Data Report or Treasure Chest?
Using What You Have to Support Students
Get to Know NCHE
• The U.S. Department of Education’s technical assistance and information center
• NCHE has:– A comprehensive website: www.serve.org/nche– A toll-free helpline: Call 800-308-2145 or e-mail [email protected]
– A listserv: visit www.serve.org/nche/listserv.php for subscription instructions
– Free resources: Visitwww.serve.org/nche/products.php
Temperature Check
• Who’s in the room?
• How comfortable are you with data?
Big Picture
“I am a deep believer in the power of data to drive our decisions. Data gives us the road map to reform. It tells us where we are, where we need to go, and who is most at risk.”
Arni Duncan
Big Picture
• McKinney-Vento data– Districts submit to SEAs– SEAs submit to US ED via EDFacts or CSPR– NCHE reviews data, creates national summary
http://center.serve.org/nche/ibt/aw_statistics.php
• ESEA calls for collection, analysis, and use of student achievement data to improve school outcomes– Includes requirement for state report cards
Evolution
• Find kids, get them in school
• Find kids, get them in school, count them
• Find kids, get them in school, count them, find out how they’re doing
• Find kids, get them in school, count them, find out how they’re doing, actively help them grow
Self-evaluation
• Where are you in the data evolution?
• What access do you have to data?
• Do you know who your players are?
• What do you want to know?
First Steps
• Develop a plan
– Identify your questions
– Can change over time, but establish a direction
– Do your research
– Make your ask concrete
Basic Questions
• Count of students, by grade & housing
• Diversity of HCY population
• Where the students are
• State testing performance
• Special populations overview
Trend Data
2007 2008 20090
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000 72277961
9777
Homeless Students
Trend Data
Gifted & Talented Special Education LEP0
500
1000
1500
2000
2500
187
1623
598
274
1838
692
403
2124
849
2007
2008
2009
Actual Numbers vs. Percentage
Cass MorganVanderburgh Allen Lake Marion0
500
1000
1500
2000
2500
3000
3500
4000
368 428 503 528 628
3687
Counties with Largest HCY Student Popu-lation
Actual Number vs. Percentage
Grant
Batho
lom
ew
Mar
ion
Perry
Mon
tgom
ery
Mor
gan
Cass
Jenn
ings
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
2.4%3.2% 3.5% 3.6% 3.7%
4.0% 4.5%
6.5%
Percent HCY by County
Comparisons: The Next Level
Must compare the outcomes for homeless students to other student populations for true depth of growth and challenges
– Gives new meaning to data– You can mix and match based on
your needs assessment and priorities
Comparisons: The Next Level
• Graduation rates
• Special Education rates
• Gifted and Talented
• Suspensions
Comparisons: The Next Level
2007 2008 200954.0%
56.0%
58.0%
60.0%
62.0%
64.0%
66.0%
58.5%
60.9%
65.8%
The Homeless Children and Youth Gradu-ation Rate
Comparisons: The Next Level
Graduation Rate by Subpopulation
2007 2008 2009
57% 60%66%59% 59%
62%
59% 61%
66%
58%61%
68%
76%78%
82%
Black
LEP
HCY
F/R Lunch
State Avg
Comparisons: The Next Level
Percent Students in Gifted & Talented
2007 2008 2009
2.6%3.4%
4.1%
10.3%11.5%
13.8%HCY Pop.
Comparisons: Top Level
Percent Students IDEA
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%21.7%
17.5%
HCY Pop.State Avg.
Suspensions
Percent of Students that Received a Suspension
2007 2008 20090.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0% 26.5% 27.5%26.0%
14.5% 14.3% 14.1%
HCY
State Avg.
Suspensions
7%
21%
23%15%
11%
24%
Reason Stated for Expulsion over Past 3 Years
Weapons PossessionAlcohol, Drugs or TobaccoAggressionDefianceAttendanceOther
In-School vs. Out of School
43%
57%
Type of Suspensions Received HCY
In-School
54%46%
Type of Suspensions Received State Avg
Out of School
Quantitative vs. Qualitative
• Qualitative does have its place
– Can be harder to collect, analyze
– Can tell you the story behind the numbers
– What opportunities do you have to gather it
– How can you make it reasonably standardized
Data Quality
• Consider requiring liaison verification
• Consider tracking large changes
• Consider comparison groups like free lunch, employment rates, census data
• Consider n size: small group sizes skew
Tips
• Golden Rule: ALWAYS be nice to the data people
• Find reasons or ways to do things for them– Review guidance, help train, field questions
• Be mindful of their timelines
• Find ways to help assure quality
Tips
• When deciding what to look at, consider format for final report
• Explain your findings
Final Thoughts
Data…"can basically take us out of the dark ages of just kinda teaching and hoping, which is what a lot of folks have done for a very long time. A lot of teachers have taught their hearts out and don't have a good way of telling who's learning
what and what's working and what's not.“
Katie Haycock, Education Trust
Thank you!
Christina [email protected]
Beth [email protected] 336-315-7452
Data Collection Informationhttp://center.serve.org/nche/ibt/sc_data.php