21st Century Strands & Strategies
Chapter: Strands & Strategies: Deep Dive
19
Data-Driven Decision-Making
Data-driven decision making (DDDM) is "a
system of teaching and management practices
that gets better information about students into
the hands of classroom teachers" (McLeod,
2005). Using student data to better address
students' learning needs through instructional
decisions at the classroom, district, state, and
national levels has potential, when implemented
well, to be useful for improving teaching and
learning.
"Information is the key to holding schools accountable for improved
performance every year among every student group. Data is our best
management tool. I often say that what gets measured, gets done. If we know
the contours of the problem, and who is affected, we can put forward a
solution. Teachers can adjust lesson plans. Administrators can evaluate curricula.
Data can inform decision-making. "
- Margaret Spellings, U. S. Secretary of Education (January 20, 2005 – January 20, 2009)
According to Bernhardt, to move toward a data-driven decision making school, there
are eight steps that help guide the process (2004). The eight-step process is as follows:
1)
Develop a leadership team
2)
Collect and organize several
different types of data
3)
Analyze data patterns
4)
Generate hypotheses
5)
Develop goal-setting guidelines
6)
Design specific strategies for the
action plan
7)
Plan the evaluation
8)
Implement the plan
By following the steps listed, a school
can collaborate and prioritize needs in
order to sustain a vision that focuses on school improvement (NCREL, 2004).
Connections
•
There are various types of data that inform district, school and the classroom
(multilayered-attendance; formative, benchmark, formative assessment,
program, behavior, cohort data, and professional development).
•
Data must be systemically and consistently used to impact student
achievement.
