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Journal Issue
Volume 9 Issue 1, ECRM 2010 Special issue Part 2/Jan 2011 / Jan 2011  pp1‑87

Editor: Ann Brown, David Douglas, Marian Carcary, Jose Esteves

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What Can We Learn from Gender Research  pp1‑9

Eileen Trauth

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Evidence Analysis using CAQDAS: Insights from a Qualitative Researcher  pp10‑24

Marian Carcary

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Abstract

In data analysis the qualitative researcher seeks to produce a convincing explanation of the phenomena under investigation. Data analysis is an iterative process and requires reflection and interpretation on the researcher’s part on several levels. Interpretation suggests that there are no clear rules and that the researcher’s judgment, intuition and ability to highlight issues play an important part in the process. As a result, the issue as to how to analyse qualitative evidence is an area often poorly understood by researchers new to the interpretivist paradigm. The complexity of the data analysis process is increased due to the volume of evidence collected as part of a qualitative research study. The role of Computer Aided Qualitative Data Analysis Software (CAQDAS) in supporting this data analysis process is examined in this paper. It explores how CAQDAS can be used in facilitating the management of an extensive qualitative evidence base. CAQDAS enables researchers to manage qualitative data that would prove onerous through manual “pen and paper” methods. The paper examines the author’s use of the CAQDAS package N‑vivo in managing approximately 400 pages of single spaced interview transcripts resultant from a study on the evaluation of a new student ICT administrative system implementation in the Irish Institute of Technology (IoT) sector. This was an extensive empirical research study conducted across several case study sites and involved 49 informants and multiple sources of case study evidence. The objective was to develop a coherent cross‑case primary narrative of the system’s implementation from the evidence collected, reduce this to a set of key findings and ultimately develop a theoretical conjecture that provided fresh insights into the ICT investment evaluation process. The N‑vivo package served primarily as a support tool in managing the interview transcripts; in reflecting on the emerging themes; and in interpreting the body of evidence. It facilitated the identification of key points, the coding of key concepts that emerged from the body of evidence, and comparison between these concepts. It supported the later reclassification of concepts into a series of categories and sub categories; this helped to organise related concepts in relation to the overall research and facilitated greater understanding of the body of evidence. It supported the creation of memos to clarify emerging concepts and the categorisation of interview material to facilitate cross‑case analysis. Further, it facilitated analysis through for example relationship and model exploration. These features of N‑vivo played a vital role in producing a series of narrative accounts and ultimately the distillation of a new theoretical conjecture. 

 

Keywords: qualitative data analysis, CAQDAS, N-vivo, coding, categorisation, memos, interpretivist research, research audit trail

 

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Uncovering Hidden Meanings, Values and Insights Through Photos  pp25‑34

Maria Ryan, Madeleine Ogilvie

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A Strategy for Delayed Research Method Selection: Deciding Between Grounded Theory and Phenomenology  pp35‑46

Sebastian Reiter

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Counting on an Iterative Process: Initial Lessons from the Research Assessment Exercise 2008  pp47‑56

Deborah Knowles, Elisabeth Michielsens

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The use of the case study method in theory testing: the example of steel trading and electronic markets  pp57‑65

Jessica Claudia Iacono, Ann Brown, Clive Holtham

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Research Methodology by Numbers  pp66‑77

Graham Trevor Myers

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Student Research in a Web 2 world: Learning to use new Technology to Gather Primary Data  pp78‑86

Martin Rich

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