Data Driven Decisions - Frequent Data collection informs instructional decisions and groupings.

Of the Personalized Learning Core Four discussed in the last post, KPBSD has many strengths! One area that practices are particularly strong in is Data Driven Decisions. From the highest levels of the KPBSD machine to the small group specialized work with students, we are monitoring and utilizing data to drive our work.

Data Driven Decisions, as explained in Considering the Core Four, simply means that we frequently collect data to inform instructional decisions and student groupings. It also means that we use data purposefully, both at the student and teacher level, that we use formative (as you go) assessments to inform our decisions, and that we are developing a culture of openness toward use of data and feedback.

From a district level, one example of this is using progress monitoring assessment data to keep track of student growth. This data is usually more meta in scope – districtwide and occurring throughout the school year.  We use this information to guide the choices that are made regarding both district and school improvement. Such data is crucial in helping the district to identify trends and needs, then helping guide decisions in allocating support, materials and resources.

For the school level, this means meeting the needs of students through data use. The data here is usually specific to the school or a specific group within a school. School staff monitor how their school is demonstrating learning and use data to make intervention or support plans. Teachers and specialists use the afore mentioned progress monitoring to group students based on their needs, and even further alter their instruction for the student by frequently reviewing the data and letting it inform them of student needs. This allows for closing gaps in student learning efficiently.

For the student level, this means that students themselves are learning how to review the results of the assessments that they take to see how they are progressing in their own learning goals. The data here is specific to the student as an individual and students are beginning to diagnose for themselves what they need to move forward. This is the most pure form of driving learning… Student Driven.