Concept mapping, mind mapping and argument
mapping: what are the differences and do they matter?
Published online: 27 November 2010
Springer Science+Business Media B.V. 2010
Abstract In recent years, academics and educators have begun to use software mapping tools for a number of education-related purposes. Typically, the tools are used to
help impart critical and analytical skills to students, to enable students to see relationships between concepts, and also as a method of assessment. The common feature
of all these tools is the use of diagrammatic relationships of various kinds in preference
to written or verbal descriptions. Pictures and structured diagrams are thought to be
more comprehensible than just words, and a clearer way to illustrate understanding of
complex topics. Variants of these tools are available under different names: â€˜â€˜concept
mappingâ€™â€™, â€˜â€˜mind mappingâ€™â€™ and â€˜â€˜argument mappingâ€™â€™. Sometimes these terms are used
synonymously. However, as this paper will demonstrate, there are clear differences in
each of these mapping tools. This paper offers an outline of the various types of tool
available and their advantages and disadvantages. It argues that the choice of mapping
tool largely depends on the purpose or aim for which the tool is used and that the tools
may well be converging to offer educators as yet unrealised and potentially complementary functions.
Keywords Concept mapping Mind mapping Computer-aided argument mapping
Critical thinking Argument Inference-making Knowledge mapping
In the past 5â€“10 years, a variety of software packages have been developed that enable the
visual display of information, concepts and relations between ideas. These mapping tools
take a variety of names including: â€˜â€˜concept mappingâ€™â€™, â€˜â€˜mind mappingâ€™â€™ or â€˜â€˜argument
mappingâ€™â€™. The potential of these tools for educational purposes is only now starting to be
M. Davies (&)
University of Melbourne, Parkville, VIC, Australia
e-mail: [email protected]
High Educ (2011) 62:279â€“301
The idea of displaying complex information visually is, of course, quite old. Flow
charts, for example, were developed in 1972 (Nassi and Shneiderman 1973) pie charts and
other visual formats go back much earlier (Tufte 1983). More recently, visual displays
have been used to simplify complex philosophical issues (Horn 1998). Formal ways of
â€˜â€˜mappingâ€™â€™ complex informationâ€”as opposed to the earthâ€™s surface, countries, cities and
other destinationsâ€”began at least 30 years ago, and arguably even earlier.
More recently, the use of information and computer technology has enabled information
mapping to be achieved with far greater ease. A plethora of software tools has been
developed to meet various information mapping needs. What do these tools do? What are
their similarities and differences? What are their advantages and disadvantages? How
precisely do they enhance teaching and learning? This paper considers these questions and
reviews three most commonly used mapping devices. The paper claims that the type of
information mapping tool to be used is largely a function of the purpose for which it is
intended. A clear understanding of the nature and distinctiveness of these tools may offer
educators as yet unrealised and potentially complementary functions to aid and enhance
The purpose and justification for mapping tools
The over-riding aim of all mapping techniques is similar. If students can represent or
manipulate a complex set of relationships in a diagram, they are more likely to understand
those relationships, remember them, and be able to analyse their component parts. This, in
turn, promotes â€˜â€˜deepâ€™â€™ and not â€˜â€˜surfaceâ€™â€™ approaches to learning (Biggs 1987; Entwistle
1981; Marton and Saljo 1976a, b; Ramsden 1992). Secondly, for most people, maps are
also much easier to follow than verbal or written descriptions, although reservations need
to be made in terms of the kinds of â€˜â€˜mapsâ€™â€™ under consideration, for not all maps are equal
(Larkin and Simon 1987; Mayer and Gallini 1990). Thirdly, the work involved in mapmaking requires more active engagement on the part of the learner, and this too leads to
greater learning (Twardy 2004).
There is empirical support for the use of mapping in enhancing, retaining and improving
knowledge. Evidence from the cognitive sciences shows that visual displays do enhance
learning (Vekiri 2002; Winn 1991). Maps allow the separate encoding of information in
memory in visual and well as propositional form, a phenomenon called â€˜â€˜conjoint retentionâ€™â€™ or â€˜â€˜dual codingâ€™â€™ (Kulhavy et al. 1985; Paivio 1971, 1983; Schwartz 1988). In the
former hypothesis, representations are encoded as separate intact units; in the latter, visual
representations are synchronously organised and processed simultaneously and verbal
representations are hierarchically organised and serially processed (Vekiri 2002). In simple
terms, processing information verbally as well as pictorially helps learning by virtue of
using more than one modality. In a later section, I will return to the educational justification of mapping tools and why they work in more detail.
While the overriding objectives of mapping tools are similar, there are differences in
their application. Mind mapping allows students to imagine and explore associations
between concepts; concept mapping allows students to understand the relationships
between concepts and hence understand those concepts themselves and the domain to
which they belong; argument mapping allows students to display inferential connections
between propositions and contentions, and to evaluate them in terms of validity of argument structure and the soundness of argument premises. The next section of this paper
outlines each tool and briefly reviews their advantages and disadvantages.
280 High Educ (2011) 62:279â€“301
The mapping tools
An attempt has recently been made to outline the similarities and differences between
different mapping techniques (Eppler 2006). However, no mention was made of the most
recent computer-aided mapping tool, argument mapping. This paper updates this earlier
paper and outlines three key types of mapping: mind mapping, concept mapping and
argument mapping with an emphasis on the software tools used to make the maps.
Mind mapping (or â€˜â€˜ideaâ€™â€™ mapping) has been defined as â€˜visual, non-linear representations
of ideas and their relationshipsâ€™ (Biktimirov and Nilson 2006). Mind maps comprise a
network of connected and related concepts. However, in mind mapping, any idea can be
connected to any other. Free-form, spontaneous thinking is required when creating a mind
map, and the aim of mind mapping is to find creative associations between ideas. Thus,
mind maps are principally association maps. Formal mind mapping techniques arguably
began with Buzan (Buzan 1974; Buzan and Buzan 2000). These techniques involved using
line thicknesses, colours, pictures and diagrams to aid knowledge recollection. Buzan
makes the following recommendations when mind mapping (http://www.mindmap
example.com/samples.php, Buzan and Buzan 2000).
1. Place an image or topic in the centre using at least 3 colours
2. Use images, symbols, codes, and dimensions throughout your Mind Map.
3. Select key words and print using upper or lower case letters.
4. Each word/image is alone and sitting on its own line.
5. Connect the lines starting from the central image. The central lines are thicker,
organic and flowing, becoming thinner as they radiate out from the centre.
6. Make the lines the same length as the word/image.
7. Use coloursâ€”your own codeâ€”throughout the Mind Map.
8. Develop your own personal style of Mind Mapping.
9. Use emphasis and show associations in your Mind Map.
10. Keep the Mind Map clear by using radial hierarchy, numerical order or outlines to
embrace your branches.
Concept maps, as we shall see, do not use such pictorial and graphical design flourishes.
An example of a mind map on the topic on things to consider for a presentation is given in
The main use of mind mapping is to create an association of ideas. However, another
use is for memory retentionâ€”even if the advantages in the case of mind mapping might be
marginal (Farrand et al. 2002b). It is generally easier to remember a diagram than to
remember a description. Others have suggested, however, that content is more central to
learning than the format in which that content is presented (Pressley et al. 1998).
Mind mapping has been used in a variety of disciplines, including Finance (Biktimirov
and Nilson 2006), Economics (Nettleship 1992), Marketing (Eriksson and Hauer 2004),
Executive Education (Mento et al. 1999), Optometry (McClain 1987) and Medicine
(Farrand et al. 2002a). It is also widely used in professions such as Fine Art and Design,
Advertising and Public Relations.1
1 A list of mind mapping software is available (â€˜â€˜List of Mind Mapping Software,â€™â€™ 2008) and (â€˜â€˜Software
for Mind mapping and Information Storage,â€™â€™ 2008).
High Educ (2011) 62:279â€“301 281
The advantages of mind mapping include its â€˜â€˜free-formâ€™â€™ and unconstrained structure.
There are no limits on the ideas and links that can be made, and there is no necessity to
retain an ideal structure or format. Mind mapping thus promotes creative thinking, and
encourages â€˜â€˜brainstormingâ€™â€™. A disadvantage of mind mapping is that the types of links
being made are limited to simple associations. Absence of clear links between ideas is a
constraint. Mind maps have been said to be idiosyncratic in terms of their design, often
hard for others to read; representing only hierarchical relationships (in radial form);
inconsistent in terms of level of detail; and often too complex and missing the â€˜â€˜big
pictureâ€™â€™ (Eppler 2006; Zeilik, nd). Mind mapping is also limited in dealing with more
complex relationships. For example, mind mapping might be useful to brainstorm the
things that are critical for students to recall in an exam (or a presentation, as in the example
provided). However, it is hard to see it being useful for a purpose that requires an
understanding of how one concept is essential to understanding another. More complex
topics require more than an associational tool, they require relational analysis. The tool of
concept mapping has been developed to address these limitations of mind mapping.
Concept mapping is often confused with mind mapping (Ahlberg 1993, 2004; Slotte and Lonka
1999). However, unlike mind mapping, concept mapping is more structured, and less
pictorial in nature. The aim of concept mapping is not to generate spontaneous associative
elements but to outline relationships between ideas. Thus, concept mapping is a relational
device. A concept map has a hierarchical â€˜â€˜treeâ€™â€™ structure with super-ordinate and subordinate parts (primary, secondary and tertiary ideas). The map normally begins with a word
or concept or phrase which represents a focus question that requires an answer (Novak and
CanËœas 2006). Cross-links using connective terms (usually prepositional phrases) such as
â€˜â€˜leads toâ€™â€™, â€˜â€˜results fromâ€™â€™, â€˜â€˜is part ofâ€™â€™, etc., are used to show relationships between
Fig. 1 A Mind Map (â€˜â€˜Mind Maps Made With Mind Mapping Toolâ€™â€™)
282 High Educ (2011) 62:279â€“301
concepts represented. Examples (not shown here) are added to terminal concepts as
instances but these are not enclosed in boxes or circles as they are not concepts but represent
instances of a concept. Two quite different concept maps are given below on the focus
question: What is the purpose of concept mapping? Fig. 2.
The difference between mind mapping and concept mapping is also at the level of
precision and formality. Mind maps are less formal and structured. Concept maps are
formal and generally more tightly structured. Mind maps emphasise diagrams and pictures
to aid recall of associations; concept maps generally use hierarchical structure and relational phrases to aid understanding of relationships. However, concept maps can take a
variety of forms ranging from hierarchical, to non-hierarchical forms, and even data-driven
maps where the input determines the shape of the map. One recent form of the latter
involves a statistical process known as agglomerative cluster analysis when analysis is
made of terms that appear in a text across a number of respondents which are then
Fig. 2 Two different Novakian-style concept maps using the software CMap (http://cmap.ihmc.us/
conceptmap.html) (from â€˜â€˜Concept Map,â€™â€™ 2010; Zeilik nd)
High Educ (2011) 62:279â€“301 283
â€˜â€˜clusteredâ€™â€™ to form a diagrammatic representation (Jackson and Trochim 2002; Trochim
A non-hierarchical, style of concept map on the influence of labour market on the
economy is given in Fig. 3. While non-hierarchical, this map has more similarities to a
concept map than a mind map as it endeavours to establish appropriate relationships
between the economic concepts rather than simple associations. However, it has similarities
to a mind map as well in terms of its looser, non-hierarchical, unstructured form.
The development of concept mapping has been attributed to the work of Novak as early
as 1972 and his work on childrenâ€™s developing knowledge of science concepts (Novak and
CanËœas 2006). This work, in turn, was inspired by the work of learning psychologist
Ausubel (Ausubel 1963). The mapping technique was refined further (Novak 1981) and
then extended to the educational context (Novak and Gowin 1984). The resulting diagrams
are sometimes known as â€˜â€˜Novakian mapsâ€™â€™ in honour of their founder. As noted, alternative approaches are also available (Jackson and Trochim 2002).
Recent additions to the Novakian format include attempts to capture â€˜â€˜cyclicalâ€™â€™ relationships representing complex natural and social systems (Safayeni et al. 2005). Technology has aided the popularity of concept mapping by means of dedicated software tools
such as CMap Tools (CanËœas et al. 2004) and Compendium.2 Such is the interest in concept
mapping, an annual international conference began in 2005.
There are several stages in developing a Novakian concept map. However, the stages
are very different from developing a mind map:
Fig. 3 Non-linear concept map on labour market economics
2 Cmap Tools is available free from the Institute of Human and Machine Cognition (http://www.ihmc.us).
Compendium is available from the Open University (http://www.labspace.open.ac.uk). A list of concept
mapping software is available here (â€˜â€˜List of Concept Mapping Software,â€™â€™ 2008).
284 High Educ (2011) 62:279â€“301
1. Develop a declarative-type focus question (e.g., â€˜â€˜What is inflation?â€™â€™)
2. Devise a â€˜â€˜parking lotâ€™â€™ of concepts and ideas that are related to the concept of
inflation, and the question to be answered. The purpose of this stage is brainstorming.
The resulting concepts may or may not be used in the final map (Novak and CanËœas
2006). The concepts are placed in circles or boxes to designate them as concepts.
3. Put concepts in hierarchical order of importance in a provisional map. An â€˜â€˜expert
skeleton mapâ€™â€™ can be started by an instructor in a class to scaffold the learning
process, aid student participation and give students confidence. Students can complete
the map themselves with the focus question and concepts provided.
4. Link lines are then provided between the hierarchical concepts from top to bottom.
The conventions have changed over the decades since the inception of concept
mapping. Arrows were originally only used when it is necessary to link a lower
concept with a higher concept. However, this convention has recently been revised by
concept mappers to allow for arrows for all directions (Ahlberg 2004).
5. Devise suitable cross-links for key concepts in the map. Verbs and prepositions/
prepositional phrases are used most frequently, for example: â€˜â€˜requiresâ€™â€™, â€˜â€˜to work
withâ€™â€™, â€˜â€˜will lead toâ€™â€™, â€˜â€˜involvesâ€™â€™, â€˜â€˜duringâ€™â€™, â€˜â€˜ofâ€™â€™, â€˜â€˜throughâ€™â€™, and so on. The aim is to
show the relationship between the key concepts and their subordinate or super-ordinate
6. Add examples to the terminal points of a map representing the concepts. These are not
enclosed in boxes or circles to delineate them as instances of a concept.
Since its inception as a formal technique, concept mapping has been widely used in
academic disciplines, for example, Accounting (Chei-Chang 2008; Irvine et al. 2005;
Leauby and Brazina 1998; Maas and Leauby 2005; Simon 2007; van der Laan and Dean
2006), Finance (Biktimirov and Nilson 2003), Engineering (Walker and King 2002),
Statistics (Schau and Mattern 1997), Reading Comprehension (Mealy and Nist 1989),
Biology (Kinchin 2000), Nursing (Baugh and Mellott 1998; King and Shell 2002; Schuster
2000; Wilkes et al. 1999), Medicine (Hoffman et al. 2002; McGaghie et al. 2000; West
et al. 2000), Nursing (Beitz 1998) and Veterinary Science (Edmonson 1993).
Research has also been done on concept mapping as an assessment tool (Gouveia and
Valadares 2004; Jonassen et al. 1997; van der Laan and Dean 2006) and as a way to assist
academics in course design (Amundsen at al. 2008) and in managing qualitative data
(Daley 2004). Several empirical studies have ascertained the validity of the use of concept
maps (Markham et al. 1994; Ruiz-Primo and Shavelson 1996).
The main advantage of concept mapping is precisely its relational aim. Concept maps
enable relational links to be made between relevant concepts. In the educational context, it
is claimed that meaningful learning best takes place by linking new concepts to existing
knowledge (Craik and Lockhart 1972; Maas and Leauby 2005). Concept maps enable â€˜the
elements of [learning] to relate to how cognitive knowledge is developed structurally by
the learnerâ€™ (Maas and Leauby 2005, p. 77).
The main disadvantages of concept mapping are that they require some expertise to
learn; they can be idiosyncratic in terms of design; and because of their complexity they
may not always assist memorability, with learners faced with designing concepts maps
often feeling overwhelmed and de-motivated (Beitz 1998; Eppler 2006; Kinchin 2001).
Others have noted that the rigid rules used for identifying concepts and their multiple
relationships does not make the process simple or easily to learn, and the linear nature of
concept maps mean that they are not adequate to capture more complex relationships
High Educ (2011) 62:279â€“301 285
between concepts. In particular, they do not enable easy separation of concepts of critical
importance from those of secondary importance (Daley 2004).
It is also impossible to distinguish identification of concepts from identification of
arguments using a concept map. For example, it is easy to imagine developing a concept
map that canvasses the causes and effects of the global financial crisis. In a complex issue
such as this, multiple causes can be linked to effects by means of relational arrows. A
major disadvantage of concept mapping, however, is that it is limited to relations between
concepts. Many issues require more than an identification of relationships between concepts; they require arguments to be made for positions that need to be defended, and
objections to those positions. For example, it is difficult to imagine how a concept map
could represent an argument for the claim that: â€˜â€˜The US should have intervened earlier in
the global currency crisisâ€™â€™. This kind of relationship is not, strictly speaking, relational.
This is, of course, not the fault of the concept mapping format. Concept mapping is a tool
that was designed for a different purpose. This is a limitation of concept mapping and it has
led to the development of a new kind of tool; a tool for mapping arguments.
A relatively recent innovation, developed since 2000, is computer-aided argument mapping (CAAM). Available in a wide-range of software formats,3 argument mapping has a
different purpose entirely from mind maps and concept maps. Argument mapping is
concerned with explicating the inferential structure of arguments. Where images and topics
are the main feature of associative connections in mind maps, and concepts are the main
relationships in concept maps, inferences between whole propositions are the key feature
of argument maps.
â€˜â€˜Argumentsâ€™â€™ are understood in the philosopherâ€™s sense of statements (â€˜â€˜premisesâ€™â€™)
joined together to result in claims (â€˜â€˜conclusionsâ€™â€™). An example of an argument map
defending the proposition that The Reserve Bank will increase interest rates is given in
Fig. 4. At the first (top) level of the argument there is the contention. This is followed in
this example by a supporting claim (under the link word â€˜â€˜becauseâ€™â€™) and an objection
(under the link word â€˜â€˜butâ€™â€™). These are, in turn, supported by more claims of support or
objection (which become rebuttals when they are objections to objections): In the software,
claims, objections and rebuttals are coloured differently. Finally, basis boxes which provide defence for the terminal claims, are provided at the end of the argument tree.
Objections and rebuttals to objections can be added at any point in the map (in different
colours for easier visual identification). The â€˜â€˜basisâ€™â€™ boxes at the terminal points of the
argument also require evidence in place of the brackets provided. Some evidence has been
provided (â€˜â€˜statisticsâ€™â€™, â€˜â€˜expert opinionâ€™â€™, â€˜â€˜quotationâ€™â€™).
Unlike mind mapping and concept mapping, argument mapping is interested in the
inferential basis for a claim being defended and not the causal or other associative relationships between the main claim and other claims. The software also allows for an
automatically-generated description of the argument in text-form. In some template
argument formatsâ€”provided with the softwareâ€”the mapping program also constructs a
prose version of the argument complete with a limited display of linking words. However,
this function is presently underdeveloped, and is a caricature of what would be needed in
university-style assignment. However, this impressive facility is indicative of where
software tools are headed.
3 Harrell provides a comprehensive list of argument mapping software (Harrell 2008).
286 High Educ (2011) 62:279â€“301
As noted, CAAM is still fairly new. Nonetheless, there have been several studies
demonstrating its impact on student learning, especially improvements in critical thinking
(Twardy 2004; van Gelder 2001; van Gelder et al. 2004). Twardy demonstrated an
improvement in critical thinking skills as measured by a standard instrument in pre- and
post-test by a 0.72 gain of standard deviations. Van Gelder, Bissett and Cumming demonstrated an even higher gain of 0.8 standard deviations in their study. A very recent study
demonstrated greatest gains in students with the poorest argument analysis skills in two
separate studies over the course of one semester (Harrell 2011)
The main advantage argument mapping may have over other forms of mapping tools is
that it focuses on a certain sub-class of relationships (i.e., logical inferences between
propositions). It also puts limitations around the items being mapped. There is a clear sense
in which argumentsâ€”and not relationships and associationsâ€”have â€˜â€˜boundariesâ€™â€™. Eventually, all reasons have to be grounded. These grounds are presented as terminal â€˜â€˜basisâ€™â€™
boxes for assumptions. These are then evaluated for plausibility as shown. With mind
mapping and concept mapping, connections can potentially go on â€˜â€˜foreverâ€™â€™.
A weakness of argument mapping is also its strength; argument mapping does not
capture looser, more tangential relationships, e.g., cause and effect. This makes it a tool
with a very precise purpose. However, as we shall see in the final section, there is no reason
why the advantages of argument maps cannot be supplemented with the advantages of
other available tools, and with additional refinements that do not exist at present.
Another disadvantage of argument mapping is that it can assume too much. In the
educational context, argument mapping exercises can assume that students have a sufficiently clear understanding of a topic or issue and the precise nature of the task at hand.
However, this understanding may often be absent. Students themselves may need to define
The Reserve Bank
Inflation needs to
2.9% too high
inflation rate of
2.9% is too high.
ABC news online
Macquarie Bank senior
economist Brian Redican
Price Index (CPI)
is rising at 1.9 %.
This rise is lowest in
nearly eight years.
ABC news online
The RB will not
rates during an
The Reserve Bank
will be reluctant to
outcome of the
The RB Governor
has said an election
would not stop him.
The claim is widely
“If it’s clear that something needs to be
done, I don’t know what explanation we
could offer the Australian public for not
doing it, regardless of when an election
might be due.”
– Glenn Steven, Reserve Bank Governor
Fig. 4 Argument map using the software Rationale (http://www.austhink.com)
High Educ (2011) 62:279â€“301 287
the scope of the issue to be addressed and the exact parameters of the task. For example,
faced with an essay topic as:
â€¢ The changing roles of men and women have been good for society. Discuss.
Students may initially create a series of arguments which implicitly focus on changes in
their society, the society in which they are presently living, or perhaps developed Western
countries generally. They may never actually articulate what the changes might be, or in
what respects (or for whom) they might be considered â€˜â€˜goodâ€™â€™ (nor might they define what
â€˜â€˜goodâ€™â€™ means). They may not consider whether or not to confine themselves to particular
changes that have taken place over a particular time period in a particular culture.
Assignment topics are often deliberately ambiguous to allow students to demonstrate their
abilities in deconstructing the meaning of the topic itself.
Working out what needs to do in an essay and why is a preparatory, and a critically
important step, to being able to map an argument successfully. Students will have to do a
considerable amount of initial reading and thinking and struggle with key concepts before
coming to an understanding of the exact task they need to complete. It is only after this
process that the student can map an argument. Argument mapping software offers no help
with these preparatory steps. However, this is precisely where a further development in
mapping technologies might be able to help (see â€˜â€˜A convergence of mapping tools?â€™â€™).
Table 1 summarises the differences between the three forms of mapping discussed in
Notice that argument mapping shares the hierarchical form with concept mapping,
andâ€”in some variants at leastâ€”argument mapping shares the design principles of colours,
shading, and line thicknesses with mind mapping. Note too the increasing level of
sophistication in the tools. Where mind maps have a high degree of generality in their
application, concept maps are more specific (focussing on relational factors) and argument
mapping is the least general (more specific) in application of all. This indicates, in one
sense, some degree of perhaps unintended evolutionary sophistication in the development
of these tools. In the final section of this paper, suggestions will be made on the new
directions that this evolution might take.
An important area of difference between the mapping techniques is in the register and
formality of language used, i.e., the differences in linguistic â€˜â€˜granularityâ€™â€™ (see column to
far right of table). Whereas in mind mapping the language is fairly â€˜â€˜looseâ€™â€™, and can
capture a variety of associative relationships, in argument mapping the linguistic relationships are limited to whole propositions or statements linked by logical connectors such
as â€˜â€˜becauseâ€™â€™ or â€˜â€˜howeverâ€™â€™. Argument mapping requires precise rules of construction.
This forces explicit connections between propositions (from premises to conclusions or
contentions). Argument mapping thereby demonstrates a specific utility and considerable
fitness to purpose. Mind mapping does not have these constraints. Concept mapping
occupies a space in-between the loose and tightly constrained language in argument maps,
and the looser, tangential, associative language of mind maps. Concept maps typically
involve the use of prepositional phrases such as â€˜â€˜in relation toâ€™â€™, â€˜â€˜is a result ofâ€™â€™, and so on;
but, as we have seen, sometimes these rules are not adhered to. Compare, for example, the
very different examples of concept maps given earlier. The non-linear economics concept
map has elements of a more constrained mind map as well as having similarities to a
This highlights an important difference in terms of flexibility. Mind maps can sometimes take on similarities to concept maps, and can occupy a more structured place further
along the continuum between the three mapping types. It has a wider utility. This is not
288 High Educ (2011) 62:279â€“301
Table 1 Summary of the differences between knowledge-mapping software
Purpose Structure Level of
Nodes Linking devices Linking words Language register
Associations between ideas,
topics or things
Associative words (â€˜â€˜Useâ€™â€™ and
â€˜â€˜coloursâ€™â€™ and â€˜â€˜linksâ€™â€™)
Relations between concepts Hierarchical,
Boxes Arrows Relational phrases (â€˜â€˜in relation
toâ€™â€™, â€˜â€˜is composed ofâ€™â€™, etc.)
Inferences between claims
(conclusions) and support
Inferential linking words
High Educ (2011) 62:279â€“301 289
the case with argument maps which have a very specific utility. Therefore there is an
asymmetry in terms of the degree to which the mapping types can overlap in function.
The rules for mind mapping do not make any specific assumptions about learning as a
process or the nature of knowledge. The rules are â€˜â€˜looserâ€™â€™ and therefore a mind map can
sometimes take on the characteristics of a concept map. By contrast, a map that would
satisfy the rules for an argument map, cannot be a mind map because the rules of
application are much stricter. A concept map occupies something of a middle ground,
but is closer in form to a mind map than an argument map (I am indebted to an
anonymous reviewer for this point).
Why mapping tools work
The most important reason for the widespread use of mapping tools is that they are claimed
to benefit student learning. The educational justification for mapping tools was outlined
briefly in â€˜â€˜The purpose and justification for mapping toolsâ€™â€™. However, specific details
which might explain why mapping tools work were not discussed.
Knowledge mapping allows meaningful learning to occur
Hay et al. usefully distinguish between â€˜â€˜non-learningâ€™â€™, â€˜â€˜rote learningâ€™â€™ and â€˜â€˜meaningful learningâ€™â€™ (Hay et al. 2008). Using the pedagogical views of Kolb and Jarvis
(Jarvis 1992; Kolb and Fry 1975) along with an application of concept mapping tools,
they track changes in knowledge that results from the presentation of learning material
to university students (Hay et al. Forthcoming). They find that measurable improvements in meaningful learning occur using concept mapping under test conditions with
They find that non-learning occurs when no detectable change in knowledge occurs
before and after the presentation of new material. Rote learning occurs when new information is added (or rejected) in a studentsâ€™ knowledge store, but there is no new integration
made between the new or substituted information. Students accept and reject information
but do not think about it or relate it to other knowledge they possess. Meaningful learning,
by contrast, occurs when new perspectives are integrated into the knowledge structure and
prior concepts of the student. The Fig. 5 explains these differences. Hay et al. find that
concept mapping can â€˜significantly add to the quality of university teachingâ€™ as it promotes
meaningful learning (Hay et al. 2008, p. 308).
Mapping allows the presentation of new material to build on existing knowledge
Having a source of prior knowledge that is well-structured and retrievable allows students
to â€˜â€˜scaffoldâ€™â€™ new learning. This enables meaningful learning to occur. Structured diagrams incorporating proseâ€”such as the mapping devices mentioned in the paperâ€”are able
to represent new information better than traditional discursive prose on its own (van Gelder
2007). This, in turn, allows efficient learning and integration with information stored in
memory. There are two reasons why this occurs: map-making improves the usability of
information and also complements what the brain can do imperfectly. Both improve student
learning. Let us take each of these points in turn.
290 High Educ (2011) 62:279â€“301
Maps make new information more usable. Usable information can be more easily processed. This is why we draw maps in preference to providing long and detailed verbal
directions. Usability has, of course, been a driving force for improvements in other areas. A
fountain pen, and a ball-point pen, both aid in the skill of writing; so does a word processor. The word processor improves on earlier writing tools by being more usable. A
beginnerâ€™s windsurfing board provides a more usable way of improving windsurfing skills
(by being larger and more stable) than an â€˜â€˜expertâ€™â€™ board. The traditional manner of
presenting and understanding information is, of course, in prose (either spoken in a lecture
or written in textbooks). Mapping devices, it is claimed, are now more usable than prose
and results in improvements in teaching and learning.
More usable information is better in improving skill development than less usable
information. As noted by Hay et. al. the basic methodology of university teaching has
remained unchanged for centuries, despite transformations in other areas of the tertiary
sector in the past few decades. Learning simply by reading textbooks, or listening to a
presentation (incorporating linear-structured Powerpoint slides) is far more likely to result
in non-learning or rote learning (Hay et al. 2008). However, if students are asked to study,
draw or manipulate a map of what they have learned, this may yield improved learning
because it is more usable (the activity of making a map is also important, as discussed
below). This is because maps aid in linking new information with what they already know.
Mapping augments the brainâ€™s ability to understand, retrieve and process information. It
does this by complementing what the human brain can already do (albeit imperfectly). In
the cognitive science literature, this is known as complementation. Our memory stores are
seriously limitedâ€”some suggest as limited as holding only four pieces of information at a
Fig. 5 Different kinds of learning in an intervention involving students using concept mapping under test
conditions (Hay et al. 2008, p. 299)
High Educ (2011) 62:279â€“301 291
time (Cowan 2000). Similarly, our ability to â€˜â€˜chunkâ€™â€™ complex pieces of relevant information and sift them from irrelevant information is limited. Mapping allows this to be done
efficiently because diagrams are more easily stored in memory than other kinds of representational formats (Larkin and Simon 1987). Memonics also assist this. In â€˜â€˜The purpose
and justification for mapping toolsâ€™â€™, a reason was given for this. Maps allow the separate
encoding of information in memory in visual and well as propositional form.
Mapping allows students to build new and meaningful knowledge
links by active engagement
The educational literature suggests that meaningful engagement is a critical factor in
promoting deeper learning. When students are meaningfully engaged, they form longerlasting knowledge representations in memory (Craik and Lockhart 1972). The educational
focus recently has moved from what the student is, and how to teach them (i.e., studentcentred learning), to what the teacher does and how to improve it (i.e., teacher-centred
learning), to a focus now on what the student does (i.e., how they engage in taught
material) (Biggs 1999). Increasingly, good teaching and learning is focussed on how to use
engagement activities, such as problem-based learning, to teach, in a way that will engage
students in learning and narrow the gap between more academically self-engaged students
and those less inclined.
By contrast, Hay et al. note that conventional teaching formats in the university environment involve simple â€˜â€˜narrative chainsâ€™â€™ delivered in a â€˜â€˜linearâ€™â€™ manner typically on
Powerpoint slides. This material is designed to be accessible to students, but it conceals
deep and complex networks of tacit scholarly information. The way information that is
taught to students was originally understood and constructed by academics themselves is
rarely explained. Constrained by the time-scheduling required in any given academic year,
well-intentioned teachers try to circumvent the process of learning for their students. This
paradoxically usually results in less meaningful learning. It results in â€˜linearity rather than
connectivity out of which genuine understanding arisesâ€™ (Hay et al. 2008, p. 306). It also
fosters a lack of engagement critical to the development of meaningful understanding. To
meet assessment demands, students begin to rely on memorisation techniques and cramming, not meaningful activities to ensure engagement and learning, and ultimatelyâ€”via a
transformative learning cycleâ€”expertise. This failure to allow opportunities for engagement leads naturally to non-learning or simple rote learning (Fig. 6).
Hay et al. recommends that teachers take the time to construct knowledge maps and
explain their understanding of any given topic. They are less specific about the various
forms that this mapping might take. They are concerned in their paper with the promulgation of concept maps as a teaching and learning tool. However, as we have seen in
this paper, knowledge or information mapping is available in a number of discrete forms.
All forms of mapping have their place in the context of teaching and learning. Maps of
associations (mind maps), causes and effects/relationships (concept maps) and maps of
reasoning (argument maps) should all be presented in lectures in preference to linear
narrative chains. This enables teachers to show the often tacit connections that exist
between related academic areas. This would have a secondary benefit of allowing students to check their own understanding. Requiring students to devise maps of their
learning for assessment, and encouraging them to compare and contrast those maps with
fellow students is an additional activity that can promote and encourage meaningful
292 High Educ (2011) 62:279â€“301
A convergence of mapping tools?
This next section is somewhat speculative. This paper has suggested that the various
mapping tools have complementary functions. Mind mapping is an associational mapping
tool; concept mapping provides a way of mapping relationships; argument mapping
focuses on maps of inferential structures and logical connections. However, the technology
is already available to enable a convergence of these mapping tools. All mapping tools
function to improve student learning in the ways just mentioned. All of them require the
pedagogical advantages of map-making to supplement and drive student learning. What is
needed is a way of combining these advantages in an educational tool that provides more
flexibility and power than the separate tools that exist at present. Work has already been
done on a complementary approach integrating conceptual diagrams, mind maps, concept
maps and visual metaphors into an over-arching educational strategy beginning with
conceptual diagrams, then mind maps, then concepts and finally visual metaphors (Eppler
2006). However, this approach did not consider the considerable advantages of argument
mapping, and treats the mapping tools separately. I am envisaging a single mapping tool
that does the role of each of the mapping tools that exist at present.
What would a convergent mapping tool look like? Work has already been done on
linking concept mapping software to libraries of resourcesâ€”such as Global Services
Library Network (https://glsn.com/)â€”so that various â€˜â€˜nodesâ€™â€™ in a map might allow
downloading of supporting evidence that was used in making the map (van der Laan and
Dean 2006). This has a number of advantages. Using this functionality, students can
demonstrate their understanding of an assessment topic in several independent ways: firstly
Fig. 6 The narrative sequence involves an expert  giving a linear presentation . Students may either
adopt meaningful learning  or memorisation  (from Hay et al. 2008). Meaningful learning is possible
only if engagement with the material is allowed enabling the construction of knowledge in meaningful
patterns drawing upon prior knowledge. This process can continue indefinitely until expertise is attained
High Educ (2011) 62:279â€“301 293
they can demonstrate, at minimum, that they know, i.e., can list key concepts (a form of
surface learning); second, that they understand the relationships between key concepts (a
deeper form of learning requiring analytical skills); and thirdly, they can provide links to
relevant external material (or material they have written themselves) supporting nodes in
the map. This third form of learning requires considerable research and analytical skills.
Each form of learning can, of course, be independently assessed. They can provide an
indication to teaching staff of the level of competence of students in a given subject area.
Work has also been done on providing argument maps as assessment tasks for students in
preference to written assignments in subjects such as Economics (Davies 2009a). Much
work has been done on all the knowledge-mapping tools in isolation as outlined previously.
What has not been done is work on how the different tools can be integrated.
If the various mapping tools can be integrated then a number of opportunities arise. For
one thing, the disadvantages and limitations of the discrete tools are no longer constraints.
An example will make this clear.
An excerpt from a concept map on an inventory for financial accounting showing the
relationship between revenues and cash flows is provided in Fig. 7. While incomplete, we
can see that as a concept map it meets the requirement of providing relationships between
key concepts. However, in the map, there is little evidence that a student understands the
argument for why revenue may be â€˜â€˜paid in advanceâ€™â€™. Indeed, the student may be able to
draw a concept map of this kind without understanding the reasoning behind any of the
financial practices themselves. The required information may be â€˜â€˜rote learnedâ€™â€™. We
cannot tell from the map provided whether surface or deep learning has been achieved.
This knowledge may need to be assessed by other assessment modalities such as essays or
exams, or tutorial participation.
Alternatively, students may be required to link argument maps at strategic points in their
concept map to nodes in the map that require argumentative justification. This would
demonstrate a greater level of understanding. The argument map may lie behind the nodes
in the concept map and be accessible by hyperlinks. Lecturers could assess both maps
simultaneously or separately.
This way of checking understanding might also proceed in another direction. At a
greater level of generality, mind maps may also be used providing evidence of a different
kind of learning. For example, at the top most level of the concept map above, â€˜â€˜Revenueâ€™â€™
And may be
defined as: Price of
goods and services
Paid for at
time of sale â€“
And may be
Fig. 7 A partial concept map on the relationship between revenues and cash flows
294 High Educ (2011) 62:279â€“301
is stated formally as a definition. However, it is not clear whether the student has considered other associated features of the definition. The student may have merely rote
learned or copied this definition from a lecturerâ€™s Powerpoint slide. Providing a link to a
mind map showing all the associated definitional features of â€˜â€˜revenueâ€™â€™ would ensure that
the student understood the concept well and was familiar with its various facets and
associated concepts, and could demonstrate this familiarity in an assessment task. A
schematic plan of how the comparative functions of each of the tools might be integrated is
presented in Fig. 8.
A convergence of mapping tools might proceed in other ways. As noted earlier
(â€˜â€˜Argument mappingâ€™â€™), to assist students in writing assignments, mapping tools also need
to help with the preparatory stages involved. Earlier, we looked before at a sample essay
â€¢ The changing roles of men and women have been good for a society. Discuss.
The point was made that mapping tools provide little assistance with tasks such as these,
which require a clear understanding of task requirements. A fully-converged mapping tool
should be able to assist students in developing this understanding. If this understanding can
be sequenced as a series of manageable stages, this should be able to be integrated into the
computational routines of a software package and form part of a converged mapping
(High level of generality)
(Medium level of generality)
(low level of
generality â€” high
IF there is support
for AM then it
should be used as
a teaching and
There is support for
? AM is already being
in some disciplines
(Twardy, 2004; van
AM is being used in
AM uses different
parts of the brain to
informtion to be
efficiently than text
(AM) should be
used as a teaching
and learning tool
Fig. 8 Proposed convergence of knowledge mapping technologies into a single integrated platform. The
central concept map may be devised initially to demonstrate familiarity with the relationship between key
concepts in a topic. At given points, or â€˜â€˜nodesâ€™â€™, certain concepts may be further elaborated in terms of
associative structures (mind maps), and inferential or logical arguments (argument maps). NB: Maps
provided are illustrative only
High Educ (2011) 62:279â€“301 295
Understanding how to approach an assignment or essay topic typically involves a
number of steps (although the steps may not be formally identified as such). These stages
have been discussed elsewhere in detail (Davies 2009b):
â€¢ The deconstruction phase. This involves being able to select key noun phrases in a
given essay topic provided by a lecturer and being able to define them (e.g., â€˜â€˜rolesâ€™â€™,
â€˜â€˜goodâ€™â€™, â€˜â€˜societyâ€™â€™). It also involves knowing the meaning of the direction words
provided by the instructor (e.g., â€˜â€˜Discussâ€™â€™, â€˜â€˜Analyseâ€™â€™, â€˜â€˜Traceâ€™â€™, â€˜â€˜Compareâ€™â€™, etc.).
â€¢ The representation phase. This involves being able map out the main parts of the body
of the proposed essay, i.e., what topics will be discussed in each part. This is quite
different from a mind map, concept map or an argument map. It is equivalent to
â€˜â€˜brainstormingâ€™â€™ the form or structure that the essay will take. An essay plan, as
opposed to a knowledge map requires an overview of which issues and arguments
should be presented, and the order of their presentation (i.e., from weak to strong or
vice versa). Typically, the essay structure that will be formed will mirror the parts of
the assignment topic given by a lecturer, but thought will need to be given to
arrangement of ideas within each section.
â€¢ The issues phase. This involves further clarity on the issues relevant to each of the key
terms in an essay topic (e.g., what does it mean for changing gender roles to be â€˜â€˜goodâ€™â€™
for society?â€™â€™ In what sense?) This requires some idea of the evidential support that is
needed in the essay. This part of the preparation would benefit from concept mapping
and mind mapping.
â€¢ The research phase. This involves knowing where to find academic support for the
points made in an essay (e.g., the construction of search statements to be used in
â€¢ The argument phase. This involves being able construct a clear argument drawn from
wide reading. Argument mapping may be used here.
â€¢ The writing phase. Written assessment at university level takes the form of various
genres: essays, empirical reports, annotated bibliographies, literature reviews, summaries and critiques, case studies, and so on. Each genre involves the ability to writeâ€”in
clear and flowing proseâ€”the point or issue being defended. But the style of writing and
the structural requirements are very different. There are, of course, commonalities
among the genres. At postgraduate-level, for example, an introduction typically
involves an â€˜â€˜funnelâ€™â€™ structure that moves from the general topic, to the specific issue
under consideration, to the gap in the research (using embedded citations as support), to
the thesis statement and then an outline of the essay to follow. â€˜â€˜Methodologyâ€™â€™ and
â€˜â€˜Discussionâ€™â€™ sections in report writing have unique and predictable writing genres as
well. In general, good academic writing of all genres from the â€˜â€˜generalâ€™â€™ to the
â€˜â€˜specificâ€™â€™, and uses an arrangement of part-whole relationships between major ideas
and support for those ideas (e.g., support from academic literature).
An integrated mapping software should assist students in some or all of these areas. This
might be possible in further developments of mapping tools. Suggestions for how this
might happen are provided below:
â€¢ Assignment topics could be entered by students into an integrated mapping software.
Key parameters of a topic, such as important concepts, discipline-specific definitions of
terms, etc. could also be added by lecturers via a separate interface accessed by means
of a common course or subject code.
296 High Educ (2011) 62:279â€“301
â€¢ Key noun phrases might be highlighted in the assignment topic that automatically
trigger mind maps of associated key terms and synonyms. Direction words might be
explained with an in-built glossary of academic terms which could be tailored to
â€¢ Templates for developing â€˜â€˜blockâ€™â€™ and â€˜â€˜chainâ€™â€™ style essay structures might be made
available. (A â€˜â€˜blockâ€™â€™ essay presents all the points â€˜â€˜forâ€™â€™/â€˜â€˜advantagesâ€™â€™ or â€˜â€˜againstâ€™â€™/
â€˜â€˜disadvantagesâ€™â€™ for a topic first, then all the points for the opposing position; a
â€˜â€˜chainâ€™â€™ essay presents one point, then a point against, then a second point, second
point against, and so on).
â€¢ Issues for students to consider might be automatically generated based upon clusters of
key terms entered and ranked by relevance.
â€¢ Search statements of key terms, e.g., (Man OR Male) AND (Woman OR Female) AND
(Gender role OR Sex role) AND (Good OR Beneficial OR Advantageous), etc., might
be automatically constructed from submitted material to be used in databases. These
databases might also be linked to the software.
â€¢ Writing templates for different sections of assignments (essays, empirical-style reports,
case-style reports, etc.) might be made available which are suited to the needs of
students and which follows the accepted academic structure commonly used in
universities. Attempts have been made to articulate design taxonomies for graduate
student writing that use predictable structures of nested part-whole relationships
between ideas and support for ideas using commonly-used linking phrases (Rochecouste 2005). These taxonomies could be incorporated into a converged mapping tool.
An example of this is provided in Fig. 9:
Beyond defining key topic and task words and constructing writing templates, students
might also be assisted by an integrated mapping tool in turning essay statements into
questions. Questions are always easier for students to begin addressing than statements. For
example, the example provided previously can be more easily approached if the topic is
transformed into: Have the changing roles of men and women been good for society? A
student can then be directed to a template with the following terms listed: â€˜â€˜YESâ€™â€™ (the
changing roles have been good), â€˜â€˜YES butâ€™â€™ (the changing roles have generally been good
with minor exceptions to this view), â€˜â€˜yes BUTâ€™â€™ (the changing roles have generally been
good, however, there are major exceptions to this view), and â€˜â€˜NOâ€™â€™ (the changing roles have
not been good) (for an elaboration of this technique, see Davies 2009b). This might translate
into an argument map proforma which could then be modified and made more detailed.
This paper has been somewhat speculative in terms of the directions in which a converged mapping tool might take us in the future. Ideas for improvements are easy to state.
Implementation is, of course, much harder. However, at present, none of the mapping tools
discussed in this paper help students with the remedial requirements that are often needed.
Perhaps an integrated knowledge mapping tool could do more in future to help students
recognise the writing process and the conventions of the essay genre and the logic behind
This paper has argued that there are sound reasons to consider knowledge-mapping in its
various forms as a supplement to other teaching and learning activities. The paper has
outlined the differences between the main forms of map-making: mind maps, concept maps
High Educ (2011) 62:279â€“301 297
and argument maps, and has provided an educational justification for their use. The paper
claims that the choice of a given mapping tool largely depends of the purpose or aim to
which the tool is used. However, the paper also suggests that these tools may well be
converging to offer educators as yet unrealised and potentially complementary functions.
While the idea of using knowledge maps is decades old, it is only in the early twenty-first
century that this kind of map-making has come of age. This development provides new
teaching and learning tools for both students and teachers that will enrich and provide new
directions in education in the future.
Acknowledgments My thanks to Tim Beaumont and two anonymous reviewers from the journal for
useful comments on earlier versions of this paper.
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