WEBVTT

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Welcome to the overview
on Making Data Part

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of an Ongoing Cycle of
Instructional Improvement.

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Teachers can use data to help
guide their instructional

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decision making and
improve their ability

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to meet their students' learning
needs by engaging in a cycle

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of instructional improvement.

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This cycle includes:
- Collecting

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and preparing relevant data
about student learning, -

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Interpreting that data
and developing hypotheses

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about what may be needed to
help students improve, and -

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Testing those hypotheses
by implementing changes

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in instructional practice

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and assessing their
impact on student learning.

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The cycle can continue
as teachers collect

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and interpret additional
student achievement data

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and test new hypotheses.

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Teachers can enter the cycle
at any point, for example,

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testing a hypothesis
using existing data

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or evaluating a recent change
in a teaching technique.

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Because each assessment
type has its own advantages

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and limitations, and no single
assessment provides all the

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information teachers need,
it's necessary to collect data

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from multiple sources.

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Results from annual statewide
assessments can help teachers

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understand students'
strengths and weaknesses,

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identify students who may
need particular support,

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and set performance goals.

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However, significant
time may have passed

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between when the
assessment was administered

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and when the results are
available to teachers.

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During that interval,
students' knowledge

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and skills may have
changed significantly.

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Results from interim
assessments,

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which are administered
consistently across a district

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or school at regular
intervals throughout the year,

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are readily comparable
across classrooms.

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However, they do not
provide immediate feedback

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about student learning.

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Classroom data drawn from unit
tests, projects, classwork,

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and homework can be combined

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with Individualized
Education Plans and records

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from parent meetings to
provide rich, detailed pictures

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of students' academic
performance.

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This kind of data can
be gathered quickly,

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providing teachers
with immediate feedback

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about student learning.

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The disadvantage is that
the assignments, conditions,

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and scores are not generally
comparable across classrooms.

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Both teachers and
students benefit

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when data is interpreted
collaboratively in grade-level

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or department-specific teams.

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Through collaboration, teachers
can share effective practices,

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adopt common expectations
for student performance,

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and develop a collective
understanding of the needs

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of individual students.

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When interpreting data,
the first objective is

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to identify the overall areas of
relative strength and weakness

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in each class so that
instructional time

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and resources can be allocated

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to serve the most pressing
instructional needs.

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The second objective is
to identify the strengths

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and weaknesses of individual
students so that assignments,

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instructional methods,

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and feedback can be
adjusted accordingly.

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Once multiple data sources have
been analyzed, teachers need

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to develop hypotheses about
potential instructional changes

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to meet these overall and
individual student needs.

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Once hypotheses

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about instructional
changes have been formed,

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they need to be tested.

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Common strategies include:
- Allocating more time

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for instruction in
essential skills, - Reteaching

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or preteaching skills that
seem challenging for students

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to grasp, - Providing additional
help with particular skills

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to individual students, -

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Implementing different
teaching techniques

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for challenging subjects, -

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Aligning performance
expectations across classrooms

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or grade levels, and -
Improving curriculum alignment.

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For example, if student
assessment results show

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that students are having
difficulty mastering two-digit

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multiplication, teachers
may decide

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to spend an extra 20 minutes
on this skill for one week

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and then retest students to
see if mastery has improved.

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Teachers may consider
the following guidelines

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when testing hypotheses: -

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A complex instructional change
requires more time allocated

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in order to carry it out.

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- Once data on the effectiveness

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of the instructional change has
been analyzed, teachers need

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to decide whether to continue
with the change "as is,"

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modify it, or try a
totally new approach.

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The data cycle is not
without its challenges.

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Teachers may have so much
data that they are not sure

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where to focus their attention.

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By asking specific questions
and concretely identifying

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which data addresses
those questions,

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the range of data
can be narrowed

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to something more manageable.

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Administrators can
guide this process

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by setting schoolwide goals that
help clarify the kinds of data

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that teachers should
be examining.

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Some subject areas, such as
music or physical education,

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lack readily available
student achievement data.

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Teachers can work
collaboratively, however,

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to develop their own
assessments that are linked

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to schoolwide achievement goals.

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Lastly, teachers and
school staff should use data

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from multiple sources to
identify and serve the needs

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of all students, not
just an isolated group.

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No single test score should
be used to make decisions

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about individuals;
instead, multiple sources

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of information need
to be considered

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when assigning students
to courses or programs

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and making adjustments
to instruction.

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To learn more about Making
Data Part of an Ongoing Cycle

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of Instructional Improvement,

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please see the additional
resources

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on the Doing What Works website.