What Does a Proficient Student Know and Do

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Using Data to Lead Change
Welcome!
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What Do You Expect?

• Introduce yourself
• Name
• Position
• School
• Why did you choose this session?

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Jig-Saw! Youth At The Crossroads
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Essential Question 1

• What data do you collect to improve
• student achievement and school
• performance?

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Students Enrolled in College-Prep Courses in
Ninth Grade and Their Success Rates
High-enrollment Schools
All Schools
C-P Courses
Success Rate
C-P Courses
Success Rate
English 27 91 59 86 Algebra I 31 75 56
72 Algebra II/Geometry 20 91 30 90
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Students Meeting Performance Goals at 45 Schools
91
83
78
72
66
63
57
59
57
Math/Science
Basic College-
HSTW Academic
Concentration
prep (16)
Core/Career
(11)
Concentration
(21)
Reading
Mathematics
Science
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Extra Help and Higher Achievement
67
61
59
57
50
43
Reading
Mathematics
Science
Help Often Received
Help Not Readily Available
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Purpose Summary

• How are we doing?
• How can we improve?
• --Joan Herman and Lynn Winters, Tracking Your
  Schools Success
• What about different constituencies?
• Staff
• Parents
• Community
• State Leaders

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Using Data to Drive Change

• Collect formal and informal data to determine
  needs and as the foundation for decision-making
• Disaggregate data to monitor and improve
• Use data to change attitudes teachers,
  students, parents

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Essential Question 2

• Can you pick up any data at your school and
  explain
• What it is,
• What it says and
• What it means?

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CRT vs. NRT

• Criterion-referenced tests
• Score compares test takers performance to
  previously set standard
• Most teacher-made tests
• Norm-referenced tests
• Score acquires additional meaning when compared
  to others
• Shows relative performance
• Most standardized tests
• Some tests are both

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Understanding the Various Score Types

• Norm-referenced
• Criterion-referenced
• Raw Score
• Percent Correct
• Scale Score
• National Percentile Rank
• Normal Curve Equivalent
• Stanine Grade Equivalent

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Raw Score

• The number of items a student answers correctly
  on a test
• Mary took a 20-item mathematics test (where each
  item was worth one point) and correctly answered
  17 items. Her raw score for this assessment is
  17.

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Percent Correct

• To calculate the PC score, you must divide the RS
  by the total number of items on the test and
  multiply the quotient by 100.
• Mary had an RS of 17 on a 20-item mathematics
  test. 17 20 .85 .85 x 100 85
• Therefore, Marys PC score for that test was 85.

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Scale Score

• Scale scores are converted raw scores that use a
  new, arbitrarily chosen scale to represent levels
  of achievement or ability. They have no inherent
  or readily apparent meaning.
• Higher scale scores indicate higher proficiency,
  and growth in scale score units indicates growth
  in proficiency.
• Scale scores form an equal interval scale and
  have a continuous scale across levels so you can
  track a students progress from the first to 12th
  grades on one scale.

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Converting Raw Scores into Scale Scores

• RAW SCORE SCALE
• 
  x
• 0 10 20 30
  40
• CONVERTED SCORE SCALE
• 
  x
• 500 600 700 800
  900

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Normal Distribution
X Mdn Mode
0.13 2.15 13.59 34.13 34.13
13.59 2.15 0.13
-4 -3 -2 -1
0 1 2 3 4
Standard Deviations
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National Percentile Rank

• A percentile may be interpreted as the percentage
  of students in the norm group whose scores fall
  below the given score.
• For example, a students score with a NPR of 90
  indicates that the student scored better than 90
  percent of the students in the norm group.
• Dont confuse this with percentage correct.

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Scale Scores for 50th Percentile Reading Total
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Normal Curve Equivalent

• Normal Curve Equivalents (NCEs) are
  norm-referenced scores ranging from from 1 to 99,
  with an average score of 50. In this respect,
  NCEs are identical to national percentiles.
• NCEs are an equal interval scale which allows for
  arithmetic calculations.
• Changes in academic achievement are usually
  measured through NCE gains. A student or group
  of students make an average years growth if they
  receive the same NCE score in two consecutive
  years.

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Comparison of Percentile Score and NCE
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Comparison between Percentile Score and NCE
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Stanine

• The Stanine is a STAndard score related to a
  scale of NINE units. Stanines are on an equal
  interval scale and have a mean of five and a
  standard deviation of two.
• Julie received a Stanine score of 8 on her
  norm-referenced exam, which is in the
  above-average range of the test.

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Grade Equivalent

• A grade equivalent score indicates the grade
  level at which the median student achieves the
  corresponding raw score.
• A student earning a GE of 4.7 has the same raw
  score as that made by an average student in the
  fourth grade at the end of the seventh month.
• This is not usually useful for data analysis.

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Data Context Considerations

• Grouping of students (homogeneously or
  heterogeneously)
• Grouping of free/reduced lunch and ESOL or ESE
  students
• Concentration of at-risk/special needs students
  in a class
• Curriculum-content-related objectives in the
  school improvement plan
• Sub-populations of students, i.e. free/reduced
  lunch, racial/ethnic categories, lowest 25

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Test Score Distribution with a Mean and Median of
80
Mode 80 Range 30
8
7
6
5
4
3
2
1
0
65
70
75
80
85
90
95
National Percentile
No. of Students
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Test Score Distribution with a Mean and Median of
80
Mode 80 Range 0
National Percentile
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Test Score Distribution with a Mean and Median of
80
Mode 65, 95 Range 30
30
25
20
15
10
5
0
65
70
75
80
85
90
95
National Percentile
No. of Students
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Consider This!

• Which content areas and related evaluation
  criteria are included in the school improvement
  plan?
• What are the content areas and measurement
  instruments contributing data to the
  accountability criteria?
• What is the relationship of the teachers course
  content to the areas identified as strengths and
  weaknesses?
• What relevant data are readily available?
• What specific questions do you and other
  stakeholders want answered?

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Aggregated vs. Disaggregated Data

• Aggregate To combine data to summarize.
• Ex. A summary of your schools scores on a
  standardized test
• Disaggregate To separate data into sub-groups
  to determine if there are differences among those
  groups.
• Ex. Comparing male/female results
• Ex. Comparing results on subtests
• Ex. Looking at data by classroom/teacher

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Key Points

• Use data to answer critical questions about
  student performance.
• Look at relationships in individual student
  scores among multiple measures.
• Break down group data into more discrete units to
  be meaningfully interpreted.
• The leaders role is critical in using and
  interpreting data.

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Essential Question 3

• How can I use data to reach my
• vision of a school where all
• students achieve at high levels?

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Getting the Most from Data
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Getting the Most From Data
Focus

• Identify purpose/goal
• Identify related processes, inputs, outcomes
• Identify related questions

Gather Data
Analyze Data
Display Data
Take Action
Monitor Over Time
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Getting the Most From Data
Focus
Gather Data

• Gather existing data
• Gather new data, if needed

Analyze Data
Display Data
Take Action
Monitor Over Time
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Getting the Most From Data
Focus

• As many levels as needed
• Compare against standard
• Challenge assumptions

Gather Data
Analyze Data
Display Data
Take Action
Monitor Over Time
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Getting the Most From Data
Focus
Gather Data
Analyze Data

• Bar charts
• Frequency distributions
• Item analyses
• Scatter plots

Display Data
Take Action
Monitor Over Time
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Getting the Most From Data
Focus
Gather Data
Analyze Data
Display Data

• Examine research
• Create an action plan
• Get buy in

Take Action
Monitor Over Time
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Getting the Most From Data
Focus
Gather Data
Analyze Data
Display Data

• Is plan being followed?
• What are results?
• What next?

Take Action
Monitor Over Time