Transcript Data Driven Decision Making - Florida Literacy Coalition

Using Data to Improve
Adult Ed Programs
Administrators’ Workshop
Workshop Objectives
 Participants will be able to understand the data



driven decision making process.
Participants will be able to identify what types of data
can be collected.
Participants will be able to identify what data reports
are most useful to teachers and administrators.
Participants will be able to identify what major
barriers hinder the data collection process.
Participants will be able to analyze data report
examples.
What is Data-Driven Decision
Making?
 Data-driven decision making is the
process of making choices based
on appropriate analysis of relevant
information.
Why use data to make decisions?
 More access to better information enables
educational professionals to test their assumptions,
identify needs, and measure outcomes.
 Administrators and teachers are using data-driven
decision making to:





provide more individualized instruction to students
track professional development resources
identify successful instructional strategies
better allocate scarce resources
communicate better with parents and the
community.
What data should we collect and use to
make decisions?
 There is an abundance of information stored.
Examples are:






student records
student assessment
human resources
student progress
special education
curriculum management.
What data reports are most useful to
instructors?
 TABE
or CASAS test results for entire class
 Student attendance information
 Teacher developed test results for entire class
 Progress reporting information for class
 Student retention information for class
 Student performance gains (LCP/OCP) for
class
What data reports are most useful to
administrators?






TABE or CASAS test results for program area
Student attendance information for all programs
Progress reporting information for all programs
Student retention information for programs/school site
Student performance gains (LCP/OCP) for programs
and for school
Cost effectiveness of program (Income versus cost of
salaries, fringe, supplies, equipment)
What common data report formats are most
useful to administrators?

Administrators use all types of data:







attendance
enrollment
student performance (LCP’s, OCP’s)
student/teacher/parent satisfaction surveys.
Test results are used to assess progress, allocate
resources, and create school improvement plans.
Information is organized numerically rather than
alphabetically.
The information includes objective descriptions of
data, visual displays of information, and query tools.
What are the major barriers to using data
based decision-making?
 Lack of training
 Interoperability—systems that are unable to share






or exchange data
Lack of understanding of what to do with the data
Absence of clear priorities on what data should be
collected
Failure to collect data in a uniform manner
Outdated technology systems
Low quality data – inaccurate or incomplete
Timing of data collection
What are the major misconceptions about effective use
of data in decision making?
 Build it and they will use it.
 Teachers need to know how to analyze
data and use query systems.
 Test scores determine the quality of a
school and the student’s education.
What is necessary for the systematic use of data
for decision making?
 Collection, integration and dissemination of
data
 Analysis and reporting of data
 Process and procedures for acting on the
data



Review
Analysis
Planning
What types of skills are needed to implement
systemic data processes?
 Schools need both organizational and individual capacity
for improvement:


Leadership
Professional development.
 Administrators need training with the opportunity to apply
skills learned using their own institutional data.
 Dialogue with peers keeps the process going.
 School-based training for faculty and staff is necessary.

Instructors need training in different instructional strategies to
apply when the data shows that traditional methods are not
working.
Who are the key decision makers at the school site
who should be involved in the data-driven decision
making process?
 Administrators
are the change agents at the
school site.
 Administrators model data use and encourage
it by sharing the benefits and successes.
 Site-based specialists or support teams assist
administrators and teachers with data mining
and analysis.
Who are the key decision-makers at the classroom level who
should be involved?
In addition to using data for determining
instruction, teachers can engage students in
the decision making process by helping
them:



view appropriate reports;
set learning goals;
make decisions about how to meet their goals.
Where do we begin?
 The process:
 Develop a leadership team
 Collect various types of data
 Analyze data patterns
 Generate hypotheses
 Develop goal-setting guidelines
 Design specific strategies
 Define evaluation criteria
 Make the commitment
What information does our institution need to make decisions that
will improve student achievement?
 What learning strengths and weaknesses are
evident in the data?
 Which groups or subgroups of students are
having difficulty learning?
 What instructional changes might improve
student learning?
 What professional development is need to
improve student learning?
 What materials and equipment are needed to
support changes in instruction?
Example 1 – Making decisions based
on data
 A school examines its student performance
results and finds:



As a whole, the school is doing better in
reading than in math
Students are doing better in basic computation
than in problem solving
As a subgroup, Hispanic male students
perform the lowest on grades and tests at
most grade levels
Example 1- continued
 Using this information, the school
improvement team decides to find the
following:


An instructional intervention that specifically
addresses basic math computation
Interventions that have been especially
effective in improving the performance of
Hispanic male students
Example 1 - continued
 Professional development is planned to
provide instruction on the new intervention:


Staff development days are planned for
teachers to learn the new intervention before it
is implemented.
Regular short meetings are planned to give
teachers time to discuss their efforts and
troubleshoot problems while implementation
occurs in the classroom.
Example 2: FCAT Classes
Name
Course
Days
LCP
Earned
Credit
Earned
PreClass
Score
PostClass
Score
Grade
ESE
LEP
Maria
Intensive
Reading
T/R
1
.5
248
300
B
No
No
Maribel
Intensive
Reading
T/R
1
.5
223
296
B
No
Yes
Kasie
Intensive
Reading
T/R
1
.5
245
286
A
Yes
No
Elysia
Intensive
Reading
T/R
1
.5
260
301
B
No
No
Eric
Intensive
Reading
T/R
1
.5
246
185
B
No
Yes
Thordis
Intensive
Reading
T/R
1
.5
297
306
A
No
Yes
6
3
253
279
3.33
Totals/
Average
Example 3 – Budget Data Across Sites
Site
Fee
Support
Enrolled
FS Percent
Enrolled
9-12
Enrolled
9-12
Percent
Enrolled
Grades
30/31
Enrolled
Grades
30/31
Percent
Enrolled
Total
Enrollment
Budget
Cost
per
Student
ACE
1
139
12%
291
25%
715
62%
1,145
$619,537
$541
ACE
2
88
9%
322
33%
567
58%
977
$682,826
$698
ACE
3
134
16%
360
44$
327
40%
821
$481,238
$586
ACE 4
12
2%
166
27%
438
71%
616
$460,099
$746
ACE
5
192
25%
181
24%
387
51%
760
$619,698
$815
Totals/
AVG
565
13%
1,320
31%
2,434
56%
4,319
$2,863,398
$677
Example 4 – Co-Enrolled
Completion/Retention Semester II
Enrollment
LCP’s Earned
Students with
no LCP’s
Percent
Completing
Percent Not
Retained to
Completion
English I
12
8
4
67%
33%
English II
8
5
3
63%
37%
English III
9
2
7
22%
78%
English IV
17
2
15
12%
88%
Totals/
Averages
46
17
29
33%
67%
Course Title
Data Review
 Other types of information teachers may want
to review:




Student records with demographic data (LEP,
ESE, grade level completed, courses taken,
GPA)
FCAT scores
TABE scores
Other test records
More Data Review
 Administrators may collect and analyze other
reports:





Class attendance
School surveys – satisfaction or quality
surveys
Individual program/class surveys of
satisfaction or delivery of services
Student exit surveys
W-26 reports (high school students
withdrawing to attend postsecondary
programs)
Let’s Review the DATA!
 Using the handouts provided, break into small
groups and discuss the data presented on
each handout following directions provided.
 What assumptions can be made about the
data presented?
 Did the data serve to confirm ideas you had
already pondered?
 What other types of data could you collect
about your program(s)?
References/Links
 Data-Based Decision Making – Resources for
Educators.
http://www.ael.org/dbdm/Tutorial.cfm?&ider=
Deve4060
 D3M: Helping schools distill data.
http://eric.uoregon.edu/search_find/data_anal
ysis.html
 The Toolbelt: A collection of data-driven
decision-making tools for educators.
http://www.ncrel.org/toolbelt/