Docsity
Docsity
Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity

Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan

Guidelines and tips
Guidelines and tips
Sell on Docsity
Sell on Docsity
Docsity AI
Docsity AI
Log inSign up

Prepare for your exams

Study with the several resources on Docsity

Find documents

Prepare for your exams with the study notes shared by other students like you on Docsity

Search for your university

Find the specific documents for your university's exams

Docsity AINEW

Summarize your documents, ask them questions, convert them into quizzes and concept maps

Explore questions

Clear up your doubts by reading the answers to questions asked by your fellow students

Earn points to download

Earn points by helping other students or get them with a premium plan

Share documents
download point icon20 Points

For each uploaded document

Answer questions
download point icon5 Points

For each given answer (max 1 per day)

All the ways to get free points
Get points immediately

Choose a premium plan with all the points you need

Study Opportunities

Choose your next study program

Get in touch with the best universities in the world. Search through thousands of universities and official partners

Community

Ask the community

Ask the community for help and clear up your study doubts

Free resources

Our save-the-student-ebooks!

Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors

Analyzing Qualitative Data for Evaluation, Slides of Qualitative research

University of the Visayas (UV)Qualitative research

This brief focuses on analyzing qualitative data that your program has collected. It includes an overview of qualitative data; how to plan for qualitative data ...

Typology: Slides

2021/2022

Uploaded on 08/05/2022

hal_s95
hal_s95 🇵🇭

4.4

(655)

10K documents

1 / 2

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
November 19, 2018C296013-O
Evaluation Briefs
Analyzing Qualitative Data for
Evaluation
No. 19 | updated August 2018
This brief focuses on analyzing qualitative data that your program has collected. It includes an overview of qualitative
data; how to plan for qualitative data analysis; how to analyze qualitative data; and the advantages and disadvantages of
qualitative data.
Overview
Qualitative data are information in non-numeric form.
They usually appear in textual or narrative format. For
example, focus group notes, open-ended interview or
questionnaire responses, and observation notes are
all types of qualitative data. Qualitative data analysis
is the process of interpreting and understanding the
qualitative data that you have collected.
Qualitative data analysis relies heavily on interpretation.
During analysis, you will draw on your own experiences
and knowledge of your program to make sense of your
data. You will also consider the context of your program
to determine how the data fit into the bigger picture.
Qualitative data analysis is an iterative process; once
you have begun to collect qualitative data, you will
begin to review it and use your initial findings to shape
how you collect and interpret data in the future.
How do you plan for qualitative data
analysis?
Because collecting qualitative data is relatively quick
and easy, you may feel compelled to collect a large
amount. However, be mindful that analysis of qualitative
data is time-consuming and labor-intensive. Plan to
collect only as much data as your program is able to
analyze and use. There are a number of Evaluation
Briefs about data collection methods for evaluation (see
Resources below).
It is important to plan ahead when analyzing qualitative
data to ensure that it will be meaningful and useful.
Determine your focus. Consider the evaluation
question(s) you want to answer. Keep in mind that these
questions will guide the interpretation of your data.
Decide how your data will be used to improve your
program.
Determine who will analyze the data. Multiple
people should analyze the data to be sure that the
interpretation of findings is not biased. Those who
conduct the analysis should have ample time and
energy to comb through large amounts of text-
based data. They should also have enough program
knowledge to interpret findings appropriately. When
more than one person analyzes data, everyone must
use the same systematic approach for reviewing,
organizing, and coding the data.
Obtain the necessary tools you need to analyze your
data. Qualitative data can be analyzed either manually
or using a computer software package.
• Manual analysis involves organizing and labeling your
data by hand. You may only need some additional
office supplies such as folders and highlighters
to store and label your data. This method can be
cost effective because of the small amount of extra
materials needed. Manual analysis is typically the
best method for analyzing your data if you only
collect qualitative data periodically and have a
manageable amount of data.
• There are several computer software programs that
allow you to organize, label, and search qualitative
data by participant, question, or topic area. Computer
software programs vary in cost and are often
available online for computer download. Keep in
mind that computer software programs do not do the
analysis for you; they are simply a tool for organizing
and searching the data. This method is ideal if you
frequently collect qualitative data and have large
amounts of data.
pf2

Partial preview of the text

Download Analyzing Qualitative Data for Evaluation and more Slides Qualitative research in PDF only on Docsity!

C296013-O November 19, 2018

Evaluation Briefs

Analyzing Qualitative Data for

Evaluation

No. 19 | updated August 2018 This brief focuses on analyzing qualitative data that your program has collected. It includes an overview of qualitative data; how to plan for qualitative data analysis; how to analyze qualitative data; and the advantages and disadvantages of qualitative data.

Overview

Qualitative data are information in non-numeric form. They usually appear in textual or narrative format. For example, focus group notes, open-ended interview or questionnaire responses, and observation notes are all types of qualitative data. Qualitative data analysis is the process of interpreting and understanding the qualitative data that you have collected. Qualitative data analysis relies heavily on interpretation. During analysis, you will draw on your own experiences and knowledge of your program to make sense of your data. You will also consider the context of your program to determine how the data fit into the bigger picture. Qualitative data analysis is an iterative process; once you have begun to collect qualitative data, you will begin to review it and use your initial findings to shape how you collect and interpret data in the future.

How do you plan for qualitative data

analysis?

Because collecting qualitative data is relatively quick and easy, you may feel compelled to collect a large amount. However, be mindful that analysis of qualitative data is time-consuming and labor-intensive. Plan to collect only as much data as your program is able to analyze and use. There are a number of Evaluation Briefs about data collection methods for evaluation (see Resources below). It is important to plan ahead when analyzing qualitative data to ensure that it will be meaningful and useful. Determine your focus. Consider the evaluation question(s) you want to answer. Keep in mind that these questions will guide the interpretation of your data. Decide how your data will be used to improve your program. Determine who will analyze the data. Multiple people should analyze the data to be sure that the interpretation of findings is not biased. Those who conduct the analysis should have ample time and energy to comb through large amounts of text- based data. They should also have enough program knowledge to interpret findings appropriately. When more than one person analyzes data, everyone must use the same systematic approach for reviewing, organizing, and coding the data. Obtain the necessary tools you need to analyze your data. Qualitative data can be analyzed either manually or using a computer software package.

  • Manual analysis involves organizing and labeling your data by hand. You may only need some additional office supplies such as folders and highlighters to store and label your data. This method can be cost effective because of the small amount of extra materials needed. Manual analysis is typically the best method for analyzing your data if you only collect qualitative data periodically and have a manageable amount of data.
  • There are several computer software programs that allow you to organize, label, and search qualitative data by participant, question, or topic area. Computer software programs vary in cost and are often available online for computer download. Keep in mind that computer software programs do not do the analysis for you; they are simply a tool for organizing and searching the data. This method is ideal if you frequently collect qualitative data and have large amounts of data.

Both methods require you to review, code, and interpret your data. You will have to determine which method is most appropriate for your program.

How do you analyze qualitative data?

It is critical that you develop a systematic approach for analyzing your qualitative data. There are four major steps to this process:

  • Review your data. Before beginning any analysis, it is important that you understand the data you have collected by reviewing them several times. For example, if your data consist of interview transcripts, read and re-read the transcripts until you have a general understanding of the content. As you are reviewing, write notes of your first impressions of the data; these initial responses may be useful later as you interpret your data.
  • Organize your data. Qualitative data sets tend to be very lengthy and complex. Once you have reviewed your data and are familiar with what you have, organize your data so that they are more manageable and easy to navigate. This can save you time and energy later. Depending on the evaluation question(s) you want to answer, there are a variety of ways to group your data, including by date, by data collection type (such as focus group vs. interview), or by question asked.
  • Code your data. Coding is the process of identifying and labeling themes within your data that correspond with the evaluation questions you want to answer. Themes are common trends or ideas that appear repeatedly throughout the data. You may have to read through your data several times before you identify all of the themes within them.
  • Interpret your data. Interpretation involves attaching meaning and significance to your data. Start by making a list of key themes. Revisit your review notes to factor in your initial responses to the data. Review each theme that arose during the coding process and identify similarities and differences in responses from participants with differing characteristics. Also, consider the relationships between themes to determine how they may be connected. Determine what new lessons you have learned about your program and how those lessons can be applied to different parts of your program. Qualitative data are rich and complex; you will want to get the most out of your data. When your analysis is complete, share your data with stakeholders in an evaluation report (see Evaluation Brief 11: Preparing an Evaluation Report).

What are the advantages of qualitative data?

  • Useful for gaining insight and understanding into process and context.
  • Can fill gaps in your program’s quantitative data findings.
  • Allow you to use your own knowledge and expertise of your program to make sense of your data.
  • Add depth to understanding your program.

What are the disadvantages of qualitative

data?

  • Analysis can be time-consuming and labor-intensive.
  • Findings will not likely be generalizable outside the group from which you sampled participants during data collection.
  • Reviewer interpretation introduces bias during analysis.
  • Findings are subjective and can be interpreted differently by different stakeholders.

Resources

Brief 19: Analyzing Qualitative Data for Evaluation Available at: https://www.cdc.gov/healthyyouth/evaluation/ pdf/brief19.pdf For further information or assistance, contact the Evaluation Research Team at [email protected]. You can also contact us via our website: http://www.cdc.gov/ healthyyouth/evaluation/index.htm.