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May 02, 2023

Watch the video, engaging in analytic coding and iterative analysis, which you will draw on to complete part two and the discussion board for this activity.

 

Directions for Part 2:

Part 2: After completing your coding and analysis, prepare a written response to the following 3 prompts (250 words)

What is one theme you noticed in this video? How could you test this?
Why is it important to go beyond initial observations?
How can you apply analytic coding and iterative analysis into your research design for your own Capstone?
This activity will take at least an hour. Please allow adequate time to complete. You may complete this activity as many times as you would like, and can revisit it later in the term.

Activity Wrap Up and Final Thoughts…

Now that we have some refined claims, we can consider if there are other ways to test them. Just like we might return to the scene to observe people during a particular time of the day, we could also use the codes we’ve come up with to guide other data. Specifically, we could build an interview questionnaire or a survey with people in the park later.
Note that our new research claims guide our survey questions. If we had developed this research questionnaire up-front, we might have asked different questions than we might ask now. If we had stopped at our initial observations, we may have recommended something else — replacing the playground equipment, or worse, telling the city that the park is not appreciated and could be better utilized for another purpose. But our curiosity and research skills helped us fully understand and examine the issues, which helps us inform our suggestions. And we used multiple types of data and iterations of analysis to reach a conclusion.
It seems safety is an important issue for the community. So, let’s go back to our original task and revisit the research process:
Should the city keep the park?
Show the claims and supporting evidence (data) that the park is frequently used (including the codes trash, events, frequency/walking path)
We can conclude, yes
What is the most important investment the park should make?
There are various options here, but based on the data we focused on collecting in this scenario, and the results, show the claims and supporting evidence for “safety.”
In the end, it would be reasonable to conclude that the city should add an additional walking path away from the road, so that pedestrians can pass through the park away from traffic. It would also be reasonable to conclude that the path should relocate the trash cans. And perhaps more of them should be added.
Note that our original proposed claim that we need more frequent trash pick-up could still be valid. And that if we wanted to directly test that claim, we could have measured or assessed that by gathering different data (i.e., getting the waste management pick-up schedule from the city).
Conclusion: In the end, the same data can point us to different conclusions. We have to engage in a process of deductive and abductive claims-making, and finding supporting and alternative evidence. We should consider the data in context and frequently ask questions about our data, especially asking what the data mean when we’re analyzing it. Now when you submit your report and recommendation to the city, you can show them the research process, data, and analytic decisions you made along the way.

Discussion

Share your claims and observations/field notes with your peers. What did you count as observable data?
Reflect on how priming forced you to focus on certain points of evidence, and made you de-prioritize others.
Provide feedback to your classmates about the claims and evidence they used. Consider what conclusions (claims) could be drawn based on your evidence, and what additional research or data are needed to make those interpretations.

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