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Concept Mapping as a Learning Tool inHigher Education: A Critical Analysis ofRecent ReviewsIan M. Kinchin aa University of Surrey , Guildford , Surrey , United KingdomPublished online: 03 Mar 2014.

To cite this article: Ian M. Kinchin (2014) Concept Mapping as a Learning Tool in Higher Education:A Critical Analysis of Recent Reviews, The Journal of Continuing Higher Education, 62:1, 39-49, DOI:10.1080/07377363.2014.872011

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Ian M. Kinchin is Professor of Higher Education and Head of Department of Higher Education at the University of Surrey, Guildford, Surrey,

United Kingdom.

Address correspondence to Ian M. Kinchin, Department of Higher Education, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom

(E-mail: i.kinchin@surrey.ac.uk).

The Journal of Continuing Higher Education, 62:39–49, 2014

Copyright © 2014, Association for Con tinu ing Higher Education

ISSN 0737-7363

DOI: 10.1080/07377363.2014.872011

Introduction

Concept mapping is a tool that has been dem-

onstrated repeatedly to have a positive impact on the

quality of student learning (e.g., Nesbit & Adesope,

2006; Ritchhart, Turner, & Hadar, 2009) and has been

received positively within higher education (e.g., Gravett

& Swart, 1997; Santhanam, Leach, & Dawson, 1998),

and especially within nursing education (e.g., Lee et al.,

2013; Hunter Revell, 2012; Gerdeman, Lux, & Jacko,

2013). Indeed, the large number of research papers

that consider varying aspects of concept mapping ap-

plication to higher education require the development

of suitable reviews to assist in the navigation through

the appropriate literature.

The analysis offered by Horton and colleagues (1993)

has been one of the most infl uential reviews of the past

20 years with more than 250 citations listed by Google

Scholar. The article concentrates exclusively on studies that

offer quantitative data—probably for ease of comparison

in the meta-analysis and possibly refl ecting a bias toward

“traditional, experimental” research designs. However,

the quantitative results given in the three papers identifi ed

within that meta-analysis as the most signifi cant are incon-

clusive, with two concluding no statistically signifi cant dif-

ference between control groups and test groups ( Lehman,

Carter, & Kahle, 1985; Heinze-Fry & Novak, 1990) and

one only showing signifi cance for certain types of students

when responding to certain types of questions (Schmid &

Telaro, 1990). Despite this, average results were seen to be

better for mappers than for non-mappers and these results

are seen as “indicators of a tendency toward an effect of

the experimental treatment” (e.g., Lehman et al., 1985,

p. 670). In all three papers, the most positive elements of

Concept Mapping as a Learning Tool

in Higher Education: A Critical Analysis

of Recent Reviews

Ian M. Kinchin

Abstract. This article aims to reexamine conclusions drawn by recent analyses of the literature on concept mapping as

an educational tool by considering the wider literature on curriculum development. This is with the aim of enhancing

the application of concept mapping to higher education. As part of an iterative review process, issues raised by previous

analyses are reconsidered with reference to educational research papers that were not considered previously. A greater

consideration of the context for learning provides alternatives to some of the assumptions that underpin the discipline-

specifi c concept mapping literature. The methodological shortcomings in the literature on concept mapping revealed by

earlier reviews are reevaluated to support refl ection on how the tool may be profi tably used and also how such reviews

may be conducted to better inform practice. This article offers enhanced guidance on the contextualisation of concept

mapping and recommendations for its future use in higher education.

Keywords. visualising learning; knowledge structures; literature reviews; university teaching; curriculum application

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40 • Concept Mapping as a Learning Tool

their conclusions are derived from more qualitative and

intuitive observations.

None of the three papers discussed by Horton and col-

leagues (1993) gave in-depth consideration of the environ-

ment for learning with concept mapping being “tacked on” to

lessons rather than being indicative of an overall approach or

underlying epistemological belief. For example, Schmid and

Telaro (1990, p. 80) explain how “the instructor introduced

the content in the normal fashion [mainly lecturing] and,

at the appropriate point, set aside time for each student to

create a map of a specifi ed concept.”

The possible confl ict that this could generate between

constructivist and objectivist traditions is not mentioned by

Schmid and Telaro, nor is the infl uence of the concept map-

ping tasks on the teachers’ perceptions of their students’

learning. Indeed, the impact of teachers is not only poorly

discussed in these papers, but is seen by some as irrelevant

to the research process: “Because . . . the teachers were all

of similar experiences and ability . . . [they] were not con-

sidered signifi cant infl uences in this study”(Lehman et al.,

1985, p. 669). This should raise a query. If teachers are not

signifi cantly infl uencing what goes on in their classrooms,

what are they doing there? Through their personalities and

classroom performances, teachers are one of the strongest

infl uences in the classroom (e.g., Reiss, 2000). In striv-

ing to conduct controlled, laboratory-style experiments,

authors have attempted to neutralize (or ignore) contextual

factors which may have had the most infl uence upon their

results (Cobern, 1993). This is an issue that persists in the

literature (e.g., Karpicke & Blunt, 2011).

However, a comparison of more recent literature

reviews will reveal discrepancies in the literature and varia-

tions in interpretation as the literature has become more

diverse in its application and methodological approach (e.g.,

Pudelko, Young, Vincent-Lamarre, & Charlin, 2012; Daley &

Torre, 2010). The critical analysis of mapping as a learning

strategy offered recently by Pudelko and colleagues (2012) is

welcomed and provides a necessary addition to the literature.

However, the limited scope of that review (looking at 65 pa-

pers identifi ed from MEDLINE and published between 2000

and 2011) means that some of the conclusions drawn are not

generalizable to the wider application of knowledge mapping.

This exemplifi es the recent claim by Finfgeld-Connett and

Johnson (2013) that linear search strategies are unlikely to

generate search results that are helpful in knowledge building

and theory generation. This article offers an additional turn of

the review cycle (described by Boell and Cecez-Kecmanovic,

2010). As such, it is totally dependent upon earlier iterations

(e.g., Horton et al., 1993; Pudelko et al., 2012) that provide

the basis for further review.

Method

The typical review takes a predefi ned body of literature

(often from a predetermined source such as a database)

and then each publication is evaluated against a clearly

defi ned set of criteria to allow the process to be reproduced

by other researchers. However, such a structured approach

requires that research questions are fi xed before the review

starts. This may inhibit diversions into unanticipated areas

of interest or learning from adjacent areas (MacLure,

2005), and lead to an instrumental approach to the task

(Nind, 2006). Boell and Cecez-Kecmanovic (2010) have

been highly critical of systematic reviews that focus on

literature gathered in this way from a database for two

reasons: (1) databases are limited in their coverage, each

considering only a subset of academic journals, and (2)

a specifi c topic can be described by a range of keywords

so that search strategies often fail to capture all relevant

expressions. Boell and Cecez-Kecmanovic (2010) go on

to describe a more interpretivist approach to literature

review in which understanding of the literature is infl uenced

by the reading of each new paper in an iterative cycle. In

this way, rather than having fi xed questions at the outset,

new questions may emerge as a result of reading so that

additional search terms and related theories may assume

greater relevance during the review process.

Assumptions in the Literature

Where some mapping interventions are seen to have

an insignifi cant impact on subsequent student learning

(Wheeler & Collins, 2003), it has often been assumed that

the mapping has been ineffective at raising the quality of

student learning. The possibility that the examination fails

to adequately assess understanding is rarely considered,

even though students will say that they are able to pass

examinations without having to understand the content

being examined (Kinchin, Baysan, & Cabot, 2008). Exami-

nations tend to focus on recall of itemized facts (equating to

the nodes on a concept map), whereas mapping focuses on

the higher-level reasoning skills that are represented by the

links on a concept map. It is refl ection on these links that is

required to develop reasoning skills (McMillan, 2010).

The experimental approach of many studies builds on

the assumption that each student embarking upon a course

of study is starting his or her continued learning from the

same point. This is clearly erroneous. One of the values of

concept mapping is that it makes prior knowledge visible

(Hay, Kinchin, & Lygo-Baker, 2008; Popova-Gonci & Lamb,

2012). From this, one can see that students embark upon a

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The Journal of Continuing Higher Education • 41

course of study with quantitatively and qualitatively different

knowledge structures, and this prior knowledge has to be

integrated with new information in order for the student’s

understanding to develop (Clifton & Slowiaczek, 1981). As

prior knowledge is the only place for a student to continue

his or her learning (Ausubel, 2000), the structure of this

prior knowledge will infl uence the way in which he or she

will interact with new knowledge. Some prior knowledge

structures are more receptive than others to the assimilation

of new knowledge (Kinchin, Hay, & Adams, 2000; Hay &

Kinchin, 2006) and will be a determining factor in the suc-

cess of any particular mapping intervention for a particular

student as they will govern the likelihood of assimilation or

rejection of new content (Hay, 2007).

Concept Mapping Versus Mind Mapping

There are a number of mapping tools available to

the university teacher to support student learning and

this has caused some confusion in the literature. In their

review, Pudelko and colleagues (2012) considered mind

mapping (Buzan, 1995; Noonan, 2013) and concept map-

ping (Novak, 2010) together, with the justifi cation that

“… researchers often considered the two techniques to

be similar and, as a result, we did not distinguish between

them in our analysis” (p. 1,222).

Blurring of the boundaries between these tools rep-

resents a methodological error in the research literature

and reviewing it in this combined way simply replicates and

perpetuates that error. This lack of discrimination between

tools has also led Pudelko and colleagues (2012) to con-

sider verbal representations of the relationships between

concepts (i.e., the links on the connecting arrows) to be

“optional” in concept mapping. This has never been the

case for concept maps—indeed it is the descriptions of

the links that are seen to confer understanding within these

maps (Novak, 2010). Discussions of the various knowledge

mapping techniques have shown that mind mapping and

concept mapping are distinct tools with very different

uses (Eppler, 2006; Davis, 2011). Whilst mind mapping

is a helpful study tool that can facilitate rapid note-taking

and the retention of information (Noonan, 2013), concept

mapping is a tool that promotes a greater level of refl ec-

tion on learning that encourages the student to uncover

the systematic relationships between concepts (Eppler,

2006). It is this refl ective power of concept mapping that

provides potential as a learning tool in higher education,

and it is concept mapping as developed by Novak (2010)

that is the focus of this article.

An additional reason for the focus on concept mapping

here is that it is a tool that is deeply embedded in educa-

tional theory (Ausubel, 2000; Novak & Cañas, 2007), and

so it addresses the call for research that is conceptual and

thoughtful that will also give access to “a deeper under-

standing of the mechanism of its impact” (Krupat, 2010,

p. 854). Only by knowing why a certain intervention may

enhance learning can we go on to use our results to develop

a more effective curriculum.

Curriculum and Context

One of the key issues when implementing a concept

mapping intervention is the nature of the curriculum

in which it will be embedded. There are numerous

potential benefits to be gained from mapping knowl-

edge (e.g., Wexler, 2001), but it cannot be assumed

that they will all be realised in every intervention that

employs maps. As Tzeng points out, “concept maps with

different strategic orientations may lead to the forma-

tion of different mental representations . . . therefore,

instructors need to know exactly what they intend . . .

to determine whether the design of their concept

maps effectively conveys their instructional objectives”

(2010, p. 143).

This is emphasised by Cañas, Novak, and Reiska

(2012), who describe in some detail the variation in

outcome that may be achieved when students are offered

varying degrees of freedom, in terms of map content and

map structure (Figure 1).

When students start with a blank sheet of paper (top

right corner of the fi gure), they have total freedom in terms

of content to populate their map, and the structure that will

form. This is restricted when the student is told to start with

a particular concept and is restricted even more when a list

of concepts is given from which the student must select the

appropriate content. The most restricted mapping activity

would be a “fi ll-the-gap” activity where a student has to

insert the correct answer in a space on a pre-constructed

map. Where students are instructed to memorise a com-

plete map (bottom left corner of the fi gure), then we are

no longer considering meaningful learning, but rather rote

learning. The degree of freedom offered to a student within

a mapping activity needs to align with the amount of free-

dom that a student has within the curriculum more gener-

ally in terms of constructing personal understanding if the

mapping activity is to support the student’s learning rather

than offer a distraction from it. Therefore, as most concept

mapping activities would be aiming to promote higher-

level thinking and reasoning skills, it is not a surprise that

mapping is not seen to be a way of developing lower-order

skills such as memorisation and recall (Pudelko et al.,

2012, p. 1,221).

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42 • Concept Mapping as a Learning Tool

Student learning does not occur in a vacuum. It has a

context in which the student makes sense of what is going

on. This is why “controlled experiments” can be diffi cult to

design in the fi eld of classroom teaching. By controlling the

environment to make it replicable, it is diffi cult to retain the

ecological authenticity that enables educational research

to impact upon classroom practice. The nature of the cur-

riculum and the relationship between student and teacher is

diffi cult to replicate between researcher and student. Where

the fi t is not acknowledged, the observed results gained can

run against observations from authentic classroom practice

(e.g., Karpicke & Blunt, 2011). The curriculum helps to

provide this context, but in order for concept mapping to

have a role in the students’ learning, it must complement

the way in which the curriculum is applied, and the as-

sumptions that follow from that—in Wexler’s terms, the

“who, what and why” (Wexler, 2001).

Piihl and Philipsen (2011) have used the conceptual

lens provided by Gibbons and colleagues (1994) in their

studies of teaching, and consider that the context-indepen-

dent knowledge that students acquire in lectures (what they

term the “mode 1 curriculum”) can be viewed as different

from the context-dependent knowledge created through

the solving of practical problems, such as those that may

be encountered in the clinic or laboratory (“mode 2 cur-

riculum”) in terms of the “theory-of-application” employed

by each (Figure 2). By this they mean that in mode 1 the

teacher acts as expert, based on the premise that they hold

the appropriate knowledge to be taught. However, in mode

2, the teacher needs to be able to construct the knowledge

that is necessary for a given situation and should be seen

more as a change agent (Rogan & Anderson, 2011).

It would seem that the mode 1 curriculum would be

representative of the decontextualized research environ-

ment in which the students are encouraged to produce

concept maps that are static representations of acquired

knowledge, whereas the mode 2 curriculum would be a

more dynamic environment in which the maps are seen as

tools to aid the construction of understanding. The latter

would seem to fi t best with the constructivist underpinnings

of concept mapping (Novak & Cañas, 2007), where map

morphology and linking phrase quality are key indicators of

active learning (Popova-Gonci & Lamb, 2012). The mode 2

curriculum aligns with Wexler’s assertion that “knowledge

maps must direct the search for information, not end it”

(Wexler, 2001, p. 251).

Figure 1. Freedom of structure and freedom of content conditions during concept mapping (redrawn from

Cañas et al., 2012).

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The Journal of Continuing Higher Education • 43

Concept mapping seems to offer the most valuable

contribution to student learning where the mapping task

mirrors the actions undertaken to practise the discipline

being studied (DiCarlo, 2006). So, for example, in the

teaching of physiology, students who are encouraged to

construct concept maps are actively integrating the com-

ponents of the subject and identifying causal relationships

between them in a way that also typically refl ects the desired

learning outcomes of a physiology course (Henige, 2012).

If there is a mismatch between the learning practices and

the professional practices that represent the desired learn-

ing outcomes of a programme, then the result is unlikely

to be successful (DiCarlo, 2006).

Evaluating Maps (Quantitative and Qualitative

Analysis)

Whilst there has often been a tendency to score maps

to provide a clear and simple way of recording a student’s

progress, there needs to be some caution with this ap-

proach as the reduction of the rich insights to a student’s

learning offered by a map in this way has the potential

to lose vital information. For example, studies that look

only at the “proportion of correct ideas produced in the

concept map” (e.g., Karpicke & Blunt, 2011, p. 773) fail

to acknowledge that some concepts are more important

than others in the construction of understanding (Mintzes

& Quinn, 2007), or that students who may include a lot of

correct information in their maps may not always include

the most important terms or, indeed, place those key

terms in the most appropriate space on the map ( Clariana

& Taricani, 2010). It is also clear that students who

produce “poor” concept maps can fall equally into the

lower and upper quartiles of normal assessment regimes

(Johnstone & Otis, 2006). This is because some of the

poor maps can indicate students have a weak grasp of the

ideas under discussion whilst other (more knowledge-

able students) can produce an apparently poor map as

this may be suffi cient for them to act as a “set of keys”

to retrieve information from their memory and support

their reasoning strategies.

Figure 2. A conceptual framework to illustrate the link between curriculum and theory of application (redrawn

from Piihl & Philipsen, 2011).

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44 • Concept Mapping as a Learning Tool

Figure 3 offers depictions of exemplar concept maps

that may be typical of the “good” and “poor” maps that may

be produced by students across the spectrum of examina-

tion results. Those poor maps that are related to students

from the lower quartile of exam marks tend to have few

concepts with rudimentary links (therefore they might be

considered poor as they will achieve a relatively low score

when evaluated using scoring protocols such as that devel-

oped by Novak, 2010). In comparison, the poor maps that

are produced by students from the upper quartile of exam

results may also feature a small number of concepts (and

so also achieve a relatively low score), but these concepts

may better represent the key ideas within a topic and may

be linked with phrases that are more dynamic (and less

descriptive) in nature. The “good” maps that feature par-

ticularly among the middle quartiles of examination results

are often quite extensive in their content (and so may score

more highly), but may not be very selective in terms of the

concepts or links used.

This suggests that concept mapping may be viewed

primarily as a learning tool rather than as an assessment

tool (Johnstone & Otis, 2006). In most scoring protocols,

there is an underlying assumption that bigger equals better.

But with this starting point, one can be misled when expert

maps can be smaller than novice maps of the same subject.

This occurs because experts can select the key concepts

and explanatory links that are economical in presentation.

A more nuanced appreciation of student understanding that

goes beyond the quantity of information recalled requires

an acknowledgement of the structure and quality of maps

to complement the content that is included.

Qualitative analyses of concept maps have resulted in

the proposal to consider them by reference to their gross

morphology, as spokes, nets, chains (Kinchin et al., 2000),

and cycles (Safayeni, Derbentseva, & Cañas, 2005). These

structures have been shown to be indicative of particular

learning orientations (Kinchin, 2011a). Spokes tend to

offer no more insight to understanding than a bulleted

list and are often accompanied by static linking phrases.

Chains appear to correlate with rote learning and tend to be

learned as a complete sequence that is resistant to develop-

ment. Networks seem to be most closely associated with

Figure 3. Distribution of maps across fi nal exam results with exemplar map morphologies inset (redrawn and

modifi ed from Johnstone & Otis, 2006).

Lower Quartile 2nd Quartile 3rd Quartile Upper Quartile

“GOOD” MAPS “GOOD” MAPS “POOR” MAPS“POOR” MAPS

A CB

Examination results

Fre

qu

ency

of

map

s

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The Journal of Continuing Higher Education • 45

the structures of organic and inorganic chemistry (Green

& Rollnick, 2006).

The tendency of scoring of concept maps refl ects

the dominance in educational research of quantitative

methodologies to discover the relationship between, for

example, teaching interventions and learning outcomes.

However, it is clear that such studies are better at revealing

what a relationship might be than why the relationship is

as it appears. To uncover the why, a qualitative approach

is often required as “qualitative research is well-suited to

answer questions about how learners and teachers make

sense of the educational events in which they participate,

complex learning environments, and subtle learning rela-

tionships; learning outcomes that are best described rather

than counted or measured” (Hanson, Balmer, & Giardino,

2011, pp. 375–376).

And so while there is a tendency to want to score

concept maps for analysis of learning gains, there is also

a place for the qualitative analysis of maps (Kinchin et al.,

2000), as this will provide “insight into the nuances and

complexities of the learning and teaching processes” (Boet

& Goldman, 2012, p. 160).

Concept Mapping and Collaborative

Learning

Pudelko and colleagues (2012, p. 1,222) have inter-

preted Novak’s work to suggest that concept mapping is a

solitary activity in which learning occurs with “little guid-

ance,” whereas undergraduates would benefi t from greater

feedback and scaffolding to support their learning. This is a

misrepresentation of Novak’s work; Novak has stressed that

whilst learners must construct their own meanings, teachers

are in a position to facilitate it (J. D. Novak, personal com-

munication, 2012), and indeed within his “new model for

education,” Novak has repeatedly highlighted the importance

of scaffolding student learning by, for example, the use of

expert maps and feedback (Novak, 2005; Novak & Cañas,

2004; Cañas & Novak, 2008). Current literature on concept

mapping considers the benefi ts of collaborative concept

mapping (Kinchin, DeLeij, & Hay, 2005; van Boxtel, van der

Linden, Roelofs, & Erkens, 2010; Torres & Marriott, 2010;

Moon, Hansberger, & Tate, 2011), with particular reference

to the promotion of dialogue between teachers and students

(Kinchin, 2003; Hay, 2008). The importance of providing

feedback on students’ maps is emphasised by Morse and

Jutras (2008), who concluded that “concept maps without

feedback have no signifi cant effect on student performance,

whereas concept maps with feedback produced a measur-

able increase in student problem-solving performance and

meaningful learning, especially when the linking phrases

are dynamic and explanatory. The cycles offer the greatest

degree of dynamism and are often linked with iterative

learning processes in which the meaning of concepts can

evolve with each turn of the cycle. These structures each

have their roles to play in student learning and they are not

mutually exclusive, as one structure may evolve into another

over a period of time so that a spoke structure may develop

into a chain or a network as the student’s understanding is

elaborated and codifi ed in response to further learning. It

is also clear that whilst some structures are more or less

contextually appropriate in a given situation, the student

needs to appreciate this and to construct understanding

accordingly (Kinchin, 2011b).

Clariana (2010, p. 128) warns against training par-

ticipants to create hierarchical concept maps where the

domain organization may not be hierarchical as this will “al-

ter the obtained knowledge structure improperly towards

hierarchical relationships,” and goes on to comment that

this could “devastate the relationship between the artefact

obtained and the participant’s actual knowledge structure.”

Whilst concept mapping rules offer helpful guidelines and

help to maintain consistency of presentation to assist in

analysis for research purposes, they should not be used

to inhibit expression of understanding among learners or

to create confl ict with disciplinary ways of thinking. The

structure of the discipline must be acknowledged when

observing maps from various contexts. Indeed, where the

learning context is “multidisciplinary” in nature (such as in

the clinical sciences) it should be anticipated that a possible

duality of structures may coexist, and that this duality may

actually defi ne that particular area of study/practice (e.g.,

Anderson & Schönborn, 2008; McMillan, 2010; Kinchin &

Cabot, 2010; Clarke, 2011) as theory and practice combine

to form disciplinary expertise.

This provides additional justifi cation for the comment

made by Pudelko and colleagues (2012) that future map-

ping studies should “focus more on the representational

guidance . . . based on the fi eld of knowledge in question”

(p. 1,222). This also fi nds agreement from the work by

Donald (2002), who found that separate disciplinary areas

exhibit different disciplinary structures so that whilst the

sciences may be considered to be highly integrated and

tightly bounded, the humanities will be seen to be organised

into more loosely aggregated collections of concepts. The

structural consequences for the development of interdisci-

plinary approaches (for example with medical humanities;

Evans & Macnaughton, 2004) become visible. But even

within a single discipline, different subject areas can be

seen to be constructed in different ways—for example,

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46 • Concept Mapping as a Learning Tool

a decrease in failure rates” (p. 243). Some studies have

attempted to experimentally isolate the infl uence of concept

mapping, and by doing so they may have diluted the effect

they have set out to measure. This provides researchers with

a methodological paradox if isolating mapping from other

measurables then dissociates mapping from its context and

so reduces ecological validity.

Pudelko and colleagues (2012) are correct in their

assertion that “acceptance of concept mapping… came

about as a direct transfer of an educational solution from

one context to another . . . without undertaking an in-depth

analysis of the nature of the learning problem” (p. 1,222). It

is important to analyse higher education from a knowledge

structures perspective (Kinchin, 2011b; Kinchin, Cabot, &

Hay, 2008) before considering how concept mapping may

actively contribute to students’ learning to ensure that we do

not promote an inappropriate structure within any mapping

activity. This has also been emphasised recently by Gamble

(2014), who offers an analysis of the way in which the

structure of disciplinary knowledge can determine peda-

gogy and how “the relation between knowledge structure,

curriculum and pedagogy in different disciplinary subject

fi elds has crucial consequences for teacher competence”

(p. 68). This provides a qualifi cation to the assertion made

by Pudelko and colleagues (2012) that “. . . structuring

knowledge in propositional form can improve teaching

and learning in any fi eld of knowledge, regardless of its

nature” (p. 1,221), and would suggest that this should be

re-phrased to say “. . . with due regard to its nature.”

Recommendations

In order to avoid some of the weaknesses highlighted

with the literature reviewed by Horton and colleagues

(1993) and by Pudelko and colleagues (2012), the follow-

ing recommendations are offered to guide the development

of future concept mapping interventions:

Concept mapping should be used in compatible •

curriculum settings that refl ect the constructivist

underpinnings of the tool. It is important that the

concept mapping tool is epistemologically aligned

with the context in which it is set. If the teaching and

the assessment regimes within a curriculum are intent

on transmitting fixed information from teacher to

student, then the potential utility of concept mapping

is lessened. There must be room in the curriculum

for students to visualise personal understanding if the

tool is to be helpful. Concept mapping should be used

where assessment regimes are focussed on meaningful

learning and not memorization and recall.

Concept mapping should be used as a learning tool, •

“directing” the search for information, not “ending” it.

If the expert concept map represents the answer to

be memorised by students then the curriculum intent

is non-learning (Kinchin, Lygo-Baker, & Hay, 2008)

rather than meaningful learning (Novak, 2010).

Possible pathways to meaningful learning must be

recognised if concept mapping is to play an active part

in the students’ development.

Teachers/researchers should have clear instructional •

objectives for the use of concept mapping that need

to be conveyed to students. It is not helpful to students

to simply deposit concept mapping as an activity within

the teaching scheme unless there is a clear aim in

doing so. Teachers need to be clear regarding what the

benefi ts of a concept mapping activity might be, and

should share this with their students.

The degree of freedom afforded students in a concept •

mapping intervention should be justifi ed and explicit.

Students may be presented with a blank sheet of paper

or with a list of concepts to link. Either approach has

validity, depending what it is that the teacher is hoping

to achieve.

The structural grammar used within a concept •

mapping intervention should be representative of

the discipline. It is only sensible to insist that students

construct hierarchical concept maps if the structure

of the discipline being mapped is indeed hierarchical.

It is, therefore, important to determine the structure

of the discipline before asking students to map it. It

should also be noted that a single map may not be

adequate in representing the structure of applied

sciences, and that sequential mapping over time may

be required to observe changes in understanding.

Concept mapping should be combined with other •

learning strategies such as retrieval practices,

collaborative learning, dialogue, and feedback.

Concept mapping is most effective as a learning

tool when combined with complementary activities

to enhance the learning environment. Students’

interactions with concept mapping will be personal

and idiosyncratic, with some students requiring more

scaffolding and supplementary learning tools than

others in order to gain the most from concept mapping

activities.

Mapping interventions that offer consideration to these

six points are likely to offer greater utility to the students

involved, and result in more robust and ecologically valid

research reports in the future.

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The Journal of Continuing Higher Education • 47

References

Anderson, T. R., & Schönborn, K. J. (2008). Bridging

the educational research-teaching practice gap.

Conceptual understanding, part 1: The multifaceted

nature of expert knowledge. Biochemistry and

Molecular Biology Education, 36, 309–315.

Ausubel, D. P. (2000). The acquisition and retention

of knowledge: A cognitive view. Dordrecht, The

Netherlands: Kluwer Academic Publishers.

Boell, S. K., & Cecez-Kecmanovic, D. (2010). Literature

reviews and the hermeneutic circle. Australian

Academic & Research Libraries, 41, 129–144.

Boet, S., & Goldman, J. (2012). Review article: Medical

education research: An overview of methods. Canadian

Journal of Anesthesia /Journal Canadien d’Anethésie,

59, 159–170.

Buzan, T. (1995). The mind map book (2nd ed.).

London, UK: BBC Books.

Cañas, A. J., & Novak, J. D. (2008). Concept mapping using

cmap tools to enhance meaningful learning. In A.

Okada, S. Buckingham Shum, & T. Sherborne (Eds.),

Knowledge cartography: Software tools and mapping

techniques (pp. 25–46). London, UK: Springer-Verlag.

Cañas, A. J., Novak, J. D., & Reiska, P. (2012). Freedom

vs. restriction of content and structure during

concept mapping—possibilities and limitations for

construction and assessment. In A. J. Cañas, J. D.

Novak, & J. Vanhear (Eds.), Concept maps: Theory,

methodology, technology. Proceedings of the Fifth

International Conference on Concept Mapping,

17–20 September, Valletta, Malta (pp. 247–257).

Retrieved from http://cmc.ihmc.us/

Clariana, R. B. (2010). Deriving individual and group

knowledge structure from network diagrams and

from essays. In D. Ifenthaler, P. Pirnay-Dummer, &

N. M. Seel (Eds.), Computer-based diagnostics and

systematic analysis of knowledge (pp. 117–130).

New York, NY: Springer Science + Business Media.

Clariana, R. B., & Taricani, E. M. (2010). The consequences

of increasing the number of terms used to score

open-ended concept maps. International Journal of

Instructional Media, 37, 218–226.

Clarke, F. (2011). Injecting expertise: Developing

an expertise-based pedagogy for teaching local

anaesthesia in dentistry. Higher Education Research

Network Journal, 2, 29–43.

Clifton, C., & Slowiaczek, M. L. (1981). Integrating new

information with old knowledge. Memory and

Cognition, 9, 142–148.

Cobern, W. W. (1993). Contextual constructivism: The

impact of culture on the learning and teaching

of science. In K. Tobin (Ed.), The practice of

constructivism in science education (pp. 51–69).

Hillsdale, NJ: Lawrence Erlbaum Associates.

Daley, B. J., & Torre, D. M. (2010). Concept maps in

medical education: An analytical literature review.

Medical Education, 44, 440–448.

Davis, M. (2011). Concept mapping, mind mapping and

argument mapping: What are the differences and do

they matter? Higher Education, 62, 279–301.

DiCarlo, S. E. (2006). Cell biology should be taught as

science is practised. Nature Reviews Molecular Cell

Biology, 7, 290–296.

Donald, J. G. (2002). Learning to think: Disciplinary

perspectives. San Francisco, CA: Jossey-Bass.

Eppler, M. J. (2006). A comparison between concept

maps, mind maps, conceptual diagrams, and

visual metaphors as complementary tools for

knowledge construction and sharing. Information

Visualisation, 5, 202–210.

Evans, H. M., & Macnaughton, J. (2004). Should

medical humanities be a multidisciplinary or an

interdisciplinary study? Medical Humanities, 30,

1–4.

Finfgeld-Connett, D., & Johnson, D. (2013).

Literature search strategies for conducting

knowledge-building and theory-generating

qualitative systematic reviews. Journal of

Advanced Nursing, 69, 194–204.

Gamble, J. (2014). “Approaching the sacred”:

Directionality in the relation between curriculum

and knowledge structure. British Journal of

Sociology of Education, 35(1), 56–72.

Gerdeman, J. L., Lux, K., & Jacko, J. (2013). Using

concept mapping to build clinical judgment skills.

Nurse Education in Practice, 13, 11–17.

Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S.,

Scott, P., & Trow, M. (1994). The new production

of knowledge: The dynamics of science and

research in contemporary societies. London,

UK: Sage.

Gravett, S. J., & Swart, E. (1997). Concept mapping: A

tool for promoting and assessing conceptual change.

South African Journal of Higher Education, 11(2),

122–126.

Green, G., & Rollnick, M. (2006). The role of structure

of the discipline in improving student understanding:

The case of organic chemistry. Journal of Chemical

Education, 83, 1376–1381.

Dow

nloa

ded

by [

Uni

vers

ity o

f C

onne

ctic

ut]

at 1

7:58

10

Oct

ober

201

4

48 • Concept Mapping as a Learning Tool

Hanson, J. L., Balmer, D. F., & Giardino, A. P. (2011).

Qualitative research methods for medical educators.

Academic Pediatrics, 11, 375–386.

Hay, D. B. (2007). Using concept maps to measure deep,

surface and non-learning outcomes. Studies in

Higher Education, 32, 39–58.

Hay, D. B. (2008). Developing dialogical concept mapping

as an e-learning technology. British Journal of

Educational Technology, 39, 1057–1060.

Hay, D. B., & Kinchin, I. M. (2006). Using concept maps

to reveal conceptual typologies. Education and

Training, 48, 127–142.

Hay, D. B., Kinchin, I. M., & Lygo-Baker, S. (2008).

Making learning visible: The role of concept

mapping in higher education. Studies in Higher

Education, 33, 295–311.

Heinze-Fry, J. A., & Novak, J. D. (1990). Concept mapping

brings long-term movement toward meaningful

learning. Science Education, 74, 461–472.

Henige, K. (2012). Use of concept mapping in an

undergraduate introductory exercise physiology

course. Advances in Physiology Education, 36,

197–206.

Horton, P. B., McConney, A. A., Gallo, M., Woods, A. L.,

Senn, G. J., & Hamelin, D. (1993). An investigation

of the effectiveness of concept mapping as an

instructional tool. Science Education, 77, 95–111.

Hunter Revell, S. M. (2012). Concept maps and nursing

theory: A pedagogical approach. Nurse Educator,

37, 131–135.

Johnstone, A. H., & Otis, K. H. (2006). Concept mapping in

problem based learning: A cautionary tale. Chemistry

Education Research and Practice, 7, 84–95.

Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice

produces more learning than elaborative studying with

concept mapping. Science, 331(6018), 772–775.

Kinchin, I. M. (2003). Effective teacher↔student

dialogue: A model from biological education.

Journal of Biological Education, 37, 110–113.

Kinchin, I. M. (2011a). Relating knowledge structures to

learning styles and university teaching. In S. Rayner

& E. Cools (Eds.), Style differences in cognition,

learning, and management (pp. 129–142).

London, UK: Routledge.

Kinchin, I. M. (2011b). Visualizing knowledge structures

in biology: Discipline, curriculum and student

understanding. Journal of Biological Education,

45, 176–182.

Kinchin, I. M., Baysan, A., & Cabot, L. B. (2008).

Towards a pedagogy for clinical education: Beyond

individual learning differences. Journal of Further

and Higher Education, 32, 373–388.

Kinchin, I. M., & Cabot, L. B. (2010). Reconsidering the

dimensions of expertise: From linear stages towards

dual processing. London Review of Education, 8,

153–166.

Kinchin, I. M., Cabot, L. B., & Hay, D. B. (2008). Using

concept mapping to locate the tacit dimension of

clinical expertise: Towards a theoretical framework

to support critical refl ection on teaching. Learning

in Health and Social Care, 7, 93–104.

Kinchin, I. M., DeLeij, F. A. A. M., & Hay, D. B. (2005).

The evolution of a collaborative concept mapping

activity for undergraduate microbiology students.

Journal of Further and Higher Education, 29,

1–14.

Kinchin, I. M., Hay, D. B., & Adams, A. A. (2000). How

a qualitative approach to concept map analysis can

be used to aid learning by illustrating patterns of

conceptual development. Educational Research, 42,

43–57.

Kinchin, I. M., Lygo-Baker, S., & Hay, D. B. (2008).

Universities as centres of non-learning. Studies in

Higher Education, 33, 89–103.

Krupat, E. (2010). A call for more RCTs (Research that

is Conceptual and Thoughtful). Medical Education,

44, 852–855.

Lee, W., Chiang, C.-H., Liao, I.-C., Lee, M.-L., Chen, S.

L., & Liang, T. (2013). The longitudinal effect of

concept mapping teaching on critical thinking.

Nurse Education Today, 33, 1219–1223.

Lehman, J. D., Carter, C., & Kahle, J. B. (1985). Concept

mapping, vee mapping, and achievement: Results

of a fi eld study with black high school students.

Journal of Research in Science Teaching, 22(7),

663–673.

MacLure, M. (2005). “Clarity bordering on stupidity”:

Where’s the quality in systematic review? Journal of

Education Policy, 20, 393–416.

McMillan, W. J. (2010). Teaching for clinical

reasoning—helping students make the conceptual

links. Medical Teacher, 32, e436–e442.

Mintzes, J., & Quinn, H. J. (2007). Knowledge

restructuring in biology: Testing a punctuated

model of conceptual change. International

Journal of Science and Mathematics Education,

5, 281–306.

Moon, B. M., Hansberger, J. T., & Tate, A. (2011).

Concept mapping in virtual collaboration

environments. In B. M. Moon, R. R. Hoffman, J.

Dow

nloa

ded

by [

Uni

vers

ity o

f C

onne

ctic

ut]

at 1

7:58

10

Oct

ober

201

4

The Journal of Continuing Higher Education • 49

D. Novak, & A. J. Cañas (Eds.), Applied concept

mapping: Capturing, analysing, and organizing

knowledge (pp. 293–316). London, UK: CRC Press.

Morse, D., & Jutras, F. (2008). Implementing concept-

based learning in a large undergraduate classroom.

CBE—Life Sciences Education, 7, 243–253.

Nesbit, J. C., & Adesope, O. O. (2006). Learning with

concept and knowledge maps: A meta-analysis.

Review of Educational Research, 76, 413–448.

Nind, M. (2006). Conducting systematic review in

education: A refl exive narrative. London Review of

Education, 4, 183–195.

Noonan, M. (2013). Mind maps: Enhancing midwifery

education. Nurse Education Today, 33(8),

847–852.

Novak, J. D. (2005). Results and implications of a

12-year longitudinal study of science concept

learning. Research in Science Education, 35,

23–40.

Novak, J. D. (2010). Learning, creating, and using

knowledge: Concept maps as facilitative tools in

schools and corporations (2nd ed.). London, UK:

Routledge.

Novak, J. D., & Cañas, A. J. (2004). Building on new

constructivist ideas and cmap tools to create

a new model for education. In A. J. Cañas, J. D.

Novak, & F. M. Gonzalez (Eds.), Proceedings of

the First International Conference on Concept

Mapping, 14–17 September, Pamplona, Spain

(pp. 469–476). Retrieved from http://cmc.ihmc.us/

Novak, J. D., & Cañas, A. J. (2007). Theoretical origins

of concept maps, how to construct them, and uses in

education. Refl ecting Education, 3, 29–42.

Piihl, J., & Philipsen, K. (2011). A research-based

approach to university curriculum development

that prepares students for subsequent practice.

In C. Nygaard, N. Courtney, & C. Holtham

(Eds.), Beyond transmission—innovations in

university teaching (pp. 27–43). Faringdon, UK:

Libri Publishing.

Popova-Gonci, V., & Lamb, M. C. (2012). Assessment of

integrated learning: Suggested application of concept

mapping to prior learning assessment practices.

The Journal of Continuing Higher Education, 60,

186–191.

Pudelko, B., Young, M., Vincent-Lamarre, P., & Charlin,

B. (2012). Mapping as a learning strategy in health

professions education: A critical analysis. Medical

Education, 46, 1215–1225.

Reiss, M. J. (2000). Understanding science lessons:

Five years of science teaching. Buckingham, UK:

Open University Press.

Ritchhart, R., Turner, T., & Hadar, L. (2009). Uncovering

students’ thinking about thinking using concept

maps. Metacognition Learning, 4, 145–159.

Rogan, J. M., & Anderson, T. R. (2011). Bridging

the educational research-teaching practice gap:

Curriculum development, part 2: Becoming an agent

of change. Biochemistry and Molecular Biology

Education, 39, 233–241.

Safayeni, F., Derbentseva, N., & Cañas, A. J. (2005). A

theoretical note on concepts and the need for cyclic

concept maps. Journal of Research in Science

Teaching, 42, 741–766.

Santhanam, E., Leach, C., & Dawson, C. (1998). Concept

mapping: How should it be introduced, and is there

evidence for long term benefi t? Higher Education,

35, 317–328.

Schmid, R. F., & Telaro, G. (1990). Concept mapping

as an instructional strategy for high school biology.

Journal of Educational Research, 84(2), 78–85.

Torres, P. L., & Marriott, R. C. V. (2010). Handbook

of research on collaborative learning using

concept mapping. Hershey, PA: Information Science

Reference.

Tzeng, J.-Y. (2010). Design of concept maps and their

impacts on readers’ performance in memory and

reasoning while reading. Journal of Research in

Reading, 33, 128–147.

van Boxtel, C., van der Linden, J., Roelofs, E., & Erkens,

G. (2010). Collaborative concept mapping:

Provoking and supporting meaningful discourse.

Theory Into Practice, 41, 40–46.

Wexler, M. N. (2001). The who, what and why of

knowledge mapping. Journal of Knowledge

Management, 5, 249–263.

Wheeler, L. A., & Collins, S. K. R. (2003). The

infl uence of concept mapping on critical thinking

in baccalaureate nursing students. Journal of

Professional Nursing, 19, 339– 346.

Dow

nloa

ded

by [

Uni

vers

ity o

f C

onne

ctic

ut]

at 1

7:58

10

Oct

ober

201

4