Benchmark data review protocol

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DATA WALLS Click here

Student Learning Objectives page
Click HERE

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Protocols are methods of pulling data from various sources in order to make sense of it. Below you will find sample Data Protocols that we've developed or that have been shared with us within our district.

Principles of Data Use and Safety Regs

data_principles_safety_regs.pdf
File Size: 118 kb
File Type: pdf

Root Cause Analysis Primer

csi_root_cause_analysis_v2.0.pdf
File Size: 3788 kb
File Type: pdf

DATA PROTOCOLS . . . from A - Z

National School Reform Faculty downloadable protocols. Great Resource!
Click HERE

Abbreviated Protocols Guide

Click HERE

5 Why 's Protocol: Root Cause

Data observation & at risk lists

data_observations__at_risk_lists_v2.docx
File Size: 15 kb
File Type: docx

data analysis protocol

benchmark_analysis_questions_for_teachers.doc
File Size: 59 kb
File Type: doc

Guiding Questions Common Assessment Data

guiding_questions_for_analyzing_common_assessment_data.docx
File Size: 27 kb
File Type: docx

Looking Back Instructional Planning

looking_back_instructional_planning_protocol_school_level.docx
File Size: 58 kb
File Type: docx

Local Assessment Analysis ELA-Math

local_assessment_analysis_-_data_analysis.docx
File Size: 27 kb
File Type: docx

Creating Student Learning Objectives

creating_student_learning_objectives.docx
File Size: 35 kb
File Type: docx

ATLAS PROTOCOL

atlas_looking_data_0.pdf
File Size: 69 kb
File Type: pdf

Data TEAM TOOLKIT

district_data_team_toolkit.pdf
File Size: 5282 kb
File Type: pdf

MUST SEE VIDEO from Dr. Elizabeth City of the Harvard Graduate School of Education, as she talks about the  use of data protocols  to analyze data.

Effective Use of Data Assumptions
. from Nancy Love's book Data Coaches Guide to Improving Learning for All Students

Download article HERE

ASSUMPTION 1: Making significant progress in improving student learning and closing achievement gaps is a moral responsibility and a real possibility in a relatively short amount of time—two to five years. It is not children’s poverty or race or ethnic background that stands in the way of achievement; it is school practices and policies and the beliefs that underlie them that pose the biggest obstacles.

ASSUMPTION 2: Data have no meaning. Meaning is imposed through interpretation. Frames of reference—the way we see the world—influence the meaning we derive from data. Effective data users become aware of and critically examine their frames of reference and assumptions. Conversely, data themselves can also be catalysts for questioning assumptions and changing practices based on new ways of thinking.

ASSUMPTION 3: Collaborative inquiry—a process where teachers construct their understanding of student-learning problems and invent and test out solutions together through rigorous and frequent use of data and reflective dialogue--unleashes the resourcefulness and creativity to continuously improve instruction and student learning.

ASSUMPTION 4: A school culture characterized by collective responsibility for student learning, commitment to equity, and trust is the foundation for collaborative inquiry. In the absence of such a culture, schools may be unable to respond effectively to the data they have.

ASSUMPTION 5: Using data itself does not improve teaching. Improved teaching comes about when teachers implement sound teaching practices grounded in cultural proficiency—understanding of and respect for their students’ cultures—and a thorough understanding of the subject matter and how to teach it, including understanding student thinking and ways of making content accessible to all students.

ASSUMPTION 6: Every member of a collaborative school community can act as a leader, dramatically impacting the quality of relationships, the school culture, and student learning.