Activities for Data Analysis

1) Analyzing Your Data

Consider the data that you collected, now is the time to analyze it. Your goal is to review, find relationships, condense, and display. This does not mean putting the collected data in the paper, it means making sense of the data and sharing the overview with your readers. You do the hard work of making sense of the data so that others can benefit. But you have to do it in a way that is reliable... that is in a way that if the reader invested the time and energy to follow your steps, they would come up with a similar summary. : Keep very careful notes of exactly what you did as you will need to describe that steps. It should be detailed enough that you or someone else can repeat what you did. (Thinking of showing your work in math class). Here are some possible steps but you may follow a different path

A. Organize Your Data Into Your Storyline:

storyline.jpg Organize your data into themes or topics that relate to your research question and to the outcomes that listed on the logic model. For example, if your action was to help foster a community of practice orientation at your workplace, in your logic model you might have predicted the following near outcomes: higher productivity, less duplication of services, and a more cohesive and creative working group. So for data analysis you might start by using these categories. Then you could look at the data you collected and arrange it under each of these categories. Your approach will depend on the type of data. (See the video and resources for other ideas for organizing your data).

B. Explore your Data to Find your Story: FeaturePics-Person-Magnifier-184325-2599418.jpg

    • Descriptive data (numerical or quantitative): Where you have data that can be counted, compute the numbers. Size matters in reporting descriptive data. Always tell your reader how large your data set is. N =15 is the shorthand for the number of respondents. Percents are only meaningful when you know the size of the whole. If you say 50% of the students, this could mean 10 or 200 depending on class size. You have to use percents when you are comparing groups with different sizes. So if you are working with two teams and one has 20 people and the other 10, and you say that 10 in each group responded yes, one might assume this response was the same for both groups. But in fact, 50% of group 1 and 100% of Group 2 responded yes. If you only have one group and there are less than 10 respondents, number is a better representation of the value.
    • Narrative or textual data (qualitative): Analysis of student blogs or opened ended questions often involves coding. The codes can come from the data or from your research questions. Suppose you asked students to reflect on what they learned from a project you designed. Read through the responses and come up with a plan for coding. Often this entails writing notes in the margins and then looking for patterns. If you start to see something that many of the students are saying you give that a code. For example, maybe students described some of the concepts they learned, some of the technology they mastered, and some changes in attitude or identity. You could then code each response to see if it mentioned one or more of these outcomes. If your goal was to increase content knowledge, then you might only code comments about knowledge but you might have five concepts you are looking for. In this case, each response could be coded for how many of these concepts it contained. And if you have more data than you can code, you can "sample" by taking a subset of responses. Sometimes it will be a random set and other times a random choice within categories. For example you could group your class by grade and take three blogs from each of the grade grousings
    • Media Data: If you took pictures you can study the pictures for evidence. For example if you took pictures of your class every 10 minutes during a project or have a video that you can stop at regular intervals, you could count how many students look like they are fully engage in teamwork and how many appear to be off task. With an audio of a meeting, you could focus only on questions-- who asks questions, how often and what type of question.

C. Display your Data to Tell Your Story:casestudies-forpalgrave.jpg

Once you have counted your data you will be ready to create charts, tables, graphs or other ways to help your audience see at a glance what you had to spend hours finding. Whatever tool you have used, share it with someone who does not know what you have done and ask them what they see. This is the communication test, does it convey what you intended.

Action Research Report Development

Your should be ready to write a draft of your first cycle report. All that you will be missing in the reflection and we will discuss that in the next tutorial.
See template 8D for writing your cycle report


  • CYCLE RESEARCH QUESTION: This question needs to contain two very important parts. The first part clearly states what you did. And the second part shares your best guess at the outcome(s) you anticipate. Your action research is a design experiment. You are designing with a eye towards a deeper understanding of the consequences of actions.

  • ACTION TAKEN: Describe what you did in enough detail that we understand the action that was taken.

  • EVIDENCE USED TO EVALUATE THE ACTION: Describe the data that you collected to give you direct or indirect evidence of what happened.

  • EVALUATION: Share the summary of the data analysis process from these activities

  • REFLECTION: (to be added after the cycle is complete) see next tutorial


working groups.jpgYour learning circles or critical friend discussions are very important. Talk is the central vehicle for sharing, analyzing and evaluating actions that define your practice. It is how we learn. Hopefully you are working with a group of people engaged in action research either through a university or a more informal learning circle (see Here are some ideas to support these discussions:

  • 1) Revisit the description of your practiceand logic model--provide an overview of what you are doing and why. This will be helpful as you develop your action research portfolio
  • 2) Attention to evidence--Bring your data and analysis plan to the forum and look carefully at the plans that others bring. Concentrate on developing alternative interpretations and other possibilities. We are often blinded by what we think. We depend on each others to see without the blinders. That is one of the fundamental reasons for learning circles, to share alternate way of thinking. Do NOT be afraid to challenge data as this will help action researchers to see past what they think.

In a discussion, what builds knowledge... Here are some ideas of how you can participate in discussions in way that build knowledge together:

1) Affirmations --

  • Help others see their strengths
  • Compliments are more effective with you can be specific about what make something good.

3) Extensions--

  • Look for underlying causes or draw connections between behavior on one setting and another.
  • Share a relevant story from your practice and making the conceptual link back to the their situation.
  • Summarize a discussion pulling what others have said and synthesizing into a few clear positions and then extending the discussion.
  • Find more evidence to support their ideas or practice.
  • Represent the information in the way that helps see the connections

4) Constructive Criticism --

  • Suggest design improvement in the action research or different methods that they might try.
  • Challenge a position or assumption with the goal of helping the person be more reflective on different perspectives.
  • Find and share information that challenge there ideas or practice.
  • Represent the information in a way that helps one see different connections.

Ask yourself what you are doing before, during and after writing a comment. Be aware of your development of your skill to build knowledge collaboratively through dialogue.

T8 Resources or RETURN TO Tutorial 8

Continue forward to Tutorial 9

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