Gathering data
Developing an analysis plan
Analyzing data
Interpreting results
Implementing changes
Additional resources

Use existing data sources – i.e., MEAP, AYP, DIBELS, etc.
Consider levels of data – individual student, classroom, school, etc...
Formative vs. Summative
Use technology for storing data (warehouse?)
Integrate school improvement plan goals and objectives

What data to analyze?
Measuring progress on standards and benchmarks
Prioritize key areas of interest (and possible impact)
Points of collection & analysis (daily?)
External requirements vs. internal focus
Assessment data vs. grades

Formative vs. summative data?
Recording strategies?
Responsibility for gathering and submitting data?
Oversight?
District, school & classroom improvement
Validity & reliability issues

Validity – evolved from psychometrics, the degree to which a test item measures what it was designed to measure
Types: Internal, external & construct
Can be resolved by using multiple data points--this is often a weakness in technology-based assessments
Reliability – consistency of results
Can be resolved by using inter-rater measures (degree of agreement among raters) Often the strength of tech based assessments

Which content standard indicator(s) was the teacher assessing?
What percent of students demonstrated proficiency?
What implications does that have for instruction?
Which students have not demonstrated that they can do this?
What diagnostic information did an examination of student work provide?
Based on individual student performance, what do we need to do next to move the student to proficiency?
Based on the class performance, what re-teaching do we need to do?

When we compare performance by subgroups (e.g., by racial group, gender, students with disabilities, ESL students, or students in the free and reduced meals program), do we see any groups not performing as well as the whole group? If so, what are we going to do about that?
Do we have any students who are not attaining proficiency across indicators?
What diagnostic information do we have about them to inform instruction?
What interventions have we tried? What interventions do we plan to try next?
Source: School improvement in Maryland (http://mdk12.org/data/)

Pie charts
Line graphs
Bar graphs
Box plots

Consider color coding

Hans Rosling is the first person that I recall sharing what I now know is data visualization, and his material can be find on gapminder.org

If you haven't done so recently, go ahead and start with the basic changes and open a new Excel document. Click on "Insert" in the top menu ribbon, and spend a bit of time exploring the different possible charts and sparklines you see available in the choices that come up.

Many other specialty programs and strategies exist for analysis types made possible with technology, such as social network analysis from social media.
Other helpful programs of different types are in this blog: http://www.creativebloq.com/design-tools/data-visualization-712402

"Lies, damn lies, and statistics."

Do you see spindles or people?
Remember optical illusions

Use results to inform professional development – purpose, focus, etc.
Leadership teams review results
Develop/Update a plan for improvement
Evaluate professional development
Be an advocate for change and improvement

Support for school improvement and AYP
Decision making shared amongst teachers and administrators
Impacting classroom instructional practices
Organizational issues – training, support, apps, etc.
Ongoing evaluation & improvement (NCLB/SBA)

Link to Video: https://youtu.be/RXMnDG3QzxE