Positivist and interpretivist researchers have different views on how their research outcomes may be evaluated. The issues of validity, reliability and generalisability, used in evaluating positivist studies, are regarded of relatively little significance by many qualitative researchers for judging the merits of their interpretive investigations. In confirming the research, those three canons need at least to be re‑conceptualised in order to reflect the keys issues of concern for interpretivists. Some interpretivists address alternative issues such as credibility, dependability and transferability when determining the trustworthiness of their qualitative investigations. A strategy proposed by several authors for establishing the trustworthiness of the qualitative inquiry is the development of a research audit trail. The audit trail enables readers to trace through a researcher's logic and determine whether the study's findings may be relied upon as a platform for further enquiry. While recommended in theory, this strategy is rarely implemented in practice. This paper examines the role of the research audit trail in improving the trustworthiness of qualitative research. Further, it documents the development of an audit trail for an empirical qualitative research study that centred on an interpretive evaluation of a new Information and Communication Technology (ICT) student administrative system in the tertiary education sector in the Republic of Ireland. This research study examined the impact of system introduction across five Institutes of Technology (IoTs) through case study research that incorporated multiple evidence sources. The evidence collected was analysed using a grounded theory method, which was supported by qualitative data analysis software. The key concepts and categories that emerged from this process were synthesized into a cross case primary narrative; through reflection the primary narrative was reduced to a higher order narrative that presented the principle findings or key research themes. From this higher order narrative a theoretical conjecture was distilled. Both a physical and intellectual audit trail for this study are presented in this paper. The physical audit trail documents all keys stages of a research study and reflects the key research methodology decisions. The intellectual audit trail, on the other hand, outlines how a researcher's thinking evolved throughout all phases of the study. Hence, these audit trails make transparent the key decisions taken throughout the research process. The paper concludes by discussing the value of this audit trail process in confirming a qualitative study's findings.

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.