Scout

How might Artificial Intelligence and Extended Reality technology ease a distressed education system?

An exploratory project demonstrating a possible future of immersive and personalized education experiences

Our education system is at a turning point, moving from an industrial revolution-based model of efficiency and memorization to a model that emphasizes individuality. We set out to explore how technology might enhance this effort through the combination of Extended Reality (VR, AR, or anything in between) and AI-powered automated learning. We envisioned a future of lifelong personalized learning using immersive experiences, and developed Scout – a conceptual education platform that may emerge.

Students and teachers are facing growing challenges

In our education system, teachers are spread across a number of students with a wide variety of learning styles, preferred pace, and emotional states. It’s difficult to employ an adaptive education for each student over the course of their education without one on one support. Courses often end up emphasizing memorization rather than the foundational concepts, and often lack metaphors that resonate personally with students.

The Concept

Holistic, lifelong, adaptive education, powered by AI and XR, and beyond

We envisioned a future where all students have a lifelong learning agent to observe and facilitate their education. By developing a comprehensive profile to understand their individual learning styles, an AI agent can then translate lessons into experiences that resonate. Likewise, we were fascinated with how configurable immersive environments can be, and saw them as an especially flexible medium to deliver conceptual learning. Virtual environments can be modulated in ways that aren’t possible in reality — in this case, to cater to the attention of a learner. Together these two technologies

learning framework

An new education framework that delivers immersive personalized lessons

We developed a high-level model for an education platform with three stages to demonstrate how AI and XR can work together to deliver personalized and immersive education. The Input stage captures short-term and long-term information, like the current emotional state of the user, or their learning habits, strengths, and weaknesses. The Decision Making stage uses input data to modulate the lesson in the moment to better suit the student’s situation. The Output stage is a collection of interfaces that can be adjusted by tone, context, environment, and teaching mode to provide a personalized and flexible lesson.

Prototyping the experience

Scout’s first lesson:
a personalized learning experience

To demonstrate this new model, we created Scout – an education platform for personalized lifelong learning. We developed Scout’s first lesson through the eyes of Taylor, a 6th grade student biology learning photosynthesis. We imagined how this may play out in an agile lesson given Taylor’s unique inputs. This prototype moves from instruction, inquisition, to free exploration in a matter of minutes based on Taylor’s attention span and interest level.