Presenters: Maria Dorr & Susan Simonds
Quick Write:
From what you know right now, what are the
most important things you would need to launch
a data-driven instructional model in your school?
Data & Data-Driven Decision Making
 Data
 Factual information such as measurement or statistics
that are used as a basis for reasoning, discussion, or
calculation
 Data-Driven Decision Making
 The process of making data informed decisions
Inquiry-Based Data-Driven Decision
Making
 Purpose - to increase student achievement and prepare
learners for college and career readiness
 Utilizing meaningful data to make informed decisions
 Almost all decisions we make on a daily basis are data
driven
Meaningful Data:
 Uncovers needs, priorities and resources
 Builds a school profile to better understand a schools strengths
and weaknesses
 Can develop intrinsic motivation identifying a need for change
 Creates a focused direction for change
 Establishes a baseline against which to monitor progress
 Provides information to design a plan to evaluate programs and
practices
Data Inquiry Basics
 Establishing student achievement outcomes and goals and
accepting responsibility for them as a school
 Identifying important questions that need to be answered
regarding student achievement and goals
 Collecting data to answer the questions that have been
posed regarding student achievement goals
 Conducting purposeful data analysis
 Establish student achievement goals
 Identify important questions
 Collect data to answer the important questions
 Perform purposeful data analysis
 Generate theories about data and utilize these theories to
create a plan of action
Steps for Data Inquiry
 Establish student achievement goals
 Identify important questions
 Collect data to answer the important questions
 Perform purposeful data analysis
 Generate theories about data and utilize these theories to
create a plan of action
 Develop an action plan
Interim ASSESSMENTS
Data ANALYSIS
ACTION planning
In a Data-driven CULTURE
Assessments

Common Interim

At least quarterly

Common across all teachers on the same grade level

Transparent Starting Point

Teachers see interim assessment in advance

The assessment defines the roadmap for teaching

Aligned to

State Tests (format, content, length)

Instructional Sequence (curriculum)

College ready expectations

Reassess

Standards that appear on the 1st assessment appear again on the
subsequent assessments
* Interim Assessment Calendars
 Elementary
 Middle School
 High School
Analysis
 Immediate:
 Assessment results should ideally be within 48 hours, max 1 wk.
turnaround
 Bottom Line: (How well did the students do as a whole?)
 Data Reports should be succinct item analysis, standard level
analysis and bottom-line results
 Teacher- owned:
 Analysis facilitated by effective leadership preparation
 Test-in-hand analysis:
 Between teacher and instructional leader together
 Deep analysis:
 Moves beyond What students got wrong to answer WHY they got it
wrong
Precursors to Effective Analysis
Meetings
 Did the teachers see the assessment in advance? (Transparency)
 Did they mark it up: Confident, Not Sure, No way? (Test-in-hand,
Teacher-owned)
 Did they fill out an analysis sheet? Did they answer the fundamental
questions: Why the student did not learn the material? (TeacherOwned)
 Did they have to fill out an action plan? Did you model how to fill out
an action plan using the analysis questions? (Action Plan,
Accountability)
 Did you model a poor and a good conversation so they hear your
expectations? (Professional development, deep)
 Did you analyze their results (above and beyond them analyzing
their own) in preparation for the meeting? (Leadership)
 Did you collect their analysis ahead of time and see if it looked
acceptable? ( Leadership, accountability)
 Did you have a plan ready to access content experts if the
problems were beyond your expertise? (Professional
development)
Tips for Running Data-Driven
Analysis Meetings
 Let the data do the talking
 Let the teacher do the talking
 Always go back to specific questions around the test
 You’ve got to know the data yourself to lead an analysis meeting
effectively
 Make sure the analysis is connected to a concrete action plan
 Create an instructional plan to meet the needs of whole class needs,
small group needs as well as ideas for how to teach each standard.
ACTION RESULTS MEETING
Running Effective Meetings

(50 min)
IDENTIFY ROLES: Timer, facilitator, recorder (2 min)

IDENTIFY OBJECTIVE to focus on (2 min or given)

WHAT WORKED SO FAR (5 min)
 [Or: What teaching strategies did you try so far]

CHIEF CHALLENGES (5-10 min)

BRAINSTORM proposed solutions (10 min)

REFLECTION: Feasibility of each idea (5 min)

CONSENSUS around best actions (20 min)

PUT IN CALENDAR: When will the tasks happen? When
will the teaching happen? (10 min)
RESULTS MEETING STRUCTURE:
PROTOCOLS FOR BRAINSTORMING/CONSENSUS
Identify key actions from brainstorming that everyone will agree to
implement
•
Make actions as specific as possible within the limited time
•
Identify key student/teacher guides or tasks needed to be done to be ready
to teach—Identify who will do each task
•
Spend remaining time developing concrete elements of lesson plan:
• Do Now’s
• Teacher guides (e.g., what questions to ask the students or how to
structure the activity)
• Student guides
• HW, etc.
NOTE: At least one person (if not two) should be recording
everything electronically to send to the whole group
Ideal Choices for Planning Your Time:
RESULTS MEETING:

FIRST PD SESSION WITH ENTIRE FACULTY:

Design the agenda for the whole-staff meeting introducing the datadriven instructional model you will launch

Assume that the school has done very little in this area, and the
teachers associate “data-driven” instruction with state testing and
test prep

FIRST TEAM MEETING:

Design the agenda for the first meeting with the grade-level team that
you will lead

Assume that the team has done very little in this area, and the
teachers associate “data-driven” instruction with state testing and
test prep

COLLEGE READINESS: For high school administrators, design the steps
you will take to adapt your state assessments to prepare students to
succeed at the college level
 Planning:
Action
 Using data analysis to create a plan of action such as planning new




lessons and developing new strategies
Implementation:
 Implement what you plan (dates, times, standards and strategies)
Ongoing Assessment:
 Collecting ongoing data on the plans effectiveness and analysis of
the data to monitor student understanding and progress between
assessments
Accountability:
 Observe changes in the classroom. Instructional leaders review
lesson and unit plans and give feedback driven by action plan and
student need
Engaged Students:
 Students know the end goal, how they did and what actions they are
taking to improve
*Assessment Analysis Sheet and
Instructional Plan
 Part I
 What are the standards and questions I had expected students to do well on?
 Were my predictions accurate?
 What are my biggest priorities going forward (which standards)?
Look at bombed questions—did students all choose the same wrong
answer? Why or why not?
 Who are the strong and weak students in this assessment?

Part II
Standard Analysis (Whole-Class
Instruction–RA & Writing)
What standards warrant more time for
whole-class instruction and review?
%
Class
Correc
t
 Part III
 8-Week Instructional Plan
Analysis of why students did not
learn specific standards
Instructional Plan
What techniques will you use to address
these standards?
In a Data-driven
Culture
 Highly active and trained leadership team
 Facilitate teacher leader data analysis meetings after each interim
assessment and maintain focus on the process throughout the year
 Introductory professional development
 Introduction to data-driven instruction effectively
 Understand how interim assessments define rigor
 Experience the process of analyzing results and adapting instruction
 Implementation Calendar
 Begin school year with a detailed calendar that includes



Time for assessment creation and adaptation, analysis, and action
Planning meetings
Re-teaching (flexible to adapt to district changes or mandates)
 Ongoing professional development
 Calendar is aligned with data-driven instructional plan
 Modeling assessment analysis and action planning
 Flexible to adapt to student learning needs
 Build by borrowing
 Identify and implement best practices from high achieving teachers
and schools
 Visit schools and classrooms
 Share and disseminate resources and strategies
Quick Write:
• From what you now know, what steps will you take
to launch a data-driven instructional model in your
school?
• What do I want to make sure I remember to do?
• Data-driven instruction & Assessment is quickest, most
effective lever for influencing student achievement
• Mold everything else around that goal Supervision,
Professional Development, Calendar, and Scheduling, etc.
• You Decide.
Thank you for attending
Material in part
Copyright © 2010 by Paul Bambrick-Santoyo:
Interim Assessment Review Checklist
Data-Driven Analysis Meetings: Leading Effective Assessment Analysis Meetings.pdf