Melda N. YildizUsing Computer Generated Data Analysis to Drive Classroom Instruction May 19, 2007
Vocabulary average of a 14-year-old dropped from 25,000 words in 1950s to only 10,000 words in 1999.
“Numbers.” Time Magazine 155, no 6 (Feb 14, 2000); 25
Vocabulary Average for 14-Year-Old
25,000
10,000
0
5,000
10,000
15,000
20,000
25,000
30,000
Year
Nu
mb
er o
f Vo
cab
ula
ry
VocabularyRate
VocabularyRate
25,000 10,000
1950 1999
Statistics
In political Washington, Statistics are weapons of war. That’s why they get manipulated, massaged, and twisted until any connection to reality is strictly coincidental.
Peter Carlson
CNN.com posted misleading graph showing poll results on Schiavo case
http://mediamatters.org/items/200503220005
The Truth but not the Whole Truth
0102030405060708090
100
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
EastWestNorth
020406080
100
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
EastWestNorth
0102030405060708090
100
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
EastWestNorth
How can you use this data to guide instruction?
Student data on a specific item can be valuable to teachers. Inferences based on the data can be used to guide classroom instruction.
Teachers might want to explore the following questions: What core learning goal indicator is this item testing? Is this indicator included in the curriculum in my local school system? To what extent is this indicator being taught? To what extent have I assessed this indicator? How do the results of my classroom assessment correlate with the field
test? How familiar are the students with the rubric used to score performance (for
constructed responses items only)? What common errors do you see in the way students respond? What do the distractors tell you about instructional needs?
http://www.kuhrs.com/Files/Final%20FOS%20Brochure.pdf
"Data helps you make changes. And when you see data, it really puts [student achievement] right in your face." —Virginia Lawton, 6th-grade teacher in Wisconsin
http://www.3d2know.org
Data-Driven Instruction
3D2Know: Data-Driven Decision MakingCoSN launched the Data-driven Decision Making Initiative: Vision to Know and Do building upon its role in providing key K–12 school district managers with the knowledge and skills necessary for effective leadership.
Data Quality Campaign (DQC)A national, collaborative effort to encourage
and support state policymakers to improve the collection, availability and use of high-quality education data and implement state longitudinal data systems to improve student achievement.
http://www.dataqualitycampaign.org
Buried Treasure: Developing a Management Guide From Mountains of School DataThis report (in PDF format) provides a practical
discussion of what is required to develop a school district "management guide," along with an actual guide built on evidence-based indicators.
http://www.crpe.org/pubs/pdf/BuriedTreasure_celio.pdf
NCREL: School Improvement Through Data-Driven Decision MakingDesigned to give educators—and others
involved in using data in a classroom, school, or district—a variety of places to find resources, tools, and action steps to foster school improvement.
http://www.ncrel.org/datause/ http://www.ncrel.org/datause/howto.php
http://www.ncrel.org/
Statewide Longitudinal Data Systems Grant ProgramThis website acts as a resource for grantee and
non-grantee states regarding the grant program, and the development of longitudinal data systems in general.
http://165.224.221.98/Programs/SLDS/index.asp
Guide to Using Data in School Improvement EffortsA Compilation of Knowledge From Data
Retreats and Data Use at Learning Point Associates
December 2004 by Learning Point Associates
http://www.learningpt.org/pdfs/datause/guidebook.pdf
More…
http://www.success.co.il/is/dik.html
http://www.fcrr.org/science/pdf/kosanovich/jrf_leadership.pdf