![]() ![]() Put another way, the visualization must reveal the heart of the scientific data’s truths clearly, but it must also layer lessons in front of that final conclusion in a way that challenges the learner without making them want to give up. Interactive visualizations for education must intrigue learners enough to invite them into a dialogue - while also holding enough back so that students can engage in problem-solving and experiential learning. And in most other contexts, it makes sense to visualize data in a way that makes key insights and conclusions obvious at a glance. Switching from a mentality of “providing answers” to one of “provoking questions” is central to successful inquiry-based learning. After all, designers are conditioned to find elegant solutions that allow content to speak for itself. Instead, they should learn to make real-world connections through active exploration and high-level questioning.įor UI designers, this represents the biggest challenge about creating educational data visualizations. In fact, more than any other type of client we have worked with, educators are the ones who push back against the desire to “dumb things down.” Great teachers know that to enable deeper learning, students must not be served easy answers. In practice, we’ve found that oversimplifying scientific data actually detracts from its value in an educational setting. It’s easy to think that the goal of designing data visualization for educational purposes would be to make everything “so simple a fourth-grader could understand it.” In practice, we’ve found that oversimplifying scientific data actually detracts from its value in an educational setting. Designing an Inquiry-Based Learning Experience So, what are the design considerations at play when creating an interactive educational visualization? Let’s break down how we can use iterative design and development to carry scientific concepts to everyday learners. It should resist the urge to oversimplify so that a learner may be appropriately challenged before ultimately achieving clarity, usually within a relatively limited amount of time. A visualization must strike the perfect balance of explanation and exploration. They must also communicate complex data stories in accessible ways to learners who often lack the background knowledge needed to readily interpret and understand data. Visualizations must connect to learners on a personal level. The basic premises of creating educational data visualizations include the following: ![]() But, however amazing these immersive opportunities are, designing interactive visualizations for learning environments presents several unique challenges. And creating these experiences in an educational context is the ultimate balancing act between telling a clear and compelling story, and allowing for open-ended exploration and the opportunities for learning that go with it.Įducational data visualizations designed for classrooms, museums, and the web allow students and citizen scientists to explore new worlds by seeing and engaging with scientific data. Sure, data visualization allows you to see some things, but the journey doesn’t really begin until you’ve walked in and figured out where you can go next. While you could say that visualizing data is like providing a window into your data, we at Stamen know it’s more like building a door. ![]()
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