Data Driven Decision
Making
CSI Winter Regional Meeting
December 2016
Agenda
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Major Themes when Using Data to Make Decisions
Conceptual Framework/Theory of Action
Data Systems
Leadership for Uses of Data
Tools for Generating Data
Structures and Systems
Supports and PD
Tools for Acting on Data
Implementation Strategies
Major Themes about Data Analysis
• A study released by the USDE identified major themes in case
study on the use of data analysis in schools.
School
Improvement
Planning
The most common school-level
uses of data are for school
improvement planning,
curriculum decisions, and
placement or grouping of
students for instruction or
support services.
Instructional
Improvement
Use of data to support inquiry
into how one can improve one’s
teaching appears to emerge in
school’s with a more mature data
culture.
Means, B., Padilla, C., & Gallagher, L. (2010). Use of Education Data at the Local Level: From Accountability to
Instructional Improvement. US Department of Education.
Major Themes about Data Analysis
Perception of barriers to greater use of data
include a sense of lack of time, system
usability issues, the perception that the data
in the system are not useful, and policies
around pacing that prohibit modifying
learning time to match student needs.
The most powerful school-level catalysts
for teacher use of data are school leader
promotion of these activities and the
establishment of an organizational
climate of trust and mutual respect.
Means, B., Padilla, C., & Gallagher, L. (2010). Use of Education Data at the Local Level: From Accountability to
Instructional Improvement. US Department of Education.
Conceptual Framework
Data Systems
• Most schools have multiple, distinct data systems. Although not a problem in
principle, the use of multiple systems can be a problem in practice.
• A lack of interoperability across data systems was a current barrier to expanded
use of data-driven decision making.
Student information
systems
Instructional
or curriculum
management
systems
Data
warehouses
Assessment systems
Leadership for Uses of Data
School improvement planning, including setting of quantitative goals
Curriculum planning based on item or subscale analysis
Student placement in classes or special services
Grouping or regrouping of students within a class
Tailoring instruction to the skill needs of individuals or small groups
Deciding whether or what to reteach
Identifying teachers with more successful strategies in order to emulate their instructional approach
Recommendation
• Set clear expectations around the use of student data as the
basis for decisions.
• Case studies illustrated the important role that school leaders
play in modeling the use of data and in developing school
practices in which teachers are expected to use data to guide
their decisions.
Tools for Generating Data
• To support better decisions about instruction, data systems
should make available data on the same student or group of
students over time and support looking at the performance of
students with different educational experiences (i.e., different
teachers or instructional programs).
Tools for Generating Data
Types of Data Available
Student demographics
Student attendance
Student grades
Student test scores on statewide assessments
Student course enrollment histories
Student graduation status
Student behavior data
Student participation in educational programs
Student special education information
Teacher qualifications
Student test scores on interim assessments
Student test scores on school-administered assessments
Teacher professional development
Types of Data Available (CDE Required
Submissions)
Structures & Systems
• Integrate collaborative exploration of data into existing
structures for joint teacher planning and reflection on
teaching.
• Lack of time to examine and reflect on data is the greatest barrier to data-driven
decision making according to both teacher and district survey respondents.
• Given the constraints of educational budgets, funding for additional time for
teachers to engage in data use activities is likely to remain relatively unusual. Data
use can become an integral part of teacher planning and collaboration time that is
already funded in many school, provided there is school leadership for doing so.
Recommendation
• Provide a safe environment for teacher examination of their
students’ performance.
• Reports from case study schools suggest that teachers benefit from opportunities
to examine student data with their colleagues, but that they only want to do so if
they feel confident that they will not be opening themselves up to harsh
judgments.
• Small groups of teachers who typically work together as part of a grade-level,
department, or project team appear to be the most suitable for collaborative
inspection of data.
• Keeping data reflection activities separate from performance management
activities (which could affect salary or job status) helps to create a climate of trust.
Supports & Professional
Development
• Support teachers in making the link between data and
alternative instructional strategies.
• Just having student data is not sufficient if teachers do not have ideas about how
to teach differently based on student performance.
• Grouping students by their performance level and giving additional emphasis to
content on which a majority of students did poorly are responses to data
considered by most teachers. It was less common to find teachers who had ideas
about different ways to teach content depending on student assessment results.
• Instructional coaches, however, especially in the area of early literacy, were able
to bring this kind of insight to teachers in a number of the case study schools.
Coaching that combines training in research-based instructional strategies and the
use of student data as a basis for selecting and evaluating instructional strategies
should be encouraged.
Tools for Acting on Data
Tools for Acting on Data
Tools for Acting on Data
Implementation Suggestions
• The survey and case study findings presented in the USDE report suggest that
educational data systems are improving, but the combination of technical and
human resources available in schools has yet to constitute a capacity for routine
use of data to support instructional decisions.
• A good data system is not enough: Use of data to inform instruction requires
leadership and systemic realignment.
•
Data-driven decision making requires leader initiative to align curriculum and
assessment practices, professional development, and data systems.
• Efforts to promote data-driven decision making are more successful when they
are not treated as a separate innovation.
• Data-driven decision making should be implemented as a part of school and
teacher efforts to provide better instruction for every student.
• Timely, credible, interim assessment data is key to motivating teachers to use
data systems.
• Teachers’ inclination to use data systems is affected by the nature of the system
interface and the amount of training and support they receive, but these supports
are largely futile if the system itself does not contain information that teachers
consider relevant to their practice.
Theory of Action for Data Use