Utilizing Data to Facilitate Academic
Growth in Middle School
Presented by: Joseph R. Villarreal – Principal
Resaca Middle School
Los Fresnos, TX
RESACA MIDDLE SCHOOL
DEMOGRAPHICS
 Located in Los Fresnos in the Rio Grande Valley
 Population – 872 students (6-8)
 African American - .3%
 Hispanic – 95%
 White – 5%
 Economically Disadvantaged – 78%
 Advanced Academics – at least 50% of all students are
enrolled in at least one Pre-AP class
 Accelerated Reader is a curriculum requirement
STATE ASSESSMENT DATA
YEAR
MATH
READING
SCIENCE
SS
WRITING
2011
89
92
90
99
97
2010
90
93
95
99
99
2009
91
94
85
98
100
DATA IS EVERYWHERE
 School data is everywhere.
 Lexiles
 Quantiles
 Vertical Scale Scores
 Raw Score
 Schools have enough data to clearly define their strengths and
weaknesses.
 THE CHALLENGE IS NO LONGER GETTING DATA.
DATA IS EVERYWHERE
 The challenge now is using data to improve school and
classroom practices and to raise students’ achievement while
they are in school.
 It is easy to obtain end-of-the-year data, such as state
assessments results; however, schools need to take a proactive
approach in obtaining data throughout the school year.
 This includes data obtained from formative assessments and
classroom practices.
 This data will allow schools to diagnose early and provide
immediate remediation.
Comparison of Traditional and Data-Driven
Decision Making
Decision Making Based on Intuition,
Tradition, or Convenience
Data-Driven Decision Making
Scattered staff development programs
Focused staff development programs as an
improvement strategy to address documented
problems/needs
Budgetary decisions based on prior practice,
priority programs
Budget allocations based on data informed needs
Staff assignments based on interest and
availability
Staff assignments based on skills needed as
indicated by data
Staff meetings that focus on operations and the
dissemination of information
Staff meetings that focus on strategies and issues
raised by school data
Grading system based on each teacher’s criteria
of completed work and participation
Grading systems based on common studentperformance criteria that report progress on the
standards as well as work skills
Periodic administrative team meetings focused
solely on operations
Administrative team meetings that focus on
measured progress toward data-based
improvement goals
DATA IS EVERYWHERE
 Collecting the data should be a planned, purposeful process.
Valuable data will guide the school in developing
improvement goals for the benefit of all students.
 State Assessment Data
 Formative Data
 Instructional Data
STATE ASSESSMENT DATA
STATE ASSESSMENT DATA
 Class rosters are mostly determined by utilizing quantiles and lexiles.
This includes placement in General Ed. and Pre-AP classrooms.
 Reading and Math Enrichment classes are a part of the master schedule. Any
6th, 7th or 8th grade student who does not pass TAKS Reading or Math is
placed in these classes. Collaboration between the Enrichment teachers and
the general education teachers occurs so that the enrichment teachers
emphasize certain skills in the classes. The class size is small to ensure oneon-one instruction .
 Goal-setting occurs with the teachers and within each department
utilizing this data.
 Goal-setting occurs with students utilizing lexiles, quantiles,
benchmark scores and AR.
 With the advent of STAAR, TAKS item analysis data has become crucial
in identifying our weakest areas.
STATE ASSESSMENT DATA
 The disaggregation of data from the beginning of the school
year is a key indicator of instructional support.
 A two year comparison of every student’s TAKS performance
is made and is a reflection of a teacher’s performance.
VERTICAL SCALE SCORE
MATH
MATH
FULL
YEAR
READING READING
FULL
YEAR
GRADE
MET
COMM
GROWTH
MET
COMM
GROWTH
6
637
783
34
644
797
24
7
670
823
33
670
829
26
8
700
850
30
700
850
30
LEXILE DATA
A student’s lexile measure determines his/her reading grade
level and sets forth a goal for the student in the AR program.
LEXILES
Lexiles provide a common, developmental scale for matching reader ability
and text difficulty.
RESEARCH-BASED GOAL SETTING
AR goals are set utilizing research-based data. Students are expected to accumulate a
certain number of points based on their grade and reading level. Students with below
grade reading levels are graded based on reading level improvement, rather than point
accumulation.
TAKS ITEM ANALYSIS
2011 TAKS data was analyzed and weak TAKS objectives were correlated with
STAAR Readiness and Supporting Standards to identify campus weak spots.
Instruction is designed to address these hotspots.
QUANTILES
Quantiles measure both a student’s math ability and the difficulty of
math tasks
FORMATIVE DATA
DIAGNOSTICS
 Throughout the school year, periodic assessments efficiently
provide immediate results of student performance on key
TEKS.
 Diagnostic Exams – ascertain student placement and
determine students afforded early intervention through
tutorials
 Comprehensive Diagnostics – semester exams, keyed to the
state assessment and district timeline, track students’
progress and their strengths and weaknesses. Tutorials are
readjusted according to the data collected.
DIAGNOSTICS
 Periodic assessment data should be collected and used during
the school year.
 During CTLs (Cooperative Teachers Learning), assessment
data is shared among teachers and ideas are generated on how
to improve instruction.
DIAGNOSTICS
 Even if teachers are implementing a variety of assessment
methods, these assessment options are meaningless unless
their results are used to make decisions for improving
student achievement.
 Meaningful data is charted and displayed with students.
INSTRUCTIONAL DATA
DATA COLLECTION WALKTHROUGHS
 A data system exists that manipulates information from walkthroughs into percentage of
curriculum engagement, identification of instructional practices, identification of
grouping formats, and identification of research-based instructional strategies. There is
also a focus on the learner, which includes an identification of student actions,
identification of instructional materials, percentage of usage of HOTS, and percentage of
level of class engagement. This can then be compared to student data to see correlation
and areas that need attention or professional development.
INSTRUCTIONAL MEETINGS
 From the data collected, CTLs are held by department.
Instructional implications and strategies are discussed based
on the data collected.
 Each teacher who had the highest performance on a certain
TEKS teaches a lesson at a CTL.
 Teachers enter assignments into the grade book and identify
each TEKS assessed. This enables teachers to see curriculum
gaps and trends.
DATA COMES FULL CIRCLE
• CTLs and teacher/principal
conferences are held to discuss
interventios and insructional
strategies.
• Benchmark and TAKS data,
including scores, lexiles and
quantiles, are used to
identify students'
instrucional needs
• Students' progress is monitored
utilizing teacher observations and
mini-assessments; included in the
monitoring is the recognition of
successful student progress
Identify students
and their
instructional
needs
Research and plan
interventions
Progress monitor
via teacher
observations
mini-assessments
Implement ideas
and strategies
•
Interventions and
instructional strategies are
• implemented, including afterschool
tutorials, conference pullouts and
Saturday Academies.
DATA IN THE AGE OF STAAR
DATA IN THE AGE OF STAAR
 MATH AND SCIENCE
 Increase in number of open-ended items
 Process skills will be assessed in context
 4 hour time limit
 Implication
 Assess students on open-ended questions on each test
 Formulate questions to include process skills as identified by the standard
 Each test is timed and additional time is not given
DATA IN THE AGE OF STAAR
 READING




Greater emphasis on critical analysis
Increased focus on expository text
4 hour time limit
Implications
 Assessments reflect the changes
 WRITING




Assessed in two days
Two essays (personal narrative and expository)
4 hour time limit
Implications
 Every assessment includes a form of a personal narrative or expository short
answer or essay
DATA IN THE AGE OF STAAR
 Each STAAR blueprint provides a breakdown of the
assessment which should be reflected in every test that is
given, including the diagnostics.
DATA IN THE AGE OF STAAR
 Students scoring commended on the TAKS will pass the
STAAR.
 Data from students who did not score commended should be
scrutinized.
 Curriculum gaps
 Level of rigor
 Depth and Complexity
 Teacher level commended growth.
 Compare teacher data looking at scores and SE with and
without commended
HAVE A GREAT YEAR!!
For more information, email me at jvillarreal@lfcisd.net