NUD*IST

- Vasuki M. Basavanahalli

It is a software product from QSR International [http://www.qsr.com.au/index.htm]. The company has released the sixth version of the software which is popularly known as N6. It is a product which helps in doing qualitative research. Some people refer this to Computer Aided Quality Data Analysis. (CAQDA). It is especially useful when we are working with a large amount of data in a team environment. The problem in qualitative research is not about getting the data but as to how to interpret it. (1994, Walcott). This software comes in handy there.

[A good presentation on qualitative research is: http://kerlins.net/bobbi/research/myresearch/chifoo/]

NUDIST stands for Non Numerical Unstructured Data Indexing Searching & Theorizing.

So how it relates to text mining? [or data mining]

My guess is that the ability of this software becomes very evident when we are working with a huge amount of data; which are also in different format –may be emails, interviews, texts etc..and we are trying to make a sense out of this data.

The first thing we do as in data mining is to arrange the data.[ie give it some structure—byusing the concept of nodes]. Then we use the “Text Search” function to find out a particular text or word OR it can be searched by using ideas or themes or to find out if certain themes occur in only certain contexts.

Here is where the search command becomes powerful. In case of N6, it is the search button. A window called “Text Search” would pop up as shown below.

Fig: Text Search being shown.

One can then type in say for example *chris; and wherever the mention of Chris was there in the document would pop up.

The search result would come out something as shown below:

Fig: Search Result.

Hence one can search for a specific phrase, searching for whole word or phrases only.

Different types of searches can be performed like:

Intersection search. [For example-is the concept of “home tutor” and “governess” is used interchangeably?]

Overlap search.

Cross tabulating comparison [vector and matrix searches.]

What can Nudist do?

NUD.IST will help you

1. “Manage” your data as you analyze documents such as interview transcripts, field notes, journal articles, papers, email archives or any other data you can save as a text file. 2. It will also facilitate your management of other data formats such as video and audio tapes.

3. You can search and code your data and automate many of the coding, searching and reporting tasks.

4. You can write memos and add context-sensitive annotations to your data. As you progress through your analysis you can use NUD.IST to document your analytic process and reflect on your role as a researcher.

NUD.IST Interface

As we open the software we get the following interface:

Fig 1: Start up screen

There are two windows: Node window and Document Window. Only One window can be active at a time.

NUDIST Project Directory

Need to have some idea about how the project folders are organized in this program. And some imp. Tips to manage the above directory.

Document Explorer Window

Node Explorer Window

Node Explorer is called the Node Browser. The terms explorer and browser are used interchangeably.

Node contains conceptually organized information you’ve coded from your documents. There are 6 types of nodes which are listed on the left window of the Node Browser. These are Free Nodes, Index Tree Root, Text Searches, Index Searches, Document Annotations and Node Clipboard.

Coding Palette

It is a collection of 10 buttons to assist you in coding documents in the Document Explorer or while browsing nodes in the Node Explorer.

Understanding the Index (Tree) System

When we click the “Index System” on the menu bar, the first option is “Explore”. By clicking it, will open the Node Explorer window.

Although there are 6 types of nodes, Index Tree Root will be central to the project development. It is on this root that we will form other nodes which is the backbone for

Project analysis.

However, unlike a family tree, you won’t be limited to two Parents. You may have many “Parent ideas” which are conceptually linked to many “child ideas”.

Hence we can think of Index Tree Root as the family tree of all the ideas that we develop in our analysis.

Using the metaphor of Family tree, NUDIST takes the tree and flips it on its axis so that it is displayed vertically as shown in the illustration below:

A Model Index System:

The model index system below contains 10 parent nodes on the Index Tree Root: Base data, Interview questions, Methodology, Role, Context, Relationships-Other, Relationship-Self, Critical Events, Issues, and Persistence.

In most cases the parent nodes are no more than three levels deep.

Index Tree Root

(1) Base Data

(1 1) Age

(1 1 1) 20s

(1 1 2) 30s

(1 1 3) 40s

(1 1 4) 50s

(1 2) Gender

(1 2 1) Female

(1 3) Social Class

(1 3 1) Middle Class

(1 3 2) Working Class

(1 3 3) Upper Class

(1 4) Ethnicity

(1 4 1) Chicano

(1 4 2) Italian

(1 4 3) Native

(1 4 4) WAS

(2) Interview Questions

(2 1) Motivation to pursue PhD

(2 2) Orientation to field of study

(2 3) Pre-doc expectations

(2 4) Changed view of PhD

(2 5) Challenges

(2 6) People, Experiences, Events

(2 7) Advisor Relationship

(2 8) Dissertation Committee

(2 9) Relationship with committee

(2 10) Candidacy exams

(2 11) Diss topic

(2 12) Data collection

(2 13) Data analysis - writing

(2 14) Final defense

(2 15) Impact on relationships

(2 16) Highs - Lows

(2 17) Unanticipated outcomes

(2 18) Health

(2 19) Self-confidence

(2 20) Secrets

(2 21) Finances

(2 22) Expectations exceeded - fallen short

(2 23) More meaningful experience

(2 24) Wish I'd known

(2 25) Things I'd do differently

(2 26) Critical to success

(2 27) How have you changed?

(2 28) Writing about your experiences

(2 29) Need for active listener

(3) Methodology

(3 1) Negotiating Participation

(3 2) Pseudonym

(3 3) Email as a Research Medium

(3 4) Importance of Reflection

(3 5) Writing About Your Story

(3 6) Importance of Audience

(3 7) Technology expertise

(4) Role

(4 1) Daughter

(4 2) Sister

(4 3) Student

(4 4) Employee

(4 4 1) Teaching Assistant

(4 4 2) Research Assistant

(4 4 3) Non-Uni Work

(4 5) Partner

(4 6) Wife

(4 7) Mother

(4 8) Being Female

(4 9) Study Participant

(4 10) Graduate

(4 11) Mentor

(5) Context

(5 1) Ph.D. Degree

(5 1 1) Pre-Admission

(5 1 2) Admission Process

(5 1 3) Program Description

(5 1 4) Course Work

(5 1 5) Committee

(5 1 5 1) Choosing advisor-committee

(5 1 5 2) Restructuring committee

(5 1 6) Candidacy

(5 1 7) Proposal

(5 1 8) Data Collection Analysis Writing

(5 1 9) ABD

(5 1 10) Defense

(5 1 11) Post Degree

(5 1 12) Institution

(5 1 13) Job Search

(5 2) Other Educational Contexts

(5 2 1) K-12 School Setting

(5 2 2) Community College

(5 2 3) Undergraduate

(5 2 4) Masters

(5 2 5) Post-Doc

(5 3) Family

(5 4) Work

(5 5) Social

(5 5 1) Class

(5 5 2) Culture

(6) Relationships: Other People

(6 1) Researcher-Participant

(6 1 1) Reciprocity

(6 1 2) Advice to Researcher

(6 1 3) Pleasing the Researcher

(6 1 4) Role of Audience

(6 2) Partner

(6 3) Advisor

(6 3 1) Being peer

(6 3 2) Advisor as authority figure

(6 3 3) Feedback from advisor

(6 4) Faculty

(6 4 1) Men faculty

(6 4 2) Women faculty

(6 5) Committee

(6 6) Student Colleagues

(6 7) Prog Support Personnel

(6 8) Family

(6 8 1) Childhood Family

(6 8 2) Adult Family

(6 9) Friends

(6 10) Coworkers

(7) Relationship: with Self (Identity)

(7 1) Goals

(7 2) Self-Descriptors

(7 3) Self-Confidence

(7 3 1) High Confidence

(7 3 2) Low Confidence

(7 4) Gender

(7 5) Social Self

(7 6) Sexual Identity

(7 7) Academic-Scholarly Identity

(7 8) Transformations-Changes

(7 9) Beliefs

(7 10) Feelings

(7 10 1) Exhaustion

(7 10 2) Stress

(7 10 3) Over work

(7 10 4) Overwhelming

(7 10 5) Humour

(7 10 6) Lonely

(7 10 7) Anger

(7 10 8) Imposter Syndrome

(7 10 9) Pain

(8) Critical Events

(8 1) Paradigm conflicts

(8 2) Unanticipated changes-surprises

(9) Issues

(9 1) Abuse

(9 2) Elitism

(9 3) Enrollment Status

(9 4) Ethics

(9 5) Finances

(9 6) Gender

(9 7) Health

(9 8) Hidden agendas

(9 9) Sex

(9 10) Secrets

(9 11) Trust

(9 12) Voice

(9 13) Work

(9 14) Recovering from PhD

(9 15) Balancing Needs

(9 16) Competition

(9 17) Collaboration

(9 18) Grilling

(9 19) Sleep

(9 20) Lack of time

(9 21) Isolation

(10) Persistence

(10 1) Persistence Enhanced

(10 2) Persistence Diminished

(10 2 1) PhD is hard on relationships

(10 2 2) Obstacles to completion

(10 3) Diss Topic

(10 3 1) Orientation to Fld of Study

(10 3 2) Relationship to MA

(10 3 3) Title

(10 4) Unanticipated Outcomes

(10 5) Survival Strategies

(10 6) Nature of PhD

(10 6 1) Motivation to Pursue PhD

(10 6 2) Expectations of Program

(10 6 3) I wish I'd known...

(10 6 4) Things I'd Do Differently

(10 6 5) How could PhD be more meaningful?

(10 6 6) Post Degree View

(10 6 7) Describe the dissertation process

(10 6 8) Suffering the PhD in silence

(10 7) Time to Degree

Document Preparation

Before we make any analysis of the data, we need to do some preliminary formatting with the documents or transcripts.

Document is any file that can be saved as a text file and can be imported. [To add more here..]

References

1. Kerlin A. Bobbi; http://kerlins.net/bobbi/research/nudist/

2.Walcott Henry, Transforming Qualitative Data: Description, Analysis and Interpretation.

3.