83
Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement” -Victoria L. Bernhardt, Ph.D.- 1

Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Embed Size (px)

Citation preview

Page 1: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Data Analysis for Educational Leaders

“Data Rich, Information Rich!”

“Comprehensive data analysis is tied to systematic and systemic continuous

improvement” -Victoria L. Bernhardt, Ph.D.-

1

Page 2: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

The ResearchThe ability to accurately and

appropriately use the data … is critical to principals' effectiveness at ultimately improving student achievement (Price & Burton, 2004; Yeagley, 2001)

Holcomb (2004) found that proper training is key to effectively using data.

3

Page 3: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Article Review

Group A: “Developing an Inquiry-Minded District”

Group B: “Looking Deeper into Data”

Group C: “Expanding data analysis skills in educational leaders: implications for preparation programs.”

Group D: “First Things First: Demystifying Data Analysis”

4

Page 4: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Continuous School Improvement…..

Analyze&

Prioritize

Set S-M-A-R-TGoals

Select Instructional Strategies

Determine Results

Indicators

Progress Monitor, Examine Student

Work & Adjust through Instructional

Conversations

Collect and Chart Data

(Treasure Hunt)

Inquiry:•Question•Triangulate•Examine Angles

5

Page 5: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

In this workshop, you will:

• Become familiar with analyzing and interpreting data.

• Learn how to translate data into SMART Goals.• Develop a school-wide method of progress

monitoring.

6

Page 6: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Statistics

Two types:1.Descriptive statistics are used to describe or summarize our observations without making inferences.

2.Inferential statistics are to make predictions or estimates using a sample population.

What type of Statistics will we be using?

7

Page 7: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Tria

ngul

atio

n

Usi

ng M

ultip

le

Mea

sure

s!

SummativeStrandLevel

Disaggregation

Evidence of instructional

practice

What does the data tell us about our students?

What are the curricular, programmatic, and instructional implications?

Why is triangulati

on essential?

Benchmark

8

Page 8: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Take a few minutes to answer a question:

What was your school or district goal for reading last year?

For reading, how many students at each grade level were: Below Basic? Basic? Proficient? Goal? Advanced?

9

Page 9: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

How well did the students perform overall?

10

Page 10: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Is this information enough to make a school-wide goal? If so, what could one be? If not, what other information do you need?

11

Page 11: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Why is it important to see the proficiency levels?

CMT 2010 Data Grade 3

12

Page 12: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Administrators must look at “Big Picture Data”!

13

Page 13: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Grade

“N”(#of

Students

# Below Basic

# Basic#

Proficient# Goal

# Advanced

3 75 52% 0% 16% 13.3% 18.7%

4 52 40.4% 11.5% 13.5% 30.8% 3.8%

5 66 40.4% 12.1% 6.7% 27.3% 1.5%

aggregate 193 46% 7% 16% 23% 9%

Performance Level Scores School A

This school’s goal was to increase the

% of students scoring at

proficiency in math by 10%. Was this a good goal? Why or

why not?

14

Page 14: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Grade

“N”(#of

Students

# Below Basic

# Basic#

Proficient# Goal

# Advanced

3 75

75 x 52% = 39

Students

75 x 0% = 0

Students

75 x 16% = 12

Students

75 x 13.3% =

10 Students

75 x 18.7% =

14 Students

4 52

52 X 40.4%=

21 Students

52 X 11.5%=

6 Students

52 X 13.5%=

7 Students

52 X 30.8%=

16 Students

52 X 3.8%=

2 Students

5 66

66 X 40.4%=

28 Students

66 X 12.1%=

8 Students

66 X 16.7%=

11 Students

66 X 27.3%=

18 Students

66 X 1.5%=

1 Student

aggregate 193

46% 88

Students

7%14

Students

16%30

Students

23%44

Students

9%17

Students

Performance Level Scores School A

Total # of students

% of students in this level

How does this data impact your action plan? What are the instructional, professional development, curricular, and programmatic implications? Resources vs. Need?

How does this data impact your action plan? What are the instructional, professional development, curricular, and programmatic implications? Resources vs. Need?

15

Page 15: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

16

Page 16: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Group Work

Work with your group to determine the overall performance of the following school. Then answer the following questions:

1.What could a goal be?2.How does this data impact your action

plan? 3.What are the instructional, professional

development, curricular, and programmatic implications? Resources vs. Need?

17

Page 17: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Grade

“N”(#of

Students

# Below Basic

# Basic#

Proficient# Goal

# Advanced

3 40 40 X 0%=

4 43

5 49

Aggregate3-5

132

Grade

“N”(#of

Students

% Below Basic

% Basic%

Proficient% Goal

% Advanced

3 40 0% 13% 13% 43% 32%

4 43 5% 2% 24% 35% 35%

5 49 4% 6% 8% 45% 37%

18

Page 18: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Grade

“N”(#of

Students

# Below Basic

# Basic#

Proficient# Goal

# Advanced

3 4040 X 0%=0 Students

40x13%=5 Students

40x13%=5 Students

40x43%=17

Students

40x32%=13

Students

4 4343 x 5%=2 Students

43 x 2%=1 Students

43 x 24%=

10 Students

43 x 35%=

15 Students

43 x 35%=

15 Students

5 4949 x 3%=2 Students

49 x 6%=3 Students

49 x 8%=4 Students

49 x 45%=

22 Students

49 x 37%=

18 Students

Aggregate3-5

132(4/132) x1001%

(9/132) x1007%

(19/132)x100

14%

(54/132)x100

41%

(46/132)x100

35%

Grade

“N”(#of

Students

% Below Basic

% Basic%

Proficient% Goal

% Advanced

3 40 0% 13% 13% 43% 32%

4 43 5% 2% 24% 35% 35%

5 49 4% 6% 8% 45% 37%

19

Page 19: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

AYP (Reading 2010-2011=89%)

Goal= To increase the % of Students scoring At/Above Proficiency from 90% (14+41+35) to 95% (91%needed for AYP plus, in this case, because the scores are so

close to AYP, add an educational significant difference of 4%pts.) as measured by the 2011 CMT Math Score and monitored by the Common Assessments.

20

Page 20: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Where do we need to be? AYP vs. Safe Harbor

21

Page 21: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

BLOOM’S TAXONOMY How We Teach

WEBB’S DEPTH OF KNOWLEDGE How We Assess

KNOWLEDGE “The recall of specifics and

universals, involving little more than bringing to

mind the appropriate material” Recall – Recall of a fact, information, or procedure

(e.g., What are 3 critical skill cues for the overhand throw?) COMPREHENSION

“Ability to process knowledge on a low level such that the knowledge

can be reproduced or communicated without a verbatim repetition.”

APPLICATION “The use of abstractions in

concrete situations.”

Basic Application of Skill/Concept – Use of information, conceptual knowledge, procedures, two or more steps, etc. (e.g., Explain why each skill cue is important to the overhand throw. “By stepping forward you are able to throw the ball

further.”)

ANALYSIS “The breakdown of a situation into

its component parts.”

Strategic Thinking – Requires reasoning, developing a plan or sequence of steps; has some

complexity; more than one possible answer; generally takes less than 10 minutes to do (e.g., Design 2 different plays in basketball and explain

what different skills are needed and when the plays should be carried out.)

SYNTHESIS AND EVALUATION “Putting together elements & parts to form a whole, then making value

judgments about the method.”

Extended Thinking – Requires an investigation; time to think and process multiple conditions of the problem or task; and more than 10 minutes to do

non-routine manipulations (e.g., Analyze 3 different tennis, racquetball, and badminton strokes for similarities, differences, and purposes. Then,

discuss the relationship between the mechanics of the stroke and the strategy for using the stroke

during game play.)

Below Basic

Proficient

Basic

Goal

Advanced

22

Page 22: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Grade

“N”(#of

Students

# Below Basic

# Basic#

Proficient# Goal

# Advanced

3 75

75 x 52% = 39

Students

75 x 0% = 0

Students

75 x 16% = 12

Students

75 x 13.3% =

10 Students

75 x 18.7% =

14 Students

4 52

52 X 40.4%=

21 Students

52 X 11.5%=

6 Students

52 X 13.5%=

7 Students

52 X 30.8%=

16 Students

52 X 3.8%=

2 Students

5 66

66 X 40.4%=

28 Students

66 X 12.1%=

8 Students

66 X 16.7%=

11 Students

66 X 27.3%=

18 Students

66 X 1.5%=

1 Student

aggregate 193

46% 88

Students

7%14

Students

16%30

Students

23%44

Students

9%17

Students

Performance Level Scores School A

23

Page 23: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Safe Harbor: An alternate method for measuring progress toward AYP. For any school and/or subgroup that does not meet the proficiency target:– Reduce the % not proficient by 10 %– Meet the additional academic indicators– Meet the 95% participation rate

requirement.– Example:% Proficient Safe

HarborMathematics 45% 55% X .10 = 5.5% 51%

Reading 60% 40% x .10 = 4% 64%24

Page 24: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Group Work:

Work with your partner to figure out safe harbor for this school.Use this information to develop a school-wide goalIs there anything else this data tells you?

25

Page 25: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

This same process can be used for all sorts of data (subgroup, instructional, attendance….)!

Lets Try!

Group A: Attendance DataGroup B: Instructional DataGroup C: Subgroup Data

26

Page 26: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Number of Days Absent vs. Grade

Grade “N” 0-5 Days

6-10 Days

11-15 Days

16-20 Days

21+ Days

9 150 44% 20% 11% 15% 10%

10 150 35% 20% 15% 18% 12%

11 150 40% 43% 12% 3% 5%

12 150 40% 10% 25% 17% 8%

2009-2010

27

What could be a goal for grade 9?

Page 27: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

28

Your assessment results should render information

about curriculum implementation and

instruction.

How would this data impact your action plan

(PD, support, data collection…)?

Page 28: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

29

Page 29: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Grade

“N”(#of

Students

# Below Basic

# Basic#

Proficient# Goal

# Advanced

30

Page 30: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

31

Vertical Scale Scores

Page 31: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

32

Page 32: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Disaggregation

33

Page 33: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

34

Page 34: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

READING COMPBlack not of Hispanic origin

Proficiency Level # of Students PercentBelow Basic 15 14.85%

Basic 8 7.92%Proficient 21 20.79%

Goal 52 51.49%Advanced 5 4.95%

Total 101   

White not of Hispanic origin

Proficiency Level # of Students PercentBelow Basic 0 0.00%

Basic 2 5.56%Proficient 3 8.33%

Goal 20 55.56%Advanced 11 30.56%

Total 36  

Notice: there is

no overlap

35

Page 35: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Economically Disadvantaged (Free and Reduced Lunch)

Proficiency Level # of Students PercentBelow Basic 11 13.92%

Basic 4 5.06%Proficient 14 17.72%

Goal 44 55.70%Advanced 6 7.59%

Total 79  

For the Economically Disadvantaged student

data below, to what subgroup should we compare this data?

36

Page 36: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

The SIOP model was

implemented to reach these learners and

additional instructional hours Is it working?

%%ELL Subgroup

37

Page 37: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

%% %%

%%ELL SubgroupNon-ELL 38

Page 38: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

ELL Group “N”=25

Non-ELL Group “N”=50

New Arrival ”N”=1

%

39

Page 39: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

ELL Group “N”=25

Non-ELL Group “N”=50

New Arrival ”N”=1

%

40

Page 40: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

What questions do you have? What are

some cautions here?

41

Page 41: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

What is Educationally Significant?

Page 42: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

N (Male)=142N (Female)=139

Is this significant?

43

Page 43: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Look at the following graphs: What are the “take away” messages?

Is there any actions you would do as a result of this information?

44

Page 44: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

45

Page 45: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

46

Page 46: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

N=200

47

Page 47: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Know the assessment

Summative, Formative, DiagnosticPoints needed for mastery (Benchmark)# and types of questions.Strand make-up

48

Page 48: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

49

Page 49: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

CMT READING COMPREHENSION TEST BLUEPRINT       

GradeNumber of Test Items Per Content Strand/Objective + Point Value

A. General UnderstandingB. Developing Interpretation

C. Making Connections D. Content and Structure Total

3

12 mc, 1oe 7 mc, 1oe 0 mc, 4 oe 5 mc, 2 oe 24 mcA1 - 2mc - 2 pts B1 - 2mc - 2 pts C1 - 2oe - 4 pts D1 - 1mc, 1oe - 3 pts 8 oeA2 - 5mc - 5 pts B2 - 0 N/A C2 - 2oe - 4 pts D2 - 2mc, 1oe - 4 pts  A3 - 1oe - 2 pts B3 - 5mc, 1oe - 7 pts   D3 - 2mc - 2 pts  A4 - 1mc - 1 pts        A5 - 4mc - 4 pts        

4

8 mc, 2 oe 10 mc, 0 oe 0 mc, 4 oe 6 mc, 2 oe 24 mcA1 - 1mc, 1oe - 3 pts B1 - 2mc - 2 pts C1 - 2oe - 4 pts D1 - 2mc, 1oe - 4 pts 8 oe

A2 - 4mc - 4 pts B2 - 4mc - 4 pts C2 - 2oe - 4 pts D2 - 2mc, 1oe - 4 pts  A3 - 1oe - 2 pts B3 - 4mc - 4 pts   D3 - 2mc - 2 pts  A4 - 1mc - 1 pts        A5 - 2mc - 2 pts        

5+6

7 mc, 2 oe 8 mc, 1oe 0 mc, 4 oe 7 mc, 2 oe 22 mcA1 - 1mc, 1oe - 3 pts B1 - 2mc - 2 pts C1 - 2oe - 4 pts D1 - 2mc, 1oe - 4 pts 9 oe

A2 - 3mc - 3 pts B2 - 3mc, 1oe - 5 pts C2 - 2oe - 4 pts D2 - 2mc, 1oe - 4pts  A3 - 1oe - 2 pts B3 - 3mc - 3 pts   D3 - 3mc - 3 pts  A4 - 1mc - 1 pts        A5 - 2mc - 2 pts      

7+8

6 mc, 2 oe 8 mc, 1oe 0 mc, 4 oe 6 mc, 3 oe 20 mcA1 - 1oe - 2 pts B1 - 2mc - 2 pts C1 - 2oe - 4 pts D1 - 2mc, 1oe - 4 pts 10 oeA2 - 3mc - 3 pts B2 - 3mc, 1oe - 5 pts C2 - 2oe - 4 pts D2 - 2mc, 1oe - 4pts  A3 - 1oe - 2 pts B3 - 3mc - 3 pts   D3 - 2mc, 1oe - 4 pts  A4 - 1mc - 1 pts        A5 - 2mc - 2 pts      

KEY- oe = open ended mc = multiple choice

Point Value/ Strand and Questions Possible Point Value of

ObjectiveHighest Pt. Value = Priority 5 + points 7 pts. Grade 3

  4 points  3 points  2 points

Lowest 1 point 0 points B2- N/A grade 3

Adapted from the CMT4 L.A. Handbook /CREC

50

Page 50: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Content Standard Number of Points

1. Algebraic Reasoning1.1 4-51.2 4-51.3 2-3

2. Numerical and Proportional Reasoning

2.1 3-4

2.2 8-9

3. Geometry and Measurement

3.1 3-53.2 2-33.3 5-6

4. Statistics and Probability

4.1 34.2 4-54.3 4-5

Number of Items and Points Across Standards

CAPTMathematics

OE Items(3 points each)

Grid Items ( 1 point each)

TotalPoints

Algebraic Reasoning 2 6 12

Numerical & ProportionalReasoning 2 6 12

Measurement and Geometry 2 6 12

Working with Data 2 6 12

8 OE Items 24 Grid Items 48 Points

Third Generation CAPT Mathematics Assessment Blueprint

KEY-Point Value/ Strand and

Questions Possible Point Value of

Objective

Highest Pt. Value = Priority 6+points

  3-5pointsLowest 3 or below point

51

Page 51: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

CMT Math (3rd)

52

Page 52: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

CAPT-ReadingRtL

70-minute session

1 published fictional text

2,000-3,000-word text

10th-grade readability

4 response questions

4 dimensions assessed

6-point rubric

2-12 score

50% of CAPT reading score

RfI•45-minute session•3 published nonfiction texts•500 -1,000-word texts•10th-grade readability•12 multiple-choice, 6 open-ended questions•2 dimensions assessed•3-point rubric (0-2)•0-24 score•50% of CAPT reading score

53

Page 53: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Important!

CMTs at various grades differ in content, difficulty, and length. Therefore, NOT directly comparable.You can examine data longitudinally within grade and within CMT generation from year to year. This includes strand and subgroup data. Note: it is recommended that 3 years of historical data be used. CMT4 was first administered March 2006 and should be considered the benchmark .

Reference: Krisst, Abe & Martin, Paul. Guidelines for proper CMT Data Analysis. 2007. CSDE

54

Page 54: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Important!

Within a generation and grade, comparisons may be made on the basis of scale scores and achievement levels for all students. DRP unit scores can also be compared.Within a generation, grade and year, strand level performance can be compared to other strands. It is important that strand makeup is part of the analysis. This will help guide your action plan.

Reference: Krisst, Abe & Martin, Paul. Guidelines for proper CMT Data Analysis. 2007. CSDE

55

Page 55: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Trajectory

56

Demands/Skills

Time

Expectations for All Students

Baseline/Current Level of Performance

Goal

Tier 2 Projected Growth Line

4 weeks

8 weeks

6 weeks

16 weeks

Scores/Skills

Page 56: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

What is the trajectory of the school below? If they continue on this path will they make AYP next year?

57

Page 57: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

5% pts

58

Page 58: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

4% pts

59

Page 59: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Strand Analysis- Strand scores are useful when analyzing data about

discrete parts of the content area. Do not compare strand and scale data across

grades. They are tested in different ways-different level. To find trends you should have 3 years of historical data.

Look at trends rather than small differences. Strands are not precisely comparable.

Compare within the SAME Generation. 2006 is the baseline for the generation 4.

Once trends are identified, determine if the trend is statewide. If not, which districts are exceeding?

Compare district to state, over time or for one year. Compare strand individual strand performance against

other strands for the same grade.

60

Page 60: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

 

Reading1 . Forming a

General Understanding

2 . Developing Interpretation

3 . Making Reader/Text Connections

4 . Examining the Content and

StructureGrade 4 2006 64 62 34 50Grade 4 2007 81 66 36 60Grade 4 2008 81 66 49 51Grade 4 2009 86 70 59 61

61

Page 61: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

62

Page 62: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

63

Page 63: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

SMART Goal

Basic Proficient Goal

Each post-it contains:Student Name: __________________

•Oct. Score: ________ •Jan. Score: ________•May Score: ________

SPED ELL ________

Below Basic Advanced

What does a S-M-A-R-T Goal look like for this class?

64

Page 64: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Teacher B

Basic Proficient GoalBelow Basic Advanced65

Page 65: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Teacher A

Basic Proficient Goal

Each post-it contains:Student Name: __________________

•Oct. Score: ________ •Jan. Score: ________•May Score: ________

SPED ELL ________

Below Basic Advanced66

Page 66: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Teacher B

Basic Proficient GoalBelow Basic Advanced67

Page 67: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Teacher C

Basic Proficient GoalBelow Basic Advanced68

Page 68: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

School Improvement Planning Process

Analyze data to identify needs and goals

Set measurable goals and targets based on in depth data analysis

Clearly identify target levels of performance for all students

Develop SIP with timeline, benchmarks, and clear responsibilities

Align professional development with desired outcomes.

Monitor progress using interim assessments and data team process

69

Page 69: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Lessons Learned

Data driven decision making can be a powerful tool in changing student outcomes and promoting continuous improvement in achievement.

Progress has to be measurable. Community outreach is

essential.It has to start at the top.It takes time.

70

Page 70: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

7 Characteristics of Effective Accountability Systems High Expectations for all studentsHigh-quality assessments aligned with standardsAlignment of resources, support and assistance for improvementSanctions and rewards linked to

resultsMultiple measuresData use in districts and schoolsInformed stakeholders

71

Page 71: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Bar Graphs: Points to Remember1. Bar Graphs are used to compare, each item is mutually exclusive and is collected at approximately the same time.2. Independent variables should be on the horizontal axis3. A descriptive tool that creates a picture of “What is”4. Individual bars represent independent events, groups, or individuals.Answers “how many” or “how much” groups or individuals earned or scaled at the time the data were collected.5. The most highly recommended format for descriptive data.6. Keep the easy to read as possible7. Reduce grid lines to the fewest needed for clarity8. Label data within the graph wherever possible

72

Page 72: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Bar Graphs: Points to Remember9. Eliminate boxes around the legend and use patterns sparingly10. You might want to move the legend to underneath if it is easier to read or include a portion of the legend in the graph11. Use type size that can be easily read and is consistent throughout the graph12. Make sure that the colors contrast enough to show the data clearly, and use colors that enable you to print or photocopy in Black and White12. ALWAYS include the “n” 13. Be sure to label both axes on the graph14. Use Data Labels when the value is difficult to see15. Dark background shading=white gridlines; white shading=dark thin gridlines16. Make sure that when presenting a series of graphs, the scales are consistent and accurate.

73

Page 73: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

N=450

74

Page 74: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Line GraphsLine graphs are good at showing a series of numbers over time (for instance a disaggregated line graph is great for showing the achievement gap over time). Trends over time.To keep graphs easier to read, avoid graphing more then 5 lines.Be sure to include the number of people in each subgroup (subgroups less then 8 are too small to be included in a graph)Use a combination of colors and symbols to allow for black and white printing.Label axis and titles

75

Page 75: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

When do you use a line graph?

76

Page 76: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

When do you use a line graph?

77

Page 77: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

•Explain purpose of the test/assessment•Communicate the standards and benchmarks for the assessments.•Indicate the type of assessment and reporting method (norm-referenced, percentile ranks, normal curve equivalents, standardized…)•Use a simple graph to display information.•Put data in context, with detail.•NEVER SPECULATE or infer the reason(s) for results.•Protect identities of individual test takers.•Always state your school’s plans for the results.

When communicating test results:

78

Page 78: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Continuous School Improvement…..

Analyze&

Prioritize

Set S-M-A-R-TGoals

Select Instructional

Strategies

Determine Results

Indicators

Progress Monitor, Examine Student

Work & Adjust through Instructional

Conversations

Collect and Chart Data

(Treasure Hunt)

Inquiry:•Question•Triangulate•Examine Angles

•Differentiation •Strong tier one•Ongoing progress monitoring using formative assessment•“None of us are as strong as all of us”

address needs of ALL students

EVERYONE is involved!All efforts align and contribute!

79

Page 79: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Resources

http://www.sde.ct.gov/sde/cwp/view.asp?a=2618&q=321744.

80

Page 80: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Thank you to the following colleagues for their support in the development of this module:

Heather Levitt, CSDE

Mary Hourdequin, CAS

Michael Wasta, CSDE

81

Page 81: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Thank you to the following colleagues for their assistance during the vetting process:

Megan Alubicki, CSDE

Shauna Brown, CSDE

Nina Butkiewicz, CAS

Jeff Greig, CSDE

Abe Krisst, CSDE

Mark Nolan, CAS

Beth McCaffery, LEARN

82

Page 82: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Contact Information:

Mara DumondEducational Specialist: Data, Assessment,

and Research Institute of Teaching and Learning, [email protected]

83

Page 83: Data Analysis for Educational Leaders “Data Rich, Information Rich!” “Comprehensive data analysis is tied to systematic and systemic continuous improvement”

Feedback

Please take a few minutes to complete the Feedback Form.

Your comments are very important to us and to your district office, as it provides

specific information and thoughts to consider for future

professional development.

84