Elementary School Bell study

Goal: To design an efficient building layout and circulation system for a new elementary school.


The new school design is 12,000 sf larger, yet .03% more efficient

It can take students up to 25 minutes to refocus from class to class

If a building is only using 5 out of 10 rooms at a time, their building efficiency is only at 50%.


During the design phase of this new Elementary School there were questions from various stakeholders around incorporating the rich programming required for 21st century learning while keeping the building size manageable for the proposed new school. To help answer these concerns we studied the school’s bell schedule to track space utilization and transit times for. Additionally to make the new school a true community asset, we mapped the building inefficiencies to determine when and where community activities could happen within the building off school hours.

To help communicate how the new elementary school building would function and efficiently facilitate the daily schedule, Arrowstreet designed and developed an interactive web application. Users can simulate the school day by scrolling through the plans, simultaneously visualizing where students will be in the school based on their schedule. The visualization allows the user to identify programming overlap, efficiencies, and unused spaces throughout the day.

For example, if only 5 out of ten spaces are being used within the building at any given time its at only a 50% utilization.


Floor Plan Circulation Analysis

There is a perception that it takes students a long time to walk to and from class from faculty. Comparing circulation efficiencies. if students have an extra minute between classes, that means they have an extra minutes to refocus. if we can minimize the travel and time to transition it could potentially gives them back more time in the classroom.

We ran an algorithm that calculated the distances between every possible route students could take (in existing and proposed) and looked at benchmark walking speed for different grades (For example, on average, kindergartners walk 3.1 feet per second, while 6th graders walk 4.8 feet per second).

How does the school’s existing floorplan compare against our new design when it comes to efficiency of circulation?

The existing elementary school is at full capacity with xxx students across a 2-story xxxx SF building. To accommodate a growing enrollment and upgrade the spaces for today’s educational needs, the new design will accommodate xxx students across xxxxsf. This meant the new building will be xxx sf bigger. After studying the new design using image analysis of pixels of a bw image of the floorplans with algorithm Dijkstra’s algorithm, for analyzing shortest path to calculate distances. We were able to visualize the faculty and staff the new proposed design students travel times were not increased even thought the sf was. Actually .03% more efficient. 97.99% in new not travelling, old 98.02%

Why is travel time so important to consider?

The less time it takes to walk, the more time they have to focus on learning. When you switch tasks it takes your brain xx minutes to refocus your brain so when a student transitions there is a time period before class when kids settle and prepare mentally to learn. By providing more time in between class it gives them more time to refocus so when class starts they are ready to go. Our study revealed that students on average can save up to 1 minute in between each bell in transit time. While it may not sound like a lot, over a 6.5 hour day of learning, the minutes add up

For example, the fifth grade class of xx students spend on average xx minutes in their existing school. When our new building is complete, they will save xx time in during classroom transit.


Additional Insights

Team: Arrowstreet

Location: Harvard, MA

Client: Town of Harvard

Definitions

Dijkstra's algorithm to find the shortest path between a and b. It picks the unvisited vertex with the lowest distance, calculates the distance through it to each unvisited neighbor, and updates the neighbor's distance if smaller. Mark visited (set to red) when done with neighbors.

Dijkstra’s Algorithm: an algorithm for finding the shortest paths between nodes in a graph