Using Student-Powered Data to Design

By room2learn

Imagine a school that’s designed by every single member of a school community, from students to custodial staff. Ambitious? Yes. Impossible? No.

The tech world talks a lot about UX — user experience. At room2learn, we think about applying UX to the design of learning spaces. How can we improve the end user experience for everyone in a school building? We set out to create a digital, inclusive tool that enables 100% co-design of a classroom or school space. Here’s what we’ve learned and where we’re headed.

1. We can save time by digitizing community engagement

Community engagement is time-consuming, and often exclusive. Let’s face it. We’ve all sat in on a town hall meeting or design charrette, where you’re looking at the clock and wondering whether any of these post-it’s will have any impact. Our vision is to create a data dashboard to capture everyone’s individual thoughts, updating in real time as each community member participates.

Architects speak in images, and educators use their words. So as an educator, when a picture is worth 1,000 words, how do you know you’re speaking the same 10 words as your architect? And for architects, how do you know what your school client means by a “collaboration space”?

From this problem, we started by building out a simple survey tool to align people’s vision through images.

2. An open space might be efficient to an architect, but distracting to a user.

Next, we wanted to find out how different people might use words differently to describe images. So we tested the survey on three groups:

• A4LE: mid-career architects and district leaders who conducted the tagging exercise (choose descriptive words from a given list)
• Millennials: New York and Boston students who conducted tagging exercise
• Open-Ended: New York and Boston students who were asked to describe the images (free-response)

We asked people what types of spaces they preferred for their teaching and learning needs, and found the following:

As it turns out, all of these images were more favored by architects and district leaders, and less so by student users. Going into each image, we were able to pull the top keywords that each group saw.

Looking at the last image, we found that the architects loved the space, while students did not as much. We see nuanced differences like “peer” and “brainstorming” appear in the two groups’ vocabulary. We can speculate that from the architect’s perspective, this flexible corridor space is easy to setup and provides students with informal social space. From the student or end user perspective, the open space environment works well for group work and collaboration, but the open air environment might be too noisy or distracting for productivity. With level level of data, we can only speculate at the why behind preferences.

3. Design matters! To the untrained eye, gut reactions matter most.

Results got more interesting when we had people react to physical design elements. This time, we saw a reverse in preferences — architects and users had very different preferences.

Let’s take a closer look at the first image, which architects did not like, and users seemed to love. The keywords people chose were similar, though architects saw “geometric” while users saw “comfy” and “colorful.” From a building lens, this space poses technical challenges in terms of drawing and modelling, sourcing materials, and custom-building some of these geometric shapes. An end user might love this space for the variety of seating options, access to books, and interesting color palette. Again, we can only speculate at the why.

4. To understand why people like what they do, we may need to get nitty gritty.

Now the question becomes, if an image captures 100 square feet, how do you know we’re talking about the same square foot of an image? For the next iteration of this tool, we are developing a tagging function that allows users to share thoughts on specific areas of an image. Think Facebook’s face-tagging software, but for designs!

This allows us to generate micro-analytics for each image or rendering, allow for real-time client feedback from a variety of users.

For instance, a student might see different words than a teacher, who has different priorities than an administrator. At this micro-scale, we can have more productive conversations about end user needs, and design elements that matter for UX.

Our co-design tool is in beta, and we are looking for communities to test this with. If you’re interested or want to learn more, get in touch with us at team@room2learn.org!