A Journey Through Technology

How will you go about making sense of your data?

on October 31, 2015

Qualitative research yields data that can include interviews, documents, or observations (Merriam & Tisdell, 2016, p.105). In order to come to a conclusion at the end of a research project, the data that is collected must be analyzed. “Data analysis is the process used to answer your research question(s).” (Merriam & Tisdell, 2016, p.202) Some possible steps to following in conducting qualitative data analysis are to review the data, organize the data, code the data, and finally interpret the data (CDC, 2009).

As you gather data for analysis, it is helpful to review all of your data to make sure you completely understand the content (CDC, 2009). Once data has been reviewed for understanding, it then needs to be organized. In organizing, it helps to group data together that have similar themes, which can be done manually by using file folders or electronically using computer assisted qualitative analysis (CAQDAS) programs (Lewins, Taylor, & Gibbs, 2003). Once the data itself is organized, coding is a tool that is helpful for organizing information contained within the data. “Coding is the process of identifying and labeling themes within your data that correspond with the evaluation questions you want to answer.” (CDC, 2009) It is important to code your data as it is collected to make sure you don’t forget important characteristics when the data is later analyzed (Merriam & Tisdell, 2016, p.199).

The last step of data analysis is to interpret the data. A good place to start in interpreting the data is to make a list of key themes (CDC, 2009). “Qualitative data analysis is all about identifying themes, categories, patterns, or answers to your research questions” (Merriam & Tisdell, 2016, p.216). As you work on interpreting your data, you should be able to identify the answer to your research question, even if it wasn’t what you expected. One of the hardest parts about data analysis is knowing when to stop. When you are unable to produce new information or insights into your topic, saturation has occurred (Merriam & Tisdell, 2016, p.198). Once you have reached the point of saturation, data analysis does not need to continue because you won’t be able to learn anything new.

The main sources of data for my research are survey results and observation notes. The data will be organized according to type. The survey results are numeric, so they will be analyzed by comparing the survey results from the beginning of the research to the end of the research. The observation notes will be coded by looking for key words that appear in multiple observations, and then I will interpret the observations according to the different codes. The question I am trying to answer in my research is “Does the use of clickers increase student engagement in the high school chemistry classroom?”, so I will be looking for evidence of engagement when clickers are used versus when they are not used in class.

References:

Analyzing Qualitative Data for Evaluation. (2009, April 1). Retrieved October 29, 2015, from http://www.cdc.gov/healthyyouth/evaluation/pdf/brief19.pdf

Lewins, A., Taylor, C., & Gibbs, G. (2005, November 23). What is Qualitative Data Analysis. Retrieved October 30, 2015, from http://onlineqda.hud.ac.uk/Intro_QDA/what_is_qda.php

Merriam, S., & Tisdell, E. (2016). Qualitative research: A guide to design and implementation (4th ed.). San Francisco: Jossey-Bass.

O’Connor, H., & Gibson, N. (2003). A Step-by-Step Guide to Qualitative Data Analysis. Pimatisiwin: A Journal of Aboriginal and Indigenous Community Health, 1(1), 63-90. Retrieved October 29, 2015, from http://www.pimatisiwin.com/uploads/1289566991.pdf

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4 responses to “How will you go about making sense of your data?

  1. clindquist17 says:

    I think you are smart to use coding. I think my you should try to look at the data without focusing too much on whether it lines up to your research question, because you could miss some other themes that you didn’t even know would pop up.

    Like

    • Sarah K says:

      That’s a good point. I don’t want to ignore other areas that might also be relevant to the research, even if it isn’t directly related to the question. It will be interesting to see what happens when I code the survey results.

      Like

      • Sara Lucas says:

        I think this is so true. Thank you both for pointing this out. I think I have already been doing that. I was stuck in my methods and when I took a step back it just didn’t seem that useful. I think this will be hard, but it is definitely important.

        Like

  2. pwjohnsen says:

    “Data analysis is the process used to answer your research question(s).” (Merriam & Tisdell, 2016, p.202) I am so glad that you included this statement. I need to keep reminding myself of this. As I collect, sort and begin to analyze data, I need to constantly be reminding myself of the research questions I am answering. “The observation notes will be coded by looking for key words that appear in multiple observations”. I think this a great way to analyze observation data. I will be stealing this idea.

    Liked by 1 person

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