A few months ago, I embarked on a job search. In addition to the usual litmus test, considering the product, team, role, etc., I was adding some complexity. I wanted to continue my work as an educator.
Last year, my research interests had taken me as far as Chile, where I taught computer science in public high schools as a Fulbright Scholar. My research question was simple — what should skills-based education look like?
Back in San Francisco, I was disappointed to find there weren’t all that many EdTech companies that inspired me.
Enter Parabola. On the surface, the product might not look like it has much to do with education, but I saw an opportunity. Parabola gives knowledge workers the capabilities of engineers—a visual way of creating scripts to analyze data.
This happens all the time. You have data living in a few different places—lead data in Salesforce, performance data in Dropbox, and a smattering of other attributes living in Google sheets. You want to perform some analysis on them, and then move the results somewhere else. “More likely than not, you’ll want to perform the same analysis at the end of every month.
Usually, you are faced with two options. You could get really fast at doing the same things over and over again. Maybe allow yourself to dabble in the guilty pleasures side of your Spotify to make it through the final stretch. Your only other good option is bothering an engineer and convincing them this is worth it.
Parabola offers a bridge between manual work and fully engineered solutions. Instead of repeating processes or allocating engineering resources, Parabola offers a remedy where ‘mood-boosting’ Spotify playlists do not.
How to build flows with Parabola
By creating a ‘flow,’ a series of operations you can perform on your data, you can automate away a lot of the work you’re stuck repeating. Parabola’s proposed paradigm is: build a data pipeline once, so that you can run it whenever you want, thereby cutting out the tedium of repeated work
Although Parabola users are not writing code, they are learning to think like engineers. Creating a flow in Parabola requires many of the design patterns that allow engineers to build robust systems.
Creating data pipelines in Parabola is a study in how to design, build, and test systems. I like working on a product that deepens a user’s knowledge base, instead of shying away from the challenge of putting powerful tools in the hands of users.
Over the course of my research project in Chile, I became enamored with the Constructionist theory of learning, which postulates that people learn most effectively through experimentation and play. In my workshops, students built their first video games using ‘sandbox-style’ educational tools developed by MIT.
Although it’s tempting to break things into bite-sized chunks for users or students, we’re often over simplifying complex concepts. I found that teachers consistently underestimate their students’ ability to figure things out on their own. In my programming workshops, I saw the power of experimentation as a teaching method. I saw what students could build when equipped with the right tools.
Back to Parabola. I liked the idea of giving people the power to engineer solutions. But I loved the tactic: trust people to figure it out for themselves.
And that’s exactly what I saw Parabola users doing. It’s inspiring to see the complexity of flows that previously non-technical users build for themselves in Parabola.
The team has put a ton of thought into building a product you can tinker with. The interface was designed to make powerful operations easy to understand conceptually.
Whereas Excel was never designed for the crazy things it’s used for today, Parabola was. As a result, Parabola users are learning programming concepts intuitively. Parabola users are creating fully-engineered solutions all on their own. As an educator, that got (and continues to get) me really excited.