Assembling the building blocks of thought into patterns that expand our world.
When Sabrina Pasterski was applying for undergraduate admissions, she was rejected by Harvard and waitlisted by MIT, until they saw a video of her building an airplane. Due to Sabrina’s persistence, this video was eventually seen by Professors Allen Haggerty and Earll Murman who strongly advocated for her. “Our mouths were hanging open after we looked at it,” Haggerty said. “Her potential is off the charts.” She was ultimately accepted by MIT, and later graduated with a perfect GPA of 5.0. Sabrina is now earning her PhD at Harvard, earning major grants, and creating waves in the physics community. The recent profile titled “This Millennial Might be the Next Einstein” wonderfully summarizes her rocket-like launch.
While Sabrina’s story may be an extreme example, it perfectly highlights the limitations of legacy practices for detecting aptitude and potential. While standardized testing is useful for measuring basic thresholds, seeing what a person actually makes provides a unique view into how they think, their level of commitment, and what type of skills they possess.
Since Sabrina’s application, leading schools such as MIT, Carnegie Mellon, Harvard, and Yale have created an option to include STEM portfolios as part of their admissions process. However, most admissions departments have not. Education still suffers a huge divide between classroom-side enthusiasm for making and the administrative-side’s penchant for testing, particularly within admissions. Why is that? Is it the legacy momentum of a STEM culture still oriented around test scores? Or perhaps it’s a fear of not knowing how to practically evaluate portfolios at scale? If so, art schools provide a big clue. The arts have a heritage of using portfolios as a meaningful part of the selection process. They use tools like SlideRoom to receive images, videos, code, 3d models, narratives, and other media that can each highlight different aspects of an applicant’s portfolio. And digital credentials, like the one from Credly below, can play a helpful role in stitching together a story about various skills and achievements.
The New York Times story on “The Minecraft Generation” shares several inspiring stories of children going through this entire learning cycle of tinkering, discovery, and presentation within a game called Minecraft — an environment that rewards players for solving open-ended problems by playing with materials that use logic. Simple levers and switches — essentially and/or gates — allow for shockingly complex machines to be assembled out of trees, cows, rocks, stone, and other earthly elements. Players often visually record their activities while narrating what they’re doing. “Minecraft” is currently the second-most-searched term on YouTube after “music.” And most of those 70-million videos are tutorials, popular for their effectiveness in conveying how to build within this block-based world.
The tradition of block-play goes back a long time:
Friedrich Froebel — often called the inventor of kindergarten — developed block-based toys that he claimed would illustrate the spiritual connectedness of all things. Children would start with simple blocks, build up to more complex patterns, then begin to see these patterns in the world around them. Educators like Maria Montessori picked up on this concept and pioneered the teaching of math through wooden devices.
Concepts are the building blocks of thought. As we grow more sophisticated, these simple blocks come to embody subjects, skills, and knowledge — an interconnected system for engaging the world. This depends on interacting with materials — outside of ourselves — that have their own rules and reasons for being. Making is scary because it contains risk. Materials push back, asking makers to respond, debug, and improvise. Solving those problems, of course, is where the real learning happens. Being dynamically coupled with an environment and continually adjusting to new realities is the dance that leads to discovery.
The magic of cognition comes from it’s ability to expand the space of possibility beyond the apparent limitations of an environment. How does that work? While understanding cognition is humanity’s ongoing project, it does seem that interacting with a responsive medium is critical for growth and invention. Creatures learn to see their environment as a set of possible combinations. A sensorimotor loop enables the internal rehearsal of performing an action and seeing it’s consequences, causing previously hidden spaces of possibility to be disclosed. The environment becomes a place of affordances, holding discoverable truths within the combinatorial space of actions and outcomes. Finding novel ways to blend knowledge with new perceptions increases the repertoire of imaginative skill and allows new vistas to be explored and more knowledge to be gained.
Every field has similar ways of talking about invention, each containing structures for the mind to grab and use to predict outcomes. In mathematics and computer science specifically, combinatorial sets are ubiquitous. These are structures that can be arranged many ways based on a set of precise rules. Many breakthroughs have happened when new ways of thinking allow unexpected connections to emerge. For instance, in the movie “The Man Who Knew Infinity,” we learn the true story of an indian youth named Ramanujan who mysteriously was able to arrive at previously unsolvable mathematical truths. Stephen Wolfram wonderfully recounts the story and even attempts to discuss how these leaps might have occurred. One possibility describes Ramanujan as having an “aesthetic sense of which seemingly random facts would turn out to fit together and have deeper significance.” Wolfram’s own experiences of wading through complexity give real weight to that argument.
Creativity arrives in technical terms because thought is always attached to something. The structure of that thing allows us to effectively imagine, to propose the problematic, and invent our way to unexpected places. When we engage a material of any kind, we build a library of knowledge about what that material affords. And through the life of a project, we create new situations that perpetually generate new trees of combinatorial possibility. Technical knowledge is a set of known combinations that circumscribe a space. Technical creativity explores new combinations and coalitions that expand knowledge and reveal new futures to explore.
Learning is a process of discovery, a structured improvisation that struggles to create new models from a world of concealed possibilities. And it is the struggle itself, more than any polished product, that is the essence of learning and the point of any meaningful education.
“What I cannot create, I do not understand.” — Feynman