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Assessment and Data 
Phase 1
 

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"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 sometimes share formative and summative assessment data with individual students.
  • On lesson plans, only the curriculum guide is used to inform instructional decision-making. 
  • When giving instructions, introducing activities, facilitating small groups, etc., the teacher provides a general rationale to the whole class. 
  • Students articulate a rationale for their current task that is related to the classroom learning objective.
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 and curriculum guide 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 the course?
  • What evidence do you see that teachers are setting high expectations and goals for each individual student?
  • Can students articulate where they are in the learning pathway for the course?
  • What type(s) of data is included on data walls, learner profiles, or digital portfolios? 
  • 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
  • Instead of Paying Thousands for Student Data Systems, Try This Free Option Instead from EdSurge, by Chris Aviles, outlines a great way of using Google Forms for creating a Student Tracker System for essays.
  • This resource from Data Quality Review takes you through data use during one school year.
  • 6 ways to promote data-driven instruction from GettingSmart, written by Jason Lange, explains the importance of data use in education and gives tips to do it well.
Data Driven Instruction, Coaching Tool
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Data Driven Instruction, Coaching Tool
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  • Home
  • About
    • Personalized Learning
    • Meet the Team
    • In the News
    • Impact Report
    • Sharing the Work
    • Blog
    • Flip the Switch
    • Resources for Families >
      • Personalized Learning for Families
      • Hybrid Learning for Families
  • The Rubric
    • Assessment and Data >
      • Data Driven Instruction
      • Student Feedback
      • Authentic Assessment
      • Choice in Assessment
    • Instructional Rigor >
      • Varied Learning Experiences
      • Differentiated Learning Objectives
      • Personalized Learning Pathways
      • Mastery Based Progression
    • Student Agency >
      • Rapport with Students
      • Self- Direction
      • Opportunities for Input
      • Advocacy Beyond Self
    • Classroom Culture >
      • Routines and Procedures
      • Peer Accountability
      • Growth Mindset
      • Sense of Purpose
    • Equity >
      • Self- Awareness
      • Diversity in Design
      • Collaborative Grouping
      • Access to Materials
    • Phases of PL
  • Readiness Continuum
    • 1 The PL Classroom
    • 2 Curriculum + Assessment
    • 3 Data Driven Instruction
    • 4 Social Emotional Learning
    • 5 The PL Graduate
    • 6 Principal/Leader
    • 7 Collaborative Design
    • 8 PL Campus Team
    • 9 Vision + Priorities
    • 10 Personalized PD + Supports
    • 11 Culture of Innovation
    • 12 Sustainability + Access
  • Progressions
    • Lab Rotation
    • Station Rotation
    • Individual Rotation
    • Flex Model
    • Flipped Classroom
    • Enriched Virtual
    • Distance Learning >
      • DLP | Establish a Learning Management System (LMS)
      • DLP | Engagement in Guided Learning
      • DLP | Engagement in Independent Learning
      • DLP | Feedback for Learning
    • Glossary
  • Fellowships
    • Innovation Showcase
    • Innovation in Teaching Fellowship
    • School Retool
    • iDesign Central
  • At-Home Learning Webinars
  • Opportunities
    • Educator Tours
    • Winter Design Excursion Exhibition
    • Self-Paced Google Certification Courses
    • Google Certification
    • University Partnerships- Texas Tech
    • Edcamp
    • PL Homecoming 2022
  • The Lighthouse