I-Corps: An interactive gaming platform that uses motion assessment and virtual reality to incorporate STEM and social-emotional learning

The broader impact/commercial potential of this I-Corps project is the development of an educational gaming platform to improve learning outcomes in children. The proposed platform introduces students to deeper learning that encompasses analytic reasoning, complex problem solving, and teamwork. The curriculum is designed to introduce key concepts in social-emotional learning to bolster any motivational hurdles learners encounter in understanding presented materials.

Focusing on social-emotional learning may assist learners in the creative process and may more easily engage those who exhibit behavioral challenges that may have impacted learning previously. In addition, the proposed technology has the potential to assist in determining where additional resources, support, or services are needed. This platform may play a critical role in bridging the gap of services for underserved populations.

This I-Corps project is based on the development of an interactive educational platform using virtual reality to introduce STEM and social emotional learning to young learners. The proposed online platform uses a framework focusing on imitating behavioral neuronal networks based on user input. Artificial Intelligence (AI) algorithms are used to replicate the functionality of the limbic system and the prefrontal cortex to optimize habitual behaviors.

The proposed technology specifically targets increasing problem solving and creative thinking through real-life interactive scenarios. To allow for the manipulation of 3D objects in an instinctual way, the proposed platform combines the use of motion sensors with the software framework. By combining motion and real-life interactive scenarios with growth hacking development concepts, the technology may increase resiliency by instilling long-term drive and motivation in STEM.

An additional goal is increasing the representation of diverse and minority populations in data sets with the hopes of assisting in the effort to mitigate algorithmic bias.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.