Coding text data involves putting passages of text into one or more conceptual categories for later analysis. There are two primary methods by which users can code datasets in PCAT:

• Open coding with 'user-defined' codes grounded in the data
• Pre-defined coding with pre-determined categories of interest to the analytic process

• Standard Coding Select this option to allow users to code all items
• Assign users a range of items Select this option to assign a range of specific items for users to code
• Code next uncoded item Select this option to automatically load the next uncoded item for users to code

To begin coding, select “Code Datasets” from the dashboard page, or “Code Datasets” from the “Datasets” drop-down menu. Click on the name of the dataset you wish to code.

As you code, you will notice a number of icons towards the top right of the window containing the text:

Stop Coding (returns you to the Code Datasets page)
Jump To… (takes you to the Jump to Paragraph to Code page, which is a list of paragraphs within that dataset)
Add Bookmark
View Bookmarks
Previous Unit (moves you back one paragraph in the current dataset; disabled on 1st paragraph in the dataset)
Next Unit (moves you forward one paragraph in the current dataset; disabled on final paragraph in the dataset)

There is also a counter which displays:

• Current Codeable Unit
  
• Paragraph Number/Total number of units in the dataset
  
• Total number of units that have been coded.
  

In all cases, in order apply a code/codes, press the “Code” button. You will then be advanced one paragraph forward in the dataset.

On a page that has been coded, at the top of the page will be displayed “This unit is coded with: <codes>.” Next to this will be a button labeled “Edit Coding”. If at any time you wish to edit prior coding, navigate to the appropriate page using “Previous/Next Unit” or the “Jump to…“ button where you can then select the page from the list of pages for that dataset. Once you have located the page you wish to edit, select “Edit Coding” at the top of the screen, and then follow the coding steps as normal.

When coding a dataset that has verification enabled, you will see two additional buttons after pressing the “Code” button:

You may control whether coders are required to verify their codes before they are recorded in PCAT. If verification is disabled, after a coder presses “Code”, he/she will simply advance to the next paragraph in the dataset. If verification is enabled, after a coder selects “Code”, the question “Apply these codes?” will be displayed, along with the selected code(s). Coders may select either “Verify Coding” or “Edit Coding”. If “Edit Coding” is selected for user-defined codes, the chosen codes will still be displayed in the coding window. If “Edit Coding” is selected for pre-defined, multiple coding, all of the prior selected codes will be erased.

The option to disable the verification step is offered to speed up the coding process.

• To disable verification when uploading a dataset, check the box next to “Disable verification for user-defined and multiple coding.”
• If a dataset has already been uploaded, view the dataset and in the Toolbox to the right, you will see either “Enable Verification for Coding” or “Disable Verification for Coding.” Click on the link to toggle between the two.
  

Why would I use this system? | Where do I get FDMS bulk downloads? | Does PCAT identify duplicates? | What is QDAP?

© 2009 - 2010 Qualitative Data Analysis Program (QDAP), in the University Center for Social and Urban Research, at the University of Pittsburgh, and QDAP-UMass, in the College of Social and Behavioral Sciences, at the University of Massachusetts Amherst. As of 2010, PCAT and this PCAT Help Wiki are maintained and improved by personnel from Texifter, LLC, which is a software start-up located in North Amherst & Springfield, MA and online at http://texifter.com.

Content on this website was made possible with the following grants from the National Science Foundation: III-0705566 “Collaborative Research III-COR: From a Pile of Documents to a Collection of Information: A Framework for Multi-Dimensional Text Analysis” and IIS-0429293 “Collaborative Research: Language Processing Technology for Electronic Rulemaking.” We are also grateful for financial support from the U.S. Environmental Protection Agency and the U.S. Fish & Wildlife Service. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the National Science Foundation.

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