Assessment and Data 
Phase 1 

"Look-Fors" During Observation
Remember: The most helpful part of the observation is not checking off items, but the conversations and reflections that happen after the visit.  

Beginning/ Developing

• Learner Profile includes previous years' performance on state assessments and may include limited information from other academic sources. There is no evidence that non-academic data sources are being used to inform instruction e.g. interest surveys, career/aspirational surveys, etc.
• ​Teachers may not consistently share formative and summative assessment data with individual students.
• On lesson plans, there is no evidence of data to inform instructional decision-making.
• When giving instructions, introducing activities, facilitating small groups, etc., the teacher does not provide a rationale for her decision using data.
• Students are not able to articulate a rationale for their current task that is grounded in data. E.g., "I'm working on this because my teacher told me."

Practicing/ Achieving

• Learner Profile includes multiple sources of data, such as diagnostic assessments, NWEA's MAP, state assessments, adaptive software/digital content reports, career/aspirational surveys, personality tests, parent surveys, learning style inventories, etc.
• Data sources are regularly and consistently refreshed/updated to reflect the latest information about a student.
• Students have access to individual formative and summative assessment data.
• On lesson plans, teachers tag the instructional decision with the source of data that informed that decision (e.g., small group lessons).
• When giving instructions, introducing activities, facilitating small groups, etc., the teacher provides a rationale for her decision using evidence from data. E.g., (to a small group) "Based on yesterday's successful exit ticket on the circulatory system in your independent station, and your group's interest in reptiles, we're going to compare what you know about the human circulatory system to the circulatory system of snakes."
• Students are able to articulate a rationale grounded in data for why they are working on their current task.
• In PLCs, teachers regularly analyze academic and non-academic data together to make decisions on how to best support all students.

Questions to Guide Observation 

• What systems are in place to share data with students?
• ​How do students track progress towards mastery or goals?
• Can students articulate goals related to course?
• Are teachers setting high expectations and goals for each individual student?
• Can students articulate where they are in the learning pathway for course?
• What type(s) of data is included on data walls?
• Is data current?
• Are students using data to help guide their decision-making process (i.e., how they spend time in class, what playlists they complete, assignments, etc.)
• How are teachers using data to inform their instructional decisions?
• What supports do teachers have for reviewing and responding to data from the broader instructional staff?

Resources

• Click here for a great way of using Google Forms for creating a Student Tracker System for essays
• 33 Digital Tools for Advancing Formative Assessment in the Classroom  examples of various digital tools for formative assessments (Article from NWEA)
• How Data Drives Personalized Instruction in My Class  reviews balance of online learning programs, differentiate practice, and pulling targeted small groups (Teacher Blog from Rocketship)
• Ms. Bullen’s Data Rich Year : This infographic takes you through data use during one school year.
• 6 ways to promote data-driven instruction : This short blog explains the importance of data use in education and gives tips to do it well.
• The who, what, and why of using data with students : This table talks about the elements of using data with students, the roles of teacher and student, and the rationale for why.

Data Driven Instruction, Coaching Tool
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Data Driven Instruction, Coaching Tool
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