Using concept mapping as a tool for conducting research: An analysis of three approaches

Figures & data

Table 1. Matrix for analysing empirical studies using concept maps

#	Article	Study area	Method	Research phase	Advantages	Challenges/limitations

Table 2. Summary of main findings

	Relational approach	Cluster approach	Word frequency approach
Data collection	Participant-generated concept maps	N/A	N/A
	Researcher-generated concept maps
Data analysis	Identification of Themes	Participant interpreted clusters	Identifying main themes
	Summarizing interview transcripts	Researcher interpreted clusters	Studying inter-relationships
	Identifying interconnectedness among themes
Data presentation	Illustrate concepts & connections	Software generated concept maps	Simple concept maps
	Show framework of research or research process		Nuanced concept maps
	Present findings		Concept maps in colour

Table 3. Trochim’s concept mapping research methodology

Step 1	Preparation	Identifying participants and the specific topic focus
Step 2	Generation	Participants generate statements/responses to the brainstorming prompt
Step 3	Structuring	Statements are sorted and rated
Step 4	Representation	Statements are represented as point maps which are then clustered and mapped by concept mapping software
Step 5	Interpretation	Clusters are labelled
Step 6	Utilisation	Discussion follows on how the concept map can be used to inform programme planning or evaluation

Table

Relational approach
Research Phase	Strategy used	Studies
Data collection	Participant-generated concept maps	Wheeldon and Faubert (2009)
		Jones (2000)
		Xie and Sharma (2011)
		Nicholls et al. (2007)
		Brandt and de Mortanges (2011)
		Hutchings and Corr (2012)
	Researcher-generated concept maps	Meagher-Stewart et al. (2012)
		Panniers et al. (2003)
		Baugh et al. (2014)
Data Analysis	Identification of Themes	Vanderheide et al. (2013)
		Pfau et al. (2009)
		Meagher-Stewart et al. (2012)
		Friedrich et al. (2011)
		Sander et al. (2012)
	Summarizing Interview Transcripts	Kinchin et al. (2010)
		Tiberghien et al. (2011)
	Identifying Interconnectedness Among Themes	Baugh et al. (2014)
		Henderson et al. (2007)
		Egusa et al. (2010)
Data Presentation	Illustrate Concepts & Connections	Morrison (2006)
	Show Framework of Research or Research Process	DeBlieck et al. (2013)
	Present Findings	Baugh et al. (2014)
		Mount and Andrée (2013)
Cluster approach
Research Phase	Strategy Used	Studies
Data Collection	N/A
Data Analysis	Participant Interpreted Clusters	Scahill et al. (2010)
		Reavley et al. (2010)
		Baldwin et al. (2004)
		Dawson et al. (2012)
		Campbell and Salem (1999)
		van Manen et al. (2012)
		Burke et al. (2005)
		Burke et al. (2009)
		Ries, Voorhees, Gittelsohn, Roche, and Astone (2008)
		Nalavany et al. (2011)
	Researcher Interpreted Clusters	Kunkel et al. (1999)
		Schuck and Liddle (2004)
		Cash et al. (2006)
		Brown, Sigvaldason, and Bednar (2005)
		Brown, Bednar, and Sigvaldason (2007)
		Brown, Sintzel, Arnault, and George (2009)
		Brown et al. (2009)
		Brown (2007)
Data Presentation	Software generated Concept Maps	All studies using this approach presented the software generated concept maps
Word frequency approach
Research Phase	Strategy Used	Studies
Data Collection	N/A
Data Analysis	Identifying Main Themes	Khalid et al. (2013)
		Wu et al. (2014)
		Poser et al. (2012)
		Noble et al. (2011)
		Bell and Blashki (2013)
		Liesch et al. (2011)
	Studying Inter-relationships	Fanaian et al. (2013)
		Cretchley et al. (2010)
		Hostager et al. (2013)
		Baker et al. (2011)
Data Presentation	Simple Concept Maps	Constantinou and Kuys (2013)
		Kyle et al. (2008)
		Martin and Rice (2007)
		Davies and Beamish (2009)
	Nuanced Concept Maps	Baker et al. (2011)
		Cretchley et al. (2010)
		Bal et al. (2010)
		Middleton, Liesch, and Steen (2011)
		Pendergast et al. (2011)
		Chen and Bouvain (2009)
		Hepworth and Paxton (2007)
		Hostager et al. (2013)
	Colour coded Concept Maps	Freeman et al. (2012)
		Bell and Blashki (2013)
		Fruhen et al. (2013)

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