# data[].attributes.body
I feel like we can't know this unless we ask. It is important that we use surveys and feedback to get a true picture of what the learning experience is like from the student perspective. If we don't directly ask them, or their families, then the best we are doing is guessing according to our experiences, not theirs.

# data[].attributes.body
Data can be used to build relationships with students and families by accurately showing us where students are in different skill development and constructing transparent and realistic plans to support their progress forward. 

# data[].attributes.headline
In what ways could a system of distributive leadership be useful in the inquiry cycle?

# data[].attributes.subject
In what ways could a system of distributive leadership be useful in the inquiry cycle?

# data[].attributes.body
I think that when more people have the opportunity to look at the data and help develop the questions, more will buy in to the planned responses.

# data[].attributes.body
When data is used meaningfully and correctly, it can show us where we are lacking in equity for students, and sometimes inform the steps we should take to get there. As we begin taking those steps, data can tell us if we are being successful or if we need to rethink our approach.

# data[].attributes.headline
How often are data used to sort and label children?

# data[].attributes.subject
How often are data used to sort and label children?

# data[].attributes.body
A top-down approach has the potential to miss important nuances that would only be seen through experience (i.e. through classroom teacher's eyes or through lens of sp. ed. Distributive leadership increases depth of understanding of assessments, their uses, and strength of plan construction.

# data[].attributes.headline
Data are used to sort and label children in reading and math, special education, in classroom groupings, in tracking, and in college application

# data[].attributes.subject
Data are used to sort and label children in reading and math, special education, in classroom groupings, in tracking, and in college application

# data[].attributes.body
It would allow for multiple stakeholders, and staff with various experiences to come to the table, analyze what is being analyzed, and bring different ideas/thoughts/etc. to the process

# data[].attributes.headline
MCAS could be used to look at trends across years in a subject by grade(s). Looking at the standards report is helpful for this. 

# data[].attributes.subject
MCAS could be used to look at trends across years in a subject by grade(s). Looking at the standards report is helpful for this. 

# data[].attributes.body
How can data be used with an asset-based lens (not deficit)?

# data[].attributes.body
It seems when we discuss data the focus is on areas where there is evidence of deficit. Students are then potentially placed in classes (tracked) and/or in intervention classes based on this data. We could, however, begin with building on areas of strength. This could ultimately change how a student perceives school and feel better about focusing on where they are doin well. Then we can bridge off the strengths and work on the deficits. No one wants to spend all there time being told they are failing somewhere and then being forced to work on this area for hours on end.

***Students at my school who are in support and intervention classes miss out on music, art, and/or language.

# data[].attributes.headline
When students are grouped by "ability" the data has informed the administrative/teacher decisions, but may only represent limited perspectives in student learning and "ability." Using data to sort and label children contributes to an equity gap and rather than help it, can sometimes perpetuate it. 

# data[].attributes.subject
When students are grouped by "ability" the data has informed the administrative/teacher decisions, but may only represent limited perspectives in student learning and "ability." Using data to sort and label children contributes to an equity gap and rather than help it, can sometimes perpetuate it. 

# data[].attributes.body
Data Wise, p. 90: "'Learner-centered problem' means that the problem is about learning, not that the learners are the problem."  We should be using the data to assess our teaching and whether all students are able to achieve, and identify adjustments we can make so that all can access.

# data[].attributes.body
It can allow for us to look at what kids are good at, where their strengths are, and how we can leverage those strengths to increase their skills elsewhere.

# data[].attributes.body
We frequently use data to sort children into specific small groups, to allow for teachers to determine if they need to adjust their lessons, etc. We don't track our classes in a typical year, which does make special education service provision tricky, but still doable. We try to steer away from using that data to label children. So, when referring to a child with an IEP, and their IEP, we might say, "student with an IEP", or "Has an IEP" instead of "special education student."

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I am a believer in heterogenous grouping. Some schools have this in name and not in actual practice. Student placement in either high or low level courses has the danger of boxing a child in to a fixed mindset

# data[].attributes.subject
I am a believer in heterogenous grouping. Some schools have this in name and not in actual practice. Student placement in either high or low level courses has the danger of boxing a child in to a fixed mindset

# data[].attributes.body
We need to group students based on data so that we can respond to their specific learning needs - but also to form heterogenous groups where students have the opportunity to demonstrate strengths by helping others, as well as benefit from support in their growth areas.

# data[].attributes.headline
Sorting students with data for intervention is good, but only if the program is applied with the intended outcome being supporting students for success in the regular classroom and continuous mixed grouping

# data[].attributes.subject
Sorting students with data for intervention is good, but only if the program is applied with the intended outcome being supporting students for success in the regular classroom and continuous mixed grouping

# data[].attributes.body
Attendance and participation can give insight on home life. If a student or family are struggling, student may be withdrawn during class time, may often be absent. We can use this data to investigate needs for social-emotional support or community resources.

# data[].attributes.body
We can use MCAS to compare across multiple years and evaluate our program. We have to get into item analysis though, because sometimes MCAS might lead us to make a broad determination based on just a few items.

# data[].attributes.body
If we look at data broadly, we can consider all that we know about our students and their families. It's not just achievement data.

# data[].attributes.body
Schools need to be open to listening, and considering perspectives and sources of information that we may not have considered. There should be structures in place for families/caregivers to give feedback, and the school should seek criticisms and NOT get defensive. Criticism doesn't mean we aren't trying really hard.

# data[].attributes.body
Data are used to sort and label children in reading and math, special education, in classroom groupings, in tracking, and in college application

# data[].attributes.body
Students will be more willing/able to participate when their needs are met, and when school activities are appropriately challenging, meaningful, and interesting.

If we are doing interesting and exciting things, kids will be "with us."

# data[].attributes.body
We can see if all students are able to access curriculum and learn. We should analyze gaps and differences in performance of groups of students to make sure that there are appropriate supports and opportunities for all students, and that bias is not impacting access to learning.