Workshops include the following...

Smile for the camera: what to consider before collecting audiovisual data, led by Jennifer Patashnick, Video Intervention/Prevention Assessment (VIA), Children's Hospital Boston

Video Intervention/Prevention Assessment (VIA) provides participants tools to document their lives as they experience them. Since 1994, young people at Children's Hospital Boston have generated thousands of videotapes to teach their clinicians about living with a chronic health issue. Our challenge: review and analyze each video, eliciting themes affecting participants' everyday lives with which clinicians can improve healthcare communication and delivery. Each recorded moment must be viewed, coded, and compared to the rest of the individual's data and across all participants.

At first, the VIA research team logged videos manually. Adding trained interns increased the amount we logged, but the knowledge was distributed across many individuals and hundreds of log pages. Synthesizing themes without the full team present was difficult. We soon realized word-processing software would allow us to use multiple loggers, but maintain a single, searchable record. We searched for keywords, but when loggers used different vocabulary for similar ideas or if an idea was generalized as opposed to point-specific, searches were less effective and connections could not be made.

Sophisticated qualitative analysis software enabled more thorough exploration of logs. Instead of isolated word searches, we coded text to inductive and deductive themes. Memos and annotations were maintained within the project frame. Collaboration and coding, synchronously and asynchronously, were achieved through active team management, and we are overcoming our reliance on analog video data: particularly revealing video is digitized and referenced directly from the electronic logs.

However, audiovisual analysis remains suboptimal. Most qualitative analysis packages claiming to incorporate video data relegate it to a peripheral role, with text remaining central. Researchers sometimes complain that analysis software takes them away from their data. Given textual data, this is arguable; with video, no such argument exists. No programs offer the ability to code with breadth, depth, and flexibility directly with video. All require transcription, a process which constitutes a requisite analytic “pass”; future analysis becomes a “generation” removed. Video is more complex than text; every study collecting audiovisual data has developed a different method of analysis, with diverse aims and constraints. Software that can handle the volume of video VIA participants produce is rare. In part, the challenge of direct analysis of VIA audiovisual data lies in our examination of macro-behavioral themes through grounded theory-based analysis. We code narrowly, investigating the behavior itself, and broadly, examining the context of that behavior and the physical, psychosocial, and historical contexts in which it occurs, to create a database of coded segments that can be analyzed in response to specific research questions.

While qualitative analysis software has progressed dramatically for textual analyses, it has light-years to go before it adequately manages multimedia data. At minimum, video needs to replace text as the data to be structured, analyzed, coded and recoded in response to specific avenues of inquiry. Particularly in research where the participant collaborates in collecting data, analytic software must acknowledge the perspective of the “gaze,” as well as both objective and subjective content to be analyzed. Most importantly, software must provide time-efficient ways to manage, display, and analyze audiovisual data in formats that can be considered and conceptually structured by researchers.

"Talk to the mike 'cause the researcher ain't listening!" How to feel comfortable with your audio technologies so that you can focus on your research participants, led by Duncan Branley, Goldsmith's, University of London

When you're interviewing an individual or running a focus group you employ a number of strategies to generate useful data to explore your research questions. Most of these you prepare for:

* Topics: you think about the areas you want to explore and how you might guide your participants using prompts ranging from very open-ended invitations to talk through to quite highly structured questionnaires.
* Environment: you think about the sort of place in which you will be engaging with your participants. Will we be interrupted? Will we be comfortable? Will we need refreshments? * Your impact: might anything I habitually do create unintentional obstacles, perhaps even cause offence or make me seem unprofessional?

But how well do you prepare to work with your recording technology in the interview itself? What impact does it have on your interpersonal 'presence' if you're worrying if your recording is actually going to work properly?

Duncan Branley will take you through some of the basics of the science of sound to enable you to make informed choices about the equipment you might want to use to record interviews. You won't become acoustic engineers on the back of it, but you should feel secure that you are a "good enough" researcher in the field. This will also benefit your later analytical work with your recordings whether or not you use CAQDAS.

This workshop will complement Jennifer Patashnick's session on Audiovisual data.

United We Stand, Divided We Fall: How to organise teamwork when using a CAQDAS package
led by Silvana di Gregorio, SdG Associates, London and Boston

The development of software for organizing qualitative analysis has enabled (and perhaps even encouraged) the design of large-scale qualitative projects – particularly evaluation studies – with a team of researchers responsible for analysis. Software certainly helps in organizing and managing large data sets but the software itself cannot ‘manage’ a team. There is little guidance on managing team research with or without software; the underlying assumption of most textbooks is that the analysis is done by one researcher alone. However, team research has always existed and it is not exclusive to very large data sets. This workshop will provide a framework for managing team research using a CAQDAS package. Elements of the framework include:

• Mapping out types of research designs that incorporate teams
• A diagnostic tool to map out the strengths and weaknesses of team members
• Ways of dividing the work based on the profile of team members and the design of the research
• Work flow charts for managing the analysis within CAQDAS software
• Tools within CAQDAS software that support teamwork – including merging projects and merging strategies
• Other communication tools that enable teamwork including WebEx , GoToMeeting and Skype.

This workshop will be a combination of presentation and interaction with participants. Participants’ own experiences of working in a team are welcome. In addition, participants will have the opportunity to use the framework to map out how they can manage their own team projects.

Creative ways to use codes
led by Graham Gibbs, Behavioural Sciences, University of Huddersfield

The key idea behind this workshop is the recognition that although CAQDAS programs support the coding of data, the way researchers use this function does not have to be restricted to the coding activities used when doing analysis by hand. The coding function in software is just the association or linking of a name (the code’s name) with one or more chunks of text. How this is done, how often it is done, how much text is used and, most importantly, how long it is kept for, are not limited by the software. On the other hand, nor are they limited by the need to keep the data organised, manageable and focussed on key thematic ideas – which are important issues when doing analysis by hand. Thus it is possible in software to create and code with a very large number of codes that would be chaotic and unmanageable if doing the analysis by hand. This is not always good practice but it can be a way to support creative thinking in the project. It is also possible to delete and combine codes easily – something that researchers are loath to do when working by hand. And it is easy to change the size of the chunks of text that are coded, which means it is possible to use coding in a temporary way in a project, with the idea that coded text may be refined at a later stage (or even deleted).

The workshop will examine some of the ways of developing thematic codes in projects and how large code lists can be developed and managed (e.g. using code hierarchies or families, placeholder codes, and dimensionalising codes).

We shall also look at different coding strategies, such as line-by-line coding and consider how the codes and coding produced can be refined and developed.

Finally, we shall examine the role of coding in text searching and examine the ways text searching can be used to develop new codes and to undertake some automatic coding.

Examples will be taken from three programs, NVivo7, Atlas.ti 5.0 and MAXqda 2.0.

A picture is worth 1000 words : using mapping software in qualitative research, led by Clare Tagg, Tagg Oram Partnership

Pictures and diagrams can be used as a communication tool in qualitative research both as an aid to data collection and as a way of communicating results. Diagrams can also be used as an analytic tool.

Software can support the construction of diagrams by:
- making it easier for the non-artist to construct diagrams
- allowing diagrams to be amended, saved and transmitted electronically
- allowing levels of information to be hidden.

This workshop will demonstrate using three different types of software package (NVivo7, Inspiration, Mindmanager) how mapping can be effectively used in a variety of qualitative research tasks.

Multimedia and multimodality: presenting and communicating research findings
led by Inna Kotchetkova and Rachel Hurdley, Qualiti, School of Social Sciences, Cardiff University

The QUALITI team from the National Centre for Research Methods and Cardiff University will lead a discussion workshop following a short presentation. By representing a set of findings from multi-method project through one medium, we focus on the communication of research. This highlights the different affordances of different media, and how an audience might interpret these dimensions of meaning. For example, the material properties of an interview recording afford quite different meanings from its transcribed form. d

The use of multimedia – writing, film, photographs, sound - in communicating research findings raises the question of modalities of representation. It is tempting to blur the distinction between media and modes, but ‘multimodality and multimediality are not quite the same thing’ (Kress and Van Leeuwen, Multimodal Discourse 2001: 67). Modes, as abstract resources of meaning-making - such as narrative or gesture, can be realised through multiple media representations.

However, as digital technologies expand the possibilities of multimediality, researchers must become expert as designers. As media become the focus of design, they can take on modal qualities: even a typeface conveys particular meanings. By illuminating the relation between media and modes, the opening presentation invites participants to think about modalities of research representation.

Investigating Social Representations in Communities of change: The challenges of ALCESTE
led by Kavita Abraham and Angela Aubertin, London School of Economics

Public Sector Reform has been on the agenda of governments in United Kingdom for many decades. New Public Management is the most recent thinking driving the changes in Public Administration since the 1980s. This session explores an encounter between Civil Servants and the Consultants, engaged by Government in the late 1990s. This encounter between two fundamentally different groups, the institution of the British Civil Service and the community of practice of the management consultants, resulted in a culture clash of ethos, languages, rites and rituals, perceptions of change and actions. This is a crucial moment to capture the experience of change and the consequences of these representations in the process. ALCESTE was used to track the social representations of change and the acts of representing the change over a nine-month period. Over 800 staff from both groups worked intensively together, impacting over 10,000 employees, and documenting this change period. Representations are analyzed using co-occurrence analysis on the languages used in the documentation about the change (using ALCESTE software), to slice the data both cross sectionally and longitudinally. The challenges and rewards of using this software in this kind of text analysis are explored from a research and technical perspective