Strategies in Qualitative Research

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Susan Berkowitz, Karla Eisen, & Izabella Zandberg, Westat, Rockville, Maryland USA States
“Using NVivo software as part of a multi team analysis of in depth interview data in a mixed methods evaluation”

This presentation will examine the impact of the introduction of computer assisted analysis tools, specifically NVivo, into the qualitative analysis portion of a large mixed methods study employing three teams of analysts with widely varying degrees of experience conducting qualitative analysis as well as different levels of familiarity and comfort with using the software.

Westat conducted a large mixed methods study of clinical research networks in the United States and internationally. As part of the study, qualitative data were collected through in-depth, semi-structured interviews with representatives of clinical research networks to discern barriers to and facilitators of networks’ efficiency and effectiveness in six domains of network functioning. Interviews were tape-recorded, transcribed and entered into NVivo for analysis. The analysis team was trained in use of NVivo on two separate occasions. For all analysts this was the first time they had used the software for a major analytic project.

Nine analysts were clustered in three analysis teams by content areas. Although this was not the original intent, each team used the software somewhat differently. For one team (comprised of the authors) a sample of transcripts (from the management and governance content area) was first selected, and initial common coding categories developed by agreement among the three analysts. The resulting coding tree was shared with the larger qualitative analysis team, who adapted it to their needs as they saw fit. The management and governance team continued to develop and revise codes iteratively and by agreement as new themes were discerned in the remaining transcripts. This team also took advantage of such NVivo functions as Merge, node reports and matrix intersections to help guide analysis and would like to have done more had time permitted. Analysts in the other teams ended up using NVivo largely for rough data categorization (and unfortunately, in some cases, as a substitute for true analysis) or abandoned it altogether due to time pressures and the accompanying conviction that the process could be expedited by relying on tried and true “pencil and paper” methods. It is noteworthy that one of the most experienced and sophisticated qualitative analysts on the team opted for this solution.

We will present the successes, challenges, and lessons learned in incorporating NVivo into the analytic process on this study, with particular emphasis on the implications of the diversity of the analytic team, especially of varying levels of experience conducting qualitative analysis and how this interplayed with differing inclinations to use and master the software. The presentation will also consider the impact of working in a time–pressured, deadline-driven non-academic environment, which made it impossible to fully exploit either the iterative or educative potential of the software It will conclude with a discussion of what we would want to do differently next time, and why.    



Duncan Branley, Goldsmiths College, University of London, UK
Only Connect! Only Relate!

"Only connect! That was the whole of her sermon. Only connect the prose and the passion, and both will be exalted, and human love will be seen at its height. Live in fragments no longer. Only connect, and the beast and the monk, robbed of the isolation that is life to either, will die.

Nor was the message difficult to give. It need not take the form of a good "talking." By quiet indications the bridge would be built and span their lives with beauty.

But she failed. For there was one quality in Henry for which she was never prepared, however much she reminded herself of it: his obtuseness. He simply did not notice things, and there was no more to be said."
("Howards End" E M Forster, 1910)

Using a freely available digitised version of Forster's novel Duncan Branley will explore the use of the new feature in NVivo 7, 'Relationships'. What can constitute a relationship within your data and how can you integrate their tracking into your NVivo project? Are 'Relationships' just another marketing creation or can they really add value to your research?

The text used is deliberately a literary one to demonstrate that NVivo need not be limited to conventionalised social science texts. Methods of analysis, though requiring some attention to disciplinary context, are not the unique preserve of any one particular academic formation. The session will not only be exploratory technically, but also methodologically.



Karen S Buchanan, University College London
“From Grounded Theory & Discourse Analysis to Political Ecology and claim-making in socio-environmental conflicts.”

My study sets out to research the subjective experiences of the claim-makers, and the meanings of the environmental and developmental discourses used by each claim-maker within the claim-making process of a socio-environmental conflict and the relational issues of empowerment and disempowerment of claim-makers, with the aim of theorising the use and impact of environmental and developmental discourses to contest or promote large-scale open-cast copper mining in the cloud-forest of north-west Ecuador. This region is witnessing the development of opposing local movements which have explicitly constructed political strategies for the development of their territory, management of biodiversity, and social and political autonomy. This study contributes to theoretical work on nature-society relations which has tended towards dichotomous analysis by investigating these relations in the context of daily livelihood struggles, over competing claims to natural resources, embedded within larger-scale socio-political events in the form of national and international neo-liberal political and economic interventions.

The research study is qualitative, situated within the social constructionist paradigm of political ecology. Of the qualitative research methodologies available, the most appropriate framework for carrying out my investigation and analysis is the grounded theory approach which lends itself to discovery-oriented research in this under-theorized area of political ecology. Using grounded theory methodology to identify the descriptive categories in my interview transcriptions, I am using NVivo7 software to assist the process of analysing my interviews as part of the ongoing process of generating further categories which influence the direction of further interviews in which these initial concepts can be more fully explored.

My second main methodology is discourse analysis, also located in a social constructionist approach to viewing the world and its events, which provides a framework for the deconstruction of meanings in the environmental and developmental discourses being employed in this socio-environmental conflict, and how the language, terminology and forms of knowledge used by each claim-maker allows or precludes certain themes, beliefs, perceptions, attitudes and relational issues of empowerment and disempowerment within the wider international socio-political and economic context of the copper mining conflict. Still taking a grounded approach, I am using my NVivo7 project to perform searches to select parts of the interview transcripts and secondary materials produced by the claim-makers which relate clearly to my research questions; further searches using NVivo7 examine the use of language in the construction of the discourses, as I search for any inconsistencies in the meaning in the constructions, and the assumptions they reveal, finally assessing the implications of the selection, construction and use of particular discourses by claim-makers.

Particularly relevant to political ecology research is the study of the shaping and use of discourses through the power relationship between claim-makers and its effect on knowledge systems and social relations. In conclusion my research strategy aims to show how, using NVivo7 software to support my analysis, the concepts identified through grounded theory and the socially-constructed discursive strategies reveal the operation of power at institutional and societal levels, which is used in the dynamic process of empowering and disempowering claim-makers in this socio-environmental conflict.



Sara Butler & Jessica Vince Ipsos MORI
“Managing Large-Scale Qualitative Research – Two Case Studies”

The main thrust of this session will be to discuss the experiences and techniques we employed to manage two large-scale qualitative projects using QSR Xsight. The first was the 2004 qualitative evaluation of the New Deal for Communities programme which involved 78 discussion groups in 39 of the most deprived communities in England. This project was used to pilot the use of Xsight software in a commercial research context. The second was the Commission for Rural Communities’ first Thematic Inquiry into rural housing which comprised a range of different approaches including discussion groups, depth interviews and public fora which enabled us to access the views of a broad range of residents, beyond those who would normally put their views forward.
The session will consider the challenging nature of the projects which made the use of Xsight particularly appropriate. For example, both projects required large project teams, covered broad geographical areas, involved a wide range of issues that required different research approaches, and had tight project timetables which meant that efficient analysis was vital. We will also examine the design and management of the projects, using Xsight not only as an important analysis tool, but also as a means of organising and bringing together the diverse project elements. Finally, we will discuss the key benefits to incorporating Xsight in the projects, such as the systematic approach to cataloguing large quantities of data or the relative ease with which data can be revisited for further analysis. However, in order to give a fully balanced picture of our experiences, we will also highlight some of the drawbacks involved with using this kind of software.
Our session will draw on experience and understanding gained through practical application of the software in social research and give rise to discussion about how Xsight can be utilised to effectively manage large-scale qualitative research.



Karin Fisher, University New England, Armidale, New South Wales Australia
“Challenges and experiences using grounded theory and NVIVO”

This paper will address the theme of exploring the impact of methodology on the applicability and use of QSR software. The paper will use a PhD research study to discuss issues relating to the transposition of the raw transcript data into NVivo using grounded theory methods, the researchers tendency to give higher priority to the capacity of NVivo when conducting the analysis and the requirements associated with learning NVivo. Issues will be presented from a study that explored peoples experiences and the factors as they relate to access to services for Sexually Transmitted Infections in a rural area of Australia.

The use of grounded theory is a creative and complex process. The use of software such as NVivo as a tool for analysis of data is also a complex process that presents a number of challenges. Developing mastery of NVivo is time consuming. There is a potential for the researcher to be distracted from the interpretive and creative processes involved in grounded theory analysis of research data to the more routine and mechanistic procedures of NVivo potentially losing perspective of the meaning of the data. Nonetheless, NVivo offers a way in which to successfully manage the data and provide support in the use of manual methods of analysis. The paper will consider the issues surrounding the use of NVivo and manual methods and the choices made in relation to prioritising mastery of method or software.



Karin Fisher & Trish Thornberry, University of New England, Armidale, New South Wales, Australia.
"Wanted: Support mechanisms for NVivo in rural areas"

This paper explores the experiences of two PhD students in Australia who began as novice users of NVivo and progressed through the introductory phase to the more advanced phase of data analysis using this tool. During this process of frustration, trial and error and the inability to have questions answered instantly in rural Australia we came to the conclusion that there must be a better way to 'learn as you work'. Recognizing gaps in the conditions that make learning and self directed learning possible we proceeded to develop ways to help bridge these gaps.

Rural based researchers are frequently faced with the tyranny of distance, transport issues, information technology and communication difficulties. The significant cost involved in non-funded educational sessions detracts from the lifelong learning environment that is frequently embraced and encouraged in the world of research. These conditions hinder education and prevent collegial sharing of knowledge and techniques in the use of programs such as NVivo and have the potential to discourage new researchers from using technology in their research.

These issues raised many questions the most important being: how can they be resolved? Is an online course the answer? What funding sources are available to enable education of advanced NVivo courses for people who live in disadvantaged areas? How can access to expertise for novice researchers in rural areas for both NVivo and research methodologies be enhanced?

The paper will address the theme of communicating research with software. It will discuss aspects related to the education and learning processes when using NVivo in rural areas. In this presentation we would like to outline the gaps that affected our research process and use of NVivo and ways in which we strived to address those gaps.



Janice Fong, Disability Rights Commission, UK
“Exploring the use of QSR Software for understanding quality - from a research funder’s perspective”

The Disability Rights Commission (DRC) commissions a number of research projects in order to build up a body of knowledge and evidence to help inform decision making in relation to policy and practice. The DRC’s reputation as an authoritative source of information relies on the acceptance that the information is robust and rigorous. Its quarterly ‘Disability Briefing’ for instance, produces a range of statistical information and analyses that are disseminated to a range of government departments and disability organisations. From a funder’s perspective, there can be a general belief that quantitative data are superior to qualitative data since the procedures for managing and analysing the former are perceived to be more straightforward. The process of quality-checking is also more transparent.

However, to inform policy and practice, different methodologies and data are required for different purposes. There is a lack of understanding of methods which can be used to conduct an assessment of the quality of qualitative research data. Qualitative Data Analysis Software (QDAS) such as those produced by QSR provide a means for analysing qualitative data systemically.

In this paper, I use my experience as a research manager in the DRC to attempt to explain what a research funder may look for in commissioned research, and how we can be satisfied as to its quality. I attempt to determine whether the use of QSR software could provide a tool for assessing the quality and rigour of qualitative material.

DRC funded a research project studying the experiences of disabled students and their families. This is a mixed method research. The first part generates quantitative data via a structured survey of parents and carers of disabled children. The second part is a qualitative study which involves interviewing about 40 disabled children and young people in Great Britain about their schooling experiences. While many tables of figures and statistical analyses are presented in a report, the answers to open questions within the questionnaire are not systemically analysed upon the completion of the structured survey. I began to wonder about the interviews behind the statistical information and also whether the answers to open ended questions were misrepresented. As the second part of the project commenced, I also start to feel a bit lost in knowing how to assess the qualitative materials.

I began to look for possible answers from QDAS. Since I was a complete novice, I signed up for training in NVivo 7. The course has been useful in teaching me the skills to use the software. I have learnt to set up the data; to create nodes and codes and to organise the data with case and attributes. While attending the course, I was also assessing the software’s suitability for my purposes.

In this presentation, I argue that there are myths and misunderstandings surrounding functions that some non-users may ‘wish’ the software could perform. It can be seen as a magic wand which will automatically perform all the analyses and identify relationships between variables by clicking a button. However, to a certain extent, this tool can only provide a sophisticated support for a qualitative data analysis when there is a sound methodology and a comprehensible analysis plan. It is essential for a research funder to have a comprehensive understanding of the research questions underpinning the commissioned research in order to assess whether this software can be used appropriately. I conclude by giving some recommendations for the features which research funders may want to look out for in terms of being able to ask sensible questions of the data and analyses through the understanding QDAS.



García-Varela, A. B. Universidad de Alcalá, Spain) del Castillo, H. Universidad Autónoma de Madrid, Spain; Lacasa, P. Universidad de Alcalá, Spain
“Analyzing educational dialogue using ‘NVivo7’: Children and families sharing “new literacy” practices”
In this presentation we analyze an educational innovative practice, in which children and their families participate working together and sharing goals as a community of learners. In this educational setting, processes of literacy related to writing on the Internet take place. We use NVivo7 for the analysis across the whole research process in this sociocultural research.
Adopting an ethnographic, action research and socio-cultural approach in our study, we play the role of participant observers working in an extra-curricular workshop, sharing with teachers the task of introducing children and families to multiple forms of literacy, related to the use of technologies and mass media (Lacasa (ed.), 2006). We explore how children and their families approach the production of written texts in the workshop, taking into account that their texts will be published on the Internet in a digital newspaper that they are creating themselves.

Many researchers’ everyday activities take place mediated by ICT tools. New technologies afford a wider number of possibilities for developing research projects, as well as for analysing data in complex ways and producing academic reports and publications. Thus, the use of ICT in the research process is currently one of the most important challenges for social researchers, especially for those privileging the development of qualitative research.

In such a context, one crucial question is of particular interest to us: How can new ICT tools can help us across the whole research process in sociocultural research? The aim of this session is to explore how the software for qualitative data analysis NVivo7 can be used to facilitate the process of organizing, storing, retrieving and analyzing data.

All the sessions were audio and/or video-recorded. Activities were also registered in a logbook which supported a reconstruction of the general information. We elaborated fieldnotes and summaries of every session, and also considered the texts produced by the children. The process of data analysis combines narrative and analytical perspectives.

The discussion of this paper focuses on the data analysis. In the process of analysis we used NVivo7, which allowed us to work directly with the transcription of audio and video recordings in the discourse analysis. In this sense, the first step was to organize the data chronologically on each family. Then, we segmented the data in significant ‘sections’ that we described creating summaries (as memos). Also, we added codes to these sections to group them in free nodes. This was a first approach to the categories that was relatively descriptive but provided an important infrastructure for later data retrieval and for the following analysis and interpretation (Hammersley & Atkinson, 1995). On the other hand, Nvivo7, helped us in a following step to create an analytical system of nodes for coding and interpreting the data.

References
Hammersley, M. & Atkinson, D. (1995) Ethnography: Principles in Practice. London: Tavistock.
Lacasa, P. (Ed.) (2006) Aprendiendo periodismo digital: Historias de pequeñas escritoras.. Madrid: Visor.



Linda Gilbert, University of Georgia, Athens, Georgia, USA
“Tools and trustworthiness: a historical perspective”
In 1999, I completed a study on the transition experience of qualitative researchers as they moved from “manual methods” to using qualitative data analysis software. At the time, I chose the latest and greatest program on which to focus: QSR N4, still known primarily as NUD*IST at that time.
Since then, QSR software has gone through multiple changes and revisions, leaving the former “latest and greatest” far behind. N4 gave way to N5 and N6, and a sibling-product named NVivo was introduced (version 1), then updated to version 2. Recently the two lines of software have been merged in a new product, NVivo 7, which constitutes a complete re-write. In each version, the software has retained core features, added features and new capabilities, and represented functionality differently. Changes have been driven both by rapidly-increasing computer power and by user demands, both explicit and revealed in use.
At the same time, qualitative research as a field has faced new challenges from initiatives such as the United States’ emphasis on “scientifically-based” research. Responses from researchers have ranged from a refusal to engage in debate to some initial efforts at articulating standards in qualitative research. These are worth examination in themselves, but they are of particular interest when considered in light of current QDA software capabilities.
In this presentation, I wish to revisit some of the findings from my earlier study in the light of evolving software and new trends in qualitative research. In particular, I will focus on the conceptualization of “a tool” or “tools” when applied to software and on various issues of trustworthiness related to software use. In the process, I will reflect on some of the historical contexts which have affected the use of software, and raise questions for additional consideration and discussion. If time allows, small group discussion will be included.



Linda Gilbert, University of Georgia, Athens, Georgia, USA; Melissa Kelly, University of West Florida in Pensacola, Florida, USA & Dan Kaczynski, University of West Florida in Pensacola, Florida, USA
“Exploring the forces of application-sharing technologies upon NVivo: Promoting and Supporting adoption”

Application-sharing technology offers a channel for leveraging the adoption and use of QDAS tools such as NVivo. By integrating these technological tools, NVivo trainers can access a broader audience and client base, and qualitative research practitioners can extend and enhance their collaborative efforts. Successful adoption and implementation of these tools requires that organizations address two broad sets of issues: user considerations and technological considerations. One of the key user considerations to address is the role that users play in adopting technological innovations. The first of three papers to be presented in this session examines differences in adoption patterns across five categories of users: innovators, early adopters, early majority, late majority and laggards. The second paper to be presented in the session expands the discussion of user issues into considerations that need to be addressed when selecting an application sharing technology for use with NVivo. This segment also explores key technical decisions that adopters must contend with when advocating for application sharing technology. The third paper to be presented addresses the functions that academics and trainers have in defining and shaping innovations in the application of NVivo as a research tool. Together, these three papers provide insight into expanding the utility of technological tools such as NVivo and application-sharing technology and advancing the craft of qualitative research.

Paper 1: Crossing the Chasm: How do users of technology approach adoption?
Most of the literature about technology adoption is geared toward technology companies; with the most frequently-cited being Geoffrey Moore’s Crossing the Chasm. In this seminal work, Moore offers his view of the bell curve of technology adoption characterized by innovators, early adoptors, early majority, late majority, and laggards. The innovators are “techies” who will try a new product early, even if they never plan to use it. The early adopters are visionaries; they like to experiment with new technology. The early majority consists of pragmatists interested in what the product will do. In Moore’s view, the early majority is a critical group that determines the future of every new technology. “Crossing the chasm” from the early adopters to the early majority is a critical point in the acceptance of any new technology. The late majority is conservative, tends to use older technology, and is reluctant to change. Lastly, the laggards are skeptical of the technology and often resist it entirely.

In addition to categorizing adoption patterns, Moore also describes new technology in terms of whether it is discontinuous or continuous. Discontinuous technology is great, but disruptive to the existing organizational structure or business practices; continuous technology is nondisruptive, and hence, often unnoticed. In-between products, in Moore’s view, are generally not exciting or marketable. Moore’s work is well-known in the technology industry. Not surprisingly, it focuses on the implications of the model from an industry perspective, with the key question being how to “cross the chasm” to acceptance within the market. What are its implications in a nonorganizational setting? What attracts individual users to new technologies, and what impact does it have on their work and work relationships?

In the QDA world, there are two interesting topics related to these questions. The first is QDA software itself. Despite its long pedigree, QDA software is still not entirely “adopted” across the varied qualitative researcher communities, particularly in academia. Though there are groups that can be labeled as “early majority” using the software, the late majority and laggards seem to hold entrenched positions that marginalize the use of software as an ancillary rather than integral part of qualitative research.

The second interesting topic involves supportive technologies for teaching and learning interactively, such as application-sharing technologies. While in varying stages of adoption themselves, these programs offer interesting opportunities for supporting the expansion of QDA software. The potential intersection of two adoption curves raises interesting questions for both QSR and individuals teaching and learning NVivo.


Paper 2: Utilizing Application-Sharing Technologies in Qualitative Research: Considerations and Implications for Integration
Often underlying technology adoption patterns are user-related issues involving implementation and use, or technical considerations. Identifying advantages of a technology, as well as addressing concerns and barriers, are part of the adoption process. This article will explore the issues of adoption and implementation with respect to application-sharing software, particularly with the perspective of integrating application-sharing technology into the instruction and practice of qualitative research.

For example, there are a number of technical considerations that should be addressed proactively in order to realize many of the benefits of integrating application-sharing technology into instruction and practice of qualitative research. A few of the questions that decision makers should address are: (a) what product model to adopt, (b) whether to use a hosted solution or host a product internally, (c) how to define the scope for usage, (d) how to address user constraints, and (e) how to promote stakeholder acceptance. Failure to proactively address these issues can result in implementation problems, diminished return on investment, and frustrated users.

This exploration of considerations and implications will help the audience frame issues they are likely to encounter when positioned as users, adoptors, or implementation planners for technological innovations such as application-sharing. It will also highlight areas for expanded discussion among the forces shaping the innovations and the adoption of the innovations.

Paper 3: Distance sharing technologies: academics and trainers shaping future mainstream adoption of NVivo
How can these separate and distinct adoption patterns intersect in teaching and learning NVivo? Will the use of NVivo in online courses and other Web-based, synchronous collaborative platforms impact mainstream adoption of the tool by qualitative researchers? This paper builds upon work presented at Durham 2005 on the use of NVivo in a virtual setting and explores the future implications which these questions raise. The advantages and potential challenges to using NVivo in conjunction with distance software will be viewed from two perspectives: the academic using online course delivery and the trainer or facilitator using other Web-based synchronous collaborative platforms. Particular attention will be given to how student challenges, content challenges, and technological challenges shape and are shaped by the evolving process of mainstream adoption. Audience participation and discussion will be a major component of this section, addressing questions such as:
Where do you perceive the adoption curve at for application sharing technology and NVivo?
What are your thoughts regarding Lyn Richards question - 20 years on; why aren’t they using NVivo?
Is geographic isolation a major issue in promoting the use of application sharing technology? What are other major factors?
What are the potential advantages of adoption?
What are the potential barriers to adoption?
What are potential consequences to adoption?
What rules or standards should apply to adoption practices?

Input from this group discussion will be incorporated into a collective session paper that will be submitted for publication following the conference. Of particular interest in this discussion is insight to emerging rules of professional conduct and criteria setting standards and how these emerging standards of practice promote and support adoption.



Silvana di Gregorio, SdG Associates
“Research Design Issues for Software Users”

Many people approach software use without much thought of the design of their research project. It is only in later stages of the analysis that they may feel frustrated at not being able to get at the analysis they want and realise that they need to re-think the organisation of their work in the software. In this paper, I propose that the design of the research is the first consideration people should have when setting up a project in a software package. The information they need should be in their research proposal. A framework for issues they need to consider is proposed according to the complexity of the research design. Three types of designs are considered: simple, complex and compound complex . Case studies will be used to exemplify each type of design and the issues you need to consider. The paper is derived from a chapter from a book in progress by myself and Judy Davidson – Qualitative Research Design for Software Users – which draws on projects from UK, USA and Europe across a range of disciplines, range of software packages and from both the academic and commercial sectors. The paper ends with a check-list of design issues you need to consider when setting up a piece of research in a software package. The check list includes the following questions (which are expanded in greater detail in the paper) - What is the structure of the project? What kind of data am I collecting? Am I collecting more than one kind of data? Is the data structured in any way? Do I need to import the data in its entirety? Which package best supports the non-textual material I have? What format do my data have to be in? Having gone through the check-list, researchers are in a position to ask the final question – what kind of project design do I have – simple, compound or compound complex? – and the implications each type has for project set up.



Jo Haynes, University of Bristol, UK
“CAQDAS: A ‘posthuman’ research experience?”

The relationship between human beings and new technologies is often characterised by anxiety or fear about whether people will be marginalised or intimidated by technology. This anxiety characterised some of the initial speculation about the implications of the use of computer software in an increasing amount of intellectual and creative activity, specifically here, qualitative research, wherein software is perceived as potentially eroding the researcher’s control over the analytical process or will be used uncritically to produce ‘quick and dirty’ results.

In particular, the introduction of software into qualitative analysis is considered 1) to be a threat to ‘traditional’ analytical methods; 2) as unduly influencing researchers to focus on breadth rather than depth within data; 3) to disrupt or distance the researcher from the data; and, 4) risky, as it may mean that methodological, substantive and theoretical matters will become ‘artefacts’ of technology. All of these concerns however, have not heralded a decline in their use within qualitative research. Indeed, the development and use of qualitative software is arguably becoming more of a norm within academic research and beginning to have more widespread use. Researchers are not however, accepting the uncritical use of software like Nvivo, rather their wider use and acceptance is indicative of a social and cultural shift in the way technology is conceptualised. The anxiety that once determined populist beliefs about technology as a ‘Frankenstein’s monster’, i.e. what technology will inevitably do to us, is transforming into an acknowledgement that technology is an extension of us, i.e. they are an extension of human intelligence and skill. This is understood within what is referred to as the ‘posthuman condition’, whereby humans are viewed as embodied within an extended technological world.

By drawing on experience within research teams conducting qualitative cultural and social research, this paper explores the posthuman standpoint in relation to the use of qualitative software such as NUD*IST and Nvivo. In doing so, it not only highlights the creative use that can define its analytical support, but also that what should be feared in research relates more to wider and familiar political and economic processes shaping the research context.



Chih Hoong Sin, Disability Rights Commission, UK
“Using QDAS in the production of policy evidence by non-researchers: strengths, pitfalls and implications for consumers of policy evidence”

Policy research, at least within the UK, is being conducted by an increasingly heterogeneous pool of research providers. In addition to researchers working within academia or policy and research think tanks, a range of private sector organisations (such as consultancies), charities and voluntary groups are also involved in providing policy-related research evidence. Many large pieces of policy research are also contracted out to consortia comprising a diverse range of partners, not all of whom necessarily have research background. In other words, research conducted by non-researchers potentially has a huge impact on the policy-making process.

In some quarters, there can be strong arguments for commissioning non-researchers to provide research evidence. Despite the preference, in some cases, for non-academic organisations to conduct major pieces of social research, the use of such providers of research is not without significant challenges. Organisations commissioned to conduct such research do not always have dedicated research staff who are trained to conduct research. The training and management of staff who may not have a research background can be highly challenging. An ‘on-the-job’ training approach is not uncommon and this has major repercussions on the way research is conducted. Dedicated research training may also be provided for practitioner researchers but there are issues relating to quality, timeliness, and adequacy.

This paper examines the case of one private sector company that works solely to provide research and consultancy services for public sector clients. It looks at the background of staff; the way in which they are trained to use QDAS; what QDAS has been used for; how it has been used; and particular issues arising from training and using QDAS in a team context. The implications of these on how qualitative data for significant pieces of policy research are managed and analysed are explored. It raises genuine concerns about the robustness of evidence produced to inform policy and practice. This is often compounded by a real lack of understanding among consumers of policy research in relation to qualitative data and analysis as well as the attendant pressure of working in the policy environment. It concludes with some recommendations to consumers of policy evidence.



Andrew King, University of Surrey, UK
“Solving the Researcher’s Dilemma? Doing it ‘quick and dirty’ and ‘slow and methodical’”

In this paper I outline how a form of conversation analysis known as Membership Categorisation Analysis (MCA) can be applied to qualitative data using NVivo software. I begin by outlining what MCA is; its background in the work of Harvey Sacks and how it has been developed since. I note that MCA takes a specific theoretical and methodological approach to qualitative research and suggest that this may potentially create a dilemma for those researchers who are considering using NVivo software for their analysis. In response to these issues I will outline and evaluate two strategies of coding that I have used in my doctoral research to apply MCA to narratives obtained in twenty five interviews with young people who have taken a Gap Year, a break in their educational careers between leaving school and beginning university. These strategies can be characterised as “quick and dirty” and “slow and methodical”. The first makes use of text searching tools to generate codes; whilst the second uses a more methodical and perhaps more orthodox approach to reading and coding of documents. However, I will explain that when combined both of these strategies are valuable for doing MCA and solving the researcher’s dilemma. Therefore, I conclude that NVivo can be used by researchers interested in applying this type of methodology to their data.



Helen Marshall, Centre for applied social Research, Royal Melbourne Institute of Technology, Australia
“What examiners like in a qualitative thesis and how software can help us deliver it”

We know relatively little about how examiners approach marking a research thesis and what we do know is rather general. It is clear, for example, that examiners want to pass theses, that they hope for technical competence and that quality of writing is important. It is less clear what ‘technical competence’ and ‘good writing’ mean in practice. To find out more about what examiners think good qualitative analyses look like, in 2002-3, I asked some experienced examiners of qualitative research thesis ‘what are the signs by which you recognize good qualitative data analysis?’

The examiners’ responses suggested that ‘quality’ is hard to define. Nonetheless they shared some views about technical competence and good writing. Technical competence as an analyst of qualitative data means being reflective, handling data with sensitivity and ensuring that data are analysed rather than simply described. In other words, in a good thesis ‘data don’t just sit there’.
Good qualitative writing is vivid, so that ‘details stick in your mind’ and has the quality of authenticity. It means that analyses are imaginative, well presented and well written.

This paper explores the issues raised by the study, and makes some suggestions about how NVIVO, by enabling reflexive presentation of the process of analysis, can help postgraduates to meet the demands of examiners for quality.



Lyn Richards, Founder of QSR
Keynote: Farewell to the Lone Ranger? On the trend to Big and Team research (with software, of course), and the future of 'qualitative' 

Qualitative research is still, in most literature, presented as a solo act – small is written as not only beautiful but morally or methodologically preferable. The method traditionally aims at achievement of insight by an extraordinarily perceptive solo researcher, creating “indepth” understanding from small bodies of amazingly rich data.

It’s often, even usually, not like that in reality. More obvious, in today’s academic or commercial marketplace, are the trends to rigorous data management of even large scale “qualitative” databases. The blame (or much more occasionally, praise) for such changes is normally given to software tools, which are also expected to solve the problems. Teams are required to meet standards set for small, “indepth” projects, and lone researchers are under significant pressures to perform to standards set for teams. I see this as a crisis in the method, and one, interestingly, not noticed in the long list of crises normally debated. What is to be done, and can software help?



Stuart Paul Robertson, Jr., C.A.G.S.Robertson Educational Resources, Pelham, New Hampshire, USA
“Brain-based Learning and NVivo Training: A Critical Connection”

When introducing adult learners to a new piece of software such as NVivo, there are a multitude of issues to be addressed in order for the students to achieve a meaningful level of success. Competency-Based Training (CBT) approaches are the most frequently employed method during training, yet they may circumvent an important preliminary experience which is of benefit to most, if not all, learners. Brain-based research identifies five stages in the learning process: preparation, acquisition, elaboration, memory formation, functional integration. The preparation stage is often either absent from or minimized in CBT approaches.

The preparation stage provides a framework for the new learning and primes the learner’s brain with possible connections. Furthermore, the more background a learner has in the subject, the faster they will absorb and process the new information. When introducing a robust piece of software such as QSR’s NVivo, this stage is particularly important. Misunderstandings in the purpose and role of the software as it relates to the research process can manifest themselves in underutilization, misuse, or avoidance of the software.

For many adult learners, especially those new to NVivo or relational databases in general, the very first issue which needs to be addressed is establishing a conceptual understanding of what the program can do for them. This can be especially challenging for visual learners. By incorporating visual representations with rich descriptions that include similes and metaphors describing the software’s role in the research process as well as the key components of the software itself, new and inexperienced users are provided with a way to link the new information they are learning with understandings they already possess.

In this paper I draw from the areas of brain-based research, computer education, and my experiences working with novice NVivo users to discuss the theoretical underpinnings of the ideas I put forth and how they were translated into actual materials to be used with adult learners.



Sabdra Spickard Prettyman, University of Akron & Kristi Jackson, University of Colorado
“Ethics, Technology, and Qualitative Research: Thinking through the Implications of New Technologies”

As qualitative researchers in the new millennium, we have access to a wide range of new technologies with which to collect, analyze, and manage our data, as well as new forms of data to collect for analysis. The digitization of audio, video, and photographic data now makes it possible for us to create, process, and analyze this data in new and different ways, often allowing us to use these as more than just tools for data collection, but also as sources of data in and of themselves. In addition, the growth of the Internet provides us with not only new ways to collect qualitative data, but new settings in which to collect it. Today, computer assisted qualitative data analysis software (CAQDAS) such as NVivo provides powerful data analysis and management tools, that can also aid in data collection, theory building, and data representation and reporting. However, it is rare that the implications for these new technologies are scrutinized—especially as they relate to ethics, technology, and our research. We argue these tools demand that we reconsider the ethics of the research process, from beginning to end, from conceptualizing the questions to reporting the results. Issues such as confidentiality, validity, and rapport may surface and must be considered in ways that may be quite different than we had approached them in the past. As technologies continue to evolve, often in response to our demands as researchers, new features and functions appear. We need to understand not only how to use these, but also what they mean for us ethically as we engage in our research and with our research participants.

More often than not, those who use CAQDAS consider how these tools can: help us efficiently store, manage, and retrieve large quantities of data; add more rigor and transparency to data analysis and the research process; or allow multiple researchers to work effectively on the same project. Rarely discussed in the literature is how these new tools may influence the ethical enactment of our research, and the new ethical considerations that may need to emerge. For example, it is relatively easy today to incorporate digital photographic and video data into CAQDAS, which can then be used for analysis and representational purposes. What does this mean for confidentiality of participants and our commitments to them? While it is true that for many years we have had the ability to utilize photographs and even videos in our work, the ease with which this data can now be collected, manipulated, and analyzed (in new and different ways than before) means that there are also new questions that arise about the collection and use of that data.

As we move from manual to more technologically advanced processes with our research, increased familiarity with and new attitudes toward these technologies will emerge. It is clear that these technologies are now becoming more accepted and trusted in the research community, although their use continues to be contested by some. In order for these new technologies to become more widely accepted and trusted, we must become familiar with them, and with all of the issues that they raise, including ethical ones. Their role must shift from being just a handy storage and retrieval device to a fully integrated component of research project that is in place from the design stage.

References
Bourdon, Sylvain (2002, May). The Integration of Qualitative Data Analysis Software in Research Strategies: Resistances and Possibilities. Forum: Qualitative Social Research [On-line Journal], 3(2). Retrieved June 20th, 2006 from HYPERLINK "http://www.qualitative-research.net/fqs-texte/2-02/2-02bourdon-e.htm" http://www.qualitative-research.net/fqs-texte/2-02/2-02bourdon-e.htm
Ford, K., Oberski, I., & Higgins, S. (2000). Computer-Aided Qualitative Analysis of Interview Data: Some Recommendations for Collaborative Working. The Qualitative Report (4). Retrieved June 20th, 2006 from HYPERLINK "http://www.nova.edu/ssss/QR/QR4-3/oberski.html" http://www.nova.edu/ssss/QR/QR4-3/oberski.html

Gibbs, G. R., Friese, S., & Mangabeira, W. C. (2002). The Use of New Technology in Qualitative Research. Forum: Qualitative Social Research [On-line Journal], 3, (2). Retrieved June 20th, 2006 from HYPERLINK "http://www.qualitative-research.net/fqs-texte/2-02/2-02hrsg-e.htm" http://www.qualitative-research.net/fqs-texte/2-02/2-02hrsg-e.htm

Welsh, Elaine (2002, May). Dealing with Data: Using NVivo in the Qualitative Data Analysis Process. Forum: Qualitative Social Research [On-line Journal], 3(2). Retrieved June 20th, 2006 from HYPERLINK "http://www.qualitative-research.net/fqs-texte/2-02/2-02welsh-e.htm" http://www.qualitative-research.net/fqs-texte/2-02/2-02welsh-e.htm



Clare Tagg Tagg Oram Partnership & Sarah Millar et al
“Early Adopters of NVivo7”

It is normally received wisdom that it is unwise to be an early adopter of new software particularly with a large important project. But this is exactly what The Health Foundation’s evaluation team did when they decided to use NVivo7 for the evaluation of the charity’s Leadership Programme[1]. Managing large quantities of longditudial data to identify evidence for theory building and theory testing is a key challenge for the evaluation team that Nvivo7 is helping them to address.

The evaluation of The Health Foundation’s Leadership Programme is being conducted by a three-strong internal evaluation team with experience of using N6 and Nvivo V2. A decision was made to use Nvivo7 to support data analysis and retrieval because Nvivo7 offers more advanced modeling and the potential to use the ‘relationships’ node to support the exploration of logic models or ‘theories of change’ within the qualitative data collected.

The data collected by the team includes baseline semi-structured interview data, observational data, previous evaluation reports, case study biographies and monitoring reports. From the outset, there has been a desire to bring these sources together to tell longitudinal case-level stories of the individuals who participate in the Leadership Programme and to undertake thematic analysis to support theory-testing.

The paper will examine the reasons for the decision to use NVivo7 and will track the team's successes and challenges to date. In particular we will look at how the use of NVivo7 has impacted on the research approach taken including data collection, team working, analysis and reporting.

[1] The Leadership Programme comprises of six leadership development schemes aimed at a wide range of health care professionals. The aim of the programme is to develop the leadership skills and capacity of participants and, in doing so, improve the quality of health care.  



Chris Thorn, Director, Technical Services, Winconsin Centre for Education Research
Keynote : “Are we there yet? Growing maturity in qualitative tools and methods”

Like the children in the back seat of the family car, we've been asking the question "Are we there yet?" for quite some time. I'm seeing lots of signs that we have arrived.

In my area of research, Qual-Quant debates now seem old fashioned. The American Education Research Association, for example, has new draft "Standards for Reporting on Research Methods" that discuss design, interpretation, and ethics across methods. Many large scale evaluations routinely include members with qualitative and quantitative skills who work as a team in an iterative, interactive design. Likewise, our tools have come of age. The CAQDAS "choosing a package" paper outlines the growing number and increasing sophistication of tools available. Indeed, enterprise technologies in knowledge management and web based collaboration are moving to link up with our tools as well. Enterprise search and social network tools are probably the areas in which we will encounter other social scientists looking for us.



David K. Woods, Wisconsin Center for Education Research, University of Wisconsin, Madison, USA
“The Qualitative Analysis of Video and Audio using Transana”

The qualitative analysis of video and audio can be rewarding for researchers, giving them access to raw data that is considerably richer than the textual representation of the same events. Working with video data requires a different set of tools than working with text data.

This presentation will demonstrate the analytic approach embodied by Transana, a free software package designed to help researchers analyze video and audio data using qualitative techniques. Transana is particularly useful in the analysis of large video collections and for those researchers wishing to analyze video in collaboration with others.

Transana facilitates the annotated transcription of video data, allowing researchers to create a text record that corresponds to the video. The researcher can link the video and the text record together, allowing instant access to the appropriate video for an analytically interesting portion of the text. This allows the researcher to remain very close to the video data at all times.

A researcher can easily identify analytically interesting portions of video in Transana, creating a virtual clip which can be categorized, copied, coded, sorted, and manipulated in a variety of ways. (Transana does not require time-consuming manual video editing as part of the analytic process, as many other qualitative packages do.) Transana's search interface allows the researcher to perform data mining and hypothesis testing on a properly-coded data set, and Transana's Keyword Map report facilitates the examination of coding across time.

The multi-user version of Transana allows geographically-dispersed researchers to work with the same data set at the same time though the Internet, facilitating the collaborative analysis of video data.

Finally, video can be used in very powerful ways in the dissemination of the results of qualitative analysis. A few carefully-chosen video clips often have a stronger impact on an audience than a string of PowerPoint slides. Transana provides tools for sharing your results with others.

Taken together, the techniques and tools that will be described in this presentation allow for powerful analysis of video and audio data.