SD23 Dashboard
Constable Neil Bruce Middle
"Home of the Cubs"
Our Inquiry Process

So, why choose Inquiry as the vehicle for school improvement?  Traditionally, the school planning process has been a positive experience that has focused on data collection and data analysis, and then putting in systems or programs to improve that data.  Schools would improve their data, or not, and would adjust strategies and goals as needed from year to year.  Data is still central to school improvement, but what Inquiry adds to this overall process is a real focus on systems of professional learning over time that is rooted in curiousity about individual student needs.  Inquiry is a systemic and informed approach to school improvement that involves all stakeholders in a school community – school administration, staff, students, and parents/guardians – to be involved in this transformative process.  School districts around the world have been using Inquiry to guide their practice for some time, and as a result have been seeing more authentic and meaningful school improvement occur. 

The Spirals Of Inquiry is an Inquiry model out of British Columbia, stemming from the work of Judy Halbert and Linda Kaser.  The model has us ask questions as a learning community to uncover what is really going on for our students in our classrooms, to structure professional learning around what will make a difference for our students, to take informed action, and then to measure if it made enough of a difference.  The Spirals allows for constant checking and re-checking over time.  By having our students at the center of our school's inquiry, and by collaboratively tailoring learning and actions to improve their learning experience, our school will dynamically improve over time in a living, and breathing reflection of our school's learning journey.

Inquiry consists of six phases, which, it is important to note, are not linear in nature.  That is, work can be done simultaneously in different domains at once.  CNB has enjoyed beginning this process of discovery and look forward to the deep learning ahead.