Skip to main content
News

Meet Clover: A Responsive Reading Robot

Envisioned by Alex Hergenroeder, Ed.M.'17, the innovation gives children a way to practice reading aloud, interacting with gestures in an effort to build their reading and vocabulary skills.

Reading Robot
Picture a Tickle Me Elmo, but instead of Elmo only repeating “That tickles” over and over again, he is able to read aloud with your child, track their eye movements, gestures, and vocalizations, and respond accordingly in real time.

Alex Hergenroeder, Ed.M.’17, has spent the last year investigating and setting the stage for her vision: “Clover.” A soft, cuddly robot, Clover can engage with children, and can provide them with a more personal, parent-inspired way of practicing reading than other technologies currently on the market.

“This really all began with my lovely niece,” Hergenroeder says. “When she was 12-months old her favorite thing was to hand me a toy tiger and I would say ‘It’s the tiger! The tiger goes roar!’ This made her so happy and giggly, and we would repeat this process over and over — and over. On the one hand this was just a game, but on the other hand it was actually solid vocabulary practice.”

Flash forward and Hergenroeder was in Associate Professor Meredith Rowe’s class in which she learned about the crucial role of early experiences in language development. "'Social' interaction is greatly important for children's language and cognitive development,” Rowe says. “We know that parents who gesture and communicate more with children have children who learn language quicker. A robot may have the potential to play a supplemental role in that learning as well, by providing yet another mode of communication and interaction for young children. It is exciting to see how these new innovations and technologies might shape the future in childhood development and learning.”

The stars of the technology behind Clover are the responsiveness and the ability to model gestures and social cues in a three-dimensional way that babies and toddlers can naturally understand. Responsiveness sounds simple, but it is actually very complex. Hergenroeder needed to include a lot of elements in the device to achieve a high level of responsiveness: eye-gaze tracking, gesture tracking, facial-expression tracking, algorithms to level the responses based on children’s ages and ability levels, object recognition, character recognition, and more. She then incorporated elements that are important for early childhood social cues such as directed eye gaze and physical, three-dimensional gestures.

“And beyond the technology, Clover is a huggable, loveable friend for children, and it takes on a companion quality, which is important for children’s connection to a robot.” Hergenroeder says.

Outside of the home, Hergenroeder believes Clover could be a resource for early-childhood care providers and teachers, a supplemental way for children to practice reading independently. As part of the robot’s technological capabilities, she has developed a method for it to change its behavior and range of skills over time. For example, Clover can detect when children are skipping words when reading aloud, and assist with them in identifying the word and reinforcing it. Additionally, software could be updated for children’s changing skill sets as they grow and learn more.

“When you think about the different applications for this technology, you can see it also being useful for older students and English-language learners, or to help those with learning differences or struggling readers,” Hergenroeder says.

Now that she’s secured the necessary patents behind the technology, Hergenroeder hopes to see her vision for Clover come to life through the creation of a prototype and a licensing opportunity. A key part of that for her, she says, is ensuring that the robot is accessible to low-income families, citing research that shows that by the time a child from a low-income family is five years old, he or she will have heard 30 million fewer words than their high-income peers. Additionally, research shows that by the time children from lower-income families are two years old, they are already several months behind children from higher-income families in reading and vocabulary development.

“I’m deeply hopeful that this type of technology can be used to bridge these gaps and can provide low-income children with a high quantity of responsive, individualized high-quality reading and vocabulary practice that is currently more available to their higher income peers.” says Hergenroeder. “When I think about where I think it can make the biggest impact, it is for low-income families, to give children more opportunities to enrich their vocabularies, practice reading, and get a leg up on their early development and education. As this project progresses, I intend to ensure that that is a key element of the robot’s future.”

News

The latest research, perspectives, and highlights from the Harvard Graduate School of Education

Related Articles