
deep structural Change
LEARNING
the teacher presents
new material
examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the existing
prior -knowledge
structure prove
irreconcilable (at
least in the mind
of the student
the student learns to
repeat the new
material
the student repeats
only what they
knew before
NON -
LEARNING
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
Their knowledge
And understanding
LEARNING
the student chooses the student chooses
either or either or
either or
leading
to
the studentís prior-
knowledge structure
is robust enough
to include the new
material in non-trivial
ways witho ut
recourse to
deep structural change
(LEARNING)
the teacher presents
new material
to examine and evaluate
what they
already know
and what is new
NOT to examine the
new material in the context
of what they already know
the new knowledge
and the
prior -knowledge
are irreconcilable
(at least in the mind
of the student)
the student learns to
repeat the new
material by rote
the student repeats
only what they
knew before
(NON -
LEARNING)
the student forgets
what they have
learnt to repeat
the student seeks
to understand
what they have
learnt to repeat
the student forges
new knowledge
structures to reconcile
their knowledge
and understanding
(LEARNING)
the student chooses the student chooses
either or either or
either or
leading
to
which requires
that they switch
to an alternative
strategy
the student reverts
to an alternative
strategy
1a
1b
2
causing
DISJUNCTURE before
Figure 7. A general model of learning quality.
Students must choose to learn meaningfully by the purposeful integration of new knowledge with existing
understanding. Some students can grasp the meaning of new teaching quickly because their prior knowl-
edge supports new understanding (1a); others will find new learning more difficult as a consequence of
their prior knowledge (1b). Some students will remain unchanged despite the teaching they receive and
this comprises non-learning (2). Students who first learn by rote will learn meaningfully later if they can
integrate their new learning with their prior knowledge. Otherwise they will tend to forget what they have
been taught and revert to non-learning.
Downloaded By: [JISC Collections Subscription Services] At: 08:11 1 October 2010
Studies in Higher Education 307
Figure 8. A model of teaching and learning.University teachers tend to use lectures to present simple narrative sequences [1] to their students. These are actually constructed out of complex underlying knowledge networks [2], but rarely is this richness of understanding disclosed to their students. As a consequence students often choose to memorise the taught material [3], rather than engaging in a process of new-knowledge construction [4]. Nevertheless, teachers and students can use concept mapping to promotemeaningful student learning [5].
Concept mapping offers a means by which these concerns can be addressed. Where teachers
map their understandings of a topic, this can be used to give students access to the complexity
and richness of the knowledge that belies their simple narrative explanations. Where students
map the same topic as their teachers, comparing their maps can help to show the ways in which
students can (or cannot) construct meaning from the new material they encounter. If this is done
through time, it can reveal the learning process itself, by helping teachers and students to under-
stand which new concepts need further explanation to facilitate meaningful learning. The
approach will also indicate the order in which new material must be introduced if it is to be
understood. We suggest that a simple exercise involving students directly in the construction of
new understanding should probably be a part of all university-level teaching. Students can be
asked to map their prior knowledge, and all of the concepts that they use can be written on Post-
it Notes (or other movable labels). Then some of the new concept labels that their teachers hope
to introduce can be disbursed, and new mapping can be done by the students to show whether or
not the new material can be linked to prior knowledge. Such an approach actively promotes the
process of meaningful learning among students, but it is also important because it involves teach-
ers in the research of their students learning. It is a practical exercise in new-knowledge creation
Figure 8. A model of teaching and learning.
University teachers tend to use lectures to present simple narrative sequences [1] to their students. These
are actually constructed out of complex underlying knowledge networks [2], but rarely is this richness of
understanding disclosed to their students. As a consequence students often choose to memorise the taught
material [3], rather than engaging in a process of new-knowledge construction [4]. Nevertheless, teachers
and students can use concept mapping to promote meaningful student learning [5].
Downloaded By: [JISC Collections Subscription Services] At: 08:11 1 October 2010
308 D. Hay et al.
(at least for the students concerned), and it incurs negligible costs (of equipment or staff time).
It is tenable with very large student groups, and affords immediate benefits to both students and
teachers. Students are helped to understand the topic and also to learn what is expected of them
in higher education (i.e. the grasp of understanding and the construction of meaning). Teachers
are able to find out whether or not their teaching facilitates meaningful learning, and, if not, what
needs to be changed so that it does.
Concept mapping activities like this allow teachers to identify the new concepts that students
find troublesome or difficult to acquire. There is now a rich literature on ‘troublesome knowl-
edge’ (e.g. Perkins 1999) and threshold concept acquisition (e.g. Meyer and Land 2003; 2005).
Nevertheless, higher education still lacks the empirical data that show where, when and how new
knowledge and understanding is acquired. The learning trajectories of all students are likely to
be different as a consequence of their different prior knowledge and experience. But understand-
ing the ways in which people go about the construction of meaning is also likely to afford the
extraction of general principles for the enhancement of teaching and learning. As we have said
already, student learning in higher education is under-researched, but using concept mapping in
the course of teaching can embed the research of student learning in university teaching. These
issues are further explored below.
Concept mapping and the role of the university teacher
Figure 9 shows a general model of university teaching that is developed out of the arguments
presented in this article. It implies that responsible university teaching will include four distinct
practices, all of which can be achieved through concept mapping. These are:
(1) measures of student prior knowledge;
(2) the deliberate presentation of new material in the context of a known student knowledge
base;
(3) active engagement in the development of new student meaning making through the
purposeful disclosure of underlying knowledge and understanding;
(4) measurement of change among the student population so that learning (where it occurs)
is identified and the causes of non-learning are addressed.
Figure 9. A model of university teaching practice.Authentic teaching at university level comprises measures of student prior knowledge; meaningful presentation of new material; active engagement in the development of new student meaning-making; and measurement of change among the student population. All of these can be facilitated by the use of concept mapping. In using concept mapping to these ends, teachers engender meaningful learning among their students, but also accumulate important research data aboutthe quality of learning and teaching. This is a rich source of empirical data that might eventually lead to a research-led teaching practice in each of the disciplines of higher education.
It is difficult to envisage any cogent arguments against these aims excepting, of course, that they
are difficult to achieve, particularly among large classes unless specific methods are developed
to achieve them in the normal course of university teaching. We hope, therefore, that we have
shown how the concept-mapping method can do just this. Our own research (in collaboration
with other teachers in higher education) attests to the utility of the method even where classes
are very large indeed (e.g. Hay and Kinchin forthcoming) where the method is described for use
among student groups of 250 and more).
Conclusions
This article has shown how the use of the concept-mapping method can add significantly to the
quality of university teaching. Concept mapping is a teaching tool and a method of measurement
of learning quality. There might be other means of achieving both of these functions (of teaching
practice and the measurement of learning). Interviewing is an obvious example, but it is time
consuming and impractical with all but the smallest student groups. Thus, concept mapping is
likely to have an important role in the future development of higher education and its research.
We do not suggest that concept mapping should replace the conventional methods of teaching in
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Studies in Higher Education 309
higher education (lectures, tutorials, seminars, practicals, clinical experience, etc.). Nevertheless,
the quality of conventional university teaching can be considerably improved by its use. In
particular, concept mapping enables the engagement of teachers and learners in the processes of
discovery. Higher education is about more than the transmission of knowledge; it entails the
extension and creation of knowledge as well.
Concept mapping makes learning visible. It is a lens through which the quality of learning
can be determined. Teachers can use it to promote meaningful learning among their students,
Figure 9. A model of university teaching practice.
Authentic teaching at university level comprises measures of student prior knowledge; meaningful presen-
tation of new material; active engagement in the development of new student meaning-making; and mea-
surement of change among the student population. All of these can be facilitated by the use of concept
mapping. In using concept mapping to these ends, teachers engender meaningful learning among their stu-
dents, but also accumulate important research data about the quality of learning and teaching. This is a rich
source of empirical data that might eventually lead to a research-led teaching practice in each of the dis-
ciplines of higher education.
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310 D. Hay et al.
but, wherever and whenever they do, they will be collecting valuable data about the teaching that
is appropriate to their subjects and disciplines. This can provide a documented research base
from which teaching can be developed. It is an empirical methodology out of which a science of
teaching may eventually arise.
Acknowledgements
The work reported here was funded by a grant for the research of pedagogy from the Society for
Educational Studies.
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Para enfatizar o protagonismo do estudante, ao promover o ensino e aprendizagem, é necessário a utilização de metodologias ativas. Nessa perspectiva, o objetivo da pesquisa foi evidenciar diferentes pontos visualizados em publicações, desenvolvidas ao longo de quatro anos de efetivação de projetos de ensino, explorando o tema invertebrados por meio de mapas conceituais. Utilizando-se de elementos da análise de conteúdo sistematizada por Laurence Bardin, procedeu-se a estruturação de uma amostra de estudo para determinação das categorias emergentes relativas às produções realizadas no percurso de efetivação dos quatro projetos em análise. Foram detectadas inovações diferenciadas ao longo dos quatro anos consecutivos de realização das atividades, destacando-se: a) aplicação da técnica de mapeamento conceitual em zoologia utilizando mapas de referência, b) construção de mapas conceituais para aprendizagem e comunicação sobre a biodiversidade animal, c) reforços à divulgação da biodiversidade por meio de mapas conceituais, d) evidências à Convenção sobre Diversidade Biológica e a perspectiva filogenética nos mapas conceituais. Vale ressaltar que o estudo dos invertebrados, sob a ótica da biodiversidade e por meio de mapas conceituais, fomenta a contextualização do conhecimento e contribui para formar cidadãos conscientes de sua parcela de responsabilidade com os valores ambientais, para que as gerações futuras sejam também beneficiadas com as ações realizadas no presente.
... Concepts in different branches can be further connected with cross-links. Cross-links tend to be more prominent when representing complex expert understanding (Hay et al., 2008;Novak, 1985;Novak & Cañas, 2008;Watson et al., 2016;Yin et al., 2005). Concept maps often also contain examples connected to concepts with an arrowed line and a linking word (Novak, 1985;Novak & Cañas, 2008;Ruiz-Primo & Shavelson, 1996). ...
Thesis
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Elementary particle physics is a contemporary topic in science that is slowly being integrated into high-school education. These new implementations are challenging teachers’ professional knowledge worldwide. Therefore, physics education research is faced with two important questions, namely, how can particle physics be integrated in high-school physics curricula and how best to support teachers in enhancing their professional knowledge on particle physics. This doctoral research project set up to provide better guidelines for answering these two questions by conducting three studies on high-school particle physics education. First, an expert concept mapping study was conducted to elicit experts’ expectations on what high-school students should learn about particle physics. Overall, 13 experts in particle physics, computing, and physics education participated in 9 concept mapping rounds. The broad knowledge base of the experts ensured that the final expert concept map covers all major particle physics aspects. Specifically, the final expert concept map includes 180 concepts and examples, connected with 266 links and crosslinks. Among them are also several links to students’ prior knowledge in topics such as mechanics and thermodynamics. The high interconnectedness of the concepts shows possible opportunities for including particle physics as a context for other curricular topics. As such, the resulting expert concept map is showcased as a well-suited tool for teachers to scaffold their instructional practice. Second, a review of 27 high-school physics curricula was conducted. The review uncovered which concepts related to particle physics can be identified in most curricula. Each curriculum was reviewed by two reviewers that followed a codebook with 60 concepts related to particle physics. The analysis showed that most curricula mention cosmology, elementary particles, and charges, all of which are considered theoretical particle physics concepts. None of the experimental particle physics concepts appeared in more than half of the reviewed curricula. Additional analysis was done on two curricular subsets, namely curricula with and curricula without an explicit particle physics chapter. Curricula with an explicit particle physics chapter mention several additional explicit particle physics concepts, namely the Standard Model of particle physics, fundamental interactions, antimatter research, and particle accelerators. The latter is an example of experimental particle physics concepts. Additionally, the analysis revealed that, overall, most curricula include Nature of Science and history of physics, albeit both are typically used as context or as a tool for teaching, respectively. Third, a Delphi study was conducted to investigate stakeholders’ expectations regarding what teachers should learn in particle physics professional development programmes. Over 100 stakeholders from 41 countries represented four stakeholder groups, namely physics education researchers, research scientists, government representatives, and high-school teachers. The study resulted in a ranked list of the 13 most important topics to be included in particle physics professional development programmes. The highest-ranked topics are cosmology, the Standard Model, and real-life applications of particle physics. All stakeholder groups agreed on the overall ranking of the topics. While the highest-ranked topics are again more theoretical, stakeholders also expect teachers to learn about experimental particle physics topics, which are ranked as medium importance topics. The three studies addressed two research aims of this doctoral project. The first research aim was to explore to what extent particle physics is featured in high-school physics curricula. The comparison of the outcomes of the curricular review and the expert concept map showed that curricula cover significantly less than what experts expect high-school students to learn about particle physics. For example, most curricula do not include concepts that could be classified as experimental particle physics. However, the strong connections between the different concept show that experimental particle physics can be used as context for theoretical particle physics concepts, Nature of Science, and other curricular topics. In doing so, particle physics can be introduced in classrooms even though it is not (yet) explicitly mentioned in the respective curriculum. The second research aim was to identify which aspects of content knowledge teachers are expected to learn about particle physics. The comparison of the Delphi study results to the outcomes of the curricular review and the expert concept map showed that stakeholders generally expect teachers to enhance their school knowledge as defined by the curricula. Furthermore, teachers are also expected to enhance their deeper school knowledge by learning how to connect concepts from their school knowledge to other concepts in particle physics and beyond. As such, professional development programmes that focus on enhancing teachers’ school knowledge and deeper school knowledge best support teachers in building relevant context in their instruction. Overall, this doctoral research project reviewed the current state of high-school particle physics education and provided guidelines for future enhancements of the particle physics content in high-school student and teacher education. The outcomes of the project support further implementations of particle physics in high-school education both as explicit content and as context for other curricular topics. Furthermore, the mixed-methods approach and the outcomes of this research project lead to several implications for professional development programmes and science education research, that are discussed in the final chapters of this dissertation.
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... Writing to learn is a strategy that can be employed throughout to help students be engaged and develop huge ideas and concepts; it nurtures critical thinking for it requires analysis, application, and other higher level thinking skills (Michigan Department of Education, 2009). Concept mapping enables direct observation of tangible measures of learning and can be utilized to track changes in the course of learning (Hay, 2007) and transforms abstract knowledge into concrete visual images (Hay, Kinchin, Lygo-Baker, 2008). The Cognitive Academic Language Learning Approach (CALLA) integrates content, language, and learning strategies and is found useful in improving learning outcomes (Gu, 2018) while marginal notes are claimed to activate students' background knowledge, enable students to check their comprehension of the text, stimulate questioning and analysis of content and most importantly, help students become aware of relevant links between text and their own thinking (Michigan Council for Teachers of Mathematics, 2005). ...
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Part 1: Learning and Teaching in Higher Education 1.Introduction 2.Ways if Understanding Teaching 3.What Students Learn 4.Approaches to Learning 5.Learning form the Student's Perspective 6.The Nature of Good Teaching in Higher Education 7.Theories of Teaching in Higher Education Part 2: Design for Learning 8.The Goals and Structure of a Course 9.Tecahing Strategies for Effective Learning 10.Assessing for Understanding Part 3: Evaluating and Improving the Quality of Teaching and Learning 11.Evaluating the Quality of Higher Education 12.What Does it Take to Improve Teaching?