# data[].attributes.body
The categories helped to really dig into the data and understand how students understood different TEKS. I can use this in my classroom to know how I need to conduct a reteach to be the most effective for intervention.

# data[].attributes.body
To help teachers make sense of their data when planning a reteach.

# data[].attributes.body
We can add this to our DDI process during our PLCs with our teachers/teams. Along with having them create an action plan for reteach/enrichment.

# data[].attributes.body
I think it is an awesome system. I like how you can dissect data to give intervention ideas in the classroom. I think it is a great tool for guiding instruction, small group and individual interventions.

# data[].attributes.body
I can take this back to my team and coach them through this deeper dive on data analysis. I really like how it breaks it down specific on how to intervene for TEK.

# data[].attributes.body
I like how it gave us a deeper understanding of how kids are answering questions and how we can better help them.

# data[].attributes.headline
I will use this for planning targeted stations for more practice. See who I need to pull to small group for more intense review/reteach. 

# data[].attributes.subject
I will use this for planning targeted stations for more practice. See who I need to pull to small group for more intense review/reteach. 

# data[].attributes.body
Applying categories will differentiate my reteach strategies to be intentional.

# data[].attributes.body
I love this! I can use it to help my teachers pin point areas of strength and weaknesses. Then guide them to appropriate interventions.

# data[].attributes.body
Identifying Teks, Station organization, planning meaningful and internalize

# data[].attributes.body
The process helps teachers be strategic with their instruction. This allows them to continue moving forward, while still addressing the students’ needs.

# data[].attributes.body
My team can use this to pinpoint deeper misconceptions in our data. We already look at the lowest performing tek, but this takes the focus off of one question, and shifts the focus to all questions.

# data[].attributes.body
This is definitely what needs to take place for growth!! We must take ownership on what we are doing great and what we need growth in!

# data[].attributes.body
I will use this information to look at the data from my SCA’s. I will then use the appropriate reteach method based on the category.

# data[].attributes.body
This will help in PLC to target specific TEKS and see what intervention is needed for the specific categories.

# data[].attributes.body
I love that it allows us to differentiate based on how you see data in the 3 categories. This also answers the question of shape ongoing instruction through formative not just assume summative.

# data[].attributes.headline
Dedicating time to go through data and analyze it. We just need time. 

# data[].attributes.subject
Dedicating time to go through data and analyze it. We just need time. 

# data[].attributes.body
Challenges: Teacher buy-in and ownership of data, lack of understanding/capacity

Opportunities: Great opportunity to guide our teachers through DDI/PLC process,with step by step instructions, meaningful to our data

# data[].attributes.body
Data analysis knowledge, what to do with the data

# data[].attributes.body
Challenges: Getting teachers to be comfortable sharing and talking about their data.

Opportunities: Being able to share ideas, if a teacher was successful with a TEK but you weren’t, what did they do differently? What can you change when you reteach the topic?

# data[].attributes.body
Challenge: teacher buy in, most common thing we hear is “what’s the point?”

Opportunities: we are only really starting now so it’s really a blank slate and we can tailor it to our needs as a campus

# data[].attributes.body
Our school is a data driven school, but new teachers will need to be taught how we approach and look at data. I like using the 3 categories to separate data and dig deeper.

# data[].attributes.body
Most of our teachers want this and ask for it, but we struggle with time. I think if we could come up with a larger PLC block, our teachers would be very receptive.

# data[].attributes.body
Apathy is a challenge. Some teachers have not been successful and do not see success on the horizon. This applies to students as well.

# data[].attributes.body
Some challenges that we may face is just getting teachers on board who are actually doing the deep dive into their data. Being able to group into different categories to get deeper knowledge on how to help and intervene

# data[].attributes.body
Teachers not understanding why data is important and they don’t want to “add more to their plate” so they simply don’t do it.

# data[].attributes.body
Challenges: unwilling teachers, time,

Opportunities: stepping up from simply looking at data to organizing data in a way that we can be very specific

# data[].attributes.body
The push back from staff and making sure that teachers are getting it done

# data[].attributes.body
Some of the challenges and opportunities for building a data culture in our school are

Teachers are unfamiliar with data and how to analyze it.

# data[].attributes.body
I think if students realize the importance of data and how it can help them learn them they will be more susceptible to improving their own learning. Showing students their data, what it means for them, and how they can improve their learning will motivate them more