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Project Idea: KeikiBot: An Early Childhood Education Bot

Problem Statement: It is commonly understood in the neuroscience community that the first few years in a child’s life has a tremendous on brain development. According to The Education Corner, “The future success of every child is in many ways determined before he or she turns 8. During those early years, how that child learns and develops — mentally, emotionally and socially — is critical”. The very first learning experiences have substantial consequences on a child’s cognitive and social development. According to sources like https://www.naeyc.org/resources/pubs/yc/mar2017/teaching-emotional-intelligence, teaching emotional intelligence as part of an early childhood education can be pretty challenging. Learning good social behaviors and cues can require a series of positive and negative reinforcements. Additionally, for only children who haven’t necessarily already had the opportunity to interact with siblings, this can be especially challenging. Putting a large focus on early childhood nurturing is a hugely important societal investment, since it will largely affect the success of a future generation. 

A lot of life is centered around various social constructs. Functioning effectively in these sorts of environments requires more than just an academic intelligence; emotional intelligence, also known as Social Intelligence, is maintaining a balanced life with physical, mental and emotional health. EQ involves being able to identify one’s own emotions, controlling and adapting emotions, using emotions to motivate appropriate actions, discerning the feelings of others and building relationships with others. Many studies show that EQ is a major driver of success, and though it comes more naturally to some than others, it is an inherently learnable skill. Proposed robot-based solution: The use of social robots can augment early childhood education programs. By establishing key social behaviors in toddlers with the use of social robots, emotional intelligence knowledge can be successfully assimilated as a key portion of early education. 

These five key EQ metrics can be addressed:

Self-Awareness

Self-Regulation

Motivation

Empathy

Social Skills

Empirical evidence shows that many young children interact with humanoid robots as creatures, giving an interesting avenue to instill some key desirable social behaviors. These sorts of robots could be present in classrooms and homes and act as social companions as well as educational tools.

Feasibility: Introducing a social robot to interact with young children would require a robot that could perceive the face/emotions/reactions of a young child, and provide some sort of an audio or physical movement response. Kuri is a social robot, originally intended for companionship, making it a good choice for this sort of project. KeikiBot does not need to necessarily grasp or move anything, but could potentially provide some sorts of physical, positive reinforcements, such as gently patting a child on the back, or giving hugs. I think with the integration of some sorts of facial emotion recognition software and audio processing, the Kuri Robot would more than suffice for the project of providing emotional intelligence feedback to small children via interactions. In order to limit the scope of this realm for ten weeks, it would be cool to gameify social situations such that a child playing with the social robot can quickly learn.

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Prior work: Deep Phreatic Thermal Explorer (DEPTHX)

Problem: Despite the fact that nearly 71% of the Earth is covered in oceans, less than five percent of the ocean has been discovered. In fact, today, we know more about Mars than we do about the oceans on Earth. The ocean is a crucial to humans, as it moderates the planet’s climate systems, provides a multitude of resources and even has an effect on human health. It is quite important to work on furthering our understanding of this essential part of our planet, yet studying the ocean provides a great deal of challenges. Currently, the seafloor cannot be mapped using existing technologies such as radar, since ocean water obstructs radio waves. This inhibits the study of many undersea organisms, as well as the measurement and modeling of underwater environments. It’s also very difficult to collect data or capture images of the oceans.

Solution: Researchers at Carnegie Mellon University and NASA Ames Research Center worked on developing DEPTHX, a robotic undersea explorer responsible for mapping difficult portions of the seafloor. They worked on creating an autonomous robotic system that could successfully map 3D spaces. The DEPTHX Robot was the first entity to successfully explore the Zacatón Cenote, a thermal sinkhole, in central Mexico. Source: https://www.frc.ri.cmu.edu/depthx/