Title: NCLB
1NCLB Can You Afford Not To Have A Data
Warehouse
- Bill Flaherty
- Director of Technology Services
- Hanover County Public Schools
- http//hanover.k12.va.us/presentations/NCLB-dw
2- You have to be very careful if you dont know
where you are going, because you might not get
there. - -Yogi Berra
3- How would I show SOL results in deciles by school
for multiple years?
4- How would I provide produce a report with past
SOL results by subgroup and reporting category?
5- How would I provide each student with a realistic
prediction of what GPA and SAT is needed for
admission to different colleges?
6Todays Presentation
- Three Questions
- Data Driven Decision Making
- MERCs Work
- An Overview of Data Warehouse Technology
- What is Hanovers Instructional Decision Support
System? - Advantages
- Using IDSS to crack the NCLB nut
- Quality School Portfolio Program
- Demonstration of IDSS Answers to the Three
Questions, NCLB Reports More - Questions
7High Stakes Testing
8What is Data-Driven Decision Making?
- Mining the Data
- Analyzing the Data
- Communicating the Data
- Using the Data
9Teachers Use of High-Stakes Test Score Data to
Improve Instruction Metropolitan Educational
Research Consortium (MERC)
- Only half the teachers received scores by
reporting category - Most teachers focused on group averages and not
individual students - Most teachers made instructional changes
- more depth -pacing
- tests taking skills -individualization
- advanced cognitive processes
- formative assessments
- within grade collaboration
http//www.vcu.edu/eduweb/merc
10Current Systems
- On-line Transaction Processing System
- OLTP
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12Building The Data Warehouse -Bill Inmon,
1992
13Data Warehouse
- A subject-oriented, integrated, time variant,
non-volatile collection of data in support of
managements decision-making process. - -William Inmon
14Fundamental Characteristics of a Data Warehouse
- Separate Decision Support System database from
OLTP systems - Storage of data only no data is created, but it
may be derived - Integrated data
- Scrubbed data
- Historical data
15Fundamental Characteristics of a Data Warehouse
- Read only
- Various levels of summarization
- Subject oriented
- Easily accessible
16Data Warehouse
Data Source
Data Source
Data Source
17Hanover County Public Schools
- Instructional Decision
- Support System (IDSS)
18Our Current SystemCIMS
- On-line Transaction Processing System
- OLTP
19IDSS
CIMS Database
User Community (Business Objects)
Data Warehouse (SQL 7.0)
Test Scores
www.businessobjects.com
In-house Data, Surveys
201999-2000School Board Goals
- Promote instructional programming in the
following areas, among others. - Professional development
- Curriculum development
- Implications of longitudinal assessment of
student achievement - Graduation requirements staffing needs
- Vocational / technical / alternative education
study recommendations - Standards of learning implementation /
implications
21Support From The Top
- Longitudinal Assessment Committee Chaired By The
Superintendent - First Meeting May, 1999
- Committee members
- Board member
- Assistant Superintendent of Instruction
- Assistant Superintendent of Finance Technology
- Director of Guidance Testing
- Director of Technology Services
- School Principal
- Supervisor Information Technology
22Front Ends For The User Community
- Mechanism for correcting data
- Predefined reports Student Information System
- Business Objects
- Predefined reports
- Ad hoc reporting
- Technical person to assist principals in
obtaining the correct data
23Student
24Challenges
- Keeping the data in the warehouse up-to-date
nightly refresh - Information from multiple sources received in a
constant steam - Keeping the data accurate
- New State reporting has changed the whole ball
game - Keeping principals trained
25Advantage of IDSS
- Ease of use
- Speed in acquiring data
- Ability to create custom reports
- Make decisions based on information
- Improve student performance
26Key Elements of Success
- Board and Superintendent Support
- Board Goal
- Personnel to support the goal
- Cost effective
- Infrastructure in place
- Training
- Core reports
27Elementary Schools
- Passing vs. Taken
- Examined by subgroups
- No difference by minorities
- Student with disabilities are an area of concern
- School pass rate not keeping up with county pass
rate over time - Used a dual line graph to illustrate to faculty
- Uses bar graphs to compare scores over time
- Uses item analysis for improving specific
curriculum areas - Work most closely with grade-level chairmen and
curriculum content specialists
28Middle Schools
- Data Day at SJMS
- Departmental Teams (1/2 day)
- Teaching Teams (1/2 day)
- How students performed in each area, including
subtests. - Do item analysis in weak areas
- How to improve performance in cross-curricular
teams - Followed Baldridge Criteria
- Used quality tools, fishbone, issue bin,
condense-a-gram, etc. - Shared information within the groups and with the
faculty and administration as a whole.
29Middle Schools
- Request of 7th grade civics teachers
- Principals goals
30High Schools
- Principals share data with teachers
- Teachers Give us only what we need.
- Tremendous help in identifying students who need
an IEP or a SEP - Examines data by SOL Test, subgroup, subtest
- Identifies areas of concern
31High Schools
- What do we do now that we have identified the
students? - Toughest part of the problem
- Meet with individual students
- Establish tutoring schedules
- Establish an interdisciplinary team for 9th grade
at risk students - We are a good school, but not a great school
because not all students are successful. - The data warehouse gives us the ability to slice
and dice the data and look at all students as
individuals. Stan Jones, Principal, Lee-Davis
High School
32High Schools
- Ability to identify individual students quickly
after AYP information was released - Look longitudinally at courses, teachers and
subgroups - Share with department chairmen
- They work with individual departments to take
the data apart. - School and departmental goals are developed
- A valuable tool to help meet principals goals
33General
- Focus is now on pass rates by subcategories
- Principals are looking at teacher performance
- Ability to look longitudinally (1998 2004)
- PALS use of this data to adjust program for
students to ensure success with SOL testing - Gives teachers a look at their class over time
- Great tool for tracking attendance and discipline
- Has become a more user friendly front end to our
Student Information System
34Free Data-Driven Decision Making Tools
- UCLA Quality School Portfolio Program
- Used in all 50 states in more than 1,000 schools
- Web-based
- Collect, analyze use data to improve student
achievement - Main Functions
- Disaggregate data into groups
- Set goals to monitor progress
- Make charts, graphs and other reports
- Track student grades by classroom
- Enter student work samples and see students
progress over the span of their school careers - http//qsp.cse.ucla.edu
35Questions
http//hanover.k12.va.us/presentations/NCLB-dw bil
l_at_hcps.us
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