Computational Thinking and Life Science: Thinking About the Code of Life

Introduction

As part of my research at the DevTech Research Group, I (like all the researchers in our lab) have spent years collecting data about young children’s engineering, technology, and programming learning by implementing and evaluating informal curricular interventions. In the 20 years since the creation of DevTech by Marina Bers, our collective research experience on running these camps and play sessions has resulted in a cumulative wealth of knowledge about effective practices for introducing robotics, coding, and other STEAM-themed topics for the first time to 4- to 8-year-old learners. One of the very first activities that we like to play in our robot-themed camps is a game called, “Robot or Not?” The premise of the game is simple: the researcher shows a group of children a picture of an object, and asks “Is this a robot, or not?” If a child thinks yes, they jump up and down; if their answer is no, they stand still; and if they aren’t sure or they need more information, they wiggle from side-to-side. In addition to being a fun game to get some energy out, Robot or Not? provides an opportunity for children have conversations about what makes something a robot. We found early on that children exploring robotics for the first time understandably hold a variety of assumptions and ideas about robots that range from precocious to erroneous. Robot or Not? offers a low-stakes playful settting to explore children’s ideas, allowing researchers to address misconceptions and identify gaps in knowledge.

Conversations get especially rich when players disagree about whether something is a robot. For example, most children jump up and down when they see a picture of a famous robot character from a movie, and stand still for a picture of a dog, but a picture of a stuffed toy stitched to look like a robot is more ambiguous. When we reach the inevitable point in the game when children are uncertain, the researcher pauses to invite children to list characteristics that they think robots have, in order to agree on a shared definition. A common list includes the following criteria: Robots are made of metal or plastic; They have special parts like gears and motors that non-robots do not have; These special parts can move and make sounds automatically; Some robots are built to look like humans; All robots need an engineer or programmer to tell them what to do. This list may grow or change depending on the children in the group, but one criterion is common across every conversation that I’ve ever led or observed with children playing this game: robots are machines, and so they are definitely not alive. And yet, as advances in biotechnology and genetics change the very nature of what we mean by “alive”, I find myself questioning this foundational assumption about machines that even young children understand, and wondering what it could look like to have that conversation in our early childhood STEAM camps.

Thus, in my doctoral thesis, I set out to explore the relationship between children’s understanding of computational algorithms, and algorithms in the natural world, such as DNA—the genetic “code of life”. I wanted to know if we could create tools, frameworks, and lesson activities to invite children to meaningfully engage with concepts from genetics and biology in a playful and developmentally appropriate way, just as we’ve seen successfully in early computer science education (Bers, 2020). The NSF-funded Making the Invisible Tangible project led at Tufts University and Wellesley College (CHS-1564019), attempted to explore the pedagogical connections linking computational thinking to engineering design and life science content (Strawhacker, Verish, Shaer, & Bers, 2020a, 2020b, 2020c; Verish, Strawhacker, Bers, & Shaer, 2018). We sought to develop a suite of lesson activities and an educational technology prototype, called the CRISPEE kit, that could bring the real-world relevance and design creativity of coding into children’s exploration of microbiology, a historically challenging field for young learners to break into.