Review of our Book

I am pleased to announce that a review of the diGregorio and Davidson book--Qualitative Research Design for Software Users--has just been published in FQS or Forum: Qualitative Social Research, on an online journal.

Thanks to Alice Mattoni from the European University Institute for her careful read and thoughtful comments. 

Alice--  I look forward to meeting you at some point!

Mattoni Review

FQS Book Review

Intuitiveness...Thomas Muhr...and ATLAS.ti

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This is a 'reprint' from the Qual-Software Mailing List.  It is a message on the 'notion of intuitiveness' in qualitative data analysis software.  It was written by Thomas Muhr, developer of ATLAS.ti.  I reprint it here with his permission.  To contact him or to learn more about his work, please go to  www.atlasti.com

I felt that his comments on intuitiveness in qualitative data analysis software bore repeating and disseminating. This issue has long been a matter of contention in comparing quantitative and qualitative software packages AND more recently in the discussion new Web 2.0 tools in comparison to the more robust stand-alone packages.  As a developer with long experience in the field, Muhr's comments are particularly important for those of us who are advocates for QDAS software to hear.  


qual-software [QUAL-SOFTWARE@JISCMAIL.AC.UK]


Dear readers of qual-software,
this post was intended as a reply to a discussion that emerged in early
February. However, when thinking about a specific issue I decided to make
this a separate thread.

The notion of "intuitiveness" is intriguing but has its limitations.  If it
is used as a lense to evaluate tools such as software systems, the inherent
complexity of the domain augmented by the tool must be taken into account.
Intuitiveness has its obvious benefits; for one, it is associated with a
shallow learning curve, and as a corrollary, efficient and economical.
Nevertheless, I would like to raise a few points with regard to this
increasingly popular standard and expectation, and in particular question
its universal applicability.

For starters, assuming that the addressed domain (to be analyzed) is
adequately understood by the potential user (no matter if the methodology
was or was not sufficiently intuitive to abandon any manuals or courses),
the steepness of the learning curve does in fact depend on how well,
completely and congruently (emulating natural workflows) the concepts and
methods of the domain are represented in the tool. However, in reality, and
not only in the QDA field, learning a tool and learning a methodology are
often intertwined.
This can often lead to a bias and making it difficult to isolate the
learning curve for the software. Ultimately, discussions about the relative
ease of learning QDA tools often overlook that fact that essentially two
things are part of the curriculum. In some cases, users expect that a
software program might even replace proper training in methods.

Intuitiveness is not neccessarily bound to how well a given software system
intended for one domain resembles a standard in a completely different
domain such as one used for writing and reading emails. It may come as a
surprise how many users of standard email/calendar tools experience
difficulties regarding the accessibility or "user-friendliness" of important
functions.
And the functions provided by such tools, e.g. Outlook, are far less complex
than what tools in the QDA area may need to offer. The situation is even
becoming a bit more complicated with tools like Outlook. While receiving and
responding to an email is quite intuitive, changing the style of your
responses, adding or modifying mail accounts or creating a meaningful series
of calendar events is already another thing. While we expect and require a
broader range of functions, expectations of ease-in-use also continue to
grow, prompting the question of whether there is indeed a budding paradox in
the software field.

Even if all engineering efforts have been invested in making a tool as
"intuitive" as possible, there will still be a difference dictated by the
complexity of the modeled reality. t is relatively easy to create
anintuitive tool for calling a taxi with an iPhone (which I recently
installed: activate big yellow button; enter number of passengers; make
payment and voila, the taxi is on its way). Such tools obviously do not
require a manual or a two-day workshop. By the way, good examples for
intuitive interfaces are some adaptations of web sites to the limitations of
mobile devices. Modelling more complex relations obviously requires a
broader spectrum of commands, all of which the user must be at least vaguely
aware in order to benefit from them. 

And if users plan to use a tool that allows them to work on text, images,
audio, video, GIS data, (native) PDFs, as well as one that can create and
manage selected segments in each of these media types; a program that
enables the user to create and define links between codes and segments,
codes and codes, segments and segments (hyperlinks), create and manage memos
that can be associated to any kind of concept available, group concepts,
synchronize media data and transcripts, create queries & hypotheses, decide
and/or create relational prototypes modeling the methodology used, offer a
vast array of analytical tools, offer standards for importing and exporting
project data (-> 1)... and so on and so forth... comparing this type of
broad-spectrum functionality - with regard to intuitiveness - to a tool
primarily dedicated to the analysis of video and the display of an
associated transcript (i.e. Transana) is questionable, at very least.
Without a doubt, the latter tool will suffice for any task or phase
constrained to the ingredients just described.

A tool's intuitiveness can be taken to impressive heights, but if a variety
of methodologies and styles are to be supported, the increasing number of
tool functions and workflows may conflict with this effort. And of course,
personal styles and intellectual habits are also involved in the process of
getting acquainted with a tool. ATLAS.ti has always tried to be as open as
possible with regard to exploring, navigating the emerging "context of
discovery" while concurrently remaining systematical when it comes to
representation and analysis.

Human reasoning and creativity does not often fit well in a tiled
hierarchical windowing scheme, even if it is sometimes comfortable and
tidier. (-> 2) The task we have solved (and are steadily improving) is to
provide a workspace for the user in which all ingredients of a research
endeavor, including the primary data, the concepts that arise in the
process, the memos to be recorded, the linkages between the data and the
"theory", the short cuts between the conceptual level and the indicators in
the data in their original context, can be easily queried and navigated. It
would be an interesting research question itself to find out which
methodologies and which tools match which intellectual and emotional
preconditions - while of course using ATLAS.ti for the analysis!-) While I
agree completely that our system would and should benefit from certain
improvements - and we are constantly working on improvements, which by the
way, we return to our users not only in (costly) major releases but in a
constant evolutionary process, I disagree that adapting to a more standard
(i.e. "Outlook"-type) interface would make things much easier.  Our current
efforts are focussed on the different roles and levels of expertise of users
working with our tools and how different needs can be modeled in the user
interface. And in this process of change we include our users as well as our
engineers.

Thanks for your patience - comments welcome!
- Thomas Muhr (CEO ATLAS.ti GmbH)

---- end notes ---

(1) By the way, it is only the fact that ATLAS.ti exports project data in a
standard format (XML) that makes the feature "we are able to import ATLAS.ti
projects" possible. It would be much better - at least for the scientific
community - if ALL (!) makers of QDA software would finally agree to support
an open standard or at least an XML based export/import technology. Our XML
compatibility means we allow our users to "leave" us, which may not make
much sense business-wise. But with only proprietary data structures,  the
migration path to alternative and/or future tools will be long and bumpy,
not to mention the chances for smooth longitudinal designs. My advice is to
check your current system if it also gives you the freedom to say "goodbye".
If not, ask for it.

(2) When I look at my desk and desktop, I personally get the impression that
a messy environment can be quite inspiring at times!-
"Convolutedness" at first sight may indeed turn into familarity once the
main concepts and procedures are understood. Instant intuiveness on the
other hand is great, but if you need to drop important properties of your
research requirements it isn't really helpful, i.e. conducive to complex
research.

------------------------------------------------------
"Computers, like every technology, are a vehicle for the transformation of
tradition" (Winograd & Flores, 1987) ATLAS.ti Scientific Software
Development GmbH - Berlin - www.atlasti.com

Dissertations vs the IPad

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Recently my program has taken up a discussion of the dissertation--what can we agree upon about the form, contents, style, etc.  In other words, what are our standards for this culminating piece of work in the doctoral program.  We are looking at a rubric that another institution developed, and I have to say that it makes the dissertation look pretty darn BORING. 

[Ironically even this ancient manuscript to the right from about 1200 has more color and design interest  than today's dissertation.]

I have nothing against the notion of a strong literature review, compelling question, thoughtful theoretical intersections, excellent methodological description and well described findings and discussions of implications.  Although, I am not sure that we can agree on what this means cross paradigm.  I think what will be even more difficult is how to figure out what this means in light of new digital forms.  I have already run into a variety of difficulties with issues related to discussions of qualitative data analysis software (QDAS), and this is only the tip of the iceberg when it comes to addressing new forms. 

I think one of the most important challenges to the standard black and white dissertation, though, are the new visual formats.  For the last few weeks, my Google Reader has been bringing me video advertisements of the new Apple IPad and the kinds of content news media are developing for it.  The New York Times and Sports Illustrated are two I've seen, which are dazzling in their color and flexibility.  It's like a newspaper or magazine and a website combined.  But what is even more interesting is that it feels like it has jumped out of the old computer monitor and into a new kinesthetic mode with the ability to touch the screen and make things happen. 

This is not anything like the way the old dissertation looks even in digital form. Take a look at it.

Apple IPad

You'll probably notice as I did that there is not a single woman in the ad...all male speakers. That aside, (and I am sure they studied their demographic carefully before the release) this is how print of the future will look.  The dissertation looks dingy and sad beside it. Visual images are at a minimum.  Indeed, the height of visual orientation in the standard dissertation is the robust use of APA headings! 

Interestingly, though,  the Apple IPad  is loaded with skeumorphs--references to earlier times and technologies.  You turn pages, select a photo from a pile of photos, select books from bookshelves.  You feel like you are in the world of print and furniture of the late 20th century.  Things work in the same way, but they are all virtual--opening, closing, sliding forwards and backwards with the touch of a finger. 

In such a world it appears on the surface that the standard dissertation can find a place, but my question is why?  By this, I don't mean that we should give up and go on as we have for so many years, creating these five chapter documents that get shelved for eternity.  Rather, why, go on with the old form?  What's stopping us from jumping ship? Trying new forms? 

At the University of British Columbia (UBC) College of Education they have been doing experimentation with arts-based dissertations.  This may be the direction to consider.  

Three Cases of Visual Memos

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I have blogged thrice about visual memos I have created:

Visual Memos in Qualitative Research
This is an example of a visual memo developed from writing in my journal about the journal project.  I was thinking about the ways the journal project and its writing was different from formal social science writing.

Visual Memos in Qualitative Research: Part II
 This memo describes the way an image or art approach (prayer ropes) developed through a series of experiences related to the death of a dear friend. 

Visual Memos in Qualitative Research: Part IV
 This memo (a handmade book) developed as a reflection on the experience of teaching a qualitative research class in which visual memos were integrated with every component of the course experience. 

As I think across the visual memos themselves, some of the patterns I see in this work are:

• They are narrative.  They tell a story, reflect on a chain of events, connect diverse strands of thought.  
• They are combinatory.  They bring together diverse elements or thoughts in a single location. 
• They lead to strong juxtapositions.  Bringing together the different pieces leads to new positioning of ideas in relationship to each other.  
• They are sensual.  I react to the nuances of color, texture, shape, line.  Text, too, is sensual for the dedicated reader, but in a different way. 
• They reveal things to me that were hidden from me when I operated solely in my textual mode. 

I've mused about visual memos in this blog also:

Visual Memos in Qualitative Research: Part III

I've also given thought to the visual qualities of different forms of qualitative research analysis--manual modes vs. computer modes. 

Getting Visual With Qualitative Research Analysis

This week I started to think about the literature of memos in qualitative research:

Memos and Qualitative Research: Kathy Charmaz

This is a beginning for me.  There are others to examine.  What I want to bring forward from Charmaz regarding memos is how they exist in the space between data and fixed/mature interpretations.  They are the thing waiting to be heard, to take form. 

Memos...it's a juicy topic. 

Walter Gerson and "The Collaborative Turn"

Run.  Don't Walk.  To get your copy of

The Collaborative Turn

edited by Walter Gershon. 

I've been reading this book over the spring break in anticipation of reviewing it for the

International Journal of Education and the Arts

I don't want to give away the show, but truly--take a good look at this book! 

Memos and Qualitative Research: Kathy Charmaz

Image by darkmatter via Flickr

Since I started this blog I've written several entries about visual memos.  For some time I've meant to look at the discussion of memos/memoing in texts that I consider classics in this area to see how these descriptions might help me understand what I am trying to get at with the visual memo.  So here are some of my favorites on memoing:

Charmaz, K.(2006).   Constructing grounded theory: A practical guide through qualitative analysis.  Thousand Oaks, CA:  Sage Publications.

Emerson, R., Fretz,R., Shaw, L. (1995).  Writing ethnographic fieldnotes.  University of Chicago Press. 


Maxwell, J. (2005).  Qualitative research design:  An interactive approach (2nd ed.).  Thousand Oaks, CA: Sage Publications. 


Miles, M. & Huberman, A.M. (1994).  Qualitative data analysis: An expanded sourcebook.  Thousand Oaks, CA:  Sage Publications.


(Oops...just realized I left out one of my favorites by Anslem Strauss--I'll catch up with that one later.)

Today I am going to write about one of these:  Kathy Charmaz's discussion of memos. 


"Memo-writing" is the title of Chapter 4 in Charmaz's book.  It is an elegant description of memos in grounded theory.  It will really give you shivers. 

"Memos catch your thoughts, capture the comparisons and connections you make, and crystallize questions and directions you want to purse."  (p. 72)

Here are some of the functions memos fill for her:

• "conversing with yourself" (p. 72)
• "explicate and fill out categories" (p72) 
• "serve as the analytic core" for subsequent writing (p.76)

Her primary advice in creating memos is to "do what works for you" (p. 80) and "...engage a category, let your mind rove freely in, around, under, and from the category..." (p. 81)

Charmaz explores the ways the techniques that writers of many sorts employ to get themselves off the ground--clustering, freewriting, etc.--can all serve the qualitative researcher at the stage of memo writing.

She gives special attention to "Using memos to raise focused codes to conceptual categories" (91)  This seems to me key in thinking about the ways memos can assist in the refinement process, that is, the process of making a clump of data into something called evidence--that's like spinning flax into gold. 

One thing that cannot be ignored in talking about memos and qualitative research is that the discussion of memos is always right in the middle, squished between data collection and coding on one side...and products, representations, and presentations on the other side.  Memos, in the written textual mode, are always about refinement of raw data and leveraging preliminary interpretations.  As Charmaz says, the construction of the memo is the "pivotal intermediate step between data collection and writing drafts of papers" (72). 

For the novice researcher, I think that the notion of memos is hidden behind flashy things that catch their attention like coding or interviewing--things that stand out as if they have neon lights on them.  Memos, for the qualitative research connossieur, however, are like a fine wine.  They are swished around in the mouth and savored!  The tastes are subtle and learned.

I think I will stop here with Charmaz and take on another one of the classic memoists next. 

Qualitative Computing: Diverse Worlds and Research Practices

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Today I received this notice about a conference to be held in February in Istanbul.  It sounds like a great opportunity to think globablly about the ways computing has evolved in qualitative research.  

***********

Ankara University Sociology Department, Turkey and Sociology Department of Universidad Autónoma Metropolitana, Iztapalapa, México invite you to participate in the Seminar “Qualitative Computing: Diverse Worlds and Research Practices” to be held in Istanbul, February 24-26, 2011.  The Seminar aims to bring users from the North and South, from the East and the West and from the centers and the peripheries. This is an excellent occasion for CAQDAS users from all disciplines to share their experiences with qualitative software. 

“Qualitative Computing: Diverse Worlds and Research Practices” focuses on how research practices from diverse worlds have fostering qualitative computing. Such research practices has to be analyzed from methodological perspectives and the epistemological roots of each national way of practicing qualitative research must to be discussed as well. Thirty years of CAQDAS influence into the social sciences methodologies are not a simple issue and this Seminar is a great chance to discuss about the diversity of such influence.

More information at http://www.qualitativecomputing2011.net/ . Or contact Elif Kuş or César A. Cisneros 

Warmest regards,

César A. Cisneros Puebla
Departamento de Sociología
UAM Iztapalapa
San Rafael Atlixco 186
Col. Vicentina
México DF 09340
Tel. (52 55) 5804 4788
Fax (52 55) 5804 4789
http://compucualitativa.sitiosprodigy.mx/

Getting Visual with Qualitative Research Analysis

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Yesterday I spent time in the bowels of my Journal Project...to be specific the bowels of the project are located in NVivo, my Qualitative Data Analysis Software package of preference.  I was working on specific codes.  "Coding on" as we say in the trade, that is, taking a larger bin of references and hacking it up into smaller identified chunks as well as reorganizing codes--merging, deleting, etc. 

As I did this I found myself so satisfied with the visual process of how the tool was showing me the changes that were being made.  Over and over I would create a new child node, drop materials into it and see the label of the sub-node pop up underneath its 'parent'.  It was a visually satisfying process to see the shrinkage or collapse of materials, along with the relief of organization appearing.  It put me very much in mind of Bruno Latour's discussion of "cascades" of paper, graphs, charts, etc.  that emerge in modern times. 

I couldn't help but think back to the coding processes of yore.  Actually, I liked the old cut and paste, too.  (At the time I didn't know there were alternatives.)  But what I appreciated was different, visually.  I remember the importance of the wide right margin (or sometimes you put the column of text right in the center to given you a wide left and right margin)...and using the line numbering function so that you would be able to create a more exact reference.  As you can see I am describing a computer word processor based form of data analysis...which is, itself, represents a brief period at the end of the 20th century. 

I would write my codes by hand in the margins, xerox the pages later (making more copies for those pages with overlapping codes), and then cut them up, making sure to put a page # on each fragment, and then file in a file drawer full of files with little fragments of text.  I thought this was highly efficient, and I found it to be visual and satisfying.  Just as now, I feel satisfaction watching a list of codes emerge in a nice little line. 

I'm not arguing about which is best here.  Rather what has caught my attention is how, in both cases, there is a deep reliance on visualization in the qualitative research analysis process.  This is a kind of visualization that is not captured by pictures or in photos--it's not a drawing. 

I think back to Anselem Strauss' book on analysis (the white book I have always called it--because of the color of the jacket)...and Miles and Huberman (the large gray book)...and I think about the ways they describe data representation.  They are talking about text, but text that mixes the meaning of the text with visual formats that help us to move the blocks of text around in our heads:  A table with codes organized; a schematic map of social relationships or connections between events.  These qualitative researchers honed in on the ways that the work of analysis was reliant on visual constructions. 

Both manual and computer based methods of qualitative research analysis are highly visual.  It's not that manual was not and QDAS is.  QDAS, however, does have new visual affordances.  As I was working on my "dream" code, I found myself in the source bin exploring the three ways that references can be viewed:  summary, text, and icons.  I found the summary helped me to understand how much and where it was located.  I worked in the full text of the code and the view with multiple icons to choose from and single text. 

I do have to say that working in QDAS felt more efficient.  If I'd never experienced it, I wouldn't know.  But I do know, and I know it is easier to move my materials around and that the visualization of the text through terms and positioning is richer than what I had available to me before. 

Now my question is--how is this form of visualization different than the kind of visual that I was talking about earlier in the blog--drawings, collage, and other non-text creations?  It's something to think about!

Qualitative Research Dissertations: A decade of experiences

I have been giving thought to dissertations over the last few weeks and thinking about the experiences I have had as a qualitative researcher working with a variety of dissertations.  One thing that comes to mind are the sticking points I have run into between my qualitative research expectations and the expectations of other committee members who may or may not have qualitative research training. 

In raising this issue, I have to make it clear--this isn't meant to point fingers.  Many times the questions raised led everyone to better understanding of a particular feature.  In many cases, it led to better language and descriptions, richer theoretical contextualizing. 

Here are some examples: 
1.  The use of "I" in the proposal or dissertation.  Over the years I have heard many objections to the use of the first person singular. 
2.   Accounting for subjectivity.  A reflective section on how the researcher's subjectivity is engaged with the topic, what the strengths and dangers are, and how the researcher will make themselves aware of their feelings and reactions and how they might be influcing the course of the research. 
3.  Inclusion of the researcher's own story as part of the narrative.  This is why I am passionate about this topic!
4.  Accounting for the use of software in the organization and management of the data and the analysis.  Why do you need detailed technical descriptions?  Just say what you did without reference to the software. 
5.  The use of visual data.  To the credit of other committee members, they called for better theoretical contextualizing of the use of this data, that is, providing a methodological background for the use of this data. 

Interestingly, long before the dissertation defense is scheduled, many students self-censor as they try to develop a dissertation that looks like the examples to which they have been exposed.  I have to beg for a stronger person voice and inclusion of examples of the visual data they've collected.  I cajole them to add a rigorous description of the use of their software tools, and I insist upon a section where they reflect upon their subjectivity in the conduct of the study. 

When I started off into academia post-graduation, I thought I would face challenges as a qualitative researcher, but I am  not sure I anticipated that these particular issues would persist year-after-year. 

Year-after-year, I go off to the International Congress on Qualitative Inquiry and attend sessions and workshops on experimental techniques in qualitative research--performance ethnography, new directions in technologies and qualitative research, arts-based research, soul searching in regard to subjectivity, and visual data uses.  I breath in the heady atmosphere of new ideas and approaches.  I am glad to know that these ideas exist.  But I am more knowledgeable now of the path by which ideas move from the center to the margins. 

My deep thanks to the doctoral students who have joined me in the exploration.  It has been a privilege to work with each of you. 

Chip (Bertram) Bruce: Ode to a Dissertation Advisor

When I entered my doctoral program at the University of Illinois College of Education, I was assigned an advisor.  Chip Bruce was new to the Curriculum and Instruction faculty, having spent the earlier portion of his career in a Cambridge based think tank.  Thus began a mentorship with a truly Renaissance man, creative and intellectually challenging, kind and humorous.  Loath to leave his fold, I went from doctoral advisee to dissertation advisee, completing my doctorate under him four years later. 

Chip has just announced his upcoming retirement from the University of Illinois (he is now located in the School of Information Science).  It seems like a fitting moment to consider the many gifts he brought to me and the others with whom he worked, and to offer a digital thanks to him.

This is not meant to be an obituary, because Chip is headed off to many new and exciting things, but rather this is an opportunity to think about the qualities of excellent doctoral advisement.  Here's what I learned from Chip:

• Be kind:  Respect each student.
• Be curious:  All is inquiry
• Be open minded:  Try to understand all sides.
• Be intellectual: Engage in theory.
• Laugh:  Appreciate the humor in life.
• Seek Community:  It is good to work with others.
• Love Dewey:  Only good can come from Dewey.
• Enjoy conversation:  It is the fruit of good community.
• Be practical:  Test all propositions against the world of practices.
• Be well organized: You get more done.
• Explore new media
• Be a global participant
• Don't gossip: Avoid sarcasm

Thank you Chip for these excellent rules of the road.  Good wishes with the next stages of your journey...


Chip Bruce's Blog