Background

In this weeks assignment, you will examine various types of coding and apply open coding to a dataset. While the specific type of coding you use in your own dissertation research will be a collaboration between you and your chair, practical experience with open coding will provide the background and context you need to participate in that collaboration.

Instructions

Part I:

In Part I of this assignment, you will explore, compare, and contrast three different coding methods utilized in qualitative data analysis open coding and two coding methods of your choice.

1. In addition to open coding, identify two additional coding methods that you might use in the analysis of your dissertation research.
2. Highlight the unique characteristics, advantages, and limitations of each coding method.
3. Conclude by discussing circumstances where each method might be most effective and the implications of choosing one method over another in qualitative data analysis.

Part II:

In Part II of this assignment, you will familiarize yourself with the concept and practice of open coding by analyzing a qualitative dataset and generating initial codes.

1. Access a 1.5 to 3-page qualitative dataset. You have three options.

1. Choose from one of the sample interview transcripts below.

1. Use an AI-generated transcript. Use the instructions below for using ChatGPT to create your transcript.

1. Use qualitative data that you have already accessed.

2. Transfer your dataset into a Word formatted table following the instructions below (sample transcripts provided under option A already have this step completed).

3. Utilize the principles of open coding on the dataset. Apply an inductive approachallow codes to emerge directly from the data without imposing predefined categories. Use the sample in the link below to guide your coding.

Combine Parts I and II into a single Word document for upload.

Length: This assignment must be 2-3 pages (excluding the title and reference pages) and 1.5-3 pages of coding.

References: Include four (4) scholarly resources.