Using Data for Program Quality Improvement

Stephanie Lampron, Deputy Director

2

Session Overview

The Title I, Part D Data Collection

Importance of Data Quality and Data Use

Actively Using Data for Program Improvement

3

The Title I, Part D Data Collection

4

What are Title I, Part D and NDTAC?

Title I, Part D (TIPD) of the Elementary and Secondary Education Act of 2001

– Subpart 1-State Agency

– Subpart 2-LEA

National Evaluation and Technical Assistance Center for the Education of Children and Youth who Are Neglected, Delinquent or At-Risk (NDTAC)

5NDTAC's Mission Related to Data and Evaluation

Develop a uniform evaluation model for State Education Agency (SEA) Title I, Part D, programs

Provide technical assistance (TA) to States in order to increase their capacity for data collection and their ability to use that data to improve educational programming for N & D youth

6Background: NDTAC’s Role in Reporting and Evaluation

Specific to Title I, Part D, Collections TA prior to collection

Webinars, guides, and tip sheets

TA during collection

Data reviews, direct calls, and summary reports for ED

Data analysis and dissemination

GPRA, Annual Report, and online Fast Facts

Related TA Data use and program evaluation

7TIPD Basic Reporting and Evaluation Requirements

Where do requirements come from? Elementary and Secondary Education Act, amended in

2001 (No Child Left Behind)

– Purpose of Title I, Part D (Sec. 1401)

– Program evaluation for Title I, Part D (Sec. 1431-Subpart 3)

How does ED use the data? Government Performance and Results Act (GPRA) Federal budget requests for Title I, Part D Federal monitoring Provide to NDTAC for dissemination

8Collection Categories for TIPD in the Consolidated State Performance Report (CSPR)

Types/number of students and programs funded

Demographics of students within programs

Academic and vocational outcomes

Pre-posttesting results in reading and math

9

Title I, Part D in Pennsylvania

State Agency (S1) Local Agency (S2)

2008-09 2009-10 2010-11 2008-09 2009-10 2010-11

Number of Programs

US771 720 861 2,712 2,889 2,689

PA7 8 11 295 286 288

Number of Students Served

US125,456 109,146 106,747 373,071 367,121 354,591

PA 1,643 (1%)

1,189 (1%)

1,123 (1%)

24,863 (7%)

24,562 (7%)

26,510(7%)

10Local Education Agency (S2) Academic Outcomes

* 2010-11 data are preliminary

11Long-term Students Improvement in Reading (Subpart 2)

* 2010-11 data are preliminary

12Long-term Students Improvement in Math (Subpart 2)

* 2010-11 data are preliminary

13

Data Quality & Data Use

14

14

Functions of Data

Help us identify whether goals are being met (accountability)

Tell our departments, delegates, and communities about the value of our programs and the return on their investments (marketing)

Help us replace hunches and hypotheses with facts concerning the changes that are needed (program management and improvement)

Help us identify root causes of problems and monitor success of changes implemented (program management and improvement)

15

You need to TRUST your data as it informs:

Funding decisions

Technical assistance (TA) needs

Student/facility programming

15

Why Is Data Quality Important?

16

16

What Is “high data quality”?

If data quality is high, the data can be used in the manner intended because they are:

Accurate Consistent Unbiased Understandable Transparent

17

What data are the most useful?

Useful data are those that can be used to answer critical questions and are…

Longitudinal Actionable (current, user-friendly) Contextual (comparable, part of bigger picture) Interoperable (matched, linked, shared)

Source: Data Quality Campaign

Source: Data Quality Campaign

18

18

Should you use data that has lower quality data?

YES!! You can use these data to…

Become familiar with the data and readily ID problems

Know when the data are ready to be used more broadly or how they can be used

Incentivize and motivate others

19

Insure systems, practices, processes, and/or policies are in place− Understand the collection process

− Provide/request TA in advance− Develop relationships − Develop multilevel verification processes− Track problems over time− Use the data (even when problematic)− Link decisions (funding, hiring, etc.) to data evidence

Indicate needs to others 19

Data Quality Support Systems

20

Using Data Actively

21

Essential Steps Related to Data Use

1. Identify problem or goal to address

2. Explore & analyze existing data

3. Develop and implement change Set targets and goals

4. Develop processes to monitor and review data

22

Step 1: Identify concerns or goals

Identify your level of interest State Facility / School Classroom

Define, issue, priorities or goals Upcoming decisions State or district goals or initiatives Information from needs assessments (or, conduct one)

Identify how data will be used & questions

Resource: NDTAC Program Administration Planning Guide-Tool 3 on Needs Assessments

23

23

Program Components by Data Function

Program Accountability

Program Marketing/ Promotion

Program Improvement

Student demographics

Are the appropriate students being

served?

How are you addressing the

needs of diverse learners?

Which students need to be better

served?

Student achievement

Are students learning?

What are students learning? What gains have they

made?

How can we help improve student achievement?

Student academic outcomes

Are students continuing their

education?

What are students doing to continue their education?

How can we help improve student

academic outcomes?

24

24

Focusing the Questions

Break the question into inputs and outcomes:

Inputs (what your program contributes):− Teacher education, experience, full-time/part-time

− Instructional curriculum− Hours of instruction per week

Outcomes (indicators of results): − Improved posttest scores

− Completed high school− Earned GED credentials

25

25

Focusing/Refining the Question

Weak Question: Does my school have good teachers?

Good Question: Does student learning differ by teacher?

Better Question: Do students in classes taught by instructors who

have more teaching experience have higher test scores than those taught by new teachers?

26

Step 2: Explore Existing Data

Locate the data you do have

Put it in a useful format−Trends, comparisons

What story is the data telling you?−What jumps out at you about the data?−Are the data telling you something that is timely and

actionable?−What questions arise? What is the data not telling

you that you wish you knew?**−What data could help answer those questions?

27Local Education Agency (S2) Academic Outcomes

28LEA 1: Comparison data (1)Percent of Students Earning HS CC

State Average

LEA Average

29

Comparison Data (2): Context

Per Pupil Expenditure

Earning HS Course Credits

FT teachers

Entering below

grade level % LEP

Facility A $500 70% 5 65% 25%

Facility B $450 40% 5 10% 40%

Facility C $550 20% 5 91% 70%

Facility D $600 33% 5 50% 30%

30

Longitudinal data: more context

31

Do you know enough?

Sometimes, the data will lead to more questions and a need for more information…

Compare to other LEA’s facilities Use student-level data and disaggregate Look at monitoring information and applications Collect additional information-surveys, interviews

*Keep data quality in mind

32

Step 3: Implement improvement plan

Implement new programming, change, etc.

Set benchmarks, performance targets− In terms of your priorities, where do you want your

subgrantees and facilities to be in one year? Two years? Three years?

− What performance benchmarks might you set to measure progress along the way?

− How will you know when to target a subgrantee or facility for technical assistance? At what point might you sound the alarm?

33Step 4: Develop processes for reviewing data

Keep using it! Monitor change and compare against benchmarks

Review data in real time

Share it and discuss it

34

Keep in mind

Data use is not easy* Data should be a flashlight, not a hammer* Change takes time-set realistic goals “No outcome” can be a useful finding Aggregated data can usually be shared

*Source: Data Quality Campaign

35Data Capacity Exists !(Data Quality Campaign, 2011 Report)

10 Essential Elements of Longitudinal Data Systems # States

A unique student identifier 52

Student-level enrollment, demographic, and program participation information 52

The ability to match individual students’ test records from year to year to measure academic growth

52

Information on untested students and the reasons why they were not tested 51

A teacher identifier system with the ability to match teachers to students 44

Student-level transcript data, including information on courses completed and grades earned

41

Student-level college readiness test scores 50

Student-level graduation and dropout data 52

The ability to match student records between the P–12 and postsecondary systems 49

A state data audit system assessing data quality, validity, and reliability 52

36

1. Link State K-12 data systems with early learning, postsecondary education, workforce, social services, and other critical agencies. 11

2. Create stable, sustained support for robust state longitudinal data systems. 27

3. Develop governance structures to guide data collection, sharing, and use. 36

4. Build state data repositories that integrate student, staff, financial, and facility data. 445. Implement systems to provide all stakeholders with timely access to the information they need while protecting student privacy. 2

6. Create progress reports with individual student data that provide information educators, parents, and students can use to improve student performance. 297. Create reports that include longitudinal statistics on school systems and groups of students to guide school-, district-, and state-level improvement efforts. 368. Develop a purposeful research agenda and collaborate with universities, researchers, and intermediary groups to explore the data for useful information. 319. Implement policies and promote practices, including professional development and credentialing, to ensure that educators know how to access, analyze, and use data appropriately. 310. Promote strategies to raise awareness of available data and ensure that all key stakeholders, including state policymakers, know how to access, analyze, and use the information. 23

Next Step: Data Use (DQC-2011)

37

Accessible Data – N or D Related

Title I, Part D Data ED Data Express:

www.eddataexpress.ed.gov NDTAC State Fast Facts Pages:

http://data.neglected-delinquent.org/index.php?id=01 Title I, Part D, Annual Report:

www.neglected-delinquent.org/nd/data/annual_report.asp

Civil Rights Data Collection (district and school)http://ocrdata.ed.gov/

38

Accessible Data – N or D Related

OSEP Data Collectionhttps://www.ideadata.org/default.asp

Youth Behavior Survey (CDC) http://www.cdc.gov/healthyyouth/yrbs/index.htm

OJJDP Juvenile Justice Surveys /Data Bookhttp://www.ojjdp.gov/ojstatbb/

39

Resources

NDTAC reporting and evaluation resources: http://www.neglected-delinquent.org/nd/topics/index2.php?id=9

Data Quality Campaign: www.dataqualitycampaign.org Data for Action 2011—Empower With Data

40

Questions?

Stephanie Lampron

NDTAC Deputy Director

slampron@air.org

202-403-6822

NDTAC Data Team Dory Seidel: dseidel@air.org Liann Seiter: lseiter@air.org