U8d1-68 – data analysis strategies reviewed by peers – please follow

U8D1-68 – Data Analysis Strategies Peer Review

Note: You are required to complete this discussion before submitting the unit assignment.

For this discussion, complete the following:

• Develop a step-by-step strategy for data analysis that is consistent with your question and methodology.
• Describe the data analysis section you will use in your study.
• Evaluate the effectiveness of the data analysis strategy, discussing its strengths and limitations.

Once you have received feedback from other learners, revise the discussion to include the feedback from your peers.

Data Analysis Strategies Scoring Guide

1. Describes data analysis methods clearly and in a well-documented manner that are appropriate to the design, allow the research question to be answered and are supported by appropriate references.

2. Creates interview questions that are relevant to the research question and are free from leading or biased language, and ensures that questions exemplify the skills of a qualitative researcher.

3. Describes the role of the researcher, and provides an insightful analysis of any pre-understandings, preconceptions, and biases about the topic, along with a detailed plan as to how to address them.

4. Writes each item in a manner that is sufficiently scholarly in tone and contains no editorial or mechanical (grammar, usage, typographical, etcetera) errors. 

Readings

Use your Qualitative Research & Evaluation Methods text to read pages 431–651 of Chapter 8, “Qualitative Analysis and Interpretation.” This chapter highlights the analysis and interpretation of data in qualitative research.

Use your Qualitative Inquiry and Research Design text to read Chapter 8, “Data Analysis and Representation,” pages 181–224. Focus on the following subsections:

1. “Three Analysis Strategies.”

2. “The Data Analysis Spiral.”

3. “Analysis Within Approaches to Inquiry.”

Read the transcript Qualitative Research Proposal.

INTRODUCTION – Unit 8 – Data Analysis

In qualitative research, data analysis can be one of the most difficult processes to clearly delineate. Regardless of the data that are collected, the analysis must be meticulously detailed. It is never enough to state that “themes will emerge from the data.” The researcher must go into considerable detail regarding the processes by which the themes will be discovered.

After the qualitative data have been collected and recorded, the next step in the research process is to analyze the data. While all of the analytical processes used in qualitative research essentially use an indicative approach, each of the

methodologies used for this course (that is, ethnography, case study, grounded theory, generic qualitative inquiry, and phenomenology) has its own specific methods and procedures for data analysis. The analytical approaches used to conduct the data analysis must be consistent with the research methodology employed.

Themes

Once themes, meaning units, and textures and structures in phenomenology have emerged that are representative of the data as a whole, the researcher develops thematic descriptions or depictions that capture each theme that has emerged

from the data.

Having developed the themes and thematic descriptions, the researcher returns to the data and identifies direct quotes and passages that represent and exemplify each of the themes.

To illustrate the process of extracting patterns and themes from the data collected from the interviews and journals, the researcher often presents a portion of a verbatim transcript of the interview or a passage from the participant’s journal to offer an example of the process by which the patterns and themes emerged from the data collected. This also serves as a

credibility check.

OBJECTIVES

To successfully complete this learning unit, you will be expected to:

1. Examine the application of the steps of data analysis.

2. Evaluate data analysis techniques appropriate within qualitative research.

3. List guiding interview questions that can be used in the qualitative interviews with the participants.

4. Develop a strategy for data analysis that is consistent with the question developed and the methodology chosen.