This document discusses using a data-centered approach to classroom instruction. It involves determining priority standards based on assessment data, creating learning targets for those standards, setting goals for student proficiency, and using formative assessments to monitor progress toward goals and determine if re-teaching is needed. The process includes identifying priority standards, establishing learning targets, setting measurable goals, determining appropriate formative assessments, facilitating instruction and assessment, analyzing assessment data, and planning re-teaching or enrichment as needed based on that analysis.

1. Data Centered Classroom
Pasadena ISD
Cecilia Saldana
Reading Peer Facilitator
Williams Elementary
cesaldana@pasadenaisd.org

2. Data Centered Classroom
• How do we determine a “starting point” for our a
learner-centered classroom?

3. Data Centered Classroom
• Starting Point: Here’s What! Data
o How can data help us prioritize standards on
which to focus our learner-centered efforts?
 What data could be used to determine “hot
spots”/prioritized standards for your campus?
 Let’s examine our 2015 STAAR Item Analysis.
 What student expectations (SEs) in the
current/upcoming grading period were “hot spots”
for your campus/should be prioritized standards?

4. Data Centered Classroom
• How do we determine the instruction that
targets these prioritized standards?

5. Data Centered Classroom
• Next Step: So What? Learning Targets
o Riding a bike … all you need to do is get on the
bike and pedal – right?
o To be able to ride a bike, what do you need to
know and be able to do?
o Create a list of “I can” statements that describe
what one must be able to do in order to ride a
bike.
o Debrief “I can” statements.

6. Data Centered Classroom
• Learning Targets for Prioritized Standards
o What learning targets are necessary for students
to be successful with the prioritized standard(s)?
o Regroup by Content Area.
o Collaborate to record “I can” statements that
represent what students need to be able to know
and do in order to be successful with the
prioritized standard.
o Debrief “I can” statements with Content
Colleagues.

7. Data Centered Classroom
• How do we facilitate instruction in a timely
manner?

8. Data Centered Classroom
• Next Step: Now What? Establish Goals
o Record a possible SMART goal that could be used
to focus the coaching conversations in the current
grading period.
Possible SMART Goal Structure:
The percentage of students scoring proficient
and higher on (standard) will increase from (# %)
on (date) to (# %) by (date) as measured by
(name of assessment) administered on (date).

9. Data Centered Classroom
• How do we determine if students are making
progress with the learning targets/progressing
toward the goal?

10. Data Centered Classroom
• Next Step: Now What? Evidence of Understanding
o What formative assessment strategies could be
used to collect evidence student understanding?
o Record possible formative assessment strategies that
could be used to collect evidence of student
understanding.
(Possible Resource: PISD The Big 8)

11. Data Centered Classroom
• Let’s Regroup
Identify Priority
Standards
Identify Learning
Targets
Set (SMART) Goals Determine Data:
Formative
Assessment

12. Data Centered Classroom
The 4 Critical Questions
• What is it that we expect our
students to learn?
 How will we know they have
learned it?
 How will we respond when some
students do not learn?
 How will we respond when some
students already know it?
Facilitate
Instruction
and Monitor
with Formative
Assessments
Administer
Common
Assessments
Across Teams
Analyze Data
from Common
Assessments
and Plan for
Re-teaching
and
Enrichment
Develop
Assessments
for Targeted
SEs and
Collaborate to
Plan
Instruction
TEKS

13. Data Centered Classroom
• Next Steps:
• Apply Data Analysis in the Classroom
 Record the Learning Targets for 2-3 additional
Priority Standards in the current grading period
using data from Aware
 Determine possible formative assessment strategies
that could be used to (pre) assess students’
understanding of the Learning Targets based on
data from Aware