# data[].attributes.body
Data Wise is the district adopted continuous improvement cycle.

# data[].attributes.headline
Describe this district priority and or upload materials 

# data[].attributes.subject
Describe this district priority and or upload materials 

# data[].attributes.body
Example: these are formal evaluations conducted by admin for teachers annually

# data[].attributes.body
The district increased instructional coaches in literacy, humanities, mathematics, and english learners.

# data[].attributes.body
Professional learning platform that administrators are expected to use with staff to develop competency in the teacher actions of the Instructional Vision

# data[].attributes.body
Teachers are evaluated using the CCT.

# data[].attributes.body
The Learning Walk process lives outside of Teacher Evaluation. Learning Walk evidence cannot/should not be used in a teacher's evaluation (formal/informal/ROP).

This doesn't feel right if teacher evaluation is in service of professional learning (per TEVAL document), but how do we blend these?

If intention behind Learning Walks is to grow and work towards school improvement process, then evaluation of teachers...

# data[].attributes.body
Make a recommendation on if this priority is discrete or connected to the Instructional Vision Learning Walks

Discrete- separate in purpose and no need to create as much cohesion or alignment. Something might be discrete for year 1 because we don't have the time or control to make changes right now

Connected - It is important and/or can be connected to create cohesion with Instructional Vision Learning Walks

# data[].attributes.body
Elements of the Data Wise process would likely be beneficial to informing how to utilize the data to improve instruction, but unlikely that a full Data Wise swoosh would be achieved between each learning walk cycle.

# data[].attributes.body
The dashboard says teachers that are in need of support. This is a data point for coaching cycles. Coaches completing informal learning walks (Collective Goal Scores- Math) in between Learning Walks are in service of improving Learning Walk outcomes on the next Learning Walk and monitoring progress.

# data[].attributes.body
Building leaders will utilize the LW dashboard to make choices about how best to differentiate professional learning based on school needs. They will have LINCspring resources available to them to support differentiated PL for all staff.

# data[].attributes.body
Discrete, but what is more important to support a teacher with particularly during a Performance Improvement Plan?

# data[].attributes.body
Connected to larger picture around Learning Walks and Professional Learning. The days designated for Data Review are similar to Steps 1-3 of the Continuous Improvement Cycle. Steps 4-6 are aligned with the aspects of Looking at Instruction and identifying a Learner Centered Problem. The School-based PL that follows the Learning Walk is aligned to the Act segment of the Data Wise process.

# data[].attributes.body
Professional development training related to phonics.

# data[].attributes.body
LETRS professional learning should be reflected in early literacy learning walks

# data[].attributes.body
Expectation to utilize district curriculum remains.

# data[].attributes.body
We're observing implementation of the curriculum and making decisions about how its being implemented. This can't fall off as a priority.

# data[].attributes.headline
Direct connection: Look-fors --> Curriculum Enactment --> student achievement

# data[].attributes.subject
Direct connection: Look-fors --> Curriculum Enactment --> student achievement

# data[].attributes.body
Will there be time to look at student achievement outcomes or just instructional practices? Are we prioritizing the latter this year?

# data[].attributes.body
Will this coincide with learning walks? Who will own this work?

# data[].attributes.body
School-based Data Review Days occur six times per year and are led, at least in part, by building leaders. The purpose of these days is to review multiple sources of data, included, but not limited to, learning walks, student achievement, discipline, attendance, etc.

# data[].attributes.body
in the process of having admin team reviewing data

# data[].attributes.body
Data Wise is connected to the Instructional Vision Learning Walks as the nexus of student achievement data and instructional practice. The Data Wise process allows you to examine student achievement data to set priorities for instructional improvement that is then monitored/reviewed through learning walks.

# data[].attributes.body
The Portrait of a Graduate competencies are directly aligned to each of the teacher actions in the Instructional Vision. While we expect to see teacher actions in the Instructional Vision lead to student actions that support students developing proficiency in the PoG, the requisite assessment tools of the PoG have not yet been developed, nor is the curriculum in Pre-K to 12 directly aligned to the PoG. As a result, there will be no connection in year 1 of implementation of the Instructional Vision Learning Walks.

# data[].attributes.body
The Instructional Vision Learning Walks are connected to LINCspring because building leaders will utilize the LW dashboard to make choices about how best to differentiate professional learning based on school needs. Building leaders and leadership teams will have LINCspring resources available to them to support differentiated PL for all staff.

# data[].attributes.body
The process of the the ILP 1. Understand what to look for and how to look for it, 2. observe, 3. debrief and norm on evidence, 4. write evaluation/prepare for observation debrief, can be done with Both/either the Instructional Vision/Look Fors or the CCT. For the purpose of supporting with evaluations of teachers, both documents should be used during ILP. ?

The initial aspect of the ILP where principals norm on excellence and then observe using "Look Fors" is connected. Collecting evidence could be aligned to "Look Fors." But after the observation when principals norm on score and how to effectively write up the evaluation and provide oral feedback (evaluation debrief) would be discrete (because aligned with CCT/TEVAL versus Instructional Vision/Learning Walks).
[Claim- CCT Language, Connect- from Look Fors, Action- from Look Fors as they connect to CCT]

This needs further discussion with the Office of School Leadership as ILPs and TEVAL mostly fall under OSL.

# data[].attributes.body
LETRS training is not connected to the Instructional Vision Learning Walks. LETRS training follows a discrete scope and sequence of professional learning.

# data[].attributes.body
School-Based Data Review Days are connected to the Instructional Vision Learning Walks because these days represent the dedicated time when administrators will share with their staff the LW data reflected in the dashboard. Staff will review and analyze the data to determine professional learning needs at the school level.

# data[].attributes.body
Learning Walk data will be utilized by instructional coaches to inform coaching cycles. The data captured in the dashboard of teacher practice is one data point; instructional coaches' informal observations of teacher practice will also inform the coaching cycle. For coaches who have been consistently working with a teacher, it is unlikely that what is captured on the learning walk as it relates to that teacher's practice will be new information to the coach.