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-Move slow to go fast.  Consider all stakeholders.
-10,10,10 - how will you feel about the decision in 10 hours, 10 days, and 10 years....this one always helps me to think through big decisions and the lasting impact.

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While we can choose alternate frameworks for the dissertation, the Wagner 4 Cs does seem to encompass the most critical components for change. I will continue to use that in my disseration.

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Make the choices people make within an organization easy and accessible instead of being left up to chance.

Provide next steps= choices when possible to keep people on the correct direction. We know people make thinking fast decisions. Make the correct/recommended decisions accessible.

When making decisions as a leader slow down and consider what is informing and not informing your decisions.

Be aware of the thinking fast decision making system.

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-Being open to alternate ideas/solutions important when making decisions.

-Embedding time for reflection before decisions are made.

-Position decisions by sharing the why and putting a purpose behind it.

How might you nudge without a feeling of manipulated?

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Balancing thinking slow when time is limited and a fast decision needs to come quick.

Nudge people in small ways so they hear it often

When time is available the importance of stepping back and look more globally to ask the question/problem at the core

Scheduling time (dead time) to think about certain issues and look for alternatives.

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Under Wagner's 4Cs, Chatgt said connection, communication, culture, and collaboration when in reality, Wagner's 4Cs are context, conditions, culture, and competencies.

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Error is Wagner's 4Cs are listed incorrectly.

We are all using Wagner and are continuing to build on our drafts.

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-Wagner Framework has the ChatGPT error - Collaboration instead of Competencies.

-Some frameworks seem to not have the emotional impact of change embedded.

-As a leader, what is the guiding principle in choosing a framework.?

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As we are writing our chapter 4 we will be reviewing the frameworks suggested to see which applies best to our topic.

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Participants can interpret questions very differently, which can in turn give us results that can vary from what we were anticipating.

Less is more. It's about quality analysis & writing versus quantity.

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We would like to know when we will learn about board relations and policy as well as finance. We know there are some classes coming up, but those are the two areas of the program we feel very uninformed on. If we were to be dropped into a superintendent role, we would need that content to do the job. 

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We would like to know when we will learn about board relations and policy as well as finance. We know there are some classes coming up, but those are the two areas of the program we feel very uninformed on. If we were to be dropped into a superintendent role, we would need that content to do the job. 

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It is helpful to understand that we should be using the interpretations section to pull together our qualitative and quantitative data. 

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It is helpful to understand that we should be using the interpretations section to pull together our qualitative and quantitative data. 

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As we are reviewing our data, we will continue to analyze for emerging themes across our different data sets. We will make sure these themes are developed in our literature review if they aren't already.

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Take-ways: Not all data needs to be included, It is okay to reflect back on what you wish you would have done differently and comment on that, Learned ChatGPT

Questions: Not so much questions it is just needing to interact with our data

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* Utilizing completed dissertations to give examples of data visuals
* Discussions and examples to show additional data analysis tips
*Continuously looking back on data and analysis throughout the writing process

**At this time and at this point in the process - still wondering about weaving all the data together to tell our story - How do we weave in the research question, is this the place to do this?