Improving Instruction

In this scenario, conditional formatting/highlighting will be used to identify standards that identify areas of strength as well as areas of focus. Some of the questions we're asking the data include:

• What standards stand out as areas of strength?

• What standards stand out as focus areas?

• Is this consistent among all questions within those standard areas?

We will use the Replicating the ORS Display - Sample Results method to explore these questions..

In this scenario, the total questions asked per strand will assist in determining if the pacing guide aligns with the critical areas of focus for the grade. Some of the questions we're asking the data include:

• What are the most heavily assessed strands/topics in this course/grade?

• Are we dedicating adequate instructional time (pacing) to fully explore the most heavily assessed strands/topics?

• Should we consider any modifications to the current scope & sequence?

We will use the Aggregate by Standard - Sample Results method to explore these questions for 6th grade math.

In this scenario, a conceptual strand/topic area will be the focus of a unit redesign based upon item analysis. Some of the questions we're asking the data include:

• Which strand/topic stands out as an area of focus for possible unit redesign? Consider school performance in conjunction with how heavily assessed this strand/topic is.

• Which standards should be prioritized in the unit redesign?

• How do the released items compare to our current assessment items?

We will use the Aggregate by Standard - Sample Results method to explore these questions for 8th grade mathematics.

In this scenario, multi-year OST Item Analysis data is used to identify areas of focus based upon trends over time.

• Trends over Time - Sample Results

Note: the Aggregate by Standard method will also include trend data in future years.

In this scenario, a district level analysis will compare results between schools within a district while also comparing to the overall district and state average. Some of the questions we're asking the data include:

• Are different strength areas apparent in the data? Can schools learn from each other?

• How does individual school performance compare with other school(s) in the district? State?

• What are some commonalities in focus areas amongst schools?

We will use the Aggregate by Standard - Sample Results method to explore these questions for comparing Geometry results between the high school and middle school.